Psi Chi Journal of Psychological Research – Spring 2021

Psi Chi Journal of

Psychological Research SPRING 2021 | VOLUME 26 | ISSUE 1

ISSN: 2325-7342 Published by Psi Chi, The International Honor Society in Psychology

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PSI CHI JOURNAL OF PSYCHOLOGICAL RESEARCH S P RIN G 2021 | VOLU M E 26, N U M BE R 1

EDITOR DEBI BRANNAN, PhD Western Oregon University Telephone: (503) 751-4200 E-mail: debi.brannan@psichi.org ASSOCIATE EDITORS JENNIFER L. HUGHES, PhD Agnes Scott College TAMMY LOWERY ZACCHILLI, PhD Saint Leo University ALBEE MENDOZA, PhD Wesley College STEVEN V. ROUSE, PhD Pepperdine University KIMBERLI R. H. TREADWELL, PhD University of Connecticut ROBERT R. WRIGHT, PhD Brigham Young University-Idaho EDITOR EMERITUS MELANIE M. DOMENECH RODRIGUEZ, PhD Utah State University MANAGING EDITOR BRADLEY CANNON DESIGNER TAYLOR BROWN-STONE EDITORIAL ASSISTANT REBECCA STEMPEL ADVISORY EDITORIAL BOARD GLENA ANDREWS, PhD George Fox University AZENETT A. GARZA CABALLERO, PhD Weber State University MARTIN DOWNING, PhD NDRI ALLEN H. KENISTON, PhD University of Wisconsin–Eau Claire MARIANNE E. LLOYD, PhD Seton Hall University DONELLE C. POSEY, PhD Washington State University

ABOUT PSI CHI Psi Chi is the International Honor So­ci­ety in Psychology, found­ed in 1929. Its mission: "recognizing and promoting excellence in the science and application of psy­chol­ogy." Mem­ ber­ship is open to undergraduates, graduate students, faculty, and alumni mak­ing the study of psy­chol­ogy one of their major interests and who meet Psi Chi’s min­i­mum qual­i­fi­ca­tions.

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JOURNAL PURPOSE STATEMENT The twofold purpose of the Psi Chi Journal of Psychological Research is to foster and reward the scholarly efforts of Psi Chi members, whether students or faculty, as well as to provide them with a valuable learning experience. The articles published in the Journal represent the work of undergraduates, graduate students, and faculty; the Journal is dedicated to increas­ ing its scope and relevance by accepting and involving diverse people of varied racial, ethnic, gender identity, sexual orientation, religious, and social class backgrounds, among many others. To further support authors and enhance Journal visibility, articles are now available in the PsycINFO®, EBSCO®, Crossref®, and Google Scholar databases. In 2016, the Journal also became open access (i.e., free online to all readers and authors) to broad­ en the dissemination of research across the psychological science community.

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PAUL SMITH, PhD Alverno College

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Anything He Can Do, She Can Do Better: Children’s Attitudes About Gender and Occupations

Ryan Brown1 and Nanci Weinberger2* 1

Department of Psychology, Bryant University 2

Department of Psychology, Center for Health and Behavioral Sciences, Bryant University

14

The Effects of Self-Esteem, God Image, and Gender on Coping Methods

Jessica Downing, Christina Sinisi*, and Rebecca Foster Department of Psychology, Charleston Southern University

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The Stigmas Associated With Teen Parenting: How Gender-Stereotypical Expectations Contribute

Mariah Chobany and Debra Hull*

Department of Psychology, Bethany College

26

Working Memory in Chinese Text Comprehension

Sau Hou Chang1 and Tracy B. Henley2 1

School of Education, Indiana University Southeast 2

Department of Psychology, Counseling, & Special Education, Texas A&M University–Commerce

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Negative Life Events and Time Perspective Among Adolescents

Julie V. Chandler and Zena R. Mello* Department of Psychology, San Francisco State University

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The Effect of Strategic Instruction for Categorical Clustering on Preschoolers’ Recall Accuracy

Isabella DelVecchio and Mary Stone* Department of Psychology, Marist College

56

Arrival Time Matters: The Effect of Biculturalism and Age of Arrival on College Adjustment

Guicheng Tan Steinhardt School of Culture, Education, and Human Development, New York University

68 INVITED EDITORIAL: Update on Psi Chi's Response to COVID-19

Deborah Harris O’Brien1 and Martha S. Zlokovich2 1

Psi Chi President, Trinity Washington University 2

Executive Director, Psi Chi Central Office

*Faculty mentor

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https://doi.org/10.24839/2325-7342.JN26.1.2

Anything He Can Do, She Can Do Better: Children’s Attitudes About Gender and Occupations Ryan Brown1 and Nanci Weinberger2* 1 Department of Psychology, Bryant University 2 Department of Psychology, Center for Health and Behavioral Sciences, Bryant University

ABSTRACT. Children’s career aspirations are affected by cultural stereotypes about gender. We investigated rudimentary implicit associations and explicit gender attitudes about occupations with a diverse sample of fifty-eight (29 girls, 29 boys) 10-year-old children. We tested implicit gender associations using an adapted auditory Stroop task and tested explicit gender attitudes using the Gender-Stereotyped Attitude Scale for Children (GASC). We also modified a version of the GASC to assess children’s attitudes about a female and a male firefighter-paramedic seen in a brief video. Children also judged the firefighter-paramedics’ job skills. Children did not display implicit associations between occupations and one’s gender based on differences in the response times between the congruent and incongruent test trials that paired male and female voices with occupations, t(1762) = 0.65, p = .52, d = 0.03. Auditory voice stimuli might have confounded the tested associations between gender and occupations. The GASC findings highlighted gender stereotype flexibility about men and women. Girls were more flexible than boys on the job component of the GASC, t(56) = −2.12, p = .039, d = 0.55. The level of children’s gender stereotype flexibility varied by occupation. Children exhibited the most flexibility for who should be a doctor and the least flexibility for who should be a ballet dancer/teacher.

Lastly, we assessed attitudes toward the specific woman featured in the video; children overwhelmingly saw her as a potentially good fire chief (vs. the man featured in the video; 91% selected Kate or both for who would be a better fire chief).

Keywords: children, gender attitudes, occupations, counterstereotypical, stereotype flexibility

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ender is one of the most salient social categories; all human cultures identify, socialize, and prescribe roles for individuals based on their gender (Glick & Fiske, 1999).

Children demonstrate their ability to identify their own gender and readily determine which clusters of behaviors are associated with their own gender (Halim et al., 2014). Moreover, children sanction other children who are seen to be violating genderbased norms of behavior (Skočajić et al., 2019).

Among the many potential consequences of relying on gender stereotypes are the limits that adults and

children place on their career paths. Even young children base their career aspirations on gender stereotypes (Hayes et al., 2018; Liben et al., 2001).

The well-established body of research assess­ ing children’s explicitly stated attitudes about gender have expanded in recent years to more fully include children’s implicit attitudes (Skowronski & Lawrence, 2001). Less is known about children’s implicit gender attitudes about occupations as compared with their explicit attitudes about occu­ pations. The first goal of the current study was to examine 10-year-old children’s rudimentary implicit

COPYRIGHT 2021 BY PSI CHI, THE INTERNATIONAL HONOR SOCIETY IN PSYCHOLOGY (VOL. 26, NO. 1/ISSN 2325-7342)

*Faculty mentor

Brown and Weinberger | Children's Attitudes About Gender and Occupations

and explicit gender attitudes with a focus on occu­ pations. By middle childhood, children become more flexible about their explicit gender attitudes about occupations (Garrett et al., 1977; Ruble et al., 2006). This flexibility hints at the possibility that there are circumstances, such as exposure to counter-stereotypical models, that can augment children’s views about gender and occupations.

Therefore, the second goal of the current study was to examine how children evaluate a woman and a man who were realistically portrayed in the same stereotypically male occupation.

Children’s Attitudes About Gender and Occupations Considering that gender stereotypes may shape occupational aspirations, it is useful to see how chil­ dren associate gender with occupations. Children ascribe more restrictive occupational roles for men than women (Weisgram et al., 2010; Wilbourn & Kee, 2010). For example, Blakemore (2003) found that 7- to 10-year-olds were more negative in their appraisals of male nurses compared to female nurses. When faced with nontraditional or counter stereotypical examples, individuals often explicitly label neutral words with a feminine or masculine modifier that marks the perceived abnormality of the person-job pairing (e.g., “female doctor” or “male nurse”; Liben et al., 2002). Similarly, Vervecken & Hannover (2015) found that, among 6- to 12-year-old children, “linguistic feminization” of stereotypically male occupations increased children’s self-efficacy and the ascription of higher job accessibility.

Children as young as 4 and 5 years old demon­ strate stereotyped occupational goals that suggest that their behaviors and preferences are informed by their early accumulation of gender knowledge (Huston, 1983). Stereotyped knowledge of child and adult occupations increases rapidly between ages 3 to 5 and hits a ceiling by kindergarten or first grade. Until age 7 or 8, stereotypes are held rigidly, but then flexibility increases dramatically (Ruble et al., 2006). For example, older elementary school children were more likely than younger elementary school children to consider occupa­ tions as appropriate for both genders instead of just one gender (Garrett et al., 1977). This may be due to older children’s ability to identify gender stereotypes as such, whereas younger children may also be less likely to attend to counter stereotypical information (Carter & Patterson, 1982). As children become more flexible about gender attitudes, they

begin to recognize that occupations can be suitable for both men and women.

Children and adults rely on cultural, situ­ ational, and historical factors to inform their acquisition and expression of gender-based occu­ pation stereotypes. A potent demonstration of an occupational stereotype was found in the seminal Draw a Scientist study of nearly 5,000 young children; only 28 children, all girls, drew a female scientist (Chambers, 1983). A meta-analysis identified a decrease in recent decades in the proportion of children drawing a male versus a female scientist; however, the rates of drawing a male scientist continue to be much higher than a female scien­ tist (Miller et al., 2018). Thus, we aimed to study children’s conceptions of these roles in society to understand the implications of such gender occupation stereotypes.

Eagly (1987) identified children’s low selfefficacy beliefs toward occupations that are stereo­ typically male. During middle childhood, children also come to learn that gender-typical occupations are characterized by different values also associated with gender (Hayes et al., 2018). Children’s initial limited knowledge that men and women occupy positions that differ in attributes such as power, income, altruism, and family flexibility grow sig­ nificantly in middle childhood (Hayes et al., 2018).

This can be compounded with other gender norms.

For example, parents explain their children’s suc­ cess differently based on their gender such that boys’ success is attributed to ability, whereas girls’ success is explained by effort (Räty et al., 2002).

Yet, parents and educators can also help children to develop more egalitarian views and build skills that can foster diverse occupational interests.

For example, early career preparation and skill development can be realized in programs such as a Lego engineering summer camp (Holler, 2013).

Unfortunately, stereotypes can persist even in spe­ cially designed programs to welcome all children, potentially explaining the gender imbalances found among enrolled children.

In addition to the impact of explicit attitudes, implicit attitudes may also be contributing to children’s behavioral choices. Implicit attitudes are often not correlated with one’s explicit attitudes (Skowronski & Lawrence, 2001). Implicit attitudes represent “introspectively unidentified (or inac­ curately identified) traces of past experience that mediate favorable or unfavorable feeling, thought, or action toward social objects” (Greenwald & Banaji, 1995, p. 8). People’s implicit biases are

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potent enough to uniquely predict prejudiced behavior in both children and adults (Dunham et al., 2011; Greenwald et al., 2009).

Measurements of implicit associations differ from the vast array of measures of explicit attitudes.

Measures of implicit associations typically include processing speed and sometimes memory recall accuracy of stereotyped pairings as compared with counter-stereotyped pairings such as male or female name and occupation (e.g., Wilbourn & Kee, 2010).

In contrast, measures of explicit attitudes generally involve direct questions such as own-gender and other gender evaluations and self-reported adher­ ence or resistance to gender stereotyped behavior as well as other ratings (Mulvey & Killen, 2015).

One of the most frequently used implicit measures to date is the Implicit Association Test (IAT). The IAT, developed by Greenwald et al.

(1998), measures the strength of associations between categorical concepts (e.g., women, men) and attributes including evaluations (e.g., good, bad; Carney et al., 2007; Rae & Olson, 2018). Many applications of the IAT assume that the IAT can predict discrimination in the real world; however, there is ongoing controversy about the predictive validity of the IAT as it does not link with behavior any more strongly than explicit attitudes in some circumstances (Oswald et al., 2013). Because the IAT was primarily used to study, and hopefully predict, implicit racial attitudes that predict discriminatory behavior, these criticisms call into question conclusions that researchers draw from these studies. However, in this study, we were more interested in the associations themselves and how those implicit associations may reflect children’s perceptions of counter-stereotypical careers.

Children’s implicit associations of math with boys may contribute to early differences in girls’ beliefs that STEM careers are for them. Cvencek et al, (2011) observed both implicit and explicit mathgender stereotypes, previously identified in adults, in elementary school children using a child-specific IAT. Gender differences in these math-gender stereotypes appeared for children in Grades 1 and 2. Boys in the Cvencek et al. study associated me with math more than the girls, despite that there are no significant differences on math achievement tests in elementary school (Hyde et al., 2008). These results suggest that, when children hold stereotypes (e.g., “Math is for boys”) as well as their gender identity (e.g., “I am a girl”), the combination primes negative evaluations of one’s own ability and belongingness in a particular domain (e.g., “Math isn’t for me”).

Most et al. (2007) developed an auditory Stroop task to also evaluate implicit gender schema contents. The traditional Stroop task causes cogni­ tive interference by forcing participants to attend to a specified feature of a stimulus, such as reading the name of a color while the word is printed in an interfering ink color (i.e., the word “blue” may be printed in green ink; Stroop, 1935). In the Most et al. (2007) auditory Stroop task, the research protocol is simplified for young participants; it does not require any reading. In addition, the auditory Stroop procedure asks participants to identify only one thing about the stimulus: if the voice they hear through headphones is a male voice or a female voice.

Among adults, response times to an auditory Stroop task including incongruent word-voice pairs (e.g., male voice paired with female name) were significantly longer than that of congruent word pairs, indicating an implicit expectation that the words were bound to gender. There were no significant gender differences. However, there was an interaction between the type of word and the congruence of the word-voice pairs such that the effect of congruence of the words was amplified specifically for stereotyped names (e.g., Rachel) but not stereotyped words (e.g., football). The auditory Stroop task was adapted for 8- and 9-year-old chil­ dren in a second study in which children identified the gender of the voice by pressing specific keys marked with stickers instead of speaking into a microphone. Again, there was a significant main effect for response to different word-voice pairs.

Unlike the findings from the adult population, the effect of congruence on stereotypical words was stronger than for stereotypical names. This suggests that different categories of words may have different implicit associations to gender.

Occupations are a critical category of stereotyped concepts and therefore warrant study of children’s implicit gender associations with occupations.

The Present Study The present research was designed first to explore how children’s rudimentary implicit associations and explicit attitudes reflect gender stereotypes with a focus on occupations and second, to inves­ tigate children’s explicit attitudes about a female a stereotypically masculine occupation and her male counterpart in that same occupation. We examined children’s views of a female and a male firefighter-paramedic. We elected to examine 10-year-old children based on prior research on

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Brown and Weinberger | Children's Attitudes About Gender and Occupations

children’s implicit and explicit attitudes about race.

By age 10, implicit associations and explicit attitudes about race appear to diverge as explicit attitudes become more egalitarian (Baron & Banaji, 2006).

Moreover, implicit bias about race is amenable to change from interventions at this age but not for younger children (Gonzalez et al., 2016). Thus, children at this age may also have diverging implicit and explicit attitudes about gender representations of occupation.

To examine children’s implicit gender associa­ tions, we used a modified version of the auditory Stroop task first developed by Most et al. (2007), which tests implicit gender associations of adults and 8- and 9- year old children. Researchers found that participants had a high accuracy rate in identifying the gender of a speaker and responded more quickly to voice-word pairings that were congruent and consistent with gender stereotypes as compared with incongruent voice-word pairings (Most et al., 2007).

Here, the auditory Stroop task was modified to use occupations paired with male and female voices (A.S. Baron, personal communication, October 16, 2016). Because Most et al. did not find differences based on participant gender, we did not expect gender differences for our participants. Thus, in our first hypothesis, we predicted that children would have slower auditory Stroop response times to incongruent voice-occupation pairings as compared with congruent voice-occupation pairings.

Explicit gender attitudes show a develop­ mental pattern moving from gender attitude rigidity in early childhood to increasing levels of flexible or egalitarian responses in middle child­ hood (Signorella & Liben, 1985). The GenderStereotyped Attitude Scale for Children (GASC) is useful because it includes general activities (e.g., play football) and occupations (e.g., teacher).

Thus, the GASC allowed us to examine the general flexibility of gender attitudes as measured by a high rate of both responses across all test items and assess the flexibility of gender attitudes specifically about occupations. In our second hypothesis, we predicted that children would be flexible regarding explicit gender stereotypes about male and female activities, including ones about occupations.

Although the current study was not an interven­ tion study, we did introduce the same brief video episode featuring a female and a male firefighterparamedic to each child. To examine children’s explicit gender attitudes of the depicted firefighterparamedics, we modified the scale accordingly (mGASC) to ask children to rate them. Previous

studies using the GASC rarely found differences by participant gender and therefore we did not expect gender differences for GASC scores or mGASC scores in the current study (Signorella & Liben, 1985). Thus, in our third hypothesis, we predicted that children’s explicit gender attitudes would be flexible and egalitarian when presented with the specific case of applying gender attitudes to the firefighter-paramedics in the video.

Lastly, we investigated whether the detailed por­ trayal of an exemplar’s professional work was strong enough to counteract the stereotype of a firefighter being a man and therefore the more competent one. To this end, we developed additional questions to determine how children evaluate the specific occupation abilities of the firefighter-paramedics in the video. In an exploratory research question, we asked how children would evaluate the female firefighter’s occupation abilities and her male counterpart. In summary, we examined 10-year-old children’s implicit associations and explicit gender attitudes with a focus on occupational roles.

Method Participants Twenty-nine girls and twenty-nine boys (Mage = 10.06 years, range = 8.92 years to 11.5 years) completed the study. Two additional tested children did not complete the study. One was not included due to parental interference and a second child was not included due to technological difficulties. We recruited participants from 3 rural, 2 suburban, and 5 urban all-purpose afterschool programs held in schools and recreation centers. Racial/ethnic identity information (provided by parents) was reported for 52 children. Of this group, 10 (19%) had more than one race/ethnic selection. Of the remaining children, there were 42 (81%) single race/ethnic group selections: 34 White/European American, 5 Latinx, 2 Black/African American, 1 Asian/Asian American.

Measures Implicit Gender Associations An auditory Stroop task was used (A. S. Baron, personal communication, October 16, 2016) and run using Inquisit TM version 5 lab (Millisecond software, Seattle, WA, USA). In this task participants are asked to identify if each individual word they have heard is spoken by a “girl” or a “boy.” Half of the words were presented by a female voice and half by a male voice in a randomized order. Participants were instructed to press the matching key as fast as

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they could to indicate their choice (i.e., G key for the girl voice and B key for the boy voice). The two keys were brightly labeled with stickers and aligned on the same keyboard row. Half of the participants within each gender grouping were randomly selected to use a keyboard with the girl key on the left side and the boy key on the right side; this was reversed for the remaining participants.

The auditory test stimuli included four stereo­ typically female occupations (e.g., secretary) and four stereotypically male occupations (e.g., engineer).

Half of the voice-occupation pairings were congruent with the gender of the voice matching the gender stereotyped occupation (e.g., female voice paired with secretary) and half of the voice-occupations pairings were incongruent (e.g., female voice paired with engineer). In addition, there were four neutral test items (e.g., table) paired with female and male voices equally. The auditory stimuli were randomly presented across 48 test trials with each stimulus item being presented four times, two with a female voice and two with a male voice. Prior to the test trials, participants completed a practice session with 10 tri­ als of neutral words that were not included in the test stimuli. The measure of implicit gender associations about occupations is based on the key press response times for congruent as compared with incongruent voice-occupation pairings. Longer response times for incongruent voice-occupation pairings than congruent voice-occupation pairings indicate implicit gender associations with occupations.

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Explicit Gender Attitudes Participants completed a three-part pen and pencil survey to assess explicit gender attitudes generally and included attitudes about occupations.

Part 1. Gender-Stereotyped Attitude Scale for Children (GASC). To examine children’s explicit gender attitudes, we used the GASC developed by Signorella and Liben (1985). This widely used and adapted instrument assesses gender attitudes by asking who should do certain activities (i.e., men, women, or both men and women) rather than assessing gender knowledge by asking who does certain activities (Signorella & Liben, 2012). The test items included a range of activities (e.g., set the kitchen table) and occupations (e.g., doctor). The current version had five fewer items than the origi­ nal. Four outdated or unfamiliar test items were recommended to be eliminated by the scale authors (Signorella & Liben, 2012) and an additional test item (i.e., use a sewing machine) was eliminated by the current authors for the same reasons. Thus,

the current scale had 12 male-stereotyped items (e.g., fix a car), 11 female-stereotyped items (e.g., bake cupcakes), and seven neutral items (e.g., ride a bicycle). The stereotyped test items included six occupations and 17 other activities, later described as job and nonjob test components, respectively.

The proportion of responses for both women and men are used to indicate explicit stereotype flexibility about nonjob activities. The proportion of responses for both women and men across the six occupation items are used to indicate explicit stereotype flexibility about gender and occupations.

Part 2. Modified Gender-Stereotyped Attitude Scale for Children (mGASC). To assess how gender stereotyped attitudes might be applied to the female and male firefighter-paramedics in the video, partici­ pants completed the GASC again. The same GASC test items were used; however, the survey response options were based on the names of the firefighterparamedics in the video: Kate, Jeremiah, or both Kate and Jeremiah. The proportion of responses for both Kate and Jeremiah across test items are used to indicate explicit stereotype flexibility. These findings will be referred to as the modified GASC (mGASC) results. Construct and convergent validity have been demonstrated in the original and complete form of the GASC but not the modified versions used in the current study (Signorella & Liben, 1985).

Part 3. Occupation Ability Ratings. To deter­ mine how participants evaluated Kate and Jeremiah with respect to specific job skills, participants rated Kate and Jeremiah separately on five test items using a 7-point Likert-type scale from 1 (strongly disagree) to 7 (strongly agree). Some questions were verbatim from the video (e.g., Kate does a good job in medical emergencies) and others required more speculation (e.g., Jeremiah would make a good fire chief). In addition, participants were asked to rank who would be better for each of these test items, Kate, Jeremiah, or both Kate and Jeremiah. Similar average ratings of Kate and Jeremiah would indicate egalitarian evaluations of their professional skills.

Statistical Analysis Implicit Gender Associations The primary dependent variable of the auditory Stroop task was the response time latency from the onset of the auditory voice presentation to key selection (i.e., boy voice key or girl voice key).

The latencies in the congruent and incongruent voice-occupation pairings were compared. Longer latencies for incongruent voice-occupation pairings compared with congruent voice-occupation pairings

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indicate implicit associations. The latencies for the gender-neutral trials were not included in the main analyses and were considered separately. An addi­ tional dependent variable was included, correct or incorrect key selection (i.e., did the participant cor­ rectly identify the gender of the voice?). Latencies were only compared for correct keyed trials.

Explicit Gender Attitudes The GASC was scored by summing the number of items in which both men and women were selected among the 23 gender-stereotyped items (Signorella & Liben, 2012). The mGASC was scored similarly, by summing the number of items in which both Kate and Jeremiah were selected among the 23 gender-stereotyped items. The component parts of each scale were separated to focus on attitudes about occupations. The job component has six items and the nonjob component has 17 items. To compare the relative rate of selecting both Kate and Jeremiah for each component, ratio scores were computed. Ratio scores were based on the number of items in which both Kate and Jeremiah were selected divided by the total number of items for given scale component (i.e., 6 or 17). Thus, a higher ratio score indicates greater flexibility regarding attitudes about gender.

The occupation ability ratings were based on individual questions using 7-point Likert-type ratings.

Higher ratings indicated greater agreement that Kate and Jeremiah were each good at the specific aspects of their jobs. The occupation ability rankings were based on who would be better for each ability, Kate, Jeremiah, or both Kate and Jeremiah. These were scored similarly to the GASC in which the number of both Kate and Jeremiah responses were tallied and the percentage of participants’ both Kate and Jeremiah responses over all possible responses were computed. A higher percentage indicated an egalitar­ ian or flexible attitude about occupation abilities.

Procedure Following parental consent, we tested participants individually at their afterschool programs. The testing took place in a separate room away from the activities of other children. The researcher explained the procedure and indicated that the child could stop at any time and asked for their assent to continue. First, participants completed the auditory Stroop test on a laptop with head­ phones. Following the test, participants used a laptop with headphones to watch a brief (4.44 minute) video entitled, Kate Heckaman: FirefighterParamedic. The video was produced by PBS for their

SciGirls programming. Videos in the SciGirls series allows viewers to learn about women working in occupations that use math and science. This video introduces the viewer to two firefighter-paramedics, Kate and her partner, Jeremiah. Kate and Jeremiah can be seen doing their jobs as Kate narrates and explains the occupation and her personal story and attributes that make her good at her job (e.g., loves to learn, motivated, appreciates having an adrenaline rush). Participants were told to pay attention to the video because they would be asked questions about it later.

The final part of the study was a pencil and paper survey measuring explicit gender attitudes, including attitudes about the individuals in the video and women and men generally. Because participants saw the video before answering the questions about men and women generally, these should not be interpreted as a true “baseline” of gender attitudes.

Each child was given a modest thank you gift (i.e., Slinky toy) at the completion of their participation.

This research study was approved by the Bryant University Institutional Review Board on Human Subjects and the researchers complied with the APA ethical standards of treatment of sample participants.

Results Implicit Gender Associations We predicted that children would have slower audi­ tory Stroop response times to incongruent voiceoccupation pairings as compared with congruent voice-occupation pairings. Our first hypothesis was not supported based on the auditory Stroop task findings. As seen in Table 1, there were no signifi­ cant differences in the response times between the congruent and incongruent test trials that paired male and female voices with occupations, t(1762) = 0.65, p = .52, d = 0.03. Moreover, the incongruent trials did not lead to more key selection errors than the congruent trials, t(90) = −0.43, p = .667, d = 0.09.

As expected, the auditory Stroop findings do not indicate a difference between boys and girls in their response times between the congruent or incongruent test trials, as indicated in an analysis of variance test, F(3, 1756) = 0.41, p = .75, ηp2 = 0.00.

However, the gender of the voice stimuli impacted the response times. Specifically, response times for both congruent and incongruent voice-occupation pairings were slower for test trials with female voices as compared with trials with male voices, t(1762) = 2.90, p = .004, d = 0.14. The slower latencies for the female voice were also found for the neutral words, t(898.06) = 16.07, p < .001, d = 1.07.

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TABLE 1 Means and Standard Deviations of Latencies in Milliseconds for Auditory Stroop Trials All Children M(SD)

Boys M(SD)

Girls M(SD)

Voice Effect

Aggregated Test Trials

Test Trials

Congruent voice-job pairings

All congruent trials

1168.24 (376.83)

1166.62 (370.14)

1169.86 (383.68)

Male voice— Male jobs

1139.19 (383.40)

1134.00 (380.34)

1144.29 (387.15)

Female voice— Female jobs

1196.97 (368.40)

1198.95 (357.66)

1195.03 (379.38)

All incongruent trials

1180.90 (437.33)

1191.24 (476.27)

1171.00 (396.77)

Male voice— Female jobs

1153.23 (434.47)

1150.30 (488.26)

1155.93 (422.20)

Female voice— Male jobs

1207.75 (438.91)

1229.93 (499.25)

1185.97 (370.67)

Male voice

1146.09 (409.11)

1141.90 (414.25)

Female voice

1202.32 (404.72)

1213.86 (433.95)

1150.10 (404.56) p = .004, 1191.05 (374.15) d = 0.14

Male voice

1120.84 (459.78)

1123.81 (536.66)

Female voice

1603.78 (442.82)

1620.01 (471.73)

Incongruent voice-job pairings

Collapsed job pairings by voice:

Collapsed neutral pairings by voice: 1117.84 (367.94) p < .001, 1587.76 (412.73) d = 1.07

Note. In total there were 1,856 test trials that were made up of 32 voice-job pairings for each participant.

Analyses were based on the 1,760 correct trials. The Voice Effect indicates a significant difference in the mean latencies between male and female voice trials as tested by t tests.

TABLE 2 Ratio Scores for Gender-Stereotyped Attitude Scale (GASC) and Modified GenderStereotyped Attitude Scale (mGASC)

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Scale and Components

All Children M(SD)

Boys M(SD)

Girls M(SD)

GASC—All items

0.59 (0.29)

0.52(0.30)

0.66 (0.28)

GASC—Jobs

0.59 (0.30)

0.51(0.31)

0.67 (0.27)

GASC—Non Jobs

0.59 (0.29)

0.52(0.29)

0.65 (0.28)

mGASC—All items

0.52 (0.34)

0.43(0.32)

0.61 (0.34)

mGASC—Jobs

0.48 (0.35)

0.40(0.33)

0.56 (0.35)

mGASC—Non Jobs

0.56 (0.33)

0.46(0.32)

0.65 (0.33)

Effect

Gender

Gender Job Gender

Note. GASC = Gender-Stereotyped Attitude Scale for Children. mGASC = Modified Gender-Stereotyped Attitude Scale for Children. Ratio scores are based on the number of cases when both was selected out of all possible answers. Each scale has 23 test items consisting of two components: jobs (with 6 test items) and nonjobs (with 17 test items). The Gender Effect indicates a significant difference in the mean ratio scores between boys and girls tested with a t test and at least a p < .05 level. The Job Effect indicates a significant difference in the mean ratio scores between job and nonjob items within the mGASC as tested with a t test and having at least a p < .05 level.

Explicit Gender Attitudes Next, we predicted that children would be flexible regarding explicit gender stereotypes about male and female activities, including ones about occupa­ tions. As predicted in our second hypothesis, the most frequent selection on the GASC scale was both men and women, indicating gender flexibility about stereotypical male and female activities. To examine children’s gender attitudes with a focus on occupations, items related to occupations or jobs were compared with other activities or nonjob items on the scale. As seen in Table 2, children’s moderate and high ratio scores reflect flexibility for both the job and nonjob items of the GASC. The ratio scores ranged from 40% when boys rated jobs on the mGASC to 67% when girls rated jobs on the GASC. Unexpectedly, girls were more flexible than boys on the job component of the GASC, t(56) = −2.12, p = .039, d = 0.55.

We also predicted that children’s explicit gender attitudes would be flexible and egalitarian when presented with the specific case of gender atti­ tudes being applied to the firefighter-paramedics in the video. Our third hypothesis was confirmed; the most frequent selection on the mGASC scale was both Kate and Jeremiah (56%), indicating a general flexibility about activities and gender.

Next, we examined attitudes about occupations more closely in a paired-samples t test. As seen in Table 2, there was more flexibility for the nonjob items (i.e., 56%) as compared with the job items (i.e., 48%) for Kate and Jeremiah on the mGASC, t(56) = −2.90, p = .005, d = 0.24.

We predicted that boys and girls would have similar explicit attitudes; however, the independentsamples t test GASC findings were mixed on this prediction. As seen in Table 2, the collapsed GASC scores did not differ significantly for boys and girls, t(56) = −1.94, p = .058, d = −0.48. We did observe a significant gender difference for the collapsed mGASC scores, with girls having higher ratio scores, or more flexible gender attitudes as compared with boys, t(56) = −2.19, p = .033, d = 0.54. In contrast to the GASC findings, girls did not demonstrate significantly more stereotype flexibility than boys in the job components of the mGASC, t(56) = −1.78, p = .080, d = 0.55, but girls were more flexible than boys in the nonjobs component of the mGASC scale, t(56) = −2.23, p = .030, d = 0.58.

Children did not uniformly select both across all six jobs. Children had the highest level of stereotype flexibility for doctor in which 25 out of 28 boys responded and 26 out of 29 girls responded that

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Brown and Weinberger | Children's Attitudes About Gender and Occupations

both men and women should be a doctor. Fewer children responded that both Kate and Jeremiah should be a doctor; specifically, 12 boys and 19 girls.

The lowest level of gender stereotype flexibility was for ballet dancer/teacher in which 8 out of 27 boys responded and 16 out of 28 girls responded both men and women should be a ballet dancer/teacher.

Even fewer responded that both Kate and Jeremiah should be a ballet dancer/teacher, that is 4 boys and 10 girls. There were few cases where children responded that men (n = 1) or Jeremiah (n = 8) should be a ballet dancer/teacher; boys made the counter-stereotyped option for 7 of these 9 cases.

Lastly, in an exploratory research question, we asked how children would evaluate the female firefighter’s occupation abilities and the occupation abilities of her male counterpart. The occupation ability ratings were high for both Kate and Jeremiah, with Kate’s average ratings always higher than Jeremiah’s ratings (see Table 3). The range of rat­ ings on a 7-point scale was 5.86 to 6.76 for Kate and 5.14 to 6.41 for Jeremiah. Children endorsed Kate’s abilities more positively than Jeremiah when judging her being good in medical emergencies, t(106.22) = 2.49, p = .014, d = 0.46, and being good at saving lives in a fire, t(86.42) = 2.27, p = .026, d = 0.42. When children were asked questions about who would be better at doing their job, Kate, Jeremiah, or both Kate and Jeremiah, the most frequent response was both Kate and Jeremiah as seen in Table 3. Moreover, children frequently selected Kate as a second choice after both for these questions. For example, 91% of children selected Kate or both for who would be a better fire chief. Unlike the ability ratings, there were gender differences for ability rankings with girls always selecting both more often than boys. In four out of six of the rankings, the difference was significant, as tested by Fisher Exact and Chi-square tests. The greatest ranking disparity was found in the case of the question of who would be a better fire chief. The choice of both was selected by 38% of boys and 75% for girls, χ2 = 8.97 [2, 57], p = .011, d = 0.69.

Discussion In the present study, we expected to demonstrate that children have implicit associations that strictly link occupations with one’s gender. Our findings did not support this prediction and the possible explanation for this unexpected finding is consid­ ered here. Although prior research with 10-year-old children has demonstrated the pervasiveness of implicit gender-biased attitudes (Dunham et al., 2015), our findings suggest that implicit associations

may not be present in all domains. Other research­ ers may dispute this conclusion given the findings from two other studies with children in middle childhood that revealed children’s implicit gender associations regarding occupations.

In one of the studies, 8- and 9-year-old children were asked to generate sentences with gender ste­ reotypical name-occupation pairings (Henry-auto mechanic) and generate sentences with counter stereotypical pairings (e.g., Henry-nurse; Wilbourn & Kee, 2010). Across several measures, including mean response latency, children demonstrated TABLE 3 Occupation Ability Ratings and Rankings Occupation Ability Ratings (scale 1–7)

All Children M(SD)

Kate is good at her job as a firefighter/paramedic

6.47 (0.78)

Jeremiah is good at his job as a firefighter/paramedic

6.16 (1.07)

Kate is good at her job in medical emergencies

6.14 (1.15)

Jeremiah is good at his job in medical emergencies

5.52 (1.51)

Kate is good at saving lives when there is a fire

6.71 (0.68)

Jeremiah is good at saving lives when there is a fire

d

Boys M(SD)

d

6.48(0.95)

Girls M(SD)

d

6.45 (0.57) 0.57a

6.24(1.33)

6.07 (0.75) 6.24 (0.83)

6.03(1.40) 0.46a

0.55a 5.14(1.79)

5.90 (1.08)

6.76(0.79)

6.66 (0.55)

6.28 (1.28)

6.14(1.66)

6.41 (0.73)

Kate is good at being part of the team of firefighters/paramedics

6.57 (1.04)

6.52(1.33)

6.62 (0.68)

Jeremiah is good at being part of the team of firefighters/paramedics

6.26 (1.18)

6.17(1.51)

6.34 (0.72)

Kate would be a good fire chief

6.14 (1.34)

5.86(1.74)

6.41 (0.73)

Jeremiah would be a good fire chief

5.74 (1.45)

5.45(1.72)

6.03 (1.05)

Occupation Ability Rankings (Percentage both selected)

0.42a

All Children

d

Boys

Who does a better job as a firefighter/paramedic?

72

0.58b

59

86

Who does a better job in medical emergencies?

64

0.56b

52

76

Who does a better job at saving lives when there is a fire?

79

0.57b

69

90

Who would you choose to save someone from a burning building?

53

52

55

Who is better at being part of a team of firefighters/paramedics?

90

83

97

Who would be a better fire chief?

56

38

75

0.69b

d

Girls

d

Note. The superscript indicates a significant difference in the mean occupation ability ratings between Kate and Jeremiah as tested with an ANOVA with at least a p < .05 level. Cohen’s d effect sizes are only shown in the cases of significant differences. The b superscript indicates a significant gender difference in the percentages of the occupation ability rankings between boys and girls as tested with Chi-Square and Fisher Exact tests with at least at the p < .05 level. Cohen’s d effect sizes are only shown in the cases of significant differences. a

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the greatest difficulty when males were paired with traditionally female occupations. Moreover, chil­ dren often manipulated the counter-stereotyped information to fit with gender stereotypes. When presented with a female name and a stereotypically male occupation, some children would manipulate the sentence to either change the gender of the person (i.e., “Julie the Police Officer” became “Julian the police officer fights crime”), or a part of the occupation (i.e., “Henry the nurse is a doctor, too; Wilbourn & Kee, 2010). In another study that measured response time to assess implicit gender associations with occupations, participants were asked whether individually presented occupations paired with kinship terms they heard could describe the same person (Siyanova-Chanturia et al., 2015).

For example, could “engineer-sister” describe the same person? Children in 8-year-old and 10-year-old groups and adults more consistently responded “yes” and did so more quickly for stereotypically congruent word pairings than incongruent pair­ ings. The testing methods differed from the current study in which Most et al.’s (2007) auditory Stroop task was adapted.

Indeed, Siyanova-Chanturia et al. (2015) had noted problems with the Most et al. task methodol­ ogy. One concern was that there was no coherent rationale for the mix of target words used in the Most et al. study. This was not a problem in the adaptation we used because all of our target words were occupations. Yet, like Most et al. (2007), we did not control the lexical properties of words. In the Siyanova-Chanturia et al. (2015) study, auditory stimuli were carefully constructed, fully synthesized, neutral and natural sounding voices. In addition, it is worth noting that our adapted auditory Stroop task was designed to be easy enough to be used by young preschool children. Therefore, our 10-year-old participants might have found that the incongruent trials were not very difficult to process and therefore took about the same amount of time to react to the auditory cues in the congruent and incongruent trials. In summary, the current results indicated that children do not have implicit gender associations about occupations.

The lack of control of the lexical properties of the auditory Stroop task used in the current study may partially explain the unforeseen finding that participants’ responses to the male voices were significantly faster than their responses to the female voices, independent of occupation pairing. Prior research on the perception of voices has indicated that people are sensitive to voice characteristics

and make important evaluations based on voice qualities associated with gender (Doubleday & Lee, 2016). For example, it has been found that voicebased biases favoring men can affect how health professionals are evaluated. Relatively low pitch in voices, associated with masculinity, is preferred for both male and female voices when individuals are making hypothetical leadership choices (Anderson & Klofstad, 2012). Voice qualities have also affected hypothetical hiring decisions. Men and women using low pitched, creaky voices known as vocal fry, are evaluated poorly overall and less hirable than others; the poor evaluations were stronger for female voices (Anderson et al., 2014). Variations in female voice quality based on pitch and formant spacing has been shown to affect adults’ percep­ tion of social traits (Levitt & Lucas, 2016). In other words, characteristics of voice stimuli matter and the children in the current study responded more quickly to the male voice as compared with the female voice most likely due to the differences in the unmeasured lexical qualities of the voice stimuli.

Regarding explicit attitudes, children in our study were generally flexible as predicted, which is consistent with the findings for children’s implicit associations. On both the GASC and mGASC, the most common choice was both. The findings merit a cautious interpretation because children were presented the video prior to answering ques­ tions on both forms of the GASC, and it might have impacted not only the views about Kate and Jeremiah but also about men and women generally.

There were unexpected gender differences on these scales, but they were not uniformly present across scales or component parts. Nevertheless, in each case of a gender difference, girls had greater attitude flexibility than boys. Thus, our predic­ tion that there would be no gender differences might have been based too strictly on the research findings from an earlier time when the GASC was developed (Signorella & Liben, 1985).

Other explicit measures of gender attitudes commonly find that girls have more flexible gender attitudes than boys. A notable example comes from the recent meta-analytical study of the Draw a Scientist methodology (Miller et al., 2018). In this methodology, children were prompted to draw a scientist; 96% of the boys drew a male scientist, whereas only 58% of the girls drew a male scientist.

These results reflect a meaningful shift toward an equalitarian perspective, particularly for the girls.

In the original Chambers (1983) study, only 28 out of 5,000 children selected a woman as a scientist.

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Brown and Weinberger | Children's Attitudes About Gender and Occupations

Children in the current study differed in how flexibly they linked gender with occupations as a function of the occupations themselves. This link­ ing may be due in part to children’s exposure to different samples of careers. It is likely that most children in middle childhood have seen women and men in a range of professional roles, more so than in earlier decades. As a point of reference, 60% of pediatricians were female compared to 33% of phy­ sicians overall who were female in the United States as of 2013 (AAMC, 2014). As a result, children may be more readily accepting of female doctors than other counter-stereotypical examples. In our study, doctor was the most flexible career item among boys and girls. The lowest level of gender stereotype flexibility was found for the ballet teacher/dancer item, supporting prior research that roles for men are more restrictive and tightly held than roles for women (Blakemore, 2003; De Visser & McDonnell, 2013; Henshaw et al., 1992; Wilbourn & Kee, 2010).

This also makes sense because professional roles are not equally occupied by women and men and children can see this for themselves.

Children’s evaluations focusing on the fire­ fighter-paramedics shown in the video make clear that the female professional was evaluated equally or more favorably than her male counterpart. For example, participants rated Kate as better than Jeremiah in medical emergencies, possibly because Kate mentioned her prior work in a hospital as an occupational therapist. When asked who would be a better fire chief, participants chose Kate or both 89% of the time. Although this could reflect that there are more women firefighters, we doubt this explanation because only ~8% of firefighters in the United States are women (National Fire Protection Association, 2020). Thus, we interpret this find­ ing to reflect the short-term benefits of viewing counter-stereotypical examples of occupational roles. Because Jeremiah did not have a speaking role, Kate’s expertise as a firefighter was clearly the focus of this video. Alternatively, if children had interpreted Jeremiah as the better leader, that might have reflected that even knowing Kate’s expertise did not outweigh Jeremiah’s presence as a man.

Limitations and Strengths The novel auditory Stroop task is an inadequate test for the current study goals and might have revealed more about voice and gender associations than occupation and gender associations. Therefore, it is not recommended for future tests of genderoccupation associations.

The findings pertaining to children’s explicit attitudes should be considered in the context of the following methodological limitations. First, there were no contrasting conditions; either pre- and post­ video exposure or exposed versus nonvideo exposed condition. Second, the video was presented before both forms of the GASC and might have impacted not only attitudes about Kate and Jeremiah but also women and men generally. Third, the implicit association and explicit occupation attitude mea­ sures did not include exemplars of firefighter or paramedic. These test items could have been used as an approximation of how much children associated firefighters and paramedics with men, women, or both. Fourth, the video only included a female in a counter stereotypical occupation and not a male in a counter stereotypical occupation. A fifth study limitation is that the occupational status of the parents of participants in this small sample was not available. Parents are children’s primary models for occupational and other roles. Unfortunately, the impact of parental employment generally and regarding counter-stereotypical employment specifi­ cally, could not be examined. Ultimately, the study limitations can guide future research.

Despite these limitations, this study has several notable strengths. We selected a readily available and high-quality video from the PBS SciGirls series that was developed about women in science and sci­ ence careers and consider its counter-stereotypical depiction of a firefighter-paramedic. This video featured Kate, a firefighter who described her job and successes, and Jeremiah, her firefighter partner who did not have an active role. By modifying the GASC, we were able to assess attitudes toward the specific woman featured in the video and deter­ mine that children overwhelmingly saw her as a potentially good fire chief (vs. Jeremiah). Another strength of the sample in spite of its small size was its racial and ethnic diversity.

Future Research Implications It would be constructive to examine children’s thinking about equalitarian occupational roles that were demonstrated in the current study. Do children respond to queries about who should have a job based on what they see in the world or what they would like to see? If it is what they would like to see, why would they choose to see gender equality in the world? Examining parental role models and parental messaging along with measuring children’s attitudes about what is fair may help to tease apart if they are describing what they see or what they

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believe is right and should happen.

In addition, a continued focus on women in counter stereotypical occupations is valuable if done with experimental controls. The Sci Girls series is particularly strong because they include many different types of women, beyond the ideal­ ized European American woman who is often represented as the “standard” woman for many issues (i.e., gender pay gap). Thus, future studies can broaden our understanding of gender attitudes by looking at the breadth of gendered experiences rather than one type of women’s experiences.

Research focusing on children’s attitudes about males in counter-stereotypic careers is also war­ ranted. In our study, ballet teacher/dancer was the most stereotyped item as the participants said that Jeremiah should be a ballet teacher/dancer only 25% of the time. A study examining longitudinal labor force trends in the United States from 1950 to 2000 found evidence to support the theory that work done by women is devalued in the labor force causing occupation-wide inequities in wages (Levanon et al., 2009).

Future research that explores the impact of counter stereotypic exemplars on gender biases is particularly important given that flexible attitudes are not comprehensive across all occupations and other domains of potential bias. Prior research has highlighted that reading fiction can influence readers’ real-world beliefs and even promote more acceptance of interpersonal differences (Xu et al., 2013). Thus, future work may focus on encourag­ ing children to read fiction featuring counterstereotypical occupation models as a method of broadening children’s gender flexibility. Others have recommended that elementary schools create programs that invite wide arrays of professionals to visit (Chambers et al., 2018). Such efforts need to carefully counteract stereotypes rather than reinforce them. An illustration of this need can be found in a recent example when a preschool child told her mother that girls could not be firefighters since that is what she saw in books (Ritschel, 2019).

The parent’s social media request for images and books with female firefighters was profoundly successful, with countless professionals sharing book suggestions and their personal pictures. This opportunity needs to be widely available to children and there are programs that are doing just this. For example, Rice University’s Institute for Biosciences and Bioengineering in Houston, Texas hosts a “Girls STEM Initiative,” which immerses economi­ cally disadvantaged young women in cutting-edge

research across disciplines. They are paired in small groups with mentors (many of whom are also young women) who demonstrate their research, teach basic techniques, and answer any questions they have about pursuing STEM in college. In sum, abundant and richly detailed counter stereotypical models can offer opportunities to overcome gener­ alized gender biases about occupations.

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Brown and Weinberger | Children's Attitudes About Gender and Occupations

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Correspondence concerning this article should be addressed to Ryan Brown, Department of Psychological Sciences, Rice University. Email: rlb11@rice.edu

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https://doi.org/10.24839/2325-7342.JN26.1.14

The Effects of Self-Esteem, God Image, and Gender on Coping Methods Jessica Downing, Christina Sinisi, and Rebecca Foster Department of Psychology, Charleston Southern University

ABSTRACT. Factors such as self-esteem, God image, and gender can affect the way an individual copes with everyday stressors. Past research has shown high self-esteem to have a significant relationship with problemfocused coping, whereas low self-esteem produced mixed results between avoidance and emotion-focused coping (Chapman & Mullis, 1999).

Regarding God image, a sense of God’s presence contributed to a healthy, positive coping strategy for individuals facing difficulties (Aten et al., 2008). Studies examining the influence of gender on coping methods have generated mixed results (Cecen, 2008). The present study examined the impact of gender, self-esteem, and God image on coping methods.

Participants (N = 368) completed a survey online. Results showed that gender, self-esteem, and perceiving God as Present, Benevolent, Provident, and Challenging were significant predictors of utilizing problem-focused coping, F(8, 344) = 8.27, p < .001. Gender and viewing God as Benevolent and Accepting had significant effects on emotion-focused coping, F(8, 344) = 3.44, p = .001. Lastly, perceiving God as less Accepting was a significant predictor of using avoidance to cope, F(8, 344) = 6.44, p < .001.

In conclusion, given the potential impact of God image on coping, clinicians working with individuals who espouse a faith could incorporate the clients’ images of God into treatment and examine how these factors impact their ability to cope with life stressors.

Keywords: God image, coping, gender, self-esteem

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tress can stem from a variety of sources such as illnesses, relationships, work demands, and adverse circumstances (Aten et al., 2008; Hensley & Hurt, 2014). If individuals do not properly manage the stressors in their lives, the stress that follows as a consequence can potentially lead to a variety of negative effects listed as follows: sleep deprivation, eating irregularity, depression, and emotional instability (Hensley & Hurt, 2014).

Humans use coping strategies to alleviate the tension that accumulates in their lives; however, each individual copes with stress in a unique way.

The coping methods that individuals utilize can be influenced by factors such as God image, self-esteem, and gender.

Coping strategies are defined as cognitive and behavioral efforts people make when confronting different stressors (Sharif et al., 2014). Three of the most common coping methods used are emotionfocused, problem-focused, and avoidance (Green et al., 2010). Emotion-focused coping refers to an individual working to alter negative emotions and regulate emotional distress through tactics such as seeking social support or expressing emotions.

Problem-focused coping refers to an individual’s efforts to overcome stress by problem solving and actively implementing solutions to improve the source of stress. Finally, avoidance coping strategies refer to an individual who attempts to avoid process­ ing stressful situations altogether by minimizing or

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Downing, Sinisi, and Foster | Self-Esteem, God Image, Gender on Coping

ignoring their problems (Green et al., 2010).

The coping methods individuals use can be influenced by their God image, which is a person’s belief about the nature and character of God (Lawrence, 1997). Although past research only considered general ways of coping, the present study considered the relationship between God image and specific coping strategies. The current study also examined the six different dimensions of God image. First, the Presence dimension is the extent to which individuals view God as being there for them. Second, the Challenge dimension consid­ ers whether or not God challenges individuals to grow in a positive manner. Scoring high in these two dimensions indicates a secure attachment to and view of God. Third, the Acceptance dimension examines the extent to which people feel that God loves them personally; the fourth dimension, Benevolence, examines whether or not an individual thinks God loves everyone. The last two dimensions are Influence, which considers if a person thinks God does what individuals ask Him to do, and Providence, which considers if a person views God as being in control of all circumstances (Lawrence, 1997).

A purpose of the current study was to examine the impact of God image on an individual’s coping style. A research study done with cancer survivors showed that participants who viewed God as highly engaged in their lives were able to use their God image in a positive way to help them cope with their illnesses (Schreiber, 2011). Another study consisted of 21 Hurricane Katrina survivors who had suffered loss during the storm. Results showed that, even in the midst of a traumatic experience, participants’ views of God as being present helped them get through their adverse situations (Aten et al., 2008). Viewing God as engaged and present helped individuals who survived both severe illness and natural disaster cope with their stress (Aten et al., 2008; Shreiber, 2011). Although these studies considered how viewing God influences one’s ability to cope with a traumatic experience, they did not examine the different coping methods, the several dimensions of one’s God image, or the impact of God image on coping with general stress.

Scarce research has examined the effects of God image on self-esteem. Studies have shown that people with strongly held religious beliefs have high self-esteem (Holt et al., 2014), and those who view God as loving and empathetic may experience esteem-enhancing emotional support (Pargament, 1997). Furthermore, even the self-esteem of chil­ dren is influenced by God image, as Smith and

Crosby (2017) found that a child’s God image was related to self-esteem.

Self-esteem seems to influence how people choose to cope with stress in their lives. Chapman and Mullis (1999), in a study that included 361 male and female adolescents, found that adolescents with low self-esteem practiced avoidance coping behaviors more than those with high self-esteem. In contrast, Mullis and Chapman (2000) revealed slightly dif­ ferent results when examining the same adolescent age groups. Rather than low self-esteem leading to avoidance coping, the researchers found that those with low self-esteem practiced emotion-focused cop­ ing. Moos (1990) supported these findings through research with adolescents as well. Although results about individuals with low self-esteem in these stud­ ies differed slightly, each of the studies found that individuals with high self-esteem were more likely to utilize problem-focused coping (Chapman & Mullis, 1999; Mullis & Chapman, 2000).

Furthermore, although past research involv­ ing gender and God image exists, little research has specifically examined how gender influences which God image an individual holds. In one study, researchers found that women had higher scores on each God image than men did (Nguyen & Zuckerman, 2016). Although researchers expected to find that women prefer to view God only as rela­ tional and as a provider, they found that women also endorsed the image of God as a creator. Although men did not endorse the God images as strongly as the women did, they also viewed God as relational, as a provider, and as a creator. In an additional study examining the effects of gender on God image in adolescents, the different dimensions of God image were examined, but no significant differences were found between genders (Meier & Meier, 2004).

Gender has been reported as a significant predictor of coping styles. A study conducted by Chapman and Mullis (1999) revealed that men scored higher in avoidance coping than did women.

Researchers found that being a woman did not predict a specific coping behavior; however, women did show higher rates of seeking external social sup­ port to cope with stress (Chapman & Mullis, 1999).

Another study that was completed with college students found that men had more of a tendency to use problem-focused strategies whereas women were more likely to seek social support (Cecen, 2008).

Additional research from Ptacek and colleagues (1992) found that women practiced emotion-focused coping methods more frequently than men.

In conclusion, the present study measured the

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Self-Esteem, God Image, Gender on Coping | Downing, Sinisi, and Foster

effects of self-esteem, God image, and gender on coping strategies. No past research has considered these variables in combination. It was predicted that (a) individuals with a positive God image, who specifically view God as present, are more likely to practice problem-focused coping, (b) individuals with low self-esteem are more likely to practice emotion-focused coping, (c) individuals with high self-esteem are more likely to practice problem-focused coping, (d) male participants will practice problem-focused coping more in relation to female participants, and (e) female participants will practice emotion-focused coping more than male participants. Overall, individuals with high selfesteem, who view God as present and engaged, will be more likely to practice problem-solving coping.

Method Participants Four hundred and eight undergraduate students from a private, Christian university participated in this study. Due to incomplete data, 40 participants’ data were discarded, leaving 368 undergraduate participants (79 men, 288 women, 1 unknown).

Participants’ ages ranged from 18–50 (M = 20.97, SD = 4.61). There were 227 participants who identi­ fied as European American (61.7%), 106 African American (28.8%), 18 “other” (4.9%), 10 Asian (2.7%), 6 Hispanic (1.6%), and 1 unknown (0.3%).

Most claimed to be Christians (n = 350, 95.1%), 8 “other” (2.2%), 5 Agnostic (1.3%), 2 Jewish (0.5%), 2 unknown (0.5%), and 1 atheist (0.3%).

The denominational representation was as follows: Baptist (n = 147, 39.9%), Non-Denominational (n = 114, 31%), Catholic (n = 27, 7.3%), “other” (n = 22, 6%), unknown (n = 26, 7.1%), Methodist (n = 21, 5.7%), Pentecostal (n = 12, 3.3%), Presbyterian (n = 3, 2%), Lutheran (n = 5, 1.4%).

Materials In this study, the materials consisted of a consent form, demographics form, the Rosenberg SelfEsteem Scale (Rosenberg, 1965), Feelings of Self-Worth Measure (Critcher & Dunning, 2015), God Image scale (GIS; Lawrence, 1997), Religious Commitment Questionnaire (RCQ; Peterman et al., 2014), the Coping Style Questionnaire (Howerton & Van Gundy, 2009a), and a debriefing form.

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Self-Esteem This 10-item scale, written by Rosenberg (1965), uses a 4-point Likert-type scale from 1 (strongly disagree) to 4 (strongly agree) to examine participants’

perceptions of their own self-esteem. Cronbach’s alpha for this scale in the present study was .87; in past research, Cronbach’s alphas have ranged from .72 to .90 (Robins et al., 2001).

Self-Worth Another variable measured was feelings of selfworth. The Feelings of Self-Worth Measure (Critcher & Dunning, 2015) was used to test for both negative and positive feelings of self-worth. This 14-item, 9-point Likert-type scale ranges from 1 (not at all) to 9 (extremely). Cronbach’s alpha was reported as .91 for the negative feelings subscale and .92 for the positive feelings subscale. This measure was not relevant to the original hypotheses; therefore, no further information will be provided about The Feelings of Self-Worth Measure. Analyses using this measure are being pursued in further publications.

God Image The GIS was used to measure God image in this study. This is a 72-item, 4-point Likert-type subscale from 1 (strongly agree) to 4 (strongly disagree) of the 158-item God Image Inventory written by Lawrence (1997). The GIS consists of six subscales which are listed as follows: Presence, Challenge, Acceptance, Benevolence, Influence, and Providence. Internal reliability of each subscale ranges from .95–.99.

Lawrence (1997) reported alphas ranging from .85–.96.

Religious Commitment Religious commitment was measured using the RCQ, written by Peterman et al. (2014). This 6-item Likerttype scale measures how important religious beliefs are to participants. This is determined by three factors: importance and influence of faith (1 = not important, 5 = very important), frequency of prayer (1 = never, 6 = more than once per day), and frequency of religious service attendance (1 = never, 6 = more than once per week). The RCQ demonstrates an internal reliability of .72. Because the RCQ was not relevant to the original hypotheses, no further information will be provided. However, analyses using this measure are being pursued in further publications.

Coping Style The Coping Style Questionnaire was used to measure participants’ coping styles (Howerton & Van Gundy, 2009a). It is a 12-item measure that asks participants about activities that bring about stress as well as how they choose to handle stress.

Using this questionnaire, three different types of coping methods were measured: problem-focused,

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Downing, Sinisi, and Foster | Self-Esteem, God Image, Gender on Coping

emotion-focused, and avoidance-focused. In the present study, Cronbach’s alpha for these subscales ranged from .65–.72; Howerton and Van Gundy (2009b) reported alphas of .72, .67, and .65, respectively.

Table 1. A series of multiple linear regression analy­ ses was performed to predict the various types of cop­ ing. First, problem-focused coping was paired with the predictor variables of biological sex, the six GIS scores, and self-esteem. The forced-entry method was used with all independent variables entered in a single block. The 95% confidence intervals are reported for all B-values, as are semipartial correla­ tions between the dependent variable and each of the independent variables. Effect size was measured

by Cohen’s f 2 (0.02 = small effect, 0.15 = medium, 0.35 = large). The model explained a medium amount of the variance in problem-focused coping, R 2 = .17, adjusted R 2 = .14, F(8, 344) = 8.27, p < .001.

As indicated in Table 2, all variables except percep­ tions of God’s Influence and God’s Acceptance contributed to the model significantly. The effect size was small in all cases. In particular, gender, selfesteem and perceiving God’s Benevolence, Presence, Providence, and Challenge were significant predic­ tors of utilizing problem-focused coping.

Next, emotion-focused coping was paired with the predictor variables of biological sex, the six GIS scores, and self-esteem. The model explained a small amount of variance in emotion-focused coping, R 2 = .09, adjusted R 2 = .05, F(8, 344) = 3.47, p = .001. As indicated in Table 3, only gender and viewing God as Benevolent or Accepting had significant effects on emotion-focused coping. Females and individuals who perceived God as accepting and benevolent were most likely to use emotion-focused coping.

Finally, the third linear regression paired avoidance coping with the predictor variables of biological sex, the six GIS scores, and self-esteem.

Procedure After researchers gained approval from the insti­ tutional review board, they administered the survey online through the Qualtrics survey web­ site. Participants were recruited from Charleston Southern University via Blackboard. The survey required the participants to complete an informed consent form before participating. If participants chose to continue, they were asked to complete a short demographic survey. The next step was to com­ plete the following: Rosenberg Self-Esteem Scale, Feelings of Self-Worth Measure, GIS, RCQ, and Coping Styles Questionnaire. Finally, participants were directed to a debriefing form, and an extra credit slip.

Results To assess the impact of self-esteem, gender, and God Image on coping, a series of stepwise multiple regression analyses were performed. Each analysis considered the predictor variables in relation to avoidance, emotion-focused coping, and problemfocused coping separately. Then, exploratory analy­ ses concerning the impact of positive and negative self-worth, religious status, and religiousness were conducted using analysis of variance.

Data were analyzed using IBM SPSS v. 26.

Correlations between all variables can be found in

TABLE 1 Correlations Between Types of Coping, Gender, Self-Esteem, and God Image Scores Gender Gender Self-esteem

God as Accepting

God as Present

God as a Provider

–

Self-esteem .052

−.123*

−.261*

−.107

−.118*

−.124*

−.206**

.052

–

.423

.242

.474

.382

**

.260

.273**

.617**

.660**

.858**

.728**

.653**

.803

.728

**

.605

.746**

.764**

.590**

.698**

.791

.702**

Influence

−.123*

.423**

Benevolence

−.261

Acceptance

*

.107*

God's Influence

God's Benevolence *

–

.242

**

.617

–

.474**

.660**

.803**

**

**

**

**

**

–

Presence

−.118

.382

.858

.728

.764

Providence

−.124*

.260**

.728**

.605**

.590**

.791**

Challenging

−.206

.273

.653

.746

.698

.702

.564

Problem-focused coping

.107

−.264

−.276

−.186

**

−.273

−.281

−.143

−.293

Emotion-focused coping

.209**

−.031

−.112*

−.089

−.137**

−.111

−.074

−.152**

Avoidance coping

.017

.237

.199

.263

.355

.246

.201

.237

*

*

**

** **

**

**

** **

**

**

** **

**

**

–

God as Challenging

**

**

** **

**

**

–

−.293** –

** **

**

**

**

Note. * indicates p < .05. ** indicates p < .01 (2 tailed).

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Self-Esteem, God Image, Gender on Coping | Downing, Sinisi, and Foster

TABLE 2 Multiple Regression Analysis Predicting Problem-Solving Coping With Gender, Self-Esteem, and Six God Image Scores Predictor

B

Constant

95% CI for B

Semi- Cohen’s f 2 partial r

T

p

14.10

13.48

<.001

.64

2.08

.04

.04 – 1.24

.10

.08

Self-esteem

−.07

−2.48

.01

−.12 – −.01

−.12

.06

Perceived God’s Influence

−.01

−0.31

.76

−.09 – .07

−.02

.18

Gender

12.04 – 16.16

Perceived God’s Benevolence

.10

2.39

.02

.08 – .18

.12

.06

Perceived God’s Acceptance

−.05

−1.12

.26

−.13 – .04

−.06

.13

Perceived God’s Presence

−.09

−2.06

.04

−.17 – −.00

−.11

.07

.08

2.39

.02

.01 – .15

.13

.05

−.12

−2.88

<.01

.07 – −.04

−.15

.02

Perceived God’s Providence Perceived God as Challenging

TABLE 3 Multiple Regression Analysis Predicting Emotion-Focused Coping With Gender, Self-Esteem, and Six God Image Scores Predictor

B

Constant Gender Self-esteem Perceived God’s Influence

95% CI for B

Semi- Cohen’s f 2 partial r

T

p

12.15

8.18

<.001

1.69

3.86

<.001

.83 – 2.55

.20

.13

.02

0.52

.60

−.06 – .10

.03

.05

9.30 – 15.20

−.01

−0.21

.84

−.13 – .10

−.01

.08

Perceived God’s Benevolence

.13

2.23

.03

.02 – .25

.12

.04

Perceived God’s Acceptance

−.13

−2.14

.03

−.24 – −.01

−.11

.03

Perceived God’s Presence

−.00

−0.02

.99

−.12 – −.12

−.00

.09

.01

0.23

.82

−.08 – −.11

.01

.08

−.09

−1.55

.12

.12 – −.03

−.08

.00

Perceived God’s Providence Perceived God as Challenging

TABLE 4 Multiple Regression Analysis Predicting Avoidance Coping With Gender, Self-Esteem, and Six God Image Scores Predictor

B

T

p

95% CI for B

Constant

2.01

2.24

<.05

.24 – 3.78

Gender

Semi- Cohen’s f 2 partial r

.18

0.70

.49

−.34 – −.70

.04

.12

Self-esteem

−.04

1.85

.07

−.00 – .20

.09

.06

Perceived God’s Influence

−.04

−1.02

.31

−.11 – .03

−.06

.09

Perceived God’s Benevolence

−.00

−0.10

.92

−.07 – .07

−.01

.15

Perceived God’s Acceptance

.12

3.26

.01

.05 – .19

.17

.03

−.01

−0.24

.81

−.08 – .06

−.01

.15

Perceived God’s Providence

.02

0.74

.46

−.04 – .08

.04

.12

Perceived God as Challenging

.01

0.39

.70

−.06 – .09

.02

.14

Perceived God’s Presence

18

The model explained a small amount of variance in avoidance coping, R 2 = .14, Adjusted R 2 = .12, F(8, 344) = 6.74, p < .001. As can be seen in Table 4, the dimension of GIS as Accepting contributed to the model significantly. Given the scoring of the GIS, a positive correlation in this case indicates that viewing God as less accepting contributed to an increased use of avoidance coping.

Discussion The overall purpose of this study was to determine how God image, self-esteem, and gender affect one’s ability to cope with stress. It was hypothesized that individuals who view God as Present would practice problem-focused coping; this was sup­ ported. However, a number of other dimensions also predicted problem-focused coping, which was not originally hypothesized. Further, although it was also hypothesized that gender and self-esteem would predict coping, self-esteem only predicted problemfocused coping and not the other two methods of coping. Gender predicted both problem-focused and emotion-focused coping but not avoidance.

Gender and self-esteem, in addition to the Benevolence, Providence, Presence, and Challenge dimensions were all predictors of problem-focused coping. Viewing God as present, having high self-esteem, and being male were the focus of the original hypotheses. Results of this study suggest that individuals with higher self-esteem scores, who believe God is in control, loves and supports all individuals, and wants individuals to grow, tend to actively cope with their stressors through problemfocused coping methods. This cluster of God image dimensions seems to correspond to a locus of con­ trol in which God is in control. Rather than being an external locus of control, God control appears to be equivalent to an internal locus of control where individuals are responsible for addressing their own problems because God has given them talents and abilities (Welton et al., 1996). These findings suggest that individuals with higher self-esteem, who believe God is in control, have the confidence needed to deal directly with stressful circumstances.

Results also revealed that female participants and individuals who view God as accepting and benevolent are more likely to utilize emotionfocused coping. These results are congruent with past research indicating that women often seek social support during coping and men tend to actively work through stressful situations (Cecen, 2008). Gender differences related to coping could be due to the sociocultural expectations placed

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upon women and men (Chapman & Mullis, 1999).

Furthermore, those who believe God loves and accepts them, regardless of their circumstances, may overcome stressors by simply relying on God’s comfort and focusing on His love and acceptance.

Lastly, individuals who do not view God as accept­ ing of them are more likely to utilize avoidance cop­ ing. These results seem to correspond with another area of research considering religious coping rather than generalized coping. Negative religious coping, particularly spiritual discontent, refers to a belief that one is not deserving of God’s love (Lehmann & Steele, 2020). Because negative religious coping can contribute to passivity and deferring problem-solving, this kind of coping can exacerbate posttraumatic stress (Lehmann & Steele, 2020).

Limitations of the study include a lack of diversity in race, educational level, and religious beliefs held by the participants. Religious views of the participants are highly reflective of Western religious principles, and further research could seek a sample which includes a broader scope of religious beliefs (i.e., Eastern religions). Effect sizes were small; consequently, a follow-up study should consider examining additional factors that have typi­ cally been found to influence the coping methods individuals use. The instruments were presented in order; future research could counterbalance the instruments to negate the negative impacts of participant fatigue and response sets. Although the Coping Style Questionnaire is a well-established and frequently used measure, its assessment of coping is narrow. Future research may include measures that consider types of stressors, current coping skills, and distress level of participants. Lastly, the present study was the first to examine God image as separate dimensions in relation to specific coping styles.

High interscale correlations may serve as a limiting factor current analysis. However, significant differ­ ences were found in the relation of the individual dimensions to coping strategies, indicating that they should be considered as separate dimensions.

Due to the global prevalence of religion (Pew Research Center, 2012) and the impact of religion in individuals’ lives, further exploration involving God image and its relationship to coping with stress effectively and enhancing self-esteem is necessary.

Results of the current study related to God image and self-esteem may have implications for individu­ als coping with stress and professionals treating sur­ vivors of stressful events and traumatic experiences.

For individuals who espouse a faith, exploring the image they have of God can be helpful for dealing

with stress. Clinicians working with individuals who choose to incorporate faith into treatment could explore the clients’ images of God and how this has improved or harmed their ability to cope with stress. Incorporating these individuals’ views of God into treatment may also be beneficial in addressing overall wellness, as self-esteem and ability to cope can contribute to mental wellness. Future research involving coping, religiousness, and the interaction of God image offers a promising avenue for helping individuals cope with life’s adverse experiences.

References Aten, J. D., Moore, M., Denney, R. M., Bayne, T., Stagg, A., Owens, S., Daniels, S., Boswell, S., Schenck, J., Adams, J., & Jones, C. (2008). God images following Hurricane Katrina in South Mississippi: An exploratory study. Journal of Psychology and Theology, 36(4), 249–257. https://doi.org/10.1177%2F009164710803600401 Cecen, A. R. (2008). The effects of gender and loneliness levels on ways of coping among university students. College Student Journal, 42(2), 510–516.

Chapman, P. L., & Mullis, R. L. (1999). Adolescent coping strategies and selfesteem. Child Study Journal, 29(1), 69–77.

Critcher, C. R., & Dunning, D. (2015). Feelings of Self-Worth Measure [Database record]. PsycTests. https://doi.org/10.1037/t38184-000 Green, D. L., Choi, J. J., & Kane, M. N. (2010). Coping strategies for victims of crime: Effects of the use of emotion-focused, problem-focused, and avoidance-oriented coping. Journal of Human Behavior in the Social Environment, 20(6), 732–743. https://doi.org/10.1080/10911351003749128 Hensley, S. & Hurt, A. (2014, July 7). Stressed out: Americans tell us about stress in their lives. NPR. http://www.npr.org/sections/healthshots/2014/07/07/327322187/stressed-out-americans-tell-us-about-stressin-their-lives Holt, C. L., Roth, D. L., Clark, E. M., & Debnam, K. (2014). Positive self-perceptions as a mediator of religious involvement and health behaviors in a national sample of African Americans. Journal of Behavioral Medicine, 37(1), 102–112. https://doi.org/10.1007/s10865-012-9472-7 Howerton, A., & Van Gundy, K. (2009a). Coping Style Questionnaire. PsycTests [Database record]. https://doi.org/10.1037/t02941-000 Howerton, A., & Van Gundy, K. (2009b). Sex differences in coping styles and implications for depressed mood. International Journal of Stress Management, 16(4), 333–350. https://psycnet.apa.org/doi/10.1037/a0016843 Lawrence, R. T. (1997). Measuring the image of God: The God Image Inventory and the God Image Scales. Journal of Psychology & Theology, 25(2), 214–226. https://doi.org/10.1177%2F009164719702500206 Lehmann, C., & Steele, E. (2020). Going beyond positive and negative: Clarifying relationships of specific religious coping styles with posttraumatic outcomes. Psychology of Religion and Spirituality, 12(3), 345–355. https://doi.org/10.1037/rel0000310 Meier, A., & Meier, M. (2004). The formation of adolescent’s image of God: Predictors and age and gender differences. American Journal of Pastoral Counseling, 7(2), 91–111. https://doi.org/10.1300/J062v07n02_07 Moos, R. H. (1990). Coping Responses Inventory: Youth form manual. Stanford University and Veterans Administration Medical Centers.

Mullis, R. L., & Chapman, P. (2000). Age, gender, and self-esteem differences in adolescent coping styles. The Journal of Social Psychology, 140(4), 539–541. https://doi.org/10.1080/00224540009600494 Nguyen, T., & Zuckerman, M. (2016). The links of God images to women’s religiosity and coping with depression: A socialization explanation of gender difference in religiosity. Psychology of Religion and Spirituality, 8(4), 309–317. https://doi.org/10.1037/rel0000060 Pargament, K. I. (1997). The psychology of religion and coping: Theory, research, and practice. Guilford Press.

Peterman, J. S., LaBelle, D. R., & Steinberg, L. (2014). Religious Commitment Questionnaire [Database record]. PsycTests. https://doi.org/10.1037/t32310-000 Pew Research Center. (2012). The global religious landscape. https://www.pewforum.org/2012/12/18/global-religious-landscape-exec/ Ptacek, J. T., Smith, R. E. & Zanas, J. (1992). Gender, appraisal, and coping: A

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longitudinal analysis. Journal of Personality, 60(4), 745–770. https://doi.org/10.1111/j.1467-6494.1992.tb00272.x Robins, R. W., Hendin, H. M., & Trzesniewski, K. H. (2001). Measuring global selfesteem: Construct validation of a single-item measure and the Rosenberg Self-Esteem Scale. Personality and Social Psychology Bulletin, 127(2), 151–161. https://doi.org/10.1177%2F0146167201272002 Rosenberg, M. (1965). Rosenberg Self-Esteem Scale [Database record]. PsycTests. https://doi.org/10.1037/t01038-000 Schreiber, J. A. (2011). Image of God: Effect on coping and psychospiritual outcomes in early breast cancer survivors. Oncology Nursing Forum, 38(3), 293–301. https://doi.org/10.1188/11.ONF.293-301 Sharif, F., Parsnia, A., Mani, A., Vosoghi, M., & Setoodeh, G. (2014). Comparison of personality traits, coping styles, and psychiatric disorders in adult suicidal and non-suicidal individuals. International Journal of Community Based Nursing & Midwifery, 2(3), 148–156.

Smith, E. I., & Crosby, R. G. (2017). Unpacking religious affiliation: Exploring

associations between Christian children’s religious cultural context, God image, and self-esteem across development. British Journal of Developmental Psychology, 35(1), 76–90. https://doi.org/10.1111/bjdp.12156 Welton, G. L., Adkins, A., Ingle, S. L., & Dixon, W. A. (1996). God control: The fourth dimension. Journal of Psychology and Theology, 24(1), 13–25. https://doi.org/10.1177/009164719602400102 Author Note. Jessica Downing https://orcid.org/0000-00026544-3932 Jessica Downing is now at the Department of Psychology at The Citadel in Charleston, South Carolina.

Thank you, Psi Chi Journal reviewers, for your time and consideration.

Correspondence concerning this article should be addressed to Jessica Downing.

Email: jessdowning123@gmail.com

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https://doi.org/10.24839/2325-7342.JN26.1.21

The Stigmas Associated With Teen Parenting: How Gender-Stereotypical Expectations Contribute Mariah Chobany and Debra Hull* Department of Psychology, Bethany College

ABSTRACT. One hundred three students from a small liberal arts college rated statements about potential stigma associated with unmarried teen parents. After reading a scenario describing an unmarried teen couple’s pregnancy and early parenting experiences, participants indicated their level of agreement with 11 statements for either the mother or the father.

Multivariate analysis of variance comparisons of the items indicated that the focus of attention was on the mother, in both positive and negative ways. Compared to unmarried teen fathers, unmarried teen mothers were seen as more sexually promiscuous, and too young to be a parent. On the other hand, mothers were also rated significantly as spending more time with their child, and assumed as more responsible. Unmarried teen fathers were seen as significantly more ambitious, whereas respondents thought it was more important for mothers to continue their education. Results reinforce the idea that unmarried teen mothers are expected to bear a disproportionate amount of the burden of care for their child. Knowledge of these results could lead to greater sensitivity toward unmarried teen parents and lend to more helpful support, which could assist them, and their children, to succeed despite their circumstances.

Keywords: gender stereotypes, pregnant and parenting teens, stigma

A

gender stereotype is a generalized view, or preconception, concerning the roles and characteristics of women and men.

Gender-stereotypical expectations influence the way people judge the abilities of women and men. Ellemers (2018) found that stereotypes affect the way people interpret and attend to information about themselves and others.

MacNell (2015) indicated that gender stereotypes could have significant consequences for the career development, education experience, and income level for women and men. Not only could these stereotypes impact a person’s career and educational experience, but they could also affect how they are perceived as a parent.

According to Fuegen et al. (2004), gender stereotypes could interfere with parental roles, affecting the judgments of mothers and fathers.

Because of gender-stereotyping, attitudes toward *Faculty mentor

parents are implicitly guided. When women become mothers, society assumes that they are caring for their children and less ambitious in their careers. Whereas, when men become fathers, they do not receive that negative assumption.

Instead, fathers are looked at as hard working and responsible (Lyness & Judiesch, 2014). Lyness and Judiesch (2014) found that, when both women and men with children applied for the same job, women with children were less likely to be recommended for a job. However, their male counterparts, with the same credentials, were more likely to be recom­ mended. Etaugh and Folger (1998) found that, because of gender roles and expectations, mothers who are employed full-time are perceived as less nurturing and less professionally competent than full-time employed fathers. Gender stereotypes of parents between the ages of 25 to 45 have been extensively researched, but less is known about

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mothers and fathers who take on the parental role during adolescence.

Existing research has suggested that pregnant and parenting teens are negatively stereotyped and stigmatized (Weed & Nicholson, 2014). For instance, teen mothers reported that they received negative judgments involving their age and being unfit to be a mother. Some mothers were perceived as sexually promiscuous, whereas teen fathers just felt the pressure to provide for, and be involved in, the life of their child (Wilkes et al., 2012).

Weber (2012) conducted in-depth interviews with unmarried teen fathers concerning their experi­ ences and found that young men were labeled as selfish and uncaring. Many of these fathers said they felt as if they had to prove their masculinity, and that their involvement in the pregnancy was one way to signify their manhood (Weber, 2012).

An earlier study by Richards et al. (1977) found that, in the first year of their child’s life, teen fathers regularly played with their children, but rarely engaged in caretaking activities. Compared to more recent studies, their findings may indicate how the expectations and roles of teen fathers had changed over time.

In comparing the stigma experienced by moth­ ers and fathers, Weed and Nicholson (2014) found that mothers were more likely to experience nega­ tive stigma associated with their pregnancy—from strangers, educators, and healthcare providers—in the form of disapproving facial expressions and body language, judgmental comments, and harsh treatment. Comments indicated that pregnant and parenting teen mothers are too young, irrespon­ sible, ruining their lives, that they got pregnant because they are lazy, and that having a baby is an easy way to get in the welfare system (Yardley, 2008). Very little research has been conducted on adolescent parents and the adversities they face.

The research previously conducted has not shown the difference in stigma and treatment based on the gender of the adolescent parent.

The purpose of the present study was to inves­ tigate how college students stigmatize unmarried teen mothers and fathers, potentially in different ways. We asked colleagues their opinions of a stereotypical teen parenting situation. After we heard their opinions, we drafted a scenario and questionnaire that highlighted the main ideas from the discussions, along with common themes found in the literature review. We hypothesized that students rating the mother would respond more negatively than the students rating the father.

Method Participants The sample was comprised of 103 Bethany College undergraduates (43 women; 60 men). The mean age of participants was 19 with a standard deviation of 1.32 (range = 18–22). Participants were currently living on Bethany College’s campus, located in the northern panhandle of West Virginia. Using a con­ venience sampling method, 92 of the participants were recruited from Greek organizations and/or enrolled in a psychology course, and were given extra-credit for their participation.

Materials and Measures Prior to data collection, Bethany College’s IRB, known as Bethany Ethical Research and Animal Care Committee, approved the project.

Participants were asked to read and sign consent forms. Completed consent forms were placed in a folder separate from where the completed surveys were kept, to ensure anonymity. After all consent forms were gathered, participants received the scenario describing the teen parenting situation (see Appendix A). Participants then responded to 11 items on a 5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree; see Appendix B). Participants were randomly assigned to one of two groups; the first group rated the mother, and the second group rated the father in the scenario.

Questions for the mother and father version were identical and included common stigmas that young parents face. Participants completed their surveys independently and were treated in accordance with APA ethical standards.

Procedure Participants were given the made-up scenario, which followed a teenage couple throughout pregnancy and into the first years of parenthood.

Both the mother and father were portrayed. In the scenario, the mother held off graduating high school to care for the child, and the father contin­ ued his education, but was involved in the child’s life. All participants received the same scenario, half of the participants were asked to evaluate the male teen, and half were asked to evaluate the female teen. After reading the scenario, participants were provided with one of two short surveys, where they rated statements regarding the parent they were randomly assigned; items included their opinion on the young parents’ judgement, age, sexuality, and ambition.

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Chobany and Hull | Stigmas Associated With Teen Parenting

Results This study assessed stigmas and stereotypes of pregnant and parenting teens, specifically the dif­ ferences in stigma between teen fathers and teen mothers. Each of the 11 items were analyzed using a multivariate analysis of variance to compare the difference in responses for the mother and the father in the given scenario. The mean ratings for each variable are presented in Figure 1, and significant findings are discussed below. Results showed significant differences in mother and father ratings for several of the items.

Participants rating mothers were more likely to agree with the negative stigmas surrounding teen pregnancy and parenting. Participants were asked about their feelings regarding if the mother or father was sexually promiscuous. Analysis revealed that mothers were more likely to be seen as sexually promiscuous compared to fathers, F(1, 102) = 32.10, p < .001, ηp2 = .24 . When asked if the mother/father was ambitious, participants were more likely to agree that the father was ambitious compared to the mother, F(1, 102) = 13.02, p < .001, ηp2 = .11.

Participants were more likely to agree that teen mothers were too young to be a parent, yet were less likely to agree that teen fathers were too young to be a parent, F(1, 102) = 18.37, p < .001, ηp2 = .16.

In addition, we found that participants were more likely to label teen mothers as irresponsible, unlike their male counterpart, F(1, 102) = 5.49, p = .02, ηp2 = .05, who was rated more responsible (M = 3.25, SD = 1.31) than the mother (M = 2.98, SD = 1.25).

However, participants agreed that mothers spent more time with their child, F(1, 102) = 2.70, p < .001, ηp2 =.14, and that pursuing an education was the best thing they could do for their child, F(1, 102) = 4.14, p = .04, ηp2 = .04.

Although not of statistical significance, we found that teen mothers were more likely to be perceived as better parents (M = 3.41, SD = 1.09) than teen fathers (M = 3.02, SD = 1.24). There were no significant differences between pregnancy prevention, cuteness of parent, responsibility of parent, if the parent is a good parent, and whether or not the parent is doing their best.

Discussion Consistent with our prediction, the results of our study show that the focus in evaluating teenage pregnancy continues to be on the mother. The only positive stereotype that we came across about moth­ ers is that they are more likely to spend adequate time with their child. This result is understandable,

given the gender expectation that women are primary caregivers. The only stereotype that we uncovered about fathers is a positive one—that they are more ambitious than mothers.

The results of Richards et al. (1977) revealed that teenage fathers regularly played with their children; however, our results show that teenage fathers were perceived as less likely to spend time with their children. Our finding contradicts their research. This shows a potential change in the expectations toward young fathers. Based on Wilkes et al. (2012) results and ours, we can assume that the gender expectations for young fathers has shifted—they are less likely to spend time with their child, and more likely to show ambition.

In addition, one might expect that the need to complete one’s education would be seen as more important for fathers, especially in light of their stereotypical need to provide. However, we found that participants thought it was more important for mothers to complete their education. That result makes sense if one also thinks that the mother will be more involved in their child’s care than the father, as our participants did. Taken together, our findings suggest a gender-based double standard, in which the focus, both positive and negative, is on mothers with fathers more or less getting a pass when it comes to teen pregnancy.

We are aware that our results directly reflect the scenario participants read. The scenario was framed from the mothers’ point of view, with little information about the father. The framing of the scenario and the information provided might have created bias in our results. It may be that certain characteristics of it prompted some of the ratings, and if we just asked participants to imagine an unmarried teen pregnancy situation, we might have gotten different results. Our conclusions are also FIGURE 1 Mean Responses of Parental Stereotypes Between Teen Mothers and Teen Fathers Mother Father

Promiscuity Irresponsible Cuteness Good parent Time spent Ambitious Too young Responsible Best they can do Prevent Education is best 0

1

2

3

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Stigmas Associated With Teen Parenting | Chobany and Hull

limited by the items we created. If we had asked participants if they knew of any teenage parents or if they themselves were a teen parent, then we would have been able to identify any biases or potential effects of our results. In retrospect, if we had included items about selfishness and an uncaring attitude, we might have picked up more stigma associated with the father reflecting Wilkes et al. (2014) findings.

In the future, we would like to recreate the study with a more diverse sample to generate more varia­ tion in responses and to potentially identify patterns among the different generations. We would also ask participants to envision their own idea of a teen pregnancy situation to see how that alters the results.

Additionally, we would like to create a scenario in which the mother gets an abortion in order to see how she might be viewed differently from a young mother who carries her pregnancy to term. We would also like to see whether unmarried parents in general, and especially those over 40, would be perceived differently. Again, we think that it would be more negatively stigmatized for mothers than fathers based on their age and the gender expectations.

Our study has the potential to inform school counselors, social workers, healthcare providers, and counselors about stigma facing (especially) unmarried teen mothers so that they can help teen parents navigate interactions with their peers, teachers, doctors, and religious leaders in more positive ways. Awareness of the stigma associated with teen pregnancy may be the first step in addressing it directly and helping to change it.

Perhaps our study also sets forth a method that will prompt others to study the nuances of responses to teen pregnancy and look for mediating factors

in that response. In all, our study shows that judgments about teen pregnancy continue to fall disproportionally on young mothers and that there is need to support them more fully.

References Ellemers, N. (2018). Gender stereotypes. Annual Review of Psychology, 69, 275–298. https://doi.org/10.1146/annurev-psych-122216-011719 Etaugh, C., & Folger, D. (1998). Perceptions of parents whose work and parenting behaviors deviate from role expectations. Sex Roles, 39(3–4), 215–223. https://doi.org/10.1023/A:1018850404838 Fuegen, K., Biernat, M., Haines, E., & Deaux, K. (2004). Mothers and fathers in the workplace: How gender and parental status influence judgements of job-related competence. Journal of Social Issues, 60(4). https://doi.org/10.1111/j.0022-4537.2004.00383.x Lyness, K. S., & Judiesch, M. K. (2014). Gender egalitarianism and work-life balance for managers: A multi-source perspective in 36 countries.

Application of Psychology International Review, 63(1), 96–129. https://doi.org/10.1111/apps.12011 MacNell, L., Driscoll, A., & Hunt, A. N. (2015). What’s in a name: Exposing gender bias in student ratings of teaching? Innovation of Higher Education, 40(4), 291–303. https://doi.org/10.1007/s10755-014-9313-4 Richards, M. P., Dunn, J. F., & Antonis, B. (1977). Caretaking in the first year of life: The role of fathers, and mothers’ social isolation. Child: Care, Health and Development, 3(1), 23–36. https://doi.org/10.1111/j.1365-2214.1977.tb00023 Weber, J. B. (2012). Becoming teen fathers: Stories of teen pregnancy, responsibility, and masculinity. Gender and Society, 26(6), 900–921. https://doi.org/10.1177/0891243212459074 Weed, K., & Nicholson, J. S. (2015). Differential social evaluation of pregnant teens, teen mothers, and teen fathers by university students. International Journal of Adolescent and Youth, 20(1), 1–16. https://doi.org/10.1080/02673843.2014.963630 Yardley, E. (2008). Teenage mothers’ experience of stigma. Journal of Youth Studies, 12(6), 671–684. https://doi.org/10.1080/13676260802392940 Author Note. Debra Hull https://orcid.org/0000-0002-84509984 Special thanks to class peers and Mark A. Affeltranger for reading and commenting on an earlier draft of this article.

Thank you also to Debra Hull for also reading and providing input. Copies of the scenario, surveys, and informed consent for are available from the author.

Correspondence concerning this research should be addressed to Debra Hull, Department of Psychology, Bethany College, 31 E. Campus Drive, Bethany, WV 73008.

Email: dkhull@bethanywv.edu

Appendix A Teen Parenting Scenario

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I guess you could say I was popular in high school—it was fun because I fit in. I was a cheerleader and I did color guard. I've never been the type to party, and I never drank or did drugs or any of that. School was so important to me. However, I did have a boyfriend. It was the classic high school romance: I was the cheerleader, and he played football, baseball, and basketball.

One Friday night over Christmas break, he got me some chicken for dinner, and it made me throw up. I told him that I was late, so we thought we should take a test. Finally, four positive results later, I realized that I was pregnant, and I just cried. He told me he would stay with me. I decided to tell my mom three or four days later. She was so supportive and I was lucky for that.

About five months into the pregnancy my boyfriend asked to talk to me. He met me and told me, “I think it'd be better for both of us if we took a break from each other for a while.

We might get back tomorrow, you never know, I just think we should take a break." I was pregnant at 16 and now alone.

We never got back together, but he said he would still be there for the baby. At 35 weeks pregnant I went into labor and had our baby boy. His father never made it in time for his birth. After spending a few days in the hospital I was cleared to go home. I had to parent this child with only support from my mom and his father. I was scared.

After having my son, life was hard. I had to drop out of high school so I didn’t have to pay for childcare. I had to be home with him, change his diapers, feed him, take him to doctors and just be his person. I was living at home with my mom, so thankfully I didn’t have to pay bills or worry about working. I was eligible for welfare, which was a big help.

The first two months of my son’s life his father came around a lot. He was over to visit him on the weekends and would even take him for walks so that I could rest. Sometimes he would change his diaper for me, but not when he pooped—I don’t blame him. After the first few months his father stopped coming around as much because he was working and preparing for college. He would sometimes give me half of his paychecks to help with the child. He was a huge help.

Now, our son is three years old. I am still living at home with my mom, but I am now studying and working towards my GED. My baby’s father is in his last year of college—He lives across the state, so we don’t see him much. Though we don’t see him as frequently, he still comes to visit once a month and continues to send money for support.

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Chobany and Hull | Stigmas Associated With Teen Parenting

Appendix B Teen Parenting Survey Strongly Disagree

Disagree

Neutral

Agree

Strongly Agree

1

2

3

4

5

Please use the scale to rate the following statements about the FATHER in the scenario. ____ 1. This parent is sexually promiscuous. ____ 2. This parent’s actions are irresponsible. ____ 3. This parent’s role is adorable or cute. ____ 4. This parent is a good parent. ____ 5. This parent spends enough time with their child. ____ 6. This parent is ambitious. ____ 7. This parent is a responsible parent. ____ 8. This parent was too young to become a parent. _____9. This parent is doing the best they can. _____10. It was this parent’s responsibility to prevent the pregnancy in the first place. _____11. The best thing this parent can do for the child is get a good education.

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https://doi.org/10.24839/2325-7342.JN26.1.26

Working Memory in Chinese Text Comprehension Sau Hou Chang1 and Tracy B. Henley2 1 School of Education, Indiana University Southeast 2 Department of Psychology, Counseling, & Special Education, Texas A&M University–Commerce

ABSTRACT. The purpose of the present study was to examine the relationship between working memory and text coherence in Chinese text comprehension.

Eighty-six native Cantonese speakers completed an operation-character working memory span task to be classified into low-span or high-span readers and a reading task to measure the time to detect inconsistency as well as the accuracy of recall. High-span readers took less time to detect inconsistency and had better recall, whereas low-span readers took a longer time to detect inconsistency and had more memory distortions. In addition, readers took more time to read passages with coherence breaks and distorted more and substituted more information in passages with coherence breaks. However, coherence breaks did not facilitate their recall as has been suggested by previous studies. This work extends the literature on working memory and comprehension from just reaction times to include recall of the passages and introduced the use of substitution units as another measure of error.

Keywords: working memory, operation-character span task, text consistency, text coherence, Chinese text comprehension 本研究旨在探討中文文字理解中工作記憶與文章一致性的關係。八十六名以 粵語為母語的參與者完成了操作字元工作記憶跨度任務(分為低工作記憶組 和高工作記憶組), 以及一項閱讀理解任務 (閱讀不一致文章的時間以及記憶 不一致文章的準確性)。結果顯示高工作記憶組用更少時間檢測文章的不一 致性, 和更準確地記憶文章的內容。低工作記憶組需要更長時間檢測文章的 不一致性, 和更不準確地記憶文章的內容。此外, 參與者花更多的時間閱讀 不一致的文章, 扭曲較多的內容, 並替換更多資訊。然而, 不一致的文章並不 有助於記憶。本研究擴展了關於工作記憶和中文文字理解的文獻, 除了測量 反應時間, 本研究新增測量回憶文章內容, 並介紹替換為另一個閱讀不一致 文章的錯誤方法。 關鍵字: 工作記憶、中文文字理解、文字一致性、操作字元跨度任務

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t is not uncommon to find readers who know all the words and grammar structures of a text yet fail to integrate these components into comprehension. In addition to understanding words and grammar, readers must be able to identify relations between the various parts of the text (local coherence), as well as between the text and their world knowledge (global coherence).

Comprehension, therefore, is the creation of a coherent mental representation of a text.

According to the minimalist hypothesis, readers are primarily concerned with maintaining local coherence, and they establish global coherence only when local coherence fails (McKoon & Ratcliff, 1992). In contrast, the constructionist hypothesis asserts that readers routinely check and maintain coherence at both a local and global level (Albrecht & O’Brien, 1993; Hakala & O’Brien, 1995; O’Brien & Albrecht, 1992).

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*Faculty mentor

Chang and Henley | Chinese Text Comprehension

Working Memory and Text Comprehension Evidence exists for an important role of work­ ing memory on text comprehension (Borella & Ribaupierre, 2014; Cain et al., 2004; Kintsch & van Dijk, 1978; Seigneuric & Ehrlich, 2005). When a sentence is processed in working memory, some ele­ ments of that sentence are presumptively stored to be processed anew with the next input sentence. If a connection is found between any of the new propo­ sitions and those retained in working memory, the input is accepted as coherent with the previous text.

If not, a search of previously processed information is made, or an inference process is initiated to construct a coherent connection.

Daneman and Carpenter (1980) noted that readers with larger working memory spans were better at identifying the correct referent of the pronoun in the final sentence, suggesting that a bigger capacity allows for more opportunities to integrate the pronoun with its referent. Although readers with smaller spans detected ambiguous words about as often as readers with larger spans, Daneman and Carpenter (1983) found that they were too “tied up” in the reading to maintain all the meanings in working memory. Miyake et al. (1994) stated that both high-span and low-span readers activated multiple meanings of an ambiguous word, but only high-span readers were able to maintain all the meanings and suppress irrelevant ones.

Likewise, Whitney et al. (1991) noted that low-span readers faced a tradeoff between maintaining an overall passage representation (global coherence) and maintaining sentence-to-sentence connections (local coherence).

Working Memory and Chinese Text Comprehension The creation of a coherent mental representation of a text is also crucial in Chinese text comprehen­ sion. From an investigation of the processing of Chinese text, Siu (1986) found that reducing incoherent ideas within a passage helped readers identify and order concepts. In addition, Chow et al. (2000) showed that readers took longer to read a target phrase inconsistent with a protagonist elaboration when the theme (the subject of the target phrase) was the same as the subject of the protagonist elaboration. This result was supported

by Wang and Mo (2001), who also showed that readers took longer to read inconsistent target sentences than consistent ones.

The effect of working memory on text com­ prehension seems to apply across writing systems

to English and Chinese. Tsung et al. (2017) stated that working memory contributed significantly to the prediction of performance in narrative and expository text comprehension. Also, Leong et al. (2008) found that children in grades 3 to 5 with better working memory performed much better in inferential text comprehension. Studies on Chinese text coherence by Yang et al. (1999) showed that readers with high working memory capacities took less time to verify the meaning of ambiguous Chinese sentences than readers with low working memory capacities. Additionally, the importance of working memory capacity in sup­ pressing irrelevant information was supported by Wang et al. (2003), who showed that suppression of identity of Chinese characters was significantly correlated with working memory capacity.

The Present Study The purpose of the present study was to further examine the relationship between working memory and text coherence in Chinese text comprehen­ sion. Specifically, (a) what are the reaction times low-span and high-span readers take in detecting inconsistency in Chinese passages with coherence breaks? And, (b) what do low-span and high-span readers recall from Chinese passages with coher­ ence breaks? We hypothesized that there would be a difference between low- and high-span readers in time to detect inconsistency as well as in the accuracy of recall.

Previous studies on Chinese text comprehen­ sion (e.g., Chow et al., 2000; Wang & Mo, 2001) have used target sentences that were either consis­ tent or inconsistent with relevant preceding elabo­ rations to investigate the effect of consistency on reaction times. The present study used that same paradigm to investigate the effect of consistency on reaction times, but also considered recall accuracy.

Unlike previous studies using passages with one protagonist (e.g., Hakala & O’Brien, 1995), the pres­ ent study used passages with two protagonists. This is an addition to the literature that should increase ecological validity, given that many “real world” texts include multiple protagonists. As such, an analysis of the number of “substitutions” (i.e., a response substituted a protagonist with another protagonist) was added to the standard methods for scoring idea units (i.e., a response captured the meaning of the respective idea) and distortion units (i.e., a response contradicted the information provided).

Last, although working memory capacity has been related to text coherence at both local and

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Chinese Text Comprehension | Chang and Henley

global levels (e.g., Kintsch & van Dijk, 1978), studies on working memory and text coherence have mostly focused on reaction times (Daneman & Carpenter, 1980; Miyake et al.; 1994; Whitney et al., 1991). In the present study, Chinese readers with different working memory capacities were also scored for recall of passages with inconsistencies at global and local levels.

Method Participants Participants were 86 undergraduate education majors enrolled in a psychology course at a public university in Southeast Asia. There were 76 women and 10 men, aged 18 to 22. All were native Cantonese speakers, and all instructions were in Cantonese.

The procedures met all American Psychological Association (APA) ethical principles for use of human subjects, and participants were provided informed consent in accordance with guidelines set by the Institutional Review Board of the university.

Materials Operation-Character Span Task This study adopted the operation-word paradigm developed by Engle and colleagues for measuring working memory capacities (e.g., La Pointe & Engle, 1990). Because participants were Chinese, the operation-word span was changed to an operation-character span. The operation-character task consisted of a series of paired mathematical operations and Chinese characters. The mathemati­ cal operations came from La Pointe and Engle, and the Chinese characters came from a database of Chinese character frequencies (Chinese University of Hong Kong, 2001). The number of pairs in a series ranged from two to seven. For each pair, there were three trials. As such, there were 81 operationcharacter pairs (2 pairs × 3 trials + 3 pairs × 3 trials + 4 pairs × 3 trials + 5 pairs × 3 trials + 6 pairs × 3 trials + 7 pairs × 3 trials). Examples of the stimuli included: (9 × 1) – 9 = 1 同; (8 × 1) + 8 = 16因.

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Reading Task Four reading passages developed by Long and Chong (2001) were rewritten into Chinese.

Contents were modified to address cultural dif­ ferences between Americans and Chinese. For example, Chinese usually do not order a cheese­ burger and fries, so the Chinese version described ordering a spicy fried chicken. Initial translations were made by the first author, then reviewed by a professor of bilingual translation who checked both

versions to verify that the Chinese corresponded with the English with respect to matters such as length, complexity, and consistency.

Each passage had five sections: introduction, elaboration, filler, target sentence, and close. Each passage began with a two- to three-sentence section introducing two protagonists. This was followed by an elaboration that would be either consistent or inconsistent with the subsequent target sentence.

A paraphrased consistent example would be: Mary loved hot food (elaboration) and ordered a spicy chicken (target). A paraphrased inconsistent example would be: Mary was a vegetarian (elabora­ tion) but ordered a spicy chicken (target). One of two possible filler sections followed to strain work­ ing memory. For the global-coherence conditions, approximately six sentences were used, and for the local-coherence condition only one sentence was used. The filler section was followed by the target sentence (which was either consistent or inconsistent with the previous elaboration), and then the story closed.

Procedure Two computer-based tasks, averaging 45 minutes total, were presented individually to subjects in a counterbalanced manner.

Operation-Character Span Task The mathematical operation and Chinese characters were presented in black against white in 44-point font as follows. At the beginning of a trial, a “+” sign was presented at the center of the screen for 1 second, followed by a blank screen for 1 second.

Then, a mathematical operation appeared, and participants were instructed to mentally calculate (e.g., [(6 × 2) – 5 = ?]). When participants had their answer, they pressed “enter” to proceed to the next screen. An answer for the operation would then be given on screen, and participants verified whether it was correct by indicating “True” or “False.” Participants were instructed to perform the verification as quickly as possible, but to be accurate.

Then, they pressed “enter” to move onto the next screen that showed a Chinese character for 1 second and were to memorize it for later recall. The screen was blank for 1 second, followed by either another operation-character pair or the recall cue (a set of question marks). The cue signaled participants to write down, in the correct order, the preceding Chinese characters. Participants were asked to refrain from writing down the last character first.

Recall was not timed. When participants finished

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Chang and Henley | Chinese Text Comprehension

writing, they pressed “enter” to proceed to the next trial starting again with a “+” sign.

Reading Task The procedure for presenting the reading task was adapted from the work of Long and Chong (2001).

Time to read the target sentence and the response to a comprehension question for each passage were recorded. Each of the four text passages was presented in four formats: global-consistent, globalinconsistent, local-consistent, local-inconsistent, resulting in 16 counterbalanced conditions.

The reading time of the target sentence was measured by the Digitest-1000, an instrument used to record reaction time in milliseconds in sports and medicine (Digitest-1000; Digitest Ltd., Muurame, Finland). Participants activated the Digitest-1000 with their dominant hand while simul­ taneously pressing “enter” on the keyboard. Each subsequent press of “enter” erased the current line of the passage and presented the next one. At the beginning of a trial, a “+” sign followed by several “~” characters was presented on the screen for 1 second, followed by a blank screen for 1 second.

The passages were presented one line at a time in black against white in 44-point font. At the end of each passage, a close-ended question was presented as a fidelity check to assure that participants were attending and understanding.

After all four texts were read on the screen, participants were given a test booklet to write down all they could remember about each passage.

Each page of the booklet provided a recall cue (the first sentence) for a particular passage in the same order that they were read. Recall was scored consistent with established methods (Hakala & O’Brien, 1995).

Results Working Memory Task The 86 participants’ span scores were screened by stem-and-leaf plot. Data that were more than 1.5 times the interquartile range from the upper or lower quartile were considered outliers, and three low span scores were thus excluded from further analyses. Cronbach’s alpha (.77) was derived from the proportion-correct scores of the six operationcharacters pairs, and suggested internal consistency was acceptable.

Operation-character span scores (M = 0.80, SD = 0.12) ranged from .49 to .98. Following the lead of Ikeda and Kitagami (2012), the median score (here, .82) was used as a cutting point between high-span

and low-span readers. Participants with working memory scores equal to or below the median were classified as low-span readers, and those with scores above the median were classified as high-span readers. An independent t test showed a significant difference between low-span (M = 0.71, SD = 0.10) and high-span readers (M = 0.89, SD = 0.05), t(81) = −10.81, p < .001.

Reading Task Reading task recall data in which participants produced no results for a passage were considered missing data. With 8 missing data and 3 span scores outliers, the analysis of the fidelity check questions was conducted on 75 participants. The percentage of correct answers was above 96% for each, and there was no difference between the low-span and high-span readers in answering these questions.

Reaction Times Latencies of all 86 reaction times were screened with the stem-and-leaf plot for outliers that were more than 1.5 times the interquartile range from the upper or lower quartile, and 12 outliers were found. In addition to the 3 outliers from the span scores, 15 participants were now excluded, so 71 participants were used.

For the reaction times (see Table 1), analyses of variance (ANOVAs) showed that there were main effects of passage condition, F(3, 207) = 2.80, p = .041, partial η2 = .039, and working memory span, F(1, 69) = 5.08, p = .027, partial η2 = .069, but no interaction between passage condition and working memory, F(3, 207) = 0.91, p = .44, partial η2 = .013. Bonferroni’s procedure further showed that the times taken to read the target sentence in the inconsistent-local condition (M = 2.08 s, SD = 0.67) were significantly longer than those in the TABLE 1 Mean Reading Times (in Seconds) for Target Sentence as a Function of Passage Condition and Working Memory Span Consistent

Inconsistent

Working Memory

Global

Local

Global

Local

Total

Low-span

M

2.16

1.98

2.15

2.26

2.14

n = 36

SD

0.70

0.53

0.60

0.64

0.62

High-span

M

1.84

1.79

2.01

1.90

1.88

n = 35

SD

0.61

0.63

0.62

0.66

0.63

Total

M

2.00

1.88

2.08

2.08

2.01

N = 71

SD

0.67

0.58

0.61

0.67

0.63

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Chinese Text Comprehension | Chang and Henley

consistent-local condition (M = 1.88 s, SD = 0.58).

Low-span readers took significantly longer to read the target sentence than high-span readers in the consistent global condition (low-span readers: M = 2.16 s, SD = 0.70; high-span readers: M = 1.84 s, SD = 0.61) and in the inconsistent local condition (low-span readers: M = 2.26 s, SD = 0.64; High-span readers: M = 1.90 s, SD = 0.66).

were main effects for the passage regions, F(3.33, 242.78) = 81.79, p < .001, partial η2 = .528, and for working memory, F(1, 73) = 4.17, p = .045, partial η2 = .05, but no interaction between passage region and working memory, F(3.33, 242.78) = .20, p = .91, partial η2 = .003. Post hoc analysis showed that high-span readers recalled more idea units (M = 0.39, SD = 0.13) than low-span readers (M = 0.33, SD = 0.13) in the elaboration region. Readers with higher working memory were able to recall more idea units about the description of the protagonist than readers with lower working memory.

Recall of Idea Units With 8 missing data and 3 span-scores outliers, 11 participants were excluded and 75 participants were used. For the idea units (recall captured the meaning of the respective idea) recalled (see Table 2), ANOVAs showed that there was a main effect for working memory, F(1, 73) = 4.17, p = .045, partial η2 = .054, but not for passage condition, F(3, 219) = 0.70, p = .55, partial η2 = .010, nor any interaction between passage condition and working memory, F(3, 219) = 0.99, p = .40, partial η2 = .013. Post hoc analysis showed that high-span readers correctly recalled more idea units (M = 0.45, SD = 0.17) than low-span readers (M = 0.36, SD = 0.17) in the inconsistent-global condition. Although the target sentence was inconsistent with the earlier elabora­ tion, and the filler section used six sentences to strain working memory, readers with higher work­ ing memory were able to resolve the inconsistency and recall more idea units than readers with lower working memory.

Considering idea units across different passage regions (see Table 3), ANOVAs showed that there

Recall of Distortion Units For the distortions (recall contradicted the infor­ mation provided in the elaboration region or the target sentence) produced (see Table 2), ANOVAs showed that there was a main effect for passage con­ dition, F(1.80, 131.61) = 3.23, p = .048, partial η2 = .042, but not for working memory, F(1, 73) = 1.87, p = .18, partial η2 = .025, nor any interaction effect between passage condition and working memory, F(1.80, 131.61) = 1.00, p = .36, partial η2 = .013.

Paired t tests showed that readers provided more distortions in the inconsistent-global condition (M = 0.01, SD = 0.04) than in the consistent-global condition (M = 0.001, SD = 0.005), t(74) = −2.47, p = .016, and consistent-local condition (M = 0, SD = 0), t(74) = −2.63, p = .01. Participants also provided more distortions in the inconsistent-local condition (M = 0.01, SD = 0.04) than in the consistent-local condition (M = 0, SD = 0), t(74) = −2.02, p = .047.

TABLE 2 Mean Percentage of Idea, Distortion, and Substitution Units Recalled as a Function of Passage Condition and Working Memory Span Idea Units Consistent

Distortion Units Inconsistent

Consistent

Working Memory

Global

Local

Global

Local

Global

Low-span (n = 39)

.414

.397

.364

.422

0

High-span (n = 36)

.435

.475

.451

.454

.001

Total (N = 75)

.424

.434

.406

.437

.001

Substitution Units

Inconsistent

Consistent

Inconsistent

Local

Global

Local

Global

Local

Global

Local

0

.013

.015

.023

.025

.058

.063

0

.009

.002

.031

.024

.021

.066

0

.011

.009

.027

.024

.04

.064

TABLE 3 Mean Percentage of Units Recalled as a Function of Passage Region and Working Memory Span Idea Units SPRING 2021 PSI CHI JOURNAL OF PSYCHOLOGICAL RESEARCH

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Distortion Units

Working Memory

Intro

Elaboration

Filler

Target

Close

Intro

Elaboration

Filler

Low-span (n = 39)

.402

.331

.441

.628

.193

0

.009

0

High-span (n = 36)

.468

.392

.495

.694

.22

.003

.012

0

Total (N = 75)

.434

.361

.467

.66

.206

.002

.01

0

Substitution Units Target

Close

Intro

Elaboration

.026

0

.011

0

.007

0

.009

0 .013

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Filler

Target

Close

.023

.003

.147

.026

.029

0

.125

.017

.026

.002

.137

.022

Chang and Henley | Chinese Text Comprehension

When the target sentence (Mary ordered a fried spicy chicken) was inconsistent with the earlier elaboration (Mary was a vegetarian), readers recalled more errors no matter whether the work­ ing memory was strained by the filler sections.

Looking at distortions across passage regions (see Table 3), ANOVAs showed that there were main effects for region, F(3, 71) = 6.56, p = .001, partial η2 = .22, but no main effect for working memory, F(1, 73) = 1.87, p = .18, partial η2 = .03, nor any interac­ tion between passage region and working memory, F(3, 71) = 1.82, p = .15, partial η2 = .07. Independent t tests showed that low-span readers (M = 0.03, SD = 0.08) produced more distortions at the target region than high-span readers (M = 0, SD = 0), t(73) = 2.00, p = .049. No matter whether the target sentence was consistent or inconsistent with the earlier elaboration, readers with low working memory recalled more errors than those with high working memory.

Recall of Substitution Units For substitution errors (recall substituted the protagonist with the other character) in Table 2, ANOVAs showed that there was a main effect for passage condition, F(3, 219) = 4.08, p = .008, partial η2 = .05, but not for working memory, F(1, 73) = 0.41, p = .53, partial η2 = .006, nor any interaction effect between passage condition and working memory, F(3, 219) = 1.23, p = 2.99, partial η2 = .017. Bonferroni’s procedure showed that readers produced more substitutions in the inconsistentlocal condition (M = 0.06, SD = 0.10) than in the consistent-global (M = 0.03, SD = 0.07) and consistent-local conditions (M = 0.02, SD = 0.07).

When the target sentence was inconsistent with the earlier elaboration, readers were confused with the protagonist and the other character. Instead of Mary ordering a fried spicy chicken, readers recalled Mary’s friend, Joan, made the order.

As for substitutions across locations (see Table 3), ANOVAs showed that there was a main effect for passage region, F(1.38, 100.44) = 31.63, p < .001, partial η2 = .30, but not for working memory, F(1, 73) = 0.41, p = .53, partial η2 = .006, nor an interac­ tion between region and working memory, F(1.38, 100.44) = 0.28, p = .67, partial η2 = .004. Bonferroni’s procedure showed that readers produced more substitutions at the target sentence (M = 0.14, SD = 0.18) than any other region. Because the target sentence described the action of the protagonist, it was easier for readers to substitute the protagonist with the other character in the passage.

Discussion The purpose of this study was to examine the relationship between working memory and text coherence in Chinese text comprehension. From the results, there was a difference between low-span readers and high-span readers in time to detect inconsistency and accuracy of recall for Chinese passages with coherence breaks. In addition, there was an effect by consistency condition on both time to detect inconsistency and accuracy of recall.

Differences Between Low-Span and High-Span Readers In support of previous studies on working memory and text coherence (e.g., Daneman & Carpenter, 1980; Miyake et al., 1994; Whitney et al., 1991; Yang et al., 1999), high-span readers took less times to detect passages with coherence breaks (M = 1.95 s, SD = 0.54) than low-span readers (M = 2.21 s, SD = 0.49), and they recalled more idea units (M = 0.45, SD = 0.17) than their low-span counterparts (M = 0.36, SD = 0.17). In addition, low-span readers distorted more target sentences (M = 0.03, SD = 0.077) than high-span readers (M = 0, SD = 0).

The reaction time and recall findings do not support previous studies on text coherence.

Albrecht and O’Brien (1993), and Hakala and O’Brien (1995) found that readers took longer to resolve the inconsistency by reprocessing earlier parts of the text, and thus had better memory for earlier text. In the present study, readers with differ­ ent working memory capacities may adopt different comprehension strategies while reading passages with coherence breaks. To resolve inconsistency, high-span readers may reprocess earlier parts of the text to integrate with the target sentences, whereas low-span readers seem to distort the target sentence (e.g., Mary orders a salad) to make it consistent with the earlier text (e.g., Mary is a vegetarian).

However, consistent with Gernsbacher (1991) and Kintsch (1998), the present study found that low-span readers may have difficulties in suppress­ ing irrelevant information from earlier parts of the text, so they revert to distorting the target sentence as a way to establish coherence. Alternatively, highspan readers appear to have the ability to deactivate irrelevant information from earlier parts of the text, so they can simply reprocess earlier parts of the text to establish coherence.

Times to Detect Inconsistency Readers took longer to read the target sen­ tence in the inconsistent conditions (M = 2.08 s,

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SD = 0.53) than in the consistent conditions (M = 1.94 s, SD = 0.55). Such findings would support the constructionist hypothesis proposed by O’Brien and colleagues, as it suggests that readers may be checking for both local and global coherence in an attempt to construct a single coherent repre­ sentation around the main protagonist (Albrecht & O’Brien, 1993; Hakala & O’Brien, 1995; O’Brien & Albrecht, 1992). When new information is inconsistent with the established representation, comprehension difficulties would occur and strate­ gies to reestablish coherence are needed. Chinese readers, like their English counterparts, took longer to detect inconsistency in passages with coherence breaks. It appears that Chinese readers routinely checked for, and maintained, coherence at both a local and global level. That is, they were able to detect inconsistency and attempted to maintain global coherence.

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Accuracy of Recall Chinese readers recalled more distortion units in the inconsistent conditions (M = 0.01, SD = 0.025) than in the consistent conditions (M = 0.00, SD = 0.00). They also introduced more substitution units in the inconsistent conditions (M = 0.05, SD = 0.07) than in the consistent conditions (M = 0.03, SD = 0.05). Because the inconsistency centered on the elaboration and the target sentence, the resolving strategies should have occurred primarily for those two passage regions. As the recall confirmed, the elaboration region was distorted more in the inconsistent conditions (M = 0.02, SD = 0.05) than consistent conditions (M = 0.00, SD = 0.01), and the target sentence was also distorted more in the inconsistent conditions (M = 0.03, SD = 0.11) than consistent conditions (M = 0, SD = 0). In addition, the target sentence was substituted more in the inconsistent conditions (M = 0.20, SD = 0.30) than consistent conditions (M = 0.07, SD = 0.18).

When Chinese readers detected inconsistency, they might have imagined that they had missed certain parts of the text or mixed up the subject of previous elaboration with the other character.

Indeed, participants spontaneously provided such explanations after the experiment was concluded.

The strategies they used to establish coherence were designed to distort the earlier parts of the text and the target sentence or to substitute the subject of the target sentence with the other character. For example, although readers remembered that Ken was a small man, they distorted that “even though Ken is small, he would like to keep in shape.”

Instead of writing that Ken enrolled in the boxing class, readers substituted that “Mike enrolled in the boxing class.”

A more detailed analysis of the recall patterns reveals that the resolution of these coherence breaks and their impact on memory depended on whether the coherence break occurred at a local or global level. When global coherence was violated, readers distorted more (M = 0.02, SD = 0.01). When local coherence was violated, readers both distorted (M = 0.01, SD = 0.01) and substituted more (M = 0.01, SD = 0.10). In addition, readers distorted more at the elaboration region when global coherence was violated (M = 0.027, SD = 0.08). Readers also substituted more at the target sentence (M = 0.25, SD = 0.44) when local coherence was violated.

Chinese readers distort at local (one sentence between the target sentence and the inconsistent elaboration) and global coherence breaks (one paragraph between the target sentence and the inconsistent elaboration) but substitute more at local coherence breaks. These results concur with the findings of Hakala and O’Brien (1995) that local coherence breaks elicited more distor­ tion units. Substitutions are found to be another comprehension strategy readers adopt to establish coherence. All information that needs to be checked is currently active in working memory at local coherence break. With the name of the other character in mind, substituting the subject of the target sentence with the other character is an efficient strategy for reestablishing coherence.

It is not surprising to find that the elaboration region was more distorted, and the target sentence was substituted more. Because the inconsistency involved the elaboration region and the target sentence, any strategies to establish coherence should involve these two regions.

The coherence breaks did not facilitate the recall of more idea units as seen in previous studies (e.g., Albrecht & O’Brien, 1993; Hakala & O’Brien, 1995). No difference was found between the idea units recalled in passages with and without coher­ ence breaks. In addition, the elaboration region and the target sentence were not better recalled with coherence breaks than without coherence breaks.

Summary and Significance For the literature on Chinese text coherence, this study shows that Chinese readers, like their English counterparts, took longer to detect inconsistency in Chinese passages with coherence breaks. It appears that they routinely checked for, and maintained,

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Chang and Henley | Chinese Text Comprehension

coherence at local and global levels. That is, they were able to detect inconsistency and attempted to maintain global coherence. In addition, when Chinese readers detected inconsistency, they seem­ ingly reasoned that they had missed certain parts of the text or mixed up the subject of previous elaboration with the other character. The strategies they used to establish coherence were designed to distort the earlier parts of the text and the target sentence or to substitute the subject of the target sentence with the other character. Specifically, Chinese readers distorted more at local and global coherence breaks and substituted more at local coherence breaks. In addition, they distorted more at the elaboration region, when global coherence was violated, and substituted more at the target sentence, when local coherence was violated. All of these results are additions to the literature on Chinese readers.

For the wider literature on text coherence, the present study shows that substituting the subject of the target sentence with the other character is found to be another comprehension strategy readers adopt to establish coherence. Like distor­ tion units, readers substituted more at the target sentence in the inconsistent conditions than in the consistent conditions. Readers also substituted more at local coherence breaks. This was the first study to examine substitution effects.

For the literature on working memory and text coherence, this study shows that high-span readers took less time to detect passages with coherence breaks and recalled more idea units than their low-span counterparts. Low-span readers took longer to detect passages with coherence breaks and distorted more than high-span readers. To resolve inconsistency, high-span readers appear to reprocess earlier parts of text to integrate the target sentences, and the reprocessing has subsequent memory benefit for the elaboration region. To resolve inconsistency, low-span readers distort the target sentence to make it consistent with the earlier parts of the text, and the distortion did not have any memory benefit for the elaboration region. These findings add to a large body of data on working memory and text coherence.

Limitation and Implications To present the working memory span task, previous research was administered with computer software, such as E-prime (e.g., Kane et al., 2004), or Micro Experimental Laboratory (e.g., Engle et al., 1992).

However, with a limitation on the availability of such

resources, this study used Microsoft PowerPoint and the Digitest-1000. Because the Digitest-1000 has been widely used for obtaining reaction times in sports science and medicine (e.g., Abrantes et al., 2004), it stands as a reliable substitute to the software solution more commonly employed in psy­ chology (e.g., Albrecht & O’Brien, 1993; Hakala & O’Brien, 1995; Long & Chong, 2001). Importantly, because this study was not interested in the accuracy to the millisecond for reading the target sentence, this limitation should have no effect on the results.

In closing, if researchers are able to come to understand how readers adapt to both the type of text being read and to their own informationprocessing limitations, they be able to better target instructional programs that shift the reader from maladaptive to adaptive strategies. By further exploring the conditions under which readers select different strategies and the factors that influence those strategies, researchers may be able to predict more precisely the conditions under which coher­ ence breaks improve and disrupt both memory and learning.

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Author Note. Sau Hou Chang https://orcid.org/0000-00028184-8040 Tracy B. Henley https://orcid.org/0000-0003-1612-0501 Special thanks to Psi Chi Journal reviewers.

Correspondence concerning this article may be addressed to Sau Hou Chang, School of Education, Indiana University Southeast, 4201 Grant Line Road, New Albany, Indiana, USA 47150. Email: sauchang@ius.edu; Telephone: 812-941-2606; Fax: 812-941-2667.

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https://doi.org/10.24839/2325-7342.JN26.1.35

Negative Life Events and Time Perspective Among Adolescents Julie V. Chandler and Zena R. Mello* Department of Psychology, San Francisco State University

ABSTRACT. We examined negative life events and time perspective in adolescents. Negative life events were nonnormative experiences including school suspension, running away from home, or the death of a family member. Time perspective referred to thoughts and feelings about the past, present, and future. We assessed multiple dimensions including orientations and positive and negative feelings about time. Participants were 790 adolescents and data were self-reported. Findings indicated that (a) adolescents who experienced the highest number of negative life events were oriented toward the past, whereas adolescents who experienced the fewest negative life events were oriented toward the three time periods equally, and (b) negative life events were positively associated with negative feelings and inversely associated with positive feelings about time.

Keywords: time perspective, life events, time attitudes, and time relation

A

s adolescents mature, they undergo a variety of positive and negative experiences including making new friends or flunking a school grade. However, negative life experiences in adolescence have been shown to affect psychological well-being in this developmental period and to impact adulthood. For example, according to the Centers for Disease Control and Prevention (CDC, 2019), adverse childhood experiences (ACES) such as abuse or parental separation or divorce have been positively associated with risky health behaviors, chronic health conditions, lower academic achievement, lost time from work, and early death. The CDC (2019) has noted that, as the number of ACES increases, the risk for these outcomes increases as well.

Given the relationship between negative life events and adverse outcomes, it is important to examine factors that could influence these associations. One such factor is time perspective.

Time perspective is a cognitive and motivational construct that refers to one’s thoughts and feelings toward the past, present, and future (Lewin, 1942; Mello, 2019; Zimbardo & Boyd, 1999). Studies have shown associations among time perspective and many important areas of adolescent development, including academic achievement (Andretta et al., 2014; Mello et al., 2013; Zimbardo & Boyd, 1999), *Faculty mentor

running away (Mello et al., 2017), substance use (Keough et al., 1999; McKay et al., 2016), and men­ tal well-being (Konowalczyk et al, 2018; Mello et al., 2013). However, research has yet to examine how negative life events are related to time perspective.

Examining the association between time per­ spective and negative life events has the potential to broaden the understanding of adolescents’ experiences with negative life events. Time perspec­ tive is a multitemporal (past, present, and future) and multidimensional construct (thoughts and feelings). Time perspective offers a new way to understand negative life events in adolescents.

Thus, the present study sought to address this gap in knowledge by investigating the associations between time perspective and negative life events among adolescents.

Negative Life Events Negative life events refer to undesirable experiences (Swearingen & Cohen, 1985a). Examples include school suspension, death of a close friend, and the experience of a serious illness or injury (Swearingen & Cohen, 1985a). One of the most widely used measures to assess negative life events among adolescents is the Junior High Life Experiences Survey (JHLES; Swearingen & Cohen, 1985a). In their original study of 233 adolescents, Swearingen

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Life Events and Time Perspective Among Adolescents | Chandler and Mello

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and Cohen (1985a) reported that the most com­ mon negative life event was an increase in arguing with parents (34%), followed by breaking up with a boyfriend/girlfriend (33%), and breaking up with a close friend (20%). Since then, the JHLES has been used in many studies with adolescents and children (Brown & Fite, 2016; Dinya et al., 2009; Ge et al., 2006; King et al., 2017; Lasgaard et al., 2016; Swearingen & Cohen, 1985b).

Research using the JHLES (Swearingen & Coen, 1985a) has indicated that negative life events are positively correlated with state anxiety and trait anxiety. For example, Brown and Fite (2016) demonstrated that, among 294 elementary schoolaged children, exposure to negative or stressful life events was positively associated with higher levels of anxiety, even after controlling for prior levels of peer victimization and depressive symptoms. Brown and Fite (2016) also observed that higher levels of anxiety, as a result of exposure to negative life events, increased the likelihood of being victimized by peers.

Negative life events have also been related to maladjustment. For example, in a study of 233 seventh- and eighth-grade students, Swearingen and Cohen (1985a) reported that negative life events were positively correlated with depression and the number of school days missed. These authors also observed a positive relationship between negative life events and psychological distress, specifically depression, among adolescents. Similarly, Hibbard et al. (1990) reported that physical and emotional abuse was associated with considering or attempting suicide, and laxative use and vomiting to lose weight among adolescents.

Negative life events have been associated with other psychological outcomes among adolescents.

In a study with 978 high school students, Lasgaard et al. (2016) demonstrated that adolescents who were frequently exposed to negative life events experienced more loneliness. Additionally, King et al. (2017) demonstrated that, among 259 adolescents aged 14 to 17 years old, the number of negative life events experienced was positively related to alcohol involvement among adolescents.

Further, Dinya et al.’s (2009) study of 644 new outpatient Hungarian adolescents from five local child psychiatric centers in Western Hungary showed that adolescents who experienced a high number of negative life events and who were more heavily impacted by negative life events had the most maladaptive and risky ways of coping.

Research has shown that experiencing negative life events in adolescence is also related to health

in adulthood. For example, Felitti et al. (1998) reported a strong positive relationship between adverse childhood experiences (ACES) and the development of multiple risk factors for several leading causes of death in adults including cancer, chronic lung disease, ischemic heart disease, and liver disease. This study examined several categories of ACES among 9,508 adults: physical abuse, sexual abuse, psychological abuse, maternal experienced violence, or household members who were mentally ill, abuse substances, suicidal, or ever imprisoned.

They observed that participants who had experi­ enced four or more categories of ACES were 4 to 12 times more at risk of developing alcoholism, abusing drugs, developing depression, and attempting sui­ cide. Moreover, the number of ACES categories was positively related to the presence of adult diseases including liver disease, ischemic heart disease, cancer, chronic lung disease, and skeletal fractures.

Similarly, other research has also indicated that experiencing negative life events is associated with delinquency in young adults (Hoffman, 2010).

Time Perspective Time perspective has long been considered to be a powerful predictor of human behavior (Lewin, 1942). Studies with adults have shown how it is associated with many areas of health including academic achievement and substance use (Keough et al, 1999; Zimbardo & Boyd, 1999). More recently, Mello and Worrell (2015) theorized that time perspective is a cognitive and multidimensional construct that is particularly salient in adolescence.

These authors proposed that time perspective dif­ fers between individuals. They proposed a model of time perspective with distinct time periods including the past, present, and future and mul­ tiple dimensions including time orientation, time frequency, and time attitude. Time orientation refers to the relative emphasis one has toward the past, present, and future. Time frequency refers to how often one thinks about each time period, and time attitude refers to whether one feels more negatively or positively about each time period. These dimen­ sions are measured with the Adolescent and Adult Time Inventory (AATI; Mello & Worrell, 2007).

Examining distinct time periods and dimensions enables researchers to generate a more nuanced understanding of time perspective in adolescents.

Although research has not yet examined negative life events and time perspective specifically, studies have examined topics similar to negative life events. For example, Mello et al. (2013) conducted

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Chandler and Mello | Life Events and Time Perspective Among Adolescents

a study with adolescents and risky behaviors that included missing school, smoking, and shoplift­ ing. Findings indicated that adolescents who were oriented toward solely the present or the future engaged in more risky behaviors than their coun­ terparts who were oriented toward multiple time periods simultaneously, and that adolescents who viewed the time periods as unrelated also reported engaging in more risky behavior than adolescents who viewed time periods as related to one another.

In a study of adolescents who had run away from home, Mello et al. (2017) observed that runaways had more negative feelings and less positive feelings toward time periods than adolescents who did not run away. Furthermore, runaways were oriented toward fewer time periods and perceived the time periods as being less related than their counterparts who did not run away from home. Notably, these results remained once controlling for academic achievement and maternal education. Overall, across these studies a pattern was observed that emphasizing multiple periods was associated with healthier developmental outcomes.

Studies with adult participants have indicated relationships between variables similar to negative life events and time perspective. In their study, Zimbardo and Boyd (1999) examined whether, among college students, negative thoughts of the past were positively associated with anxiety, low selfesteem, and depression. They also demonstrated that positive thoughts of the past were negatively associated with aggression, anxiety, and depression.

Further, in their study of 2,627 participants aged 14–67 years, Keough et al. (1999) observed that having a risk-taking, hedonistic attitude toward life was positively associated with increased risky health behaviors such as using alcohol, tobacco, and other drugs and having a greater number of sexual partners. Research has also shown that having a fatalistic, hopeless attitude toward life and the future (i.e., having a negative attitude toward the future) is related to regular tobacco use, less seatbelt use, and less safer sex practices among men (Henson et al., 2006).

Negative Life Events and Time Perspective in Adolescence Adolescence is an important developmental period to examine the association between negative life events and time perspective. Adolescents may suffer from adverse physical and psychological experi­ ences that carry over to adulthood making this age period important to investigate (Felitti et al.,

1998; Hoffman, 2010). Moreover, time perspective is especially salient in adolescence because of the developmental changes that happen in this period of the lifespan (Mello & Worrell, 2015). Specifically, a hallmark of adolescence is identity formation, a process of integrating past, present, and future selves (Erikson, 1968).

Modern approaches to identity, specifically, narrative identity (Adler et al., 2017), are also par­ ticularly relevant for understanding the associations between time perspective and negative life events in adolescents. Narrative identity refers to “dynamically reconstructed representations of events” (Adler et al., 2017, p. 5). This multifaceted construct refers to an individual’s conception of their life story that incorporates a reconstructed past, a perceived pres­ ent, and an imagined future—topics that embody temporal components akin to time perspective.

Moreover, narrative identity proposes that, when individuals describe events, they may affectively shift from positive to negative (i.e., contamination) or negative to positive (i.e., redemption). In this way, adolescents may experience negative life events and then vary individually in how the event is rep­ resented in their identity. Thus, narrative identity offers an additional framework for interpreting the ways that negative life events might be associated with time perspective in adolescents.

The Present Study Our study sought to extend knowledge on the relationship between negative life events and time perspective by examining how multiple dimensions and periods of time perspective are associated with negative life events. Thus, our study posed the following research question: How are negative life events related to time perspective? Time perspective was examined with a multidimensional measure that assesses time orientation, time frequency, and time attitudes (Mello & Worrell, 2007). Previous research has shown negative life events to be associated with negative outcomes such as loneliness, peer victimiza­ tion, and alcohol use (Brown & Fite, 2016; King et al., 2017; Lasgaard et al., 2016). Furthermore, past research has shown that adolescents who viewed the past, present, and future as unrelated reported riskier behavior (Mello et al., 2013). Based on these studies, we hypothesized that adolescents who have experienced more negative life events would be more likely to (a) be oriented toward the past, (b) think less often about time periods, and (c) report less favorable feelings about the time periods than their counterparts.

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Life Events and Time Perspective Among Adolescents | Chandler and Mello

Method Participants and Procedure Participants included 790 adolescents. The average age was 15.81 years (SD = 1.22). The sample was 56% female; 6% Black or African American, 18% Asian, 15% White, 43% Hispanic or Latino, and 15% more than one race or other racial/ethnic group. Maternal education was assessed on a scale that ranged from 1 (no high school diploma/GED) to 6 (doctoral/MD/PhD/JD). The mean level of maternal education for the sample was 2.77 (SD = 1.61), indicating an average between obtaining a high school diploma or GED, or an associate’s degree.

Data were obtained from two public Grade 9 to 12 high schools in the Western region of the United States. Participants were invited to complete the surveys with announcements made in the classroom. Participants who were interested were provided consent and assent forms. Students who returned the completed forms constituted the sample. Upon returning the surveys, each participant received a compensation of $10. The Institutional Review Board (IRB) at San Francisco State University approved the procedures for this study (IRB# H15-33c).

Measures Negative Life Events Negative life events were measured with the Junior High Life Experiences Survey (JHLES; Swearingen & Cohen, 1985a). The JHLES is a self-report measure that includes 39 items, 25 of which are negative, 9 of which are positive, and 5 of which are neutral. The most frequent way of using the JHLES is to create separate positive and negative variables.

Response options are either yes or no. Participants were asked to report if they had experienced a negative life event in the past six months. For the purposes of the current study, a negative life event variable was created by summing the total number of negative life events experienced. This form of categorization is similar to prior research (Brown & Fite, 2016). In the current study, the scores were internally consistent, as indicated by Cronbach’s alpha (α = .79).

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Time Perspective Ti m e p e r s p e c t i v e w a s m e a s u r e d w i t h t h e Adolescent and Adult Time Inventory (AATI; Mello & Worrell, 2007). The AATI included three components: time orientation, frequency, and attitudes. Time orientation included a single-item

categorical variable that asks participants to select a configuration of circles among a series of circle configurations that vary in size (see Table 1 for illustration). Larger circles indicated an emphasis toward a particular time period. Each circle con­ figuration consists of three circles labeled past, present, and future that were presented to partici­ pants. The following instructions were provided: “Select one figure below that shows how important the past, the present, and the future are to you, with larger circles being more important to you.”

Seven sets of circle figures were presented that indicated the relative importance of (a) the past, (b) the present, (c) the future, (d) the past and future, (e) the past and present, (f) the present and future, and (g) all three periods, with the final configuration representing a “balanced” view of the time periods. The item has been used success­ fully in prior studies on psychological outcomes of adolescents (e.g., Mello et al., 2013; Mello et al., 2017). Given that time orientation is a single-item variable and not a traditional scale with multiple items, reliability coefficients are not available.

Time frequency was assessed with three continu­ ous, Likert-type items that asked participants how frequently they think about the past, present, and future, respectively. Response options ranged from 1 (almost never) to 5 (almost always). The scales have been used successfully in prior studies that exam­ ine the psychological outcomes of adolescents (Mello et al., 2009). Given that these are single items, reliability coefficients are not available.

Time attitudes was assessed with was six 5-item continuous subscales that ascertain one’s positive and negative attitudes toward the past, present, and future. These subscales included Past Positive (α = .83), Past Negative (α = .85), Present Positive (α = .85), Present Negative (α = .85), Future Positive (α = .88), and Future Negative (α = .82).

Response options ranged from 1 (totally disagree) to 5 (totally agree). The psychometric properties of the time attitude subscale have been reported in several studies with adolescent samples and indi­ cate the scale yields internally consistent subscales and a six-factor structure (e.g., Mello et al., 2016).

Results Preliminary Analyses Descriptive statistics are shown in Table 2. As indicated, preliminary analyses showed that almost half of the participants experienced a death of someone close to them. Specifically, in the past

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Chandler and Mello | Life Events and Time Perspective Among Adolescents

six months, 30.04% experienced the death of a grandparent, aunt, uncle, or cousin, 15.26% of participants experienced the death of a close friend, 6.45% experienced the death of a parent, and 7.40% experienced the death of a sibling.

Moreover, 10.98% of participants were assaulted, robbed, or had been the victim of a violent crime.

Primary Analyses Negative Life Events and Time Orientation A one-way analysis of variance showed that negative life events were related to time orientation, F(6, 605) = 5.02, p < .001 (see Table 1). Specifically, adolescents who experienced the most nega­ tive life events (M = 7.07, SD = 5.89) had a time orientation that emphasized the past over the present and future compared to adolescents who experienced the fewest negative life events (M = 3.54, SD = 2.56) who reported a “balanced” time orientation, indicating that they were oriented equally toward the past, present, and future. It is worth noting that response options included groups with unequal sample sizes, which was consistent with previous literature (Mello et al., 2013). Bonferroni post-hoc comparison tests indicated several pair-wise differences: participants who were oriented toward the present and future simultaneously or who were balanced reported fewer negative life events compared to participants who were oriented toward the past solely, the past and future simultaneously, or the past and present simultaneously.

We evaluated the effect size of the results for time orientation in multiple ways. First, we examined the model and determined that the effect size for this finding was small based on the f value (5.02) and eta-squared η2 = .05. Second, given theory and prior research that has shown how “balanced” (i.e., response Option 7) was associated with healthier developmental outcomes (e.g., Mello et al., 2013), we generated pair-wise Cohen’s d values between “balanced” and the remaining response options. These analyses indicated that effect sizes between the “balanced” perspective (i.e., response Option 7) and the other response options ranged from small to large: past (i.e., response Option 1; d = 1.04); the present (i.e., response Option 2; d = 0.24); the future (i.e., response Option 3; d = 0.26); the past and the future (i.e., response Option 4; d = 0.50); the past and the present (i.e., response Option 5; d = 0.62); and the present and the future (i.e., response Option 6; d = 0.02).

TABLE 1 Negative Life Events and Time Orientation*** Negative Life Events

#

Label

Circle Configuration

n (%)

1

Past

Ooo

15 (2.45)

7.07

5.89

2

Present

oOo

47 (7.68)

4.45

4.94

3

Future

ooO

80 (13.07)

4.50

4.38

4

Past-Future

OoO

98 (16.04)

b

4.99

3.32

5

Past-Present

OOo

22 (3.60)

5.50c

4.66

6

Present-Future

oOO

282 (46.15)

a,b,c

3.59

4.66

7

Balanced

OOO

68 (11.13)

3.54a,b,c

2.56

M

SD a

Note. Circle configuration names are shown for clarity and are not included on actual instrument. Percentages are rounded. a = Bonferroni Test (p < .10) (1 > 6) (1 > 7) b = Bonferroni Test (p < .10) (4 > 6) (4 > 7) c = Bonferroni Test (p < .10) (5 > 6) (5 > 7) *** p < .001.

TABLE 2 Frequency of Negative Life Events (N = 790) Negative Life Event School suspension

n

%

68

8.6

Broke up with boy friend/girl friend

243

30.8

Broke up with close friend

245

31

Close friend died

101

12.8

Seriously ill/injured

149

18.9

Mother/father seriously ill/injured

121

15.3

Brother/sister seriously ill/injured

81

10.3

Not accepted into important extracurricular activity

107

13.5

Parent lost a job

117

14.8

Favorite pet died

87

11

Ran away from home

66

Flunked a grade

76

9.6

Brother/sister had serious trouble (e.g., arrested, pregnancy)

80

10.1

Started wearing braces or glasses

8.4

162

20.5

Assaulted, robbed, or victim of other violent crime

73

9.2

Family member a victim of violence

71

9

Mother or father died

42

5.3

Brother or sister died

49

6.2

Grandparent, aunt, uncle, or cousin died

201

25.4

Argued more with parents

305

38.6

Family had serious financial troubles

161

20.4

Because of job change or other reason, mother/father spent much more time away from home

149

18.9

Parents argued much more with each other

159

20.1

89

11.3

Parents divorced or separated

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Life Events and Time Perspective Among Adolescents | Chandler and Mello

Negative Life Events and Time Frequency Negative life events were also associated with time frequency (see Table 3). Negative life events were inversely related to thinking frequently about the present (r = −0.12, p < .001). Similarly, negative life events were inversely related to thinking frequently about the future (r = −0.10, p < .01). However, these relationships were small in effect size drawing from Cohen (1992). Moreover, there was no association between negative life events and thinking fre­ quently about the past (r = 0.02, p = .66).

Negative Life Events and Time Attitudes Negative life events and time attitudes were related to one another in theoretically expected directions (see Table 3). Results indicated that negative life events were inversely associated with positive feelings about the past (r = −.21, p < .001) and positively related to negative feelings about the past (r = .27, p < .001).

Additionally, negative life events were inversely related to positive feelings about the present (r = −.18, p < .001) and positively associated with negative feelings about the present (r = .22, p < .001). Negative life events were also inversely associated to positive feel­ ings about the future (r = −.13, p < .001) and positively related to negative feelings about the future (r = .18, p < .001). These relationships were small in magni­ tude. Based on Cohen’s (1992) guidelines, the effect sizes for these associations were mostly small. The larg­ est effect was observed between negative life events and negative feelings about the past (i.e., r = .27).

TABLE 3 Correlations Among Negative Life Events, Time Frequency, and Time Attitudes 1 1.

2

3

4

5

6

7

8

9

Negative Life Events Time Perspective Time Frequency

2.

Past

−.02

3.

Present

−.12***

.30***

4.

Future

−.10**

.27***

.33***

Time Attitudes 5.

Past Positive

6.

Past Negative

7.

Present Positive

8.

Present Negative

9.

10.

−.21*** −.02 .27

***

.21

***

−.18*** −.10** ***

.22

.27

Future Positive

−.13***

.04

Future Negative

.18

.07

p < .05. **p < .01. ***p < .001.

*

40

***

***

*

.17*** −.07

*

.23*** −.05 .21*** −.16

***

.13*** .01 −.55*** .11**

.48*** −.32***

.04 −.26***

.54*** −.36***

.33*** .30*** −.08* −.16 −.13 ***

***

.41

***

.56*** −.33*** −.34***

.58*** −.53***

Discussion The current study sought to bridge research on negative life events and time perspective. Previous research has shown that the number of negative life events experienced is related to mental health indicators such as higher levels of anxiety (Brown & Fite, 2016) and risky behavior (King et al., 2017).

We sought to extend this topic of negative life events to time perspective. Our study provided new knowledge about the relationship between nega­ tive life events and time perspective. We showed how employing a multitemporal (past, present, and future) and multidimensional (thoughts and feelings) model of time perspective (Mello, 2019; Mello & Worrell, 2015) yielded new information about associations between time perspective and negative life events. Overall, findings indicated that negative life events were associated with several time perspective dimensions including time orientation, time frequency, and time attitudes in a sample of adolescents.

Our study generated new knowledge by show­ ing how multiple time periods and multiple dimensions of time perspective were related to negative life events. As hypothesized, we observed relationships among negative life events and time orientation. Adolescents who experienced the most negative life events emphasized the past over the present and future. Conversely, adolescents who experienced the fewest negative life events displayed a “balanced” time orientation, indicated by an equal orientation toward the past, present, and future, or a “present-future” orientation, indicated by a joint emphasis toward the present and future. This finding is consistent with previous research that has shown that adolescents who are oriented toward multiple periods report the healthi­ est outcomes compared to their counterparts who are oriented solely toward one time period (Mello et al., 2013; Mello et al., 2017). Moreover, negative life events were inversely related to how frequent adolescents reported thinking about the present and the future. This is somewhat consistent with prior research that has shown how adolescents who run away from home, who are assumed to have experienced negative life events, think about the present less often than their counterparts who have not run away from home (Mello et al., 2017).

As we expected, negative life events were inversely related to positive feelings about the past, present, and future. Similarly, negative life events were positively associated with negative feelings about the past, present, and future. These findings

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Chandler and Mello | Life Events and Time Perspective Among Adolescents

are consistent with previous research that has shown how attitudes toward time are associated with risky behaviors (McKay et al., 2014), and mental well-being (Konowalczyk et al., 2018). Specifically, McKay et al. (2014) demonstrated that adolescents who held more positive and less negative attitudes toward the time periods used fewer substances than their counterparts. Conversely, these authors showed that adolescents who held negative attitudes about the time periods used more substances than their counterparts. Moreover, Konowalczyk et al.

(2018) reported that, among adolescents, negative feelings about the time periods were associated with lower mental well-being, and more psychological and somatic symptomatology. Our study extended this body of research and demonstrated that time feelings are associated with negative life events in adolescents.

Theoretically, this study provides support for the temporal qualities of negative life events, as we demonstrated associations between the self-reported negative life events that adolescents experienced and their time perspective. These find­ ings provide further support for the seminal work of Erikson (1968) who described the value of forming an identity that integrated past, present, and future selves for healthy development in adolescence.

This study also lends itself to more contemporary approaches to identity including narrative identity (Adler et al., 2017). Specifically, the association between time perspective and negative life events may be connected via the adolescents’ reflection and interpretation of the unfavorable experience.

Overall, the current study expanded the literature by examining a new area, specifically the relationship between life events and time perspec­ tive. Experiencing life events has been shown to be associated with many outcomes (e.g., Felitti et al., 1998), and now we have extended this relationship to time perspective. Although previous studies have examined the relationship between negative life events and adolescent outcomes, and between time perspective and adolescent outcomes, no studies to our knowledge have examined the relationship between negative life events and time perspective.

Thus, the current study offers a novel expansion of the literature in this area.

completed, a possible implication of this line of research could be to use the time perspective scales as a nonintrusive diagnostic tool to identify adolescents who are experiencing negative life events. Given that the time perspective scales do not mention specific life events, they could be used as subtle form of assessment that serves as an indicator of negative life events. This might be useful when adolescents are reticent to report the negative experiences they have had in life. It is possible that this type of tool could facilitate the effectiveness of adolescent-serving professionals including clinicians, counselors, and educators.

Implications The current study provides preliminary evidence that time perspective is associated with negative life events in adolescents. It is important that these results be replicated. After such studies are

Conclusion Our study sought to explore the relationship between negative life events and time perspective among adolescents. Using self-reported data with 790 adolescents, we found that participants who

Limitations and Future Directions Our study was one of the first to examine the relationship between negative life events and time perspective, but it also had some limitations. First, we did not assess the impact of the life event on the participant. It is possible that the time perspectives of adolescents may be especially impacted by nega­ tive life events that had a large impact on their life.

Future studies should seek to replicate our findings while also considering the degree that negative life events impacted the adolescent. Second, our study was cross-sectional, which limits our ability to under­ stand the direction of association between negative life events and time perspective. It is possible that the time perspective of the adolescent before they experienced the negative life event contributed to how the event impacted their life, including their time perspective. Future research would benefit from longitudinal studies to determine the causal relationships between these topics. Third, validity or manipulation checks were not completed. Thus, we were unable to confirm the occurrence of the life-events that the adolescents reported. Future studies should seek to include other reports, such as those of parents, teachers, or school counselors in an effort to validate the life-events. Lastly, response options for the time orientation variable included groups with unequal sample sizes. Although the percentage of responses in each response option was similar to prior studies (Mello et al., 2013), future studies should seek to replicate these results with a more equal distribution of responses among response options.

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Life Events and Time Perspective Among Adolescents | Chandler and Mello

experienced a higher number of negative life events were more oriented toward the past. Additionally, participants who experienced a high number of negative life events thought less frequently about the present and future and had negative attitudes toward the past, present, and future. Future research should focus on developing interventions to help educate adolescents who have experienced a large number of negative life events of their potential outcomes and to help shift the way they think about time so that they may achieve more positive outcomes in adulthood.

References Adler, J. M., Dunlop, W. L., Fivush, R., Lilgendahl, J. P., Lodi-Smith, J., McAdams, D. P., McLean, K. C., Pasupathi, M., & Syed, M. (2017). Research methods for studying narrative identity: A primer. Social Psychological and Personality Science, 8(5), 519–527. https://doi.org/10.1177/1948550617698202 Andretta, J. R., Worrell, F. C., & Mello, Z. R. (2014). Predicting educational outcomes and psychological well-being in adolescents using time attitude profiles.

Psychology in the Schools, 51(5), 434–451. https://doi.org/10.1002/pits.21762 Brown, S., & Fite, P. J. (2016). Stressful life events predict peer victimization: Does anxiety account for this link? Journal of Child and Family Studies, 25(8), 2616–2625. https://doi.org/10.1007/s10826-016-0428-3 Centers for Disease Control and Prevention. (2019). About adverse childhood experiences. https://www.cdc.gov/violenceprevention/ childabuseandneglect/acestudy/aboutace.html Cohen, J. (1992). A power primer. Psychological Bulletin, 112(1), 155–159. https://doi.org/10.1037/0033-2909.112.1.155 Dinya, E., Csorba, J., Sorfozo, Z., Steiner, P., Ficsor, B., & Horvath, A. (2009).

Profiles of suicidality and clusters of Hungarian adolescent outpatients suffering from suicidal behavior. Psychopathology, 42(5), 299–310. https://doi.org/10.1159/000228839 Erikson, E. (1968). Identity: Youth and crisis (1st ed.). Norton.

Felitti, V. J., Anda, R. F., Nordenberg, D., Williamson, D. F., Spitz, A. M., Edwards, V., Koss, M. P., & Marks, J. S. (1998). Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults: The adverse childhood experiences (ACE) study. American Journal of Preventive Medicine, 14(4), 245–258. https://doi.org/10.1016/s0749-3797(98)00017-8 Ge, X., Natsuaki, M. N., & Conger, R. D. (2006). Trajectories of depressive symptoms and stressful life events among male and female adolescents in divorced and nondivorced families. Development and Psychopathology, 18(1), 253–273. https://doi.org/10.1017/S0954579406060147 Hibbard, R. A., Ingersoll, G. M., & Orr, D. P. (1990). Behavioral risk, emotional risk, and child abuse among adolescents in a nonclinical setting. Pediatrics, 86(6), 896–901.

Henson, J. M., Carey, M. P., Carey, K. B., Maisto, S. A. (2006). Associations among health behaviors and time perspective in young adults: Model testing with boot-strapping replication. Journal of Behavioral Medicine, 29(2), 127–137. https://doi.org/10.1007/s10865-005-9027-2 Hoffmann, J. P. (2010). A life-course perspective on stress, delinquency, and young adult crime. American Journal of Criminal Justice, 35(3), 105–120. https://doi.org/10.1007/s12103-010-9072-4 Keough, K. A., Zimbardo, P. G., & Boyd, J. N. (1999). Who’s smoking, drinking, and using drugs? Time perspective as a predictor of substance use. Basic and Applied Social Psychology, 21(2), 149–164. https://doi.org/10.1207/15324839951036498 King, K. M., Pedersen, S. L., Louie, K. T., Pelham, W. J., & Molina, B. S. G. (2017).

Between- and within-person associations between negative life events and alcohol outcomes in adolescents with ADHD. Psychology of Addictive

Behaviors, 31(6), 699–711. https://doi.org/10.1037/adb0000295 Konowalczyk, S., McKay, M. T., Wells, K. E., & Cole, J. C. (2018). The influence of time attitudes profile membership on mental well-being and psychosomatic symptomatology: A United Kingdom-based prospective study. Psychiatry Research, 261, 375–382. https://doi.org/10.1016/j.psychres.2017.12.071 Lasgaard, M., Armour, C., Bramsen, R. H., & Goossens, L. (2016). Major life events as predictors of loneliness in adolescence. Journal of Child and Family Studies, 25(2), 631–637. https://doi.org/10.1007/s10826-015-0243-2 Lewin, K. (1942). Time perspective and morale. In K. Lewin (Ed.), Resolving social conflicts and field theory in social science (pp. 80–93). American Psychological Association.

McKay, M. T., Andretta, J. R., Magee, J., & Worrell, F. C. (2014). What do temporal profiles tell us about adolescent alcohol use? Results from a large sample in the United Kingdom. Journal of Adolescence, 37(8), 1319–1328. https://doi.org/10.1016/j.adolescence.2014.09.008 McKay, M. T., Percy, A., Cole, J. C., Worrell, F. C., & Andretta, J. R. (2016). The relationship between time attitudes profiles and self-efficacy, sensation seeking, and alcohol use: An exploratory study. Personality and Individual Differences, 97, 203–209. https://doi.org/10.1016/j.paid.2016.03.060 Mello, Z. R. (2019). A construct matures: Time perspective’s multidimensional, developmental, and modifiable qualities. Research in Human Development, 16(2), 93–102. https://doi.org/10.1080/15427609.2019.1651156 Mello, Z. R., Finan, L. J., & Worrell, F. C. (2013). Introducing an instrument to assess time orientation and time relation in adolescents. Journal of Adolescence, 36(3), 551–563. http://dx.doi.org/10.1016/j.adolescence.2013.03.005 Mello, Z. R., Walker, E. B., Finan, L. J., Stiasny, A., Wiggers, I. C. S., McBroom, K. A., & Worrell, F. C. (2017). Time perspective, psychological outcomes, and risky behavior among runaway adolescents. Applied Developmental Science, 22(3), 233–243. https://doi.org/10.1080/10888691.2016.1276455 Mello, Z. R., & Worrell, F. C. (2007). The Adolescent Time Inventory-English.

Unpublished scale: University of California, Berkeley.

Mello, Z. R., & Worrell, F. C. (2015). The past, the present, and the future: A conceptual model of time perspective in adolescence. In Stolarski M., van Beek W., & Fieulaine, N. (Eds), Time perspective theory: Review, research and application. Essays in honor of Philip Zimbardo. Springer.

Mello, Z. R., Worrell, F. C., & Andretta, J. R. (2009). Variation in how frequently adolescents think about the past, the present, and the future in relation to academic achievement. Research on Child and Adolescent Development [Diskurs Kindheits- und Jugendforschung], 4, 173–183.

Mello, Z. R., Zhang, J. W., Barber, S. J., Paoloni, V. C., Howell, R. T., & Worrell, F. C. (2016). Psychometric properties of time attitude scores in young, middle, and older adult samples. Personality and Individual Differences, 101, 57–61. http://dx.doi.org/10.1016/j.paid.2016.05.037 Swearingen, E. M., & Cohen, L. H. (1985a). Measurement of adolescents’ life events: The Junior High Life Experiences Survey. American Journal of Community Psychology, 13(1), 69–85. https://doi.org/10.1007/BF00923260 Swearingen, E. M., & Cohen, L. H. (1985b). Life events and psychological distress: A prospective study of young adolescents. Developmental Psychology, 21(6), 1045–1054. https://doi.org/10.1037/0012-1649.21.6.1045 Zimbardo, P. G., & Boyd, J. N. (1999). Putting time in perspective: A valid, reliable individual-differences metric. Journal of Personality and Social Psychology, 77(3), 1271–1288. https://doi.org/10.1037/0022-3514.77.6.1271 Author Note. Julie V. Chandler https://orcid.org/0000-00032369-7480 Zena R. Mello https//orcid.org/0000-0001-8218-9801 Julie V. Chandler is now at the Department of Psychology at Central Michigan University, Mount Pleasant, MI. We have no known conflict of interest to disclose. Special thanks to Psi Chi Journal reviewers for their support.

Correspondence concerning this article should be addressed to Zena R. Mello, Department of Psychology, San Francisco State University, 1600 Holloway Ave., San Francisco, CA, 94132. Email: zmello@sfsu.edu.

Telephone: (415) 338-7557. Fax: (719) 338-2398.

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https://doi.org/10.24839/2325-7342.JN26.1.43

The Effect of Strategic Instruction for Categorical Clustering on Preschoolers’ Recall Accuracy Isabella DelVecchio and Mary Stone* Department of Psychology, Marist College

ABSTRACT. Categorical clustering involves the grouping of stimuli into meaningful categories when encoding or retrieving to-be-learned information during memory tasks. The current study measured the categorical clustering behavior of 40 three- to four-year-olds who completed a spatial memory task requiring them to remove and return toys to their original locations within a box. After completing the spatial memory task without strategic instruction, participants were randomly assigned to receive instructions to categorically cluster while removing (encoding) or returning the toys (retrieval) to the box, or receive no strategic instruction (control).

Results showed increases in clustering behaviors following strategic instruction, suggesting that participants were able to successfully produce clustering behavior following instruction to do so. Although instruction to categorically cluster during encoding and retrieval generated a significant increase in clustering behavior when removing and returning the toys to the box, respectively, it only improved recall for those instructed to categorically cluster when retrieving the toy locations. Increased engagement in categorical clustering when encoding the toy locations negatively impacted recall, resulting in a utilization deficiency for participants instructed to remove the toys according to their category membership. No changes in clustering behavior or recall accuracy were observed in the participants who completed the task a second time without strategic instruction. Implications for the current understanding of utilization deficiencies observed among preschoolers and future directions for research are discussed.

Keywords: categorical clustering, encoding, retrieval, preschoolers, utilization deficiency

R

esearch on child development and learning has explored how and when memory strategies are produced and utilized by children in the context of learning new information. Memory strategies, which generally become available during the preschool years (Bjorklund et al., 2009), may be defined as goaldirected behaviors executed during the encoding or retrieval stages of a memory task, and pertain to the specific behaviors children spontaneously engage in while learning new information and then subsequently retrieving it from memory (Bjorklund, 1987). Specifically, behaviors that *Faculty mentor

children use while learning new information are referred to as encoding strategies, and behaviors that children use while attempting to retrieve that information are referred to as retrieval strategies (Roebers, 2014).

Encoding and Retrieval Strategies A classic example of young children’s organi­ zational strategy use during encoding is dem­ onstrated in Miller and Weiss’ (1981) seminal selective memory task. Here, children in second, fifth, and eighth grade were presented with an apparatus consisting of two rows of doors illustrated

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Categorical Clustering in Preschoolers | DelVecchio and Stone

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with either a cage covering a picture of an animal or a house covering a picture of a household item.

Children were told to remember as many locations of either the animals or household pictures as possible, and then were given a 30-second study period to learn the locations as they saw fit. The pattern and number of doors opened in the study phase served as indicators of strategy use during encoding. Strategy effectiveness was indexed by the relation between participants’ relevant strategy use (e.g., open only animal doors) and recall of relevant picture locations (e.g., animals) within the two rows of doors. Findings showed that children under the age of six years indiscriminately opened all doors during the study period. By the age of 10 years, children began to generate a selective encoding strategy by selectively opening only the relevant doors (see Roebers, 2014).

When modified to more closely resemble a play situation, adaptations of the Miller and Weiss (1981) memory task produce similar trends with younger participants (see Blumberg & Torenberg, 2003, 2005). Specifically, children as young as 3 years old have demonstrated the ability to sponta­ neously produce a specific memory strategy known as categorical clustering (see Stone & Blumberg, 2019; Stone et al., 2016) when completing a spatial memory task involving two categories of toys.

Categorical clustering, which involves the group­ ing of stimuli into meaningful categories, is often studied through the random presentation of words (Bjorklund et al., 1992; Coyle & Bjorklund, 1996; Schlagmüller & Schneider, 2002), pictures (Clerc & Miller, 2013; Miller & Weiss, 1981; Roderer et al., 2012; Roebers et al., 2010), or objects (Blumberg & Torenberg, 2003, 2005; Stone & Blumberg, 2019) representing specific categories (e.g., animals, tools, or fruits), and followed by an assessment of the extent to which children use those categories to recall such stimuli.

Blumberg and Torenberg (2003, 2005) set up a spatial memory task whereby three- and four-yearold children were asked to remember the locations of one of two sets of toys (either miniature animals or chairs), remove all the toys, and then replace the toys in their original locations in a square wooden box. During encoding, or while children were learning the locations of the toys, categorical clus­ tering referred to children’s ability to selectively attend to or sort information to be remembered according to category membership. Similarly, at retrieval, or when children had to remember the original locations of the toys to return them

to the box, categorical clustering referred to the organization of semantically related items while retrieving learned information. Results showed that most 3- and 3-year-old children spontaneously used categorical clustering when encoding and retrieving the spatial arrangement of the toys by removing and/or returning the toys according to their category membership. However, only the performance of the 4-year-olds was consistently enhanced via the use of the clustering strategy. The younger participants presented with a utilization deficiency, whereby clustering strategy production did not facilitate recall for the toy locations (Miller, 1990).

Utilization Deficiencies Miller (1990) introduced the term utilization deficiency to describe such instances when children spontaneously implement a strategy that yields little or no benefit. Researchers have characterized a utilization deficiency as an early stage in strategy acquisition whereby children spontaneously imple­ ment a strategy but experience no improvement in recall or present with diminished recall as a result of strategy production (Clerc & Miller, 2013; De-Marie-Dreblow & Miller, 1998; Miller, 1990).

Researchers have historically explained utilization deficiencies as reflecting limited resources whereby the spontaneous production of a strategy depletes the cognitive resources needed to benefit from it (e.g., Miller et al., 1991; Schneider et al., 2004; Woody-Dorning & Miller, 2001). However, the specific mental processes and resources used when children produce and use strategies are less clear.

First, links to age-related changes have been suggested (e.g., Bjorklund et al., 1992; Miller & Weiss, 1981). For instance, Bjorklund et al. (1992) found that, when kindergartners (6-year-olds), third graders (9-year-olds), and eighth graders (13-year-olds) were instructed to recall different lists with different categories over trials, levels of recall and clustering increased with age. Although both third and eighth graders in the study demon­ strated the use of an organizational strategy, this led to increased performance only for the eighth grad­ ers, whereas third graders demonstrated strategy use that resulted in little or no benefit. Similarly, Miller and Weiss (1981) found that the implemen­ tation of an organizational strategy only improved the recall of 13- to 14-year-olds who participated in their memory task. The pattern of performance by the eight- to nine-year-olds and 10- to 11-year-olds was reflective of a utilization deficiency, or strategic

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DelVecchio and Stone | Categorical Clustering in Preschoolers

behaviors that did not improve recall.

Second, links between strategy use and general intelligence (e.g., Bjorklund et al., 1994) have been explored and suggest that, even in potential cases where levels of categorical clustering are high, the usefulness of strategy utilization for recall accuracy may depend on intelligence level (Bjorklund et al., 1994). Lastly, theoretical links between utilization deficiencies and executive function skills such as working memory have been suggested (Clerc et al., 2014; Schleepen & Jonkman, 2012). Clerc et al. (2014) suggested that, when presented with a new task, a child must engage in effortful activities (i.e., determining whether to use a strategy, engag­ ing in strategy selection, and determining what minor modifications are necessary for applying a strategy), and that this cognitive work may result in a utilization deficiency. Schleepen and Jonkman (2012) provided empirical support for the role of executive function in utilization deficiencies. They found that, when 6- to 12-year-olds were asked to verbally recall 12 black and white line drawings that represented category exemplars, working memory mediated the effectiveness of the categorical clus­ tering strategy during both encoding and retrieval whereby participants with higher working memory capacities were more likely to benefit from the clustering strategies to accurately recall the images.

Participants with more limited working memory capacities presented with a utilization deficiency in that high levels of clustering behaviors during the encoding and retrieval phases of the task did not result in effective recall of the images.

Further Predictors of Strategy Utilization Subsequent examinations of preschoolers’ spon­ taneous strategy production and utilization (see Stone & Blumberg, 2019; Stone et al., 2016) when completing the Blumberg and Torenberg spatial memory task have helped to further elucidate predictors of strategy utilization. Stone et al. (2016) investigated how spontaneous production of a cat­ egorical clustering strategy might be mediated by preschoolers’ executive function skills, and Stone and Blumberg (2019) examined relative effective­ ness of categorical clustering as an encoding versus retrieval strategy. In both of these studies, and consistent with research on categorical clustering more generally, categorical clustering behavior was measured according to adjusted ratio of clustering (ARC) scores, which take into account the number of relevant category repetitions relative to the num­ ber of possible repetitions (corrected for chance)

in order to quantify participants’ production of (or ability to engage in) a clustering sequence (Bjorklund, 1987; Roenker et al., 1971; Roderer et al., 2012). As such, the order in which toys were removed from the box during the Blumberg and Torenberg spatial memory task served as a measure of the extent to which participants spontaneously categorically clustered while removing toys (or encoding their locations), and the order in which toys were returned to the box served as a measure of the extent to which participants categorically clustered while returning the toys (or retrieving their locations).

Similar to the rates of strategy production and utilization reported by Blumberg and Torenberg (2003, 2005), Stone et al. (2016) and Stone and Blumberg (2019) found that most preschool-aged participants spontaneously implemented a cluster­ ing strategy by removing and/or replacing the toys according to category membership, but less than half of those strategic participants showed con­ comitant memory benefits (recall of toy locations).

Stone et al. (2016) contributed that participants’ working memory capacity (but not other executive functions such as inhibition or attention shifting skills) predicted strategy utilization after control­ ling for age and IQ. Specifically, preschoolers with higher working memory capacities benefitted more from categorical clustering strategy production by recalling more toy locations than their counter­ parts with lower working memory capacities.

Further, Stone and Blumberg (2019) investi­ gated whether categorical clustering differentially impacted recall when produced when encoding and/or retrieving the toy locations, and found that the combined use of a categorical clustering strategy at the time of encoding and retrieval failed to result in greater recall performance for strategic participants. At best, using categorical clustering when both encoding and retrieving toy locations did not enhance recall beyond the benefit derived from using categorical clustering as a retrieval strategy alone, and at worst, using categorical clustering when encoding and retrieving the toy locations diminished recall in comparison to its exclusive use as a retrieval strategy. The researchers presumed that this utilization deficiency might have been observed because participants who presented with high levels of recall after exclu­ sively engaging in categorical clustering during retrieval had, in fact, implicitly encoded the toy locations despite not having explicitly produced a clustering strategy while doing so. They presumed

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that spontaneous strategy production at both timepoints is cognitively taxing and detracts from the ability to effectively recall, suggesting that the cognitive cost of overt strategy production may be higher at the time of encoding than at the time of retrieval, particularly among young children (Bjorklund, 1987; Miller et al., 1991; Schneider et al., 2004; Woody-Dorning & Miller, 2001).

Combined, these studies suggest that pre­ schoolers with lower working memory capacities (Stone et al., 2016) or those that produce a clustering strategy when encoding toy locations (Stone & Blumberg, 2019) are more likely to pres­ ent with a utilization deficiency than those with higher working memory capacities (Stone et al., 2016) or those that produce the clustering strategy when retrieving toy locations (Stone & Blumberg, 2019). These findings support previous speculation that the spontaneous production of a categorical clustering strategy may be too cognitively taxing for some preschoolers to facilitate their recall accuracy, begging the question of whether the implementa­ tion of strategic instruction to categorically cluster, whereby spontaneous production of a strategy is not relied upon, might decrease cognitive load enough to aid recall among preschoolers.

Although previous studies have examined cat­ egorical clustering related to recall accuracy, and some have explored how utilization of a memory strategy may be mediated by factors such as intel­ ligence and working memory, none have evaluated the impact of strategic instruction for categorical clustering on preschoolers’ recall accuracy. As such, the present study measured the clustering strategy production, recall accuracy, intelligence, and working memory of 3- to 4-year-old children both prior to and following strategic instruction on an adaptation of the Blumberg and Torenberg (2003, 2005) spatial memory task. This examina­ tion sought to answer the following questions: 1. Will relationships suggested by past research between spontaneous engagement in categorical clustering behavior, recall accuracy, age, working memory, and intelligence be observed?

2. Is a single instruction to engage in categorical clustering at encoding and/or retrieval sufficient to increase clustering behaviors among preschoolers?

3. Does strategic instruction for categorical clustering have a differential impact on recall accuracy for toy locations at encoding or retrieval?

Method Participants Participants were drawn from a sample of 43 three(n = 24) to four-year-old (n = 19) children (27 boys, 14 girls, and 2 gender not reported) from three pri­ vate and public preschools across two predominantly White and upper-middle socioeconomic status towns in the Northeast United States. Participants were recruited from their preschools in which the study took place. Participants ranged in age from 36 to 58 months (Mage = 46.93, SD = 5.70), and all demon­ strated average to above average IQ scores ranging from 88 to 130 (M = 106.55, SD = 10.03) on the abbreviated Stanford Binet Intelligence Scales for Early Childhood – Fifth Edition (Roid, 2005). There was a broader range in performance on the Picture Sequence Memory task of the NIH Toolbox (Zelazo et al., 2013), whereby performance ranged from two standard deviations below the mean to two standard deviations above the mean, but performance was still normally distributed across participants (M = 100.36, SD = 12.75). Children with educational classi­ fications or developmental diagnoses were excluded from the study. Although there were 43 participants for whom parental consent had been obtained, three participants were excluded from the dataset.

One participant did not meet the inclusion criteria, and two participants had incomplete data due to requests to end participation before completing all the tasks. One participant did not meet inclusion criteria because they had an Abbreviated IQ score of less than 85, a second, when asked, did not wish to participate in the study, and a third was excluded because a request to discontinue participation was made halfway through the procedure.

Materials The spatial memory task apparatus consisted of a 3" × 17" × 17" wooden box with white inside-facing walls and a white floor (see Figure 1). Inside the box were eight miniature toys ranging from 1.5 to 1.7 inches in diameter, and belonging to one of two categories: animals and chairs. The specific toys used in this administration of the spatial memory task were four chairs: kitchen chair, lawn chair, couch chair, and rocking chair, and four animals: giraffe, tiger, elephant, and zebra, of which only toys belonging to the category membership of animals (i.e., the giraffe, tiger, elephant, and zebra) were recorded as relevant items. All toys maintained the same positions across all participants, and were arranged in the box such that one toy stood in each of four corners, and the four remaining toys

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DelVecchio and Stone | Categorical Clustering in Preschoolers

stood in a diamond arrangement at the center of the box 1.5 inches from the midpoint of each of the four walls. To ensure that spatial position (corner or center) would not be redundant with category membership (animal or chair), two toys from each category were placed in corner positions, and two toys from each category were placed in center positions.

The spatial memory task apparatus (including specific toys) is consistent with that presented in previous administrations of the spatial memory task (see Blumberg & Torenberg, 2003, 2005; Stone & Blumberg, 2019; Stone et al., 2016). In addition, the configuration of toys within the box is based on the findings of past studies, which utilized the same spatial memory task; toys belonging to the category membership of animals served as relevant items because no differences according to relevant toy iden­ tification, animals or chairs, have been demonstrated with prior uses of the task, and all toys maintained the same positions across all participants because no differences in toy configuration have been found in previous investigations (Blumberg & Torenberg, 2003, 2005; Stone & Blumberg, 2019; Stone et al., 2016). Lastly, two toys from each category were placed in corner positions and two toys from each category were placed in center positions, because this configuration is consistent with previous investiga­ tions (Stone & Blumberg, 2019; Stone et al., 2016).

Procedure Approval from the Marist College Institutional Review Board was obtained prior to data collection.

Each participant completed the spatial memory task twice. During the first administration (Phase 1), no strategic instructions were given. This enabled researchers to observe spontaneous production of a categorical clustering strategy. Immediately following the first administration, participants were randomly assigned to one of three conditions, and completed the spatial memory task a second time according to the condition in which they belonged (Phase 2). Participants belonging to the encoding condition (n = 10) were instructed to remove all of the animals first when taking toys out of the box. This was strategic instruction to categorically cluster while encoding toy locations, and prompted categorical clustering during the encoding of toy locations.

Participants belonging to the retrieval condition (n = 12) were instructed to return all of the animals first when returning toys to the box. This was strategic instruction to categorically cluster while retrieving toy locations, and prompted categorical clustering

while retrieving the toy locations. Lastly, participants belonging to the control condition (n = 18) completed the spatial memory task a second time with no strategic instruction. Because of the limited (n = 40) sample size, and because participants were excluded from data analysis after they had been assigned to and completed the study procedure according to one of the conditions, the number of participants in each condition was not equal. Completion of both spatial memory task administrations lasted approximately 30 minutes.

Phase 1 One female experimenter and each participant sat across from each other in adult-sized chairs at a full-sized table with the spatial memory task set up between them. On the experimenter’s side, a sheet of paper was placed in front of the spatial memory task that contained a written script (i.e., prompts for verbal instructions to be given by the experimenter to each participant, and designated space to record participant behavior during the spatial memory task). On the participant’s side, a white cloth was placed beside the box to be used later on in the task. Because each participant sat in an adult-sized chair (either sitting flat or on the knees depending on individual height), the sheet of paper on the experimenter’s side was not easily visible, though it was visible to some participants as evidenced by their notice of the experimenter writing on the sheet in some instances.

Inside the box, all of the toys were prearranged in their proper locations such that the giraffe and zebra were the two toys closest to the child facing the box, and the kitchen chair and lawn chair were the two toys furthest away. The FIGURE 1 The Spatial Memory Task Apparatus Adapted From Blumberg and Torenberg (2003)

SPRING 2021 Note. Concept adapted from, "The Impact of Spatial Cues on Preschoolers' Selective Attention," by F.C. Blumberg and M. Torenberg, 2003, The Journal of Genetic Psychology, 164, p. 45.

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experimenter introduced the box as “a special place where people come to visit animals and sit on chairs to rest,” and then proceeded to point to and verbally identify each of the four animals in the box according to the following order: giraffe, tiger, elephant, and zebra. This was followed by introduction of each of the chairs in the same counter-clockwise fashion: rocking chair, kitchen chair, couch chair, and lawn chair.

The experimenter then told the child that “We need to clean this special place A LOT because animals get really stinky,” and informed the child that his or her job was to remember where the animals are because they would be asked to return them to their original locations.

Once the experimenter had the child repeat back to her what their job was to ensure that it was understood, and then repeated the child’s job if they appeared unsure (i.e., if a child did not respond within approximately five seconds or incorrectly stated their job), the experimenter told the child to remove every item from the box one by one. As the child removed each item, the experimenter did not intervene with any verbal feedback or further instruc­ tions. In the case that a child looked up and paused during this process, the experimenter would say the words “Keep going.” The experimenter wrote the first letter of each item (e.g., G for giraffe, R for rocking chair) on the designated sheet of paper to record the order in which each of the toys was removed.

This was done to infer the presence of a spontaneous categorical clustering strategy while encoding the toy locations, and was designed to be unobtrusive to each participant, as they were actively engaged in the task of removing items for the entirety of the time that the experimenter was recording information.

Once all of the toys were removed from the box, the experimenter handed the child the white cloth to clean the box and waited for the child to finish doing this to their level of contentment (approximately 5 seconds). When this was done, the experimenter presented a brief (5 second) distractor task whereby the child was instructed to pretend to paint the chairs while they were out of the box. Then, the child was instructed to put all of the toys back into the box one by one. In the same recording process as executed for the removal of toys, the experimenter recorded the order in which each of the toys was returned to the box in order to infer the presence of a categorical clustering retrieval strategy. In addition, the experimenter also recorded the number of correctly repositioned toys to measure recall accuracy.

Phase 2 During Phase 2 of the procedure, each participant completed the spatial memory task a second time according to which condition (i.e., encoding, retrieval, or control) they belonged. Participants were randomly assigned to (a) receive instruc­ tions to remove all of the animals first to prompt categorical clustering during the encoding of toy locations, (b) receive instructions to return all of the animals first to prompt categorical clustering while retrieving the toy locations, or (c) complete the task a second time without strategic instruc­ tion. During Phase 2 of the procedure, the order in which each toy was removed and returned to the box was recorded to infer the participants’ responsiveness to the strategic instruction. Similar to Phase 1, the number of correctly repositioned toys served as the measure of recall accuracy.

For the remainder of the procedure, the experimenter and each participant moved to sit at a separate full-sized table. The experimenter admin­ istered the Verbal and Nonverbal routing subsets of Stanford Binet Intelligence Scales for Early Childhood – Fifth Edition manual (Roid, 2005), which served as a measure of each participants’ abbreviated IQ and took approximately 10 minutes to administer.

In addition, the experimenter introduced and administered the Picture Sequence Memory task of the NIH Toolbox (Zelazo et al., 2013), which served as a measure of working memory and took approximately 5 minutes to administer. Over the course of two Picture Sequence Memory trials, participants were presented with increasingly expansive sequences of illustrated objects and activities such as having a picnic and attempted to recall and indicate the correct order in which each was presented.

Variables Categorical Clustering Behavior Following suit with past research on categorical clustering (Bjorklund, 1987; Roenker et al., 1971; Roderer et al., 2012; Stone & Blumberg, 2019), ARC scores were computed to measure the extent to which participants produced a categorical clustering strategy when removing toys from and returning toys to the box during completion of the spatial memory task. ARC scores take into account the number of relevant category repeti­ tions relative to the number of possible repeti­ tions (corrected for chance) in order to quantify participants’ production of a clustering sequence (Bjorklund, 1987; Roenker et al., 1971 Roderer et

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DelVecchio and Stone | Categorical Clustering in Preschoolers

al., 2012) while removing toys (or encoding their locations), and when returning them (retrieving their locations from memory), such that seven ARC scores were possible: 1.0, 0.67, 0.33, 0, −.33, −.67, and −1.0. According to this scale, positive values indicated clustering behaviors above chance levels, an ARC score of 1.0 reflected perfect clus­ tering, and an ARC score of 0 reflected clustering at chance level.

Participation in both phases of the spatial memory task yielded a total of four ARC scores for each participant. Two ARC scores were obtained in the first phase, and quantified the extent to which participants spontaneously categorically clustered while encoding and subsequently retrieving toy locations. Similarly, two ARC scores were obtained in the second phase, and quantified the extent to which participants in the encoding and retrieval conditions categorically clustered following strate­ gic instruction while encoding and retrieving toy locations, and the extent to which participants in the control condition categorically clustered after completing the Phase 1 procedure a second time with no strategic instruction.

Recall Accuracy Recall accuracy served as a measure of the extent to which participants were able to utilize categorical clustering as a memory strategy, i.e., benefit from its use to correctly return toys to their original locations. As such, the number of toy animals (0–4) correctly returned to their original locations (within approximately 1 inch) during the two phases of the spatial memory task served as a mea­ sure of recall accuracy. To measure how successful each participant was in returning the animals to their correct locations without strategic instruc­ tion, the experimenter recorded the number of animals (0–4) returned correctly during Phase 1 of the procedure when no strategic instruc­ tion was given. To measure how successful each participant was in returning the animals to their correct locations when strategic instruction was given, the experimenter recorded the number of animals (0–4) returned correctly during Phase 2 of the procedure after strategic instruction was given during encoding or retrieval, or not at all accord­ ing to the control condition. While the toy chairs were also returned to the box so as to contribute to the calculation of categorical clustering during retrieval, the number of chairs correctly returned to their original positions did not contribute to the recall accuracy calculation.

Intelligence The Abbreviated IQ score (M = 100, SD = 15) obtained from the Verbal and Non-Verbal Routing subsets of the Stanford Binet Intelligence Scales for Early Childhood – Fifth Edition (Early SB-5; Roid, 2005) served as the measure for each participant’s intel­ ligence quotient (IQ). The Early SB-5 was normed on 1,280 children between two- and seven-years-old, and the two- to four-year-old age range was divided into half year groupings (doubling the sample for this age range) to account for the variability and rapid cognitive gains observed during this time.

Internal consistency for the Abbreviated IQ score is .91 (Roid, 2005).

Working Memory The age-corrected standard score (M = 100, SD = 15) produced upon completion of the Picture Sequence Memory task from the NIH Toolbox (Zelazo et al., 2013) served as the measure for each participant’s working memory capacity. The test– retest reliability of the Picture Sequence Memory was reported to be excellent in a recent validation (Bauer et al., 2013) sample of 66 children, as evi­ denced by a high intraclass correlation coefficient of .76 (95% confidence interval: .64–.85).

Results Table 1 provides descriptive information for each study variable. Additionally, Table 2 provides the means for each key variable by condition and phase.

Participants randomly assigned to each of the three instructional conditions did not significantly differ from one another with respect to age, F(2, 38) = 0.05, p = .95, IQ, F(2, 38) = 0.12, p = .88, or working memory, F(2, 38) = 0.20, p = .81. Specifically, partici­ pants randomly assigned to the encoding condition had a mean age of 46.80 (SD = 5.83) months, participants in the retrieval condition had a mean age of 46.17 (SD = 6.22) months, and participants in the control condition had a mean age of 46.80 (SD = 5.83) months. Similarly, participants randomly assigned to the encoding condition had a mean IQ of 106.40 (SD = 10.44), participants in the retrieval condition had a mean IQ of 107.75 (SD = 11.33), and participants in the control condition had a mean IQ of 105.83 (SD = 9.40). Finally, participants randomly assigned to the encoding condition had a mean working memory score of 100.70 (SD = 9.23), participants in the retrieval condition had a mean working memory score of 102.58 (SD = 12.70), and participants in the control condition had a mean working memory score of 99.44 (SD = 14.89).

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Categorical Clustering in Preschoolers | DelVecchio and Stone

Research Question 1: Relationship Between Study Variables The first research question driving this investigation considered whether relationships suggested by past research between spontaneous engagement in categorical clustering behavior, recall accuracy, age, intelligence, and working memory would be observed. Table 3 provides correlations between each of the study variables. In regard to this investi­ gation, neither spontaneous categorical clustering behavior at encoding nor retrieval was significantly correlated with participant age. On the other hand, age in months was positively correlated with the number of toy animals correctly returned to their TABLE 1 Descriptive Statistics of Study Variables Variable

Min. Max.

M

SD

IQ score

88

130

106.55 10.03

Working memory score

69

130

100.36 12.75

Age (in months)

36

58

46.93

5.70

Categorical Clustering Behavior ARC score at encoding (Phase 1)

−0.67

1.00

0.51

0.59

ARC score at encoding (Phase 2)

−0.67

1.00

0.46

0.63

ARC score at retrieval (Phase 1)

−0.67

1.00

0.55

0.55

ARC score at retrieval (Phase 2)

−0.67

1.00

0.67

0.48

Number of correctly returned animals (Phase 1)

0.00

4.00

1.40

1.53

Number of correctly returned animals (Phase 2)

0.00

4.00

1.60

1.60

Recall Accuracy

Note. ARC = adjusted ratio of clustering; ABIQ = abbreviated IQ.

TABLE 2 Mean (Standard Deviation) Clustering Behaviors and Recall Accuracy Before (Phase 1) and After (Phase 2) Strategic Instruction According to Condition Variable

Instructional Condition No Instruction (n = 18)

Encoding (n = 10)

Retrieval (n = 12)

Clustering behavior (ARC score) when encoding toy locations (−1.0–1.0) Phase 1

0.57 (0.59)

0.27(0.66)

0.61 (0.51)

Phase 2

0.32 (0.62)

0.83(0.53)

0.36 (0.66)

Clustering behavior (ARC score) when retrieving toy locations (−1.0–1.0)

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Phase 1

0.59 (0.52)

0.30(0.66)

0.70 (0.46)

Phase 2

0.54 (0.50)

0.50(0.57)

1.00 (0.00)

Recall accuracy (number of correctly relocated target toys (0–4) Phase 1

1.89 (1.78)

1.40(1.17)

0.67 (1.15)

Phase 2

2.11 (1.81)

1.00(1.25)

1.33 (1.37)

original locations (r = .43, p = .01). Additionally, age in months was not significantly correlated with working memory or IQ, though there was a significant positive relationship between partici­ pants’ working memory and their abbreviated IQ (r = .61, p < .001). Findings showed no significant relationship between spontaneous categorical clustering behavior at encoding and recall accuracy.

There was also no significant relationship between spontaneous categorical clustering behavior at retrieval and recall accuracy. Lastly, the current investigation found no association between IQ and the spontaneous production of a categorical clustering strategy or recall accuracy. Likewise, it also found no significant correlation between working memory capacity and categorical clustering behavior or recall accuracy.

Research Question 2: Impact of Strategic Instruction on Clustering Behavior The second research question driving this inves­ tigation considered whether a single instruction to engage in categorical clustering at encoding and/or retrieval would impact observed clustering behaviors. As such, two separate 2 (phase) x 3 (condi­ tion) mixed analyses of variance (ANOVAs) for (a) encoding ARC scores and (b) retrieval ARC scores were conducted. For encoding ARC scores, the first 2 (phase) x 3 (condition) mixed-model ANOVA revealed no significant main effect for phase, F(1, 38) = 0.03, p = .86, eta-squared = .01, or condition, F(1, 38) = 0.15, p = .86, eta-squared = .01, on ARC scores while encoding toy locations. However, although no overall differences were observed in the ARC scores generated based on toy removal during the first and second phases of the study, or according to instructional condition, a significant phase X condition interaction was obtained, F(2, 37) = 5.63, p < .01, eta-squared = .23. Specifically, a large increase in ARC scores reflective of the order of toy removal was observed for the participants instructed to remove the toys according to category membership only. Mean ARC scores while removing the toys in Phase 1 (M = 0.27, SD = 0.19) significantly increased following instruction to remove the toys according to category membership in phase two (M = 0.83, SD = 0.19). ARC scores pertaining to toy removal did not significantly change from Phase 1 to Phase 2 for the participants who were instructed to return the toys according to category membership or received no strategic instruction during Phase 2 (see Figure 2).

For retrieval ARC scores, the second 2 (phase)

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DelVecchio and Stone | Categorical Clustering in Preschoolers

TABLE 3 Correlations Between Spontaneous Clustering Strategy Production During Phase 1 (ARC–Encoding and ARC–Retrieval) and Recall Accuracy (n = 40) on the Memory Task and Participant Age, IQ, and Working Memory Capacity Measure

1

1. ARC–encoding

–

2. ARC–retrieval

.38

–

3. Number of correctly returned animals

.02

.13

2

3

.17

.18 .43**

4

5

6

–

Participant demographics 4. Age (in months) 5. ABIQ score 6. Working memory

–

−.07 −.05 .24 −.13

–

.03 −.12 .01 −.23

.61**

Note. ARC = adjusted ratio of clustering; ABIQ = abbreviated IQ. * p < .05. **p < .01.

FIGURE 2 Changes in Clustering Behaviors When Encoding Toy Locations as a Function of Condition and Phase ARC Score Pertaining to Toy Retrieval

Research Question 3: Impact of Strategic Instruction on Recall Accuracy The third research question driving this investiga­ tion inquired whether strategic instruction for cat­ egorical clustering would have a differential impact on recall accuracy for toy locations at encoding or retrieval. Because age in months was significantly positively correlated with recall accuracy (r = .43, p = .01), a 2 (phase) x 3 (condition) mixed-model ANCOVA was conducted controlling for age. No significant main effect for phase, F(1, 38) = 1.08, p = .31, eta-squared = .03, or condition, F(1, 38) = 2.02, p = .15, eta-squared = .09, were observed on recall accuracy. However, while no overall differences were observed in the accurate recall for toy locations during the first and second phases of the study, or according to instructional condition, a significant phase X condition interaction was obtained, F(2, 37) = 3.37, p = .04, eta-squared = .15. Specifically, while recall accuracy went down from Phase 1 to Phase 2 for participants who received instructions to remove the toys according to category member­ ship, recall accuracy improved for participants who received instructions to return the toys according to their category membership. Recall accuracy did not

significantly change from Phase 1 to Phase 2 for the participants who received no strategic instruction during phase two (see Figure 4).

1.0 0.8 0.6 0.4 0.2 0.0 −0.2 −0.4 −0.6 −0.8 −1.0

Phase 1

Phase 2

Phase Encoding (n = 10)

No Training (n = 18)

Retrieval (n = 12)

Note. ARC = adjusted ratio of clustering.

FIGURE 3 Changes in Clustering Behaviors When Retrieving Toy Locations as a Function of Condition and Phase ARC Score Pertaining to Toy Replacement

x 3 (condition) mixed-model ANOVA revealed no significant main effect for phase, F(1, 38) = 2.27, p = .11, eta-squared = .07, on ARC scores while retriev­ ing toy locations. On the other hand, a significant main effect for condition was obtained, F(1, 38) = 3.49, p = .04, although this was a weak effect (etasquared = .16). ARC scores generated when partici­ pants returned the toys to the box were the highest for participants in the retrieval condition during both phases of the task (prior to and after receiving strategic instruction). Interestingly, no phase X condition interaction was obtained, F(2, 37) = 1.66, p = .20, eta-squared = .08, for ARC scores generated when participants returned the toys to the box.

Although postinstruction ARC scores pertaining to toy replacement increased the most for participants and ultimately resuled in all 12 participants in this condition demonstrating perfect clustering (ARC = 1.0) on Phase 2, clustering behaviors during toy location retrieval also increased for participants instructed to remove the toys according to category membership (a potential carry-over effect from instruction provided during the encoding phase).

ARC scores pertaining to toy replacement did not significantly change from Phase 1 to Phase 2 for the participants who received no strategic instruction during Phase 2 (see Figure 3).

0.8 0.6 0.4 0.2 0.0 −0.2 −0.4 −0.6 −0.8 −1.0

Phase 1

No Training (n = 18)

Phase 2

Phase Encoding (n = 10)

SPRING 2021 Retrieval (n = 12)

Note. ARC = adjusted ratio of clustering.

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Categorical Clustering in Preschoolers | DelVecchio and Stone

Discussion Relationship Between Study Variables Analyses pertaining to the first research question partially supported prior research. Specifically, these results support previous findings that utilization defi­ ciencies are more common in younger preschoolers.

Although spontaneous engagement in categorical clustering during Phase 1 was observed in most participants, it only enhanced recall for the older pre­ schoolers. As age in months increased, participants were able to more correctly relocate relevant toys to the box during Phase 1, indicating that older partici­ pants were more able to accurately recall toy locations during a spatial memory task. This is consistent with prior studies (Stone & Blumberg, 2019; Stone et al., 2016). The present study also replicated the previous findings (i.e., Stone & Blumberg, 2019; Stone et al., 2016) that neither spontaneous categorical clustering behavior at encoding nor retrieval was significantly correlated with participant age.

Similar to prior research (Stone & Blumberg, 2019; Stone et al., 2016), results of this investigation showed no significant relationship between sponta­ neous categorical clustering behavior at encoding and recall accuracy. On the other hand, the current study found no significant relationship between spontaneous categorical clustering behavior at retrieval and recall accuracy. This lies in contrast to past findings, which reported a significant posi­ tive relationship between spontaneous categorical clustering behavior at retrieval and recall accuracy (Stone & Blumberg, 2019). In past studies, the greater the spontaneous use of categorical cluster­ ing when returning toys to the box, the more toys were correctly replaced in their original locations.

This was not found in the current investigation.

Contrary to past research on intelligence FIGURE 4

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Number of Correctly Relocated Target Toys

Changes in Recall Accuracy as a Function of Condition and Phase 4.0 3.5 3.0 2.5 2.0 1.5 1.0 0.5 0.0

Phase 1 No Training (n = 18)

Phase Encoding (n = 10)

Phase 2 Retrieval (n = 12)

and the production or utilization of a categorical clustering strategy (Bjorklund et al., 1994; Stone et al., 2016), the current investigation found no association between IQ and the extent to which participants produced a categorical clustering strategy during encoding or retrieval without instruction. Additionally, no association between IQ and recall accuracy was observed in the present study. Likewise, contrary to past research examin­ ing the effect of working memory capacity on the production or utilization of a categorical clustering strategy (Schleepen & Jonkman, 2012; Stone et al., 2016; Woody-Dorning & Miller, 2001), the current investigation found no significant correla­ tion between working memory capacity and the production of a categorical clustering strategy or recall accuracy. It is possible that this study’s failure to replicate previous findings is related to the small sample size and limited range of participant ages, IQ, and working memory scores. Previous studies examining the relationship between age, IQ, and working memory on categorical clustering behav­ ior and recall accuracy involved a greater range of ages. Although there was less than a two-year difference (22 months) between the oldest and youngest participants in this study, participants in previous investigations ranged in age from three (Stone et al., 2016) to six (Bjorklund et al., 1992; Schleepen & Jonkman, 2012) years. The restricted range of IQ scores obtained in this investigation may also contribute to the failure to replicate previously established associations between IQ and recall accuracy. Specifically, although IQ scores are known to have a mean of 100 and a standard deviation of 15, the mean IQ score obtained in this study was nearly seven points above the typical, or expected, mean of a sample and the SD was five points smaller. Although most of the population would obtain a score between 85–115, most scores obtained for this sample ranged from 97–117.

Impact of Strategic Instruction on Clustering Behavior In regard to the second research question, which inquired whether a single instruction to engage in categorical clustering at encoding or retrieval was sufficient to increase clustering behaviors among preschoolers, findings showed that participants were responsive to strategic instruction. Specifically, higher levels of categorical clustering were observed in Phase 2 than in Phase 1 for participants in the two strategic instruction conditions only. Group comparisons demonstrated that participants

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DelVecchio and Stone | Categorical Clustering in Preschoolers

instructed to engage in categorical clustering while encoding the toy locations showed the greatest increase in strategic behavior while removing toys from the box. However, these participants also gen­ eralized the instruction when returning toys to the box, albeit to a nonsignificant extent. Participants instructed to engage in categorical clustering when returning the toys to the box only demonstrated increases in clustering behaviors when retrieving the toy locations. In fact, all participants in this con­ dition demonstrated “perfect clustering” (ARC = 1.0) when returning the toys to the box in Phase 2.

Participants in the control condition demonstrated lower levels of categorical clustering when remov­ ing the toys from the box a second time and no change in clustering when returning the toys to the box a second time. This particular finding of the control condition serves to demonstrate that the mere single repetition of the spatial memory task for those in the control condition was not suf­ ficient enough to positively influence categorical clustering behavior.

Impact of Strategic Instruction on Recall Accuracy In regard to the third research question, which inquired whether strategic instruction for categori­ cal clustering had a differential impact on recall accuracy for toy locations at encoding or retrieval, findings showed that participants instructed to cluster during retrieval (relative to participants in the other two conditions) showed the greatest improvement in recall for toy locations between Phase 1 and Phase 2 of the spatial memory task.

Participants instructed to cluster while encoding the toy locations in Phase 2 actually recalled fewer toy locations than they had prior to instruction in Phase 1. Participants instructed to cluster when retriev­ ing toy locations in Phase 2 showed a significant increase in recall relative to their Phase 1 recall.

Lastly, participants in the control condition who completed the spatial memory task a second time with no strategic instruction showed no change in recall accuracy from the first administration to the second administration of the memory task. This serves to demonstrate that exposure alone through means of repetition of the task a single additional time was not enough to prompt observable or significant changes in recall accuracy.

Overall, results showed that participants in this examination were responsive to instruction to categorically cluster when both encoding and retrieving the toy locations. However, only the

instruction to categorically cluster when retrieving the toy locations improved their recall accuracy, after controlling for the age of the participants.

Participants who engaged in higher levels of clustering when encoding the toy locations, in response to instruction, did not benefit from this instruction, and most frequently resulted in a utilization deficiency. Miller (1990) introduced the term utilization deficiency to describe such instances when children implement a strategy that yields little or no benefit. Researchers have characterized a utilization deficiency as an early stage in strategy acquisition whereby children spontaneously imple­ ment a strategy but experience no improvement in recall or present with diminished recall as a result of strategy production, which was observed in the pres­ ent study (Clerc & Miller, 2013; De-Marie-Dreblow & Miller, 1998; Miller, 1990). Researchers have historically explained utilization deficiencies as reflecting limited resources whereby the spontane­ ous production of a strategy depletes the cognitive resources needed to benefit from it (e.g., Miller et al., 1991; Schneider et al., 2004; Woody-Dorning & Miller, 2001). The results of this study suggest that only providing a categorical clustering strategy when retrieving to-be-learned information suffi­ ciently reduces the cognitive load to facilitate recall.

Instructing preschoolers to produce a categorical clustering strategy when encoding the to-be-learned information may actually increase the cognitive load inherent in the task, or may be a source of extraneous cognitive load, functionally depleting the cognitive resources needed to actually benefit from the strategy production. This finding is sup­ ported by previous findings, which have suggested that the cognitive cost of overt strategy production may be higher at the time of encoding than at the time of retrieval, particularly among young children (Stone & Blumberg, 2019).

Limitations and Future Directions Several limitations prohibit the generalization of these findings. For instance, the sample of partici­ pants whose data was able to be utilized was small (n = 40), and the sample was relatively homogenous in terms of geographic location, ethnicity, and socioeconomic status. To further explore and gen­ eralize the strategic categorical clustering behavior of preschoolers, a larger and more heterogeneous sample might be used. It is possible that, with a larger sample, the differential impact of instructing preschoolers to cluster at encoding versus retrieval may become more robust. In addition, there would

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be increased likelihood on a wider range of working memory scores, such that the extent and success of clustering behavior among participants with varying mental capacity can be explored. Future studies might include a broader range of spatial memory task items, and might also incorporate more trials through additional data collection to increase confidence in and robustness of results.

In addition, the inclusion of additional age groups beyond preschool-age children would serve to potentially illuminate at what particular age(s) a utilization deficiency ceases to influence categorical clustering behavior and recall accuracy. Because the sample size of the current study is limited in number (n = 40) and in age range (3–4 years), it is difficult to make judgment at what age exactly utilization deficiencies are less prevalent or cease to affect recall. If the current age group were to be assessed in similar future studies investigating the effect of instructed strategies, however, the incorporation of peer modeling perhaps through video methods might be explored to encourage and ensure proper procedural completion.

The present study examined the categorical clustering behavior of preschool-age students in relation to a spatial memory task which required them to remove and return toys to their original locations within a box. Evidence was found that, although participants were universally able to engage in clustering behavior following instruction to do so, not all were able to utilize the strategy to aid recall accuracy. Although instruction to categorically cluster during encoding and retrieval generated a significant increase in clustering behavior while removing and returning toys, respectively, it only improved recall for those instructed to categorically cluster during retrieval.

Increased engagement in categorical clustering when encoding toy locations negatively impacted recall, resulting in a utilization deficiency. These findings suggest that only providing a categorical clustering strategy when retrieving to-be-learned information sufficiently reduces the cognitive load to facilitate recall. Future research should further explore the differential impact of instructing preschoolers to cluster at encoding versus retrieval, and examine the particular age(s) at which a uti­ lization deficiency ceases to influence categorical clustering behavior and recall accuracy. This is important in pursuit of further understanding of how and when memory strategies are produced and utilized by children in the context of learning new information.

References Bauer, P. J., Dikmen, S. S., Heaton, R. K., Mungas, D., Slotkin, J., & Beaumont, J. L. (2013). III. NIH Toolbox Cognition Battery (CB): Measuring episodic memory. Monographs of the Society for Research in Child Development, 78(4), 34–48. https://doi.org/10.1111/mono.12033 Bjorklund, D. F. (1987). How age changes in knowledge base contribute to the development of children’s memory: An interpretive review. Developmental Review, 7(2), 93–130. https://doi.org/10.1016/0273-2297(87)90007-4 Bjorklund, D. F., Coyle, T. R., & Gaultney, J. F. (1992). Developmental differences in the acquisition and maintenance of an organizational strategy: Evidence for the utilization deficiency hypothesis. Journal of Experimental Child Psychology, 54(3), 434–448. https://doi.org/10.1016/0022-0965(92)90029-6 Bjorklund, D. F., Dukes, C., & Brown, R. D. (2009). The development of memory strategies. In M. L. Courage & N. Cowan (Eds.), The development of memory in infancy and childhood: Studies in developmental psychology. Psych Press.

Bjorklund, D. F., Schneider, W., Cassel, W. S., & Ashley, E. (1994). Training and extension of a memory strategy: Evidence for utilization deficiencies in the acquisition of an organizational strategy in high- and low-IQ children. Child Development, 65(3), 951–965. https://doi.org/10.2307/1131430 Blumberg, F. C., & Torenberg, M. (2003). The impact of spatial cues of preschoolers’ selective attention. Journal of Genetic Psychology, 164(1), 42–53. https://doi.org/10.1080/00221320309597502 Blumberg, F. C., & Torenberg, M. (2005). The effects of spatial configuration on preschoolers’ selective attention strategies, selective attention, and incidental learning. Infant and Child Development, 14(3), 243–258. https://doi.org/10.1002/icd.390 Clerc, J., & Miller, P. H. (2013). Utilization deficiencies and transfer of strategies in preschoolers. Cognitive Development, 28(1), 76–93. https://doi.org/10.1016/j.cogdev.2012.09.003 Clerc, J., Miller, P. H., & Cosnefroy, L. (2014). Young children’s transfer of strategies: Utilization deficiencies, executive function, and metacognition.

Developmental Review, 34(4), 378–393. https://doi.org/10.1016/j.dr.2014.10.002 Coyle, T. R., & Bjorklund, D. F. (1996). The development of strategic memory: A modified microgenetic assessment of utilization deficiencies. Cognitive Development, 11(2), 295–314. https://doi.org/10.1016/S0885-2014(96)90006-4 De-Marie-Dreblow, D., & Miller, P. H. (1988). The development of children’s strategies for selective attention: Evidence for a transitional period. Child Development, 59(6), 1504–1513. https://doi.org/10.2307/1130665 Miller, P. H. (1990). The development of strategies of selective attention. In D. F. Bjorklund (Ed.), Children’s strategies: Contemporary views of cognitive development (pp. 157–184). Erlbaum.

Miller, P. H., & Weiss, M. G. (1981). Children’s attention allocation, understanding of attention, and performance on the incidental learning task. Child Development, 52(4), 1183–1190. https://doi.org/10.2307/1129505 Miller, P. H., Seier, W. L., Probert, J. S., & Aloise, P. A. (1991). Age differences in the capacity demands of a strategy among spontaneously strategic children.

Journal of Experimental Child Psychology, 52(2), 149–165. https://doi.org/10.1016/0022-0965(91)90057-Y Roderer, T., Krebs, S., Schmid, C., & Roebers, C. M. (2012). The role of executive control of attention and selective encoding for preschoolers’ learning.

Infant and Child Devlopment, 21(2), 146–159. https://doi.org/10.1002/icd.738 Roebers, C. M. (2014). Children’s deliberate memory development. In P. J. Bauer & R. Fivush (Eds.), The Wiley handbook on the development of children’s memory (pp. 855–894). John Wiley & Sons, Ltd. Roebers, C. M., Schmid, C., & Roderer, T. (2010). Encoding strategies in primary school children: Insights from an eye-tracking approach and the role of individual differences in attentional control. Journal of Genetic Psychology, 171(1), 1–21. https://doi.org/10.1080/00221320903300361 Roenker, D. L., Thompson, C. P., & Brown, S. C. (1971). Comparison of measures for the estimation of clustering in free recall. Psychological Bulletin, 76(1), 45–48. https://doi.org/10.1037/h0031355 Roid, G. H. (2005). Stanford Binet Intelligence Scales for Early Childhood–Fifth edition (Early SB-5) professional manual. Riverside Publishing.

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https://doi.org/10.1016/j.cogdev.2012.03.003 Schneider, W., Kron, V., Hünnerkopf, M., & Krajewski, K. (2004). The development of young children’s memory strategies: First findings from the Wurzburg Longitudinal Study. Journal of Experimental Child Psychology, 88(2), 193–209. https://doi.org/10.1016/j.jecp.2004.02.004 Stone, M., & Blumberg, F. (2019). Effectiveness of categorical clustering as an encoding versus a retrieval strategy among preschoolers. Psychological Reports, 123(6), 2333–2352. https://doi.org/10.1177/0033294119860256 Stone, M., Blumberg, F. C., Blair, C., & Cancelli, A. A. (2016). The ‘EF’ in deficiency: Examining the linkages between executive function and the utilization deficiency observed in preschoolers. Journal of Experimental Child Psychology, 152, 367–375. https://doi.org/10.1016/j.jecp.2016.07.003 Woody-Dorning, J., & Miller, P. H. (2001). Children’s individual differences in capacity: Effects on strategy production and utilization. British Journal of Developmental Psychology, 19(4), 543–557. https://doi.org/10.1348/026151001166245 Zelazo, P. D., Anderson, J. E., Richler, J. Wallner-Allen, K., Beaumont, J. L., &

Weintraub, S. (2013). National Institutes of Health Toolbox Cognition Battery: Validation for children between 3 and 15. Monographs of the Society for Early Childhood Research Development, 78(4), 16–33. https://doi.org/10.1111/mono.12032 Author Note. Isabella DelVecchio https://orcid.org/00000001-5613-7135 Mary Stone https://orcid.org/0000-0003-0647-0508 Portions of this work were presented at the 2020 annual meeting of the Eastern Psychological Association. We have no known conflicts of interest to disclose. Special thanks to Psi Chi Journal reviewers for their support.

Correspondence concerning this article should be addressed to Isabella DelVecchio, Department of Psychology, Marist College, 3399 North Rd., Poughkeepsie, NY 12601.

Email: isabella.delvecchio1@marist.edu.

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https://doi.org/10.24839/2325-7342.JN26.1.56

Arrival Time Matters: The Effect of Biculturalism and Age of Arrival on College Adjustment Guicheng Tan Steinhardt School of Culture, Education, and Human Development, New York University

ABSTRACT. The present study aimed to examine how Chinese bicultural students adjust to college using the Bicultural Integration Identity (BII) framework and the ways BII interact with other variables. Seventy-five Chinese bicultural students between the age of 18 through 35 completed an online survey assessing their BII levels, social capital, acculturative stress, and college adjustments. Using regression analysis, participants’ BII levels were a positive indicator for their college adjustment, (p = .02, r² = .13), bridging social capitals (p = .01, r² = .11), and a negative indicator for acculturative stress related to discrimination (p = .03, r² = .12). Additionally, there was a significant interaction effect between BII levels and participants’ age of arrivals in the United States. BII levels were only a positive indicator of dependent variables for participants who arrived in the United States between the ages of 6 through 17. However, BII acted as a negative indicator for participants who arrived after 18 years old. This study revealed that BII levels improve students’ adjustment to college, but only for those who arrived in the United States during middle childhood and adolescence.

Possible limitations and implications on students’ identity development and college transition were discussed.

Keywords: bicultural identity integration, acculturative stress, social capital, college adjustment

T

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he Asian student population in the United States has become increasingly international and bicultural, and the monolithic approach no longer appropriately captures the process of identity development for Asian students. Factors such as international migration (United Nations, 2019), internationalization of higher education (Organisation for Economic Cooperation and Development, 2014), and interracial marriages (Parker et al., 2015) have allowed people to be exposed to more than one culture. Moreover, different acculturation, socialization, and racialization experiences have resulted in varying identity developments among immigrants (Berry, 2003; Kuo & Roysircar, 2004; Rumbaut, 2004). This observation led to the rise in biculturalism studies, a multicultural approach that is sensitive to the social, psychological, and cultural complications behind one’s racial, ethnic, and identity development

(Chen & Padilla, 2019; Nguyen & Benet-Martínez, 2013; Schwartz & Unger, 2010). The present study explored the relationship between biculturalism and college experience: for bicultural students such as international and immigrant students, how would their bicultural identity impact their college experience?

Biculturalism and Chinese Students in the United States Biculturalism describes the relationship between a person’s home culture (or country of origin) and their surrounding culture (or country of resi­ dence). Previous bicultural studies have focused on immigrants or children of immigrants who grew up in ethnic enclaves (Schwartz & Unger, 2010). With the growth of internationalization of higher educa­ tion, international students also became a suitable population to be examined under a bicultural lens.

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Tan | Biculturalism and College Adjustment

Between 2008 to 2018, the enrollment of international college students in the United States increased approximately 63% (IIE Open Doors / Places of Origin, n.d.). As of 2018, Chinese interna­ tional students made up 33.74% of international students within the United States (IIE Open Doors / Places of Origin, n.d.). Often associated with collegedegree seeking candidates, the term “international students” encompasses more complex narratives.

There has been a growth in U.S. secondary school enrollment among international students, and Chinese students alone made up about 58% of this population (Farrugia, 2017). Moreover, an increasing number of international schools have emerged in China since mid-2010 (Machin, 2017; Yang, 2017). Schools like these provide a Westernfocused curriculum and English language-based instruction to prepare students for a Western higher education (Yang, 2017), introducing ear­ lier opportunities for bicultural introduction for Chinese students. Studies like these have suggested that, for many international students, they had already been exposed to Western culture prior to college. As such, depending on a students’ age of arrival and secondary school experiences, Chinese international students arrive at college with dif­ ferent understandings of their cultural identity.

Regarding existing studies on Chinese bicultural college students (Ching et al., 2017), no scholarly work has investigated the implication of bicultural­ ism for college adjustment to author’s knowledge.

Therefore, the present study sought to address the relationship between biculturalism and adjustments in college for Chinese students.

Theoretical Framework Bicultural Identity Integration In the past 30 years, biculturalism has evolved from an acculturation theory to an identity-related one.

Biculturalism, also known as the integration strategy (Berry, 2003), was first perceived as an acculturation strategy used by individuals who stayed involved in both cultures. Within the past few decades, the word “biculturalism” has since transitioned into an interdisciplinary term (Benet-Martínez & Haritatos, 2005; Benet-Martínez et al., 2002; LaFromboise et al., 1993; Phinney & Davich-Navarro, 1997).

Although much of the previous framework was built on behavioral markers (i.e., switching lan­ guages in different settings), Benet-Martínez and Haritatos framed a new construct named bicultural identity integration (BII) to address the internal processing and identity management for

bicultural individuals (Benet-Martínez & Haritatos, 2005). This framework bridges the gap between the internal identity formation (how a bicultural individual self-identified conceptually) and external behavioral markers (how a bicultural individual interacted with others momentarily).

BII theory contains two independent subcon­ structs: cultural conflicts and cultural distance.

Cultural conflicts correspond to whether individuals perceive their two cultures as harmonious or con­ flicting, and cultural distance refer to the degree in which two cultures are blended or separated by the individual (Benet-Martínez & Haritatos, 2005).

Unlike previous studies that focused on observed behaviors, the 2005 study unpacked personal navi­ gations of identity-related concepts by interviewing Chinese bicultural individuals. BII’s emphasis on identity formation shifted biculturalism’s focus from between-group cultural dynamic to internal cultural integration.

BII framework could also apply to Chinese bicultural students transitioning in U.S. higher education. Despite a large representation on campus, few studies have focused on the college transition experience of Chinese students using a bicultural framework (Huynh et al., 2011). Because Benet-Martínez and Haritatos (2005) used Chinese bicultural individuals as the participant sample for the BII framework development, the present study considered it a suitable theory to apply to Chinese students. For this study, “Chinese bicultural stu­ dents” was operationally defined as individuals who have lived in the United States and China (includ­ ing Hong Kong and Taiwan) for at least 5 years each. This definition included both international and immigrant Chinese students, adapting from previous BII studies (Benet-Martínez & Haritatos, 2005; Huynh et al., 2011).

Relevant Concepts to Biculturalism Acculturative Stress. Because acculturative stress has been a prominent issue for many bicultural individuals such as immigrant and international students, the present study included acculturative stress as a part of its analysis. Previous studies have defined acculturative stress as the additional distress for people when adjusting to a new culture and the psychological stressors resulting from unfamiliarity with new cultural norms (Berry, 2003). This stress has serious health implications among people of color in the United States, and it has been associated with higher levels of mental health issues (Finch et al., 2001; Hovey & Magaña, 2000; Hwang & Ting,

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2008; Miranda & Umhoefer, 1998). Due to limited family and social support, acculturative stress contin­ ues to be a major challenge faced by international students and immigrants (Ra & Trusty, 2017; Sirin et al., 2013). As such, the present study included acculturative stress as a research component in examining biculturalism in college adjustment.

Social Capital. Within acculturation studies, social interactions persisted as both a challenging and mediating factor toward students’ transition in the United States Social capital, an evolving social construct related to social support, referred to an individual’s interaction with others and the par­ ticipation within their social networks (Bourdieu, 1983). As people acculturate to a new environment, the shifting social compositions in one’s life has important implications on their social capital, which are often gained or improved with time and interactions with others (Berry, 2003).

For international and immigrant students, social capital has been referred to as their access to social interactions and networks, which leads to positive support systems including family, friends, classmates, and other community members (Archuleta & Teasley, 2013; Concha et al., 2013; Oh, 2016). Several studies indicated that social support could affirm immigrants’ ability to rely on and relate to others (Finch & Vega, 2003), thus mediating the acculturation effects on health among immigrants of color (Concha et al., 2013; Panchang et al., 2016; Zhang & Ta, 2009). Similar effects were found in international students as well. For Chinese interna­ tional students, social network mediated their levels of acculturative stress (Lee et al., 2004; Ye, 2006).

Therefore, the present study included social capital to better understand bicultural students’ adjustment in their new social setting in college.

Age of Arrival. Age of arrival in a new envi­ ronment can lead to acculturative variation and different needs for cultural integration. For adults, language barriers, cultural adjustments, academic pressures, and social adjustments were often core issues faced by Chinese international students attending colleges, which undermined their academic performance and social interactions (Han et al., 2017; Wei et al., 2007). On the other hand, acculturative stress challenged Chinese youth in a more nuanced way. Among Chinese youth immigrants, there was a strong social restraint and introversion when associated with peers from other cultures after arriving in the United States (Berry et al., 2006). For those who arrived in their childhood, younger Chinese students had to unpack two sets

of cultural values, which could be an ambiguous or confusing process.

In a 2000 study, participants were divided into immigrated “before/at age 12” and “after age 12” due to differences in their language acquisition skills and cultural integration experiences. The association between identity and cultural domains (e.g., language, social affiliation, food) differed sig­ nificantly based on this age of immigration (Tsai et al., 2000). Similarly, Rumbat (2004) found that, for Asian immigrants, self-reported identities differed significantly based on age of arrival. For people who arrived in between the ages 6–17, they were twice as likely to self-identify by national origins than those who arrived during early childhood (before age 6), possibly due to different family background and educational experiences (Rumbaut, 2004).

Because of its influence on acculturation and identity development, this study included age of arrival as a relevant concept.

Hypotheses Through studying Chinese bicultural students’ transition, the present study sought to determine how BII theory influences acculturative stress, social capital, and the overall college adjustments. Based on BII framework and Rumbaut’s immigration study (Benet-Martínez & Haritatos, 2005; Rumbaut, 2004), this study hypothesized the following: (a) levels of BII would be a positive predictor on Chinese bicultural students’ college adjustment, (b) levels of BII would be a positive predictor on Chinese bicultural students’ level of social capital and a negative predictor to their acculturative stress, and (c) student’s age of arrival would have a significant impact on one’s bicultural integration and thus interact with other dependent variables.

Method Participants Participants were 75 undergraduate students, gradu­ ate students, and recent alumni from a large private university in a metropolitan area in the United States (age M = 24, SD = 3.74; women = 52, men = 23; graduate students = 53, undergraduate students = 32, recent alumni who graduated in 2018 = 7).

Following Benet-Martínez and Haritatos’s (2005) operational definition, Chinese bicultural students were defined as Chinese students who have lived in the United States and China for at least 5 years (years spent in China M = 16.23, SD = 4.42; years spent in the United States mean = 7.35, SD = 2.99).

See Table 1 for descriptive data.

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Tan | Biculturalism and College Adjustment

Sampling Seventy-five self-identified Chinese bicultural stu­ dents were recruited through posters and emails.

The posters included the study purpose, process, participation criteria, interest from link, and participation incentive of a $100 Amazon gift card drawing. The posters were distributed throughout the library building and one academic building’s bulletin board at the surveying institution. An electronic version of the poster was sent to 21 Asian student organizations and the international scholars’ office within the university to be included in their newsletter. Participants interested in the study had to submit the interest form advertised on the poster, indicating their interest to participate, contact email, student ID, and eligibility to par­ ticipate in the study (being over the age of 18 and having lived in both China and the United States for at least 5 years). Individuals who did not meet the criteria were rejected for the study.

Measures The independent variable in this study was the participants’ bicultural integration and their age of arrival in the United States, which were measured using the Bicultural Identity Integration (BII) Scale and participants’ self-reporting survey. The dependent variables in this study included college adjustment, acculturative stress, and social capital, which were measured by the College Adjustment Questionnaire (CAQ), Riverside Acculturation Stress Inventory (RASI), and Bonding and Bridging Social Capital Scale, respectively.

Bicultural Integration: BII Scale – Version 1 This 8-item five-point Likert scale assessed the extent to which a bicultural individual sees their two cultures as integrated and compatible (BenetMartínez & Haritatos, 2005). Compared to the 19-item BII Scale – Version 2 (Huynh et al., 2018), this version was chosen for its brevity and wide applications for assessing BII (Nguyen & BenetMartínez, 2013; Schwartz et al., 2010). It incor­ porated four cultural distance statements (i.e., “I keep Chinese and American cultures separate”) and eight cultural conflict statements (i.e., “I feel caught between the two cultures”). Participants responded to statements on a 1 (disagree strongly) to 5 (agree strongly) Likert scale. For this study, it had a moderate internal consistency (cultural distance α = .68, cultural conflict α = .66). This study combined both BII subscales and formed a BII total score that represented students’ overall integration level.

College Adjustment: College Adjustment Questionnaire (CAQ) This 22-item 5-point Likert-type scale examined how students adjust to their college environment (O’Donnell et al., 2018). It included three func­ tional areas: educational (i.e., class performance), relational (i.e., having friends), and psychological (i.e., handling stress). Participants responded to statements on a 1 (very inaccurate) to 5 (very accurate) scale. This scale was a shorter and more user-friendly version of previous college adjustment measure­ ments (educational α = .77, relational α = .78, and psychological α = .79 for this study). It focused more on students’ transition process as opposed to their overall college experiences, making it a suitable measurement for this study (Larose et al., 2019).

Acculturative Stress: Riverside Acculturation Stress Inventory (RASI) This 15-items 5-point Likert scale measured acculturating challenges in language skills, work TABLE 1 Descriptive Data and for All Participants Variable

N

Age

75 24

3.74

18

35

0.40

Women

52 23

3.94

–

–

–

Men

23 24

3.32

–

–

–

Years lived in the United States

75

7.35 2.99

5

19

2.94

Years lived in China

75 16.23 4.42

5

30

1.63

Age of arrival in the United States

75 16.05 4.44

0

30

3.18

M

Min Max Kurtosis

SD

Born–5 years old

3

–

–

–

–

6–12 years old

8

–

–

–

–

13–17 years old

35

–

–

–

–

18 years old-above

39

–

–

–

–

Chinese immigrant student

12

–

–

–

–

Chinese international student

56

–

–

–

–

7

–

–

–

–

Self-identified as

Chinese American student

TABLE 2 Summary of Correlations for Demographics 1 1. Age

2

3

4

–

2. Years lived in the United States

.28*

–

3. Years lived in China

.61

−.49**

–

4. Age of arrival in the United States

.56

−.58

.93**

** **

**

SPRING 2021 –

Note. *p < .05. **p < .01. Two-tailed test.

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Biculturalism and College Adjustment | Tan

challenge, intercultural relations, discrimination, and cultural/ethnic makeup of the community (Benet-Martínez & Haritatos, 2005; Miller et al., 2011). Participants responded to statements on a 1 (strongly disagree) to 5 (strongly agree) scale. This scale measured domains within the acculturation process comprehensively including language bar­ riers and cultural isolation, which were relevant considerations for studying relationships among biculturalism, acculturation, and social capital (language skills α = .91, work challenge α = .68, intercultural relations α = .74, discrimination α = .86, and cultural isolation α = .61 for this study).

Social Capital: Bonding and Bridging Social Capital Scale This 14-item 5-point Likert scale assessed par­ ticipants’ bridging social capital, the weak ties with online individuals, and bonding social capital, the strong relationship with family or friends (Ellison et al., 2007; William, 2006). Participants responded to statements on a 1 (strongly disagree) to 5 (strongly agree) scale. This scale was chosen for its relevance and appropriateness in reflecting an individual’s social interactions on a college campus (bonding scale α = .70, bridging scale α = .89 for this study).

Procedure After receiving participants’ interest forms, the author sent a separate survey link composed of the following questionnaires and scales to participants who qualified for the study (IRB-FY2018-1933): basic demographic questionnaires (e.g., gender, age, level of study level), BII Scale (Benet-Martínez & Haritatos, 2005), RASI (Miller et al., 2011), Social Capital Scale (Ellison et al., 2007), and CAQ (O’Donnell et al., 2018). On the landing page of the survey, participants read and signed the study consent form prior to answering questions. Data was collected via an online Qualtrics form. After TABLE 3 Descriptive Data and Regression Model for College Adjustment as a Function of Bicultural Integration, After Controlling Age and Gender Dependent Variables CAQ total

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M

SD

19.03 10.13

r2

Mean Square

F

Sig.

.13

323.30

3.42

.02*

CAQ psychological

2.07

3.66

.16

53.24

4.54

.01**

CAQ educational

13.19

4.69

.03

17.75

0.79

.51

3.77

4.36

.10

48.56

2.60

.06

CAQ relational

Note. CAQ = College Adjustment Questionnaire. * p < .05. **p < .01. Two-tailed test.

completion, the landing page presented partici­ pants with study debrief and researcher’s contact information.

Results This study utilized linear regression to detect effects of bicultural integration on dependent variables.

A new BII total score was computed by combining both the BII Distance subscale and the BII Conflict.

The purpose of this computation was to maintain simplicity and consistency when addressing a more global concept of bicultural integration as indicated in the previous study (Benet-Martínez & Haritatos, 2005). The term “high BII individual” referred to those who see their cultures as blended and harmonious, and the term “low BII individual” referred to those who see their cultures as separate and conflicting. Implications of the difference between cultural distance and conflict are discussed later in this article.

Hypothesis I: Bicultural Integration and College Adjustment There was a significant relationship between BII total scores on an individual’s CAQ total score after controlling for age and gender, F(3, 71) = 3.42, p = .02, r² = .13, and CAQ Psychological subscale, F(3, 71) = 4.54, p = .01, r² = .16. There was no signifi­ cant relationship between BII total scores on the Educational subscale, F(3, 71) = .79, p = .51, r² = .03, or Relational subscale, F(3, 71) = 2.60, p = .06, r² = .10. This suggested that BII level was a positive indicator of Chinese bicultural students’ psychologi­ cal and educational transitions in college: the more one perceived their Chinese and U.S. cultures as integrated and compatible, the better a college transition this individual would experience. See Table 3 for details.

Hypothesis II: Bicultural Integration on Social Capital and Acculturative Stress There was a significant relationship between BII total scores and bridging social capital, F(3, 71) = 4.05, p = .01, r² = .11, but no significant relationship between BII total scores and bonding social capital, F(3, 71) = 0.61, p = .61, r² = .03.

There was no significant relationship between BII total score and RASI total scores, F(3, 71) = 0.82, p = .49, r² = .02, and most of its subscales: Language, F(3, 71) = 0.34, p = .79, r² = .01, Intercultural Conflicts, F(3, 71) = 1.15, p = .34, r² = .05, Cultural Isolation, F(3, 71) = 0.41, p = .75, r² = .02, Work Challenge, F(3, 71) = 0.29, p = .83, r² = .01. However,

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Tan | Biculturalism and College Adjustment

there was a significant relationship between BII total score with the Discrimination subscale, F(3, 71) = 3.24, p = .03, r² = .12. Overall, high BII individuals had more social connections and lower acculturative stress associated with discriminatory interactions than low BII individuals. See Table 4 for details.

Hypothesis III: Age of Arrival on Bicultural Integration and College Adjustment To understand the impact of age of arrival on stu­ dents’ college adjustment, the author first analyzed the relationship between bicultural integration and dependent variables after controlling for the age of arrival in the United States: bridging social capitals, F(2, 72) = 4.95, p = .01, r² =.12, bonding social capitals, F(2, 72) = 1.07, p = .35, r² = .02, RASI, F(2, 72) = 1.23, p = .30, r² =.03, CAQ, F(2, 72) = 4.17, p = .02, r² = 0.08. See Table 5 for details.

Although age of arrival was not a significant covariant based on the linear regression model, it was a significant predictor for BII levels after controlling for age and gender, F(3, 71) = 13.74, p < 0.01, r² = .38. As such, the author was curious to see if there was an interaction between age of arrival and bicultural integration when categorizing participants by generation groups, as suggested by previous studies (Rumbaut, 2004; Tsai et al., 2000). Rumbaut (2004) found that immigrants experience cultural integration and assimilation differently based on their age of arrival, proposing a new cohort breakdown based on early childhood (before age 6), middle childhood (age 6–12) , and adolescence (age 13–17). This study followed Rumbaut’s (2004) definition of generation by divid­ ing participants into four groups based on when they arrived to the United States: 1.75th generation (born–5 years old), 1.5th generation (6–12 years old), 1.25th generation (13–17 years old), and 1st generation (18 years old and above). The break­ down was formulated considering the different language acquisition, socialization, educational experiences, and self-identification varied by age of migration (Rumbaut, 2004). Due to a high Kurtosis score of 3.18, significant outliers were removed, leaving only the 1st, 1.25th, and 1.5th generation for analysis (N = 72).

When crossing age of arrival and BII scores, significant differences emerged for bicultural students based on their arrival age. The positive effect of BII levels in improving college adjustments and reducing acculturative stress was only observed in those who arrived in the United States between the age group 6–17 (1.5th generation and 1.25th

generation): CAQ total scores, F(5, 66) = 3.15, p = .01, r² = .17, RASI total scores, F(5, 66) = 2.59, p = .03, r² = .16. For their counterpart who arrived after age 18, there was an inverse relationship between BII Total Scores and the mentioned variables.

TABLE 4 Descriptive Data and Regression Model for Social Capital and Acculturative Stress as a Function of Bicultural Integration, After Controlling Age and Gender Dependent Variables

M

SD

r2

Mean Square

F

Sig.

Bridging social capital

20.40

5.91

.11

123.16

4.05

.01*

Bonding social capital

23.36

5.33

.03

17.10

0.61

.61

RASI total

43.61 13.73

.02

158.72

0.82

.49

RASI Language

8.91

4.34

.01

6.98

0.34

.79

RASI Intercultural Conflicts

8.57

3.39

.05

21.87

1.15

.34

RASI Cultural Isolation

8.33

3.78

.02

2.52

0.41

.75

RASI Work Challenges

9.25

3.45

.01

3.46

0.29

.83

RASI Discrimination

8.55

3.66

.12

41.42

3.34

.03*

Note. RASI = Riverside Acculturation Stress Inventory. * p < .05. **p < .01. Two-tailed test.

TABLE 5 Descriptive Data and Regression Model for College Adjustment as a Function of Bicultural Integration, After Controlling Age of Arrival Bridging Social Capital Variable

r2

r 2 change

F

Sig.

Age of arrival

.001

.001

0.05

.83

BII

.12

.12

4.95

.01*

Bonding Social Capital Variable

r2

r 2 change

F

Sig.

Age of arrival

.01

.01

0.93

.34

BII

.03

.02

1.07

.35

F

Sig.

RASI Total Variable

r2

r 2 change

Age of arrival

.00

.00

0.00

.99

BII

.03

.03

1.23

.30

CAQ Total Variable

F

Sig.

Age of arrival

.00

.00

0.03

.88

BII

.11

.08

4.17

.02*

r

2

r change 2

Note. BII = Bicultural Identity Integration Scale. RASI = Riverside Acculturation Stress Inventory. CAQ = College Adjustment Questionnaire. * p < .05. **p < .01. Two-tailed test.

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Similarly, Chinese bicultural students’ BII levels were a positive indicator on social capitals for those who arrived between the age group 6–17 (1.5th generation and 1.25th generation), but a negative indicator for their counterparts: bridging social capital, F(5, 66) = 2.41, p = .04, r² = .16, bonding social capital, F(5, 66) = 2.59, p = .03, r² = .16. See Table 6 and Figure 1 for details.

To conclude, for Chinese bicultural students who arrived in the United States in the middle of their childhood and adolescence, their BII levels increased their overall adjustment to the college environment, social capital, and reduced their acculturative stress. On the other hand, Chinese bicultural students who arrived in the United States during adulthood experienced the opposite effect: their BII levels negatively affected their overall TABLE 6 Regression Model for the Interaction Between BII Score and Age of Arrival on Dependent Variables Excluding Outliers (N = 72) Bridging Social Capital Variable

Mean Square

F

Sig.

Model

77.81

2.41

.04*

BII total

92.87

2.99

.08

Age of arrival

29.86

0.10

.39

Interaction

81.72

2.63

.08

Bonding Social Capital Variable

Mean Square

F

Sig.

Model

23.38

2.59

.03*

BII total

1.24

0.05

.12

54.76

2.04

.12

125.90

5.09

<.01**

Age of arrival Interaction

RASI Total Variable

Mean Square

F

Sig.

Model

446.09

2.65

.03*

BII total

262.70

1.56

.22

Age of arrival

415.26

2.47

.10

Interaction

1069.45

3.18

.048*

Variable

Mean Square

CAQ Total

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F

Sig.

Model

278.18

3.15

.01*

BII total

225.25

2.89

.09

Age of arrival

196.61

1.11

.33

Interaction

661.24

3.74

.03*

Note. BII = Bicultural Identity Integration Scale. RASI = Riverside Acculturation Stress Inventory. CAQ = College Adjustment Questionnaire. * p < .05. **p < .01. Two-tailed test.

adjustment to the college environment, social capital, and increased their acculturative stress.

Discussions Overall, the present study explored the question: How does bicultural integration relate to Chinese bicultural individuals’ experiences with college adjustments, social capital, and acculturative stress? The findings showed that high BII Chinese bicultural students are more likely to experience better emotional support, greater social relations, more social ties with peers, and less acculturative stress in college. There was a significant interaction between age of arrival and BII levels: interestingly, only students who arrived between the age of 6–17 experienced the positive effect associated with high BII levels. For Chinese bicultural students who came to the United States after age 18, there was an inverse relationship between BII levels and dependent variables, which will be addressed in this section later.

First, high BII individuals scored significantly higher on their overall college adjustment com­ pared to low BII individuals, particularly in areas related to psychological well-being and interper­ sonal connectedness. This supports previous find­ ings on the relationship between low BII levels and personal and interpersonal challenges (Huynh et al., 2011). The CAQ psychological and relationship measurements indicated that students who saw their Chinese and American cultures as separate and conflicting displayed more unhappiness in college and more emotional distress.

Some possible explanations for high BII Chinese bicultural students’ improved college tran­ sition are the greater expansion of social network, more nuanced understanding of cultural and politi­ cal climate, and reduced impact of acculturative stress. In the present study, BII level was a significant positive predictor to greater bridging social capital.

Although bridging social capital are “weak con­ nections” that do not typically provide emotional support, it offers informative resources and social mobility opportunities (Portes & Sensenbrenner, 1993). As bicultural individuals navigate between two cultures, they interact and access resources from both cultural communities, thus forming greater social networks from both sides.

The social and political backdrops are also relevant considerations when unpacking these results. During the time in which this study took place, the Sino-American political tension was high among the Chinese community, namely the United

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Tan | Biculturalism and College Adjustment

FIGURE 1 The Relationship Between Bicultural Integration on Bridging Social Capita, Bonding Social capital, RASI Total Score, and CAQ Total Score by Different Age of Arrival Generations 30

Binding Social Capital

25 20 15 10 5

−15

−10

−5

0

5

0

5

0

5

0

5

BII Total

70

RASI Total

60 50 40 30 20 −15

−10

−5 BII Total

35

Bonding Social Capital

30 25 20 15 10 −15

−10

−5 BII Total

40 30 20 CAQ Total

States-China Trade War and disputes over technol­ ogy security (Council on Foreign Relations, n.d.; Kuo & Cecco, 2019; Valencia, 2018). This increase of international conflicts can lead to an increase in bicultural individuals’ sensitivity toward discrimina­ tory situations related to their cultural heritage. For instance, a 2008 study found that Chinese heritage had negatively impacted the college experience of Chinese students studying in Hong Kong (Chen et al., 2008). Researchers postulated that the conflict between China and Hong Kong’s historical back­ ground had led to the negative relationship between cultural identification and student experiences. Like previous findings, the present study considered that the increase in the political tension can push low BII individuals in becoming more sensitive toward cultural differences. In another word, those who see their Chinese and American cultures as separated and conflicted (low BII) are more likely to be impacted by current events revolving around antiChinese sentiments. In contrast, previous studies have demonstrated how bicultural integration is responsive to priming effect and frame switching (Cheng et al., 2006; Zou et al., 2008). Therefore, students who see their Chinese and American cultures as blended and harmonious are less likely to be impacted by these events, as they can move in between the two sides more fluidly.

Lastly, the age of arrival appears to be a key contributor to bicultural integration and its related impact on other variables. In this study, the 1.5th and 1.25th generation (age group 6–17 years old) exhibited effects consistent with the hypothesis where bicultural integration functions as a positive predictor to dependent variables. However, older students outside of this age group demonstrated an inverse effect. This reveals important generational differences in the process of bicultural integration for a Chinese student, questioning the extent to which BII operates differently for different ages.

Highlighted by Tsai et al.’s (2000) study, immigrants who arrived prior to age 12 could have been too young in their development to formulate a sense of “Chinese identity” or “American identity.” Later studies also signaled similar generational and age differences among immigrants and their identity development, in which second-generation and firstgeneration populations experienced and processed cultural components of their identities differently (Huynh et al., 2018; Liu, 2017; Wiley et al., 2008).

In a recent qualitative study conducted on a group of early teen Chinese immigrants (age 7–13), students disclosed an ambiguous sense of home

10 0 −10 −15

−10

−5 BII Total

Age of Arrival [1st Generation] Age of Arrival [1.25th Generation] Age of Arrival [1.5th Generation]

Note. RASI = Riverside Acculturation Stress Inventory. CAQ = College Adjustment Questionnaire. BII = Bicultural Integration Identity.

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Biculturalism and College Adjustment | Tan

or belonging, a pragmatic view instead of identityrelated view on citizenship, and a more expansive connotation of being an “immigrant” that mirrored BII’s framework on seeing two cultures as blended and compatible (Liu, 2017). Following Erikson’s personal identity theory (Chung, 2018), perhaps the age group 6–17 is more prone to the positive effect of bicultural integration in their identity formation stages, in which individuals are more comfortable with exploring their identity in a fluid way. Those who arrived later in their adulthood might not be receptive to cultural integrations, possibly due to the conflict between existing identities and acculturat­ ing identities which results in identity confusion or ambiguity (Chen et al., 2008).

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Limitations First, this study combined BII’s Distance and Conflict subscales to enable a more global con­ ceptualization of bicultural integration (BenetMartínez & Haritatos, 2005), generalizing the terminology “high BII” for those who had a higher sum of scores. It is important to note that BII distance and conflict can exist as independent subconstructs (Benet-Martínez & Haritatos, 2005; Huynh et al., 2011). A previous study has pointed out that BII distance could precede conflict as a more salient component of bicultural identity, and that certain personality traits and psychological states are indicative of varying levels of BII (Huynh et al., 2011). The present study did not control these predisposition variables, which weakens its internal validity that can lead to different inferential observations. Additionally, a longer version of this scale has been made to increase its reliability and to cover all relevant components of BII framework (Huynh et al., 2018). Future studies should dissect the differences between BII Distance and Conflict subscales and employ the updated measurement to provide more insightful analysis.

Second, the contextual background of this study can induce a certain level of temporal effect on participants’ BII, thus challenging this study’s external validity. Aside from the Sino-American political tension that this sample experienced within the given year, this study also took place in a diverse campus and a metropolitan area. Previous studies have found that BII responds to frame switching (Zou et al., 2008) and geographic location leads to different identity forming experience (Chan, 2019), individuals from a homogeneous or rural area will experience bicultural integration differently than those presented in the study. Different school

settings and demographics can also induce varying effects on students’ identity development and college experience. Because bicultural identity could be fluid and responsive to different settings (BenetMartínez et al., 2002; Hong et al., 2000), researchers should attend to the environmental factor that can confound the predictive effect of BII levels.

This study lacks qualitative data in understand­ ing the role of how different variables contribute to the observed effects. This study investigated the statistical relationship between BII levels and students’ transition in the college setting through the lens of social capital, acculturative stress, and CAQ, but it did not offer students’ perception or narratives on any of the measured variables.

Knowing that social class and parental involve­ ment were profound factors in Asian American students’ school experience (Chung, 2001; Kuo, 2011; Yeh, 2003), additional interviews examining family dynamics and financial stability would be helpful in understanding the process in which bicultural students unpack the transition process.

Using Liu’s (2017) study as an example, Chinese secondary students’ definitions and experiences on being an immigrant vary by a large degree based on their social experience (Liu, 2017). The individual experiences of bicultural students can influence their understanding of self and identity, thus generating needs for qualitative follow-ups.

Future studies should include a written response or interview portion for participants to elaborate on their reflections for a better inferential result.

Conclusions and Implications The present study provided both higher education practitioners and psychology researcher insights on the role of bicultural integration on Chinese bicultural students’ transition in college, reveal­ ing the significance of age of arrival on BII levels.

Different from previous bicultural studies that have suggested a positive linear relationship between BII levels and several psychological and social aspects (Huynh et al., 2011), this study showed that the positive effects of BII on bicultural individuals are only available among those who arrived in the United States between age group 6–17. This finding expands the generalized perception of the Chinese student experience in U.S. colleges and raises questions on the application of bicultural integration based on age.

The low psychological adjustment for low BII students adds another emphasis on the mental health support needed by this student group.

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Tan | Biculturalism and College Adjustment

Correlating this finding to campus resources for international and immigrant students can reveal areas of improvements. For instance, how frequently do Chinese international and immigrant students access mental health and emotional support services on college campuses?

Are mental health professionals on campus trained with enough cultural competency to understand their transitional experiences? Because mental health-related issues remain a prominent concern on college campuses today, this study sheds light on the psychological impact and cultural identity navigations for some Chinese bicultural students.

Bridging social capital are “weak ties” that provide positive and important influence in com­ munities. It also plays an important role in a stu­ dent’s college experience with the advancement of technology and social media engagement (Ellison et al., 2007). Future research should investigate the relationship between bicultural integration and social engagement. For example: How does social capital relate to bicultural students’ sense of belonging on campus? Do BII levels influence individuals’ commitment to cultural organizations?

How do bicultural individuals increase their bond­ ing social capital differently from bridging social capital? Understanding how bicultural students interact with peers and become involved on campus informs educators about how to better support and engage them in the community.

More attention is needed to inspect the relationship between cultural integration and discriminator y experiences. The process of integrating cultures starts with unpacking the meaning and experiences of being a part of both communities. This experience requires guidance and critical consciousness offered by practitioners, while recognizing social and political context on an individual level. Some questions for scholars to further explore are: Do BII levels mediate the effect of discrimination, does biculturalism improve an individual’s concept of social justice, and do high BII individuals have more access to allies and advocates than low BII individuals? Educators can use these insights, alongside campus climate reports, to better assess and understand bicultural students’ college experience.

Although a previous study explored the rela­ tionship between bicultural integration on different immigration groups (migrant workers vs. college students, Chen et al., 2008), only limited studies have focused on the generation or age effect on bicultural identity development (Huynh et al., 2018;

Nguyen & Benet-Martínez, 2013). The present study provided a narrative countering current research showing only the positive association between BII levels and acculturation variables varied by age of arrival. Perhaps the interaction observed in this study underlines psychosocial and cognitive factors that require a more clinical and experiential setting: Is there a critical age for bicultural integration?

What are the crucial factors that contributed to the positive effect of bicultural integration?

To conclude, more studies on BII framework can help understand the psychological and social construct of one’s multiple cultural selves. Educators, scholars, practitioners, and policymakers can use these results to better assist the growing presence of bicultural students in today’s globalized community.

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Adjustment trajectories during the college transition: Types, personal and family antecedents, and academic outcomes. Research in Higher Education, 60(5), 684–710. https://doi.org/10.1007/s11162-018-9538-7 Lee, J. S., Koeske, G. F., & Sales, E. (2004). Social support buffering of acculturative stress: A study of mental health symptoms among Korean international students. International Journal of Intercultural Relations, 28(5), 399–414. https://doi.org/10.1016/j.ijintrel.2004.08.005 Lee, S. J. (2006). Additional complexities: social class, ethnicity, generation, and gender in Asian American student experiences. Race Ethnicity and Education, 9(1), 17–28. https://doi.org/10.1080/13613320500490630 Liu, X. (2017). Redefining ‘immigrants’ through diaspora: Educational experience of

1.5-generation Chinese youth in Cupertino. Diaspora, Indigenous, and Minority Education, 11(4), 177–189. https://doi.org/10.1080/15595692.2016.1264384 Machin, D. (2017). The great Asian international school gold rush: An economic analysis. Journal of Research in International Education, 16(2), 131–146. https://doi.org/10.1177/1475240917722276 Miller, M. J., Kim, J., & Benet-Martínez, V. (2011). Validating the Riverside Acculturation Stress Inventory with Asian Americans. Psychological Assessment, 23(2), 300–310. https://doi.org/10.1037/a0021589 Miranda, A. O., & Umhoefer, D. L. (1998). Acculturation, language use, and demographic variables as predictors of the career self-efficacy of Latino career counseling clients. Journal of Multicultural Counseling and Development, 26(1), 39–51. https://doi.org/10.1002/j.2161-1912.1998.tb00182.x Nguyen, A.-M. D., & Benet-Martínez, V. (2013). Biculturalism and adjustment: A meta-analysis. Journal of Cross-Cultural Psychology, 44(1), 122–159. https://doi.org/10.1177/0022022111435097 O’Donnell, M. B., Shirley, L. A., Park, S. S., Nolen, J. P., Gibbons, A. M., & Rosén, L. A. (2018). The College Adjustment Questionnaire: A measure of students’ educational, relational, and psychological adjustment to the college environment. Journal of College Student Development, 59(1), 116–121. https://doi.org/10.1353/csd.2018.0009 Oh, J. H. (2016). Immigration and social capital in a Korean-American women’s online community: Supporting acculturation, cultural pluralism, and transnationalism. New Media & Society, 18(10), 2224–2241. https://doi.org/10.1177%2F1461444816655627 Organisation for Economic Cooperation and Development. (2014). Recent developments in international migration trends. In International Migration Outlook 2014. http://dx.doi.org/10.1787/migr_outlook-2014-4-en Panchang, S., Dowdy, H., Kimbro, R., & Gorman, B. (2016). Self-rated health, gender, and acculturative stress among immigrants in the US: New roles for social support. International Journal of Intercultural Relations, 55, 120–132. https://doi.org/10.1016/j.ijintrel.2016.10.001 Parker, K., Horowitz, J. M., Morin, R., & Lopez, M. H. (2015, June 11). Multiracial in America. Pew Research Center. http://www.pewsocialtrends.org/2015/06/11/multiracial-in-america/ Phinney, J. S., & Devich-Navarro, M. (1997). Variations in bicultural identification among African American and Mexican American adolescents. Journal of Research on Adolescence, 7(1), 3–32. https://doi.org/10.1207/s15327795jra0701_2 Portes, A., & Sensenbrenner, J. (1993). Embeddedness and immigration: Notes on the social determinants of economic action. American Journal of Sociology, 98(6), 1320–1350. https://doi.org/10.1086/230191 Ra, Y. A., & Trusty, J. (2017). Impact of social support and coping on acculturation and acculturative stress of East Asian international students. Journal of Multicultural Counseling and Development, 45(4), 276–291. https://doi.org/10.1002/jmcd.12078 Rumbaut, R. G. (2004). Ages, life stages, and generational cohorts: Decomposing the immigrant first and second generations in the United States. International Migration Review, 38(3), 1160–1205. https://doi.org/10.1111/j.1747-7379.2004.tb00232.x Schwartz, S. J., & Unger, J. B. (2010). Biculturalism and context: What is biculturalism, and when is it adaptive? Human Development, 53(1), 26–32. https://doi.org/10.1159/000268137 Sirin, S. R., Ryce, P., Gupta, T., & Rogers-Sirin, L. (2013). The role of acculturative stress on mental health symptoms for immigrant adolescents: A longitudinal investigation. Developmental Psychology, 49(4), 736– 748. https://doi.org/10.1037/a0028398 Tsai, J. L., Ying, Y.-W., & Lee, P. A. (2000). The meaning of ‘being Chinese’ and ‘being American’: Variation among Chinese American young adults. Journal of Cross-Cultural Psychology, 31(3), 302–332. https://doi.org/10.1177/0022022100031003002 United Nations. (2019). International Migration 2019: Report (pp. 26–29, Rep. No. ST/ESA/SER.A/438). https://www.un.org/en/development/ desa/population/migration/publications/migrationreport/docs/ InternationalMigration2019_Report.pdf Valencia, M. J. (2018, October 5). China-US relations: What’s next? The Diplomat. https://thediplomat.com/2018/10/china-us-relations-whats-next/ Wei, M., Heppner, P. P., Mallen, M. J., Ku, T.-Y., Liao, K. Y.-H., & Wu, T.-F. (2007).

Acculturative stress, perfectionism, years in the United States, and depression among Chinese international students. Journal of Counseling Psychology, 54(4), 385–394. https://doi.org/10.1037/0022-0167.54.4.385 Wiley, S., Perkins, K., & Deaux, K. (2008). Through the looking glass: Ethnic and

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Tan | Biculturalism and College Adjustment

generational patterns of immigrant identity. International Journal of Intercultural Relations, 32(5), 385–398. https://doi.org/10.1016/j.ijintrel.2008.04.002 Williams, D. (2006). On and off the ’net: Scales for social capital in an online era.

Journal of Computer-Mediated Communication, 11(2), 593–628. https://doi.org/10.1111/j.1083-6101.2006.00029.x Ye, J. (2006). An examination of acculturative stress, interpersonal social support, and use of online ethnic social groups among Chinese international students. The Howard Journal of Communications, 17(1), 1–20. https://doi.org/10.1080/10646170500487764 Yeh, C. J. (2003). Age, acculturation, cultural adjustment, and mental health symptoms of Chinese, Korean, and Japanese immigrant youths. Cultural Diversity and Ethnic Minority Psychology, 9(1), 34–48. http://dx.doi.org/10.1037/1099-9809.9.1.34 Young, N. A. E. (2017). Departing from the beaten path: International schools in China as a response to discrimination and academic failure in the Chinese educational system. Comparative Education, 54, 159–180. https://doi.org/10.1080/03050068.2017.1360566 Young, N. A. E. (2018). Departing from the beaten path: International schools in China as a response to discrimination and academic failure in the Chinese

educational system. Comparative Education, 54(2), 159–180. https://doi.org/10.1080/03050068.2017.1360566 Zhang, W., & Ta, V. M. (2009). Social connections, immigration-related factors, and self-rated physical and mental health among Asian Americans. Social Science & Medicine, 68(12), 2104–2112. https://doi.org/10.1016/j.socscimed.2009.04.012 Zou, X., Morris, M. W., & Benet-Martínez, V. (2008). Identity motives and cultural priming: Cultural (dis)identification in assimilative and contrastive responses. Journal of Experimental Social Psychology, 44(4), 1151–1159. https://doi.org/10.1016/j.jesp.2008.02.001 Author Note. Guicheng Tan https://orcid.org/0000-00019858-606X Guicheng Tan is now an independent researcher not affiliated with any institution.

This research was supported in part by Steinhardt Student Research and Creative Project Grant.

Correspondence concerning this article should be addressed to Guicheng Tan, 33445 Skylark Drive, Lake Elsinore, CA 92530. Email: arielguicheng@gmail.com

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INVITED EDITORIAL: Update on Psi Chi's Response to COVID-19 Deborah Harris O’Brien1 and Martha S. Zlokovich2 1 Psi Chi President, Trinity Washington University 2 Executive Director, Psi Chi Central Office

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hen Psi Chi Journal Editor Dr. Debi Brannan approached us with an invitation to write about Psi Chi’s response to the coronavirus pandemic, we were pleased to share with Journal readers. Just as the past 12 months have not been “business as usual” for any of our members, neither has it been for Psi Chi’s staff or Board of Directors. None of us expected to face a global pandemic, sudden massive economic stress, societal reckoning on racial justice, or political turmoil—much less all of these in the same year.

Even so, the 14 staff members, nine Board members from universities across the United States, our Journal Editor and five associate editors, as well as committee chairs and members around the globe have worked tirelessly to support Psi Chi’s members in the moment, as well as to ensure the viability of our Society into the future.

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Psychological Science: We Have Answers Dr. Harris O’Brien became President of the Board at the close of the July 2020 Board meet­ ing and launched her Presidential year theme of Psychological Science: We Have Answers. Her theme expanded on that of her predecessor, Past-President Dr. Regan A. R. Gurung. His theme promoted the ideas that psychology is present in every aspect of daily life and that psychological science can be applied to solve problems at the level of individuals, communities, and even societies.

The current presidential theme builds on our rich history of psychological research by showing that there are empirically based answers for the most pressing challenges we face, such as inequal­ ity among people, climate change, and resolving the coronavirus pandemic. You might have seen the theme appear in several ways over the last few months. Her Presidential column, “Psychological Science: Make Hope Our Goal,” appeared in the spring 2021 Eye on Psi Chi. The President and Psi Chi staff worked with psychologists around the country to develop webinars and podcasts related to her theme. Check out recent podcast topics such as “How to Study During the Pandemic,”

“Racial Slurs (That People Use All Too Often),” and “Conquering COVID-19 Loneliness,” available at https://www.psichi.org/page/Podcast. A sample of related webinars includes “Respectfully Engaging Across Our Differences in Divided Times” and “Learning Science/Student Success in the Time of COVID,” which you may access at https://www. psichi.org/page/learningresources or by logging in to your member portal.

Expanded Resources and Support for all Psi Chi Members In fact, let all your friends know about Psi Chi’s resources! Because of the pandemic, the Board decided to make all of our learning resource webinars free to not only members, but to anyone interested. Other Psi Chi publications such as the Journal, podcasts, blog, and Eye on Psi Chi magazine were already available free to the public. These are each full of helpful tips on applying for jobs and graduate school, requesting letters of recommen­ dation, writing a resumé or CV, and articles about current issues in psychology.

The Board also took action to support faculty advisors and chapters. As a temporary measure, faculty advisors may consider Pass-Fail grades, which many universities instituted during the pandemic, when determining new member eligibility. The Board also acknowledged that, in the sudden move to remote learning, graduating seniors might not have had opportunity to join Psi Chi before leaving campus. Normally that opportunity is lost after graduation; however, the Board decided to tempo­ rarily allow recent graduates to join. Students who graduated between March 1, 2020 and August 31, 2021 may join until December 2021—if they met chapter eligibility criteria as students at the time of graduation. The Board also voted not to move any Short Term Inactive chapters to Long Term Inactive status this year. Staff will instead contact these chap­ ters to see what assistance their advisors and officers need to become active and induct new members.

President Dr. Harris O’Brien, Executive Director Dr. Martha S. Zlokovich, and staff have also

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*Faculty mentor

Harris O'Brien and Zlokovich | Psi Chi’s Response to COVID-19

worked hard to make induction and graduation cer­ emonies special even though online only. Drs. Harris O’Brien and Zlokovich have been speakers at virtual induction ceremonies. Dr. Zlokovich and Director of Membership & Development Cynthia Wilson worked with the Communications Department to create induction and graduation videos for chapters to use during their online ceremonies.

Last spring, Wilson and Board members created the COVID-19 Member Support Fund to help students facing financial hardships due to the pandemic. Psi Chi set aside a $25,000 match and continues fundraising to reach $50,000 total.

Advisors may request help from this fund to cover the new member fee for a deserving student to join Psi Chi, or for free honor cords to celebrate the accomplishment of a graduating senior who cannot afford them. The fund also allowed us to offer a second round of Chapter Activity Grants—because most of our chapters have remained active and adapted to full or partial online campus life.

Did you know that Psi Chi staff are all working from their homes? As part of protecting the health of our staff, Psi Chi began virtual operations in March 2020. So when you (a) order merchandise, (b) join, or (c) apply for awards, grants or scholar­ ships, the staff members are working remotely.

Although they are working from home, you are still able to reach them by phone, email, or Psi Chi’s mailing address.

Virtual Conventions Throughout all these changes, staff and Board regrouped to support our regional Vice-Presidents planning for regional conventions, and presidents planning Psi Chi speakers at national psychology conventions as they transitioned to virtual last spring. Virtual and hybrid formats continue for the spring and summer 2021 conventions, so Psi Chi continues to support our members’ participation in these conventions including presenting the normal number of regional research awards for students presenting at each convention. Although travel will not be occurring, Psi Chi will make travel grants available to students for virtual convention registration fees.

Last year Psi Chi’s Board, Research Director, Research Advisory Committee (RAC), and Executive Director Dr. Zlokovich partnered with regional psychological associations and APS to allow students presenting their research at virtual conventions to post their work in Psi Chi’s folders on the Open Science Foundation (OSF) website. This ensures

that all students who presented their research at regional and APS conventions in 2020 will have their research in a secure repository. It is important to us that students receive recognition for their work and that it be accessible in the future. We are working with these associations to allow repositories for the 2021 conventions as well. Look for more informa­ tion on the webpage at https://www.psichi.org/ page/ResearchAdvisory and in upcoming digests.

Psi Chi’s Four Advisory Committees Work for You In addition to the RAC, three additional Advisory Committees are at work on behalf of members. Our Diversity Advisory Committee (https://www.psichi. org/page/Diversity) led by Diversity Director Dr. Susanna Gallor wrote Psi Chi’s response to the calls for social justice, assisted VPs with diversity program­ ming at their regional conventions, and contributed to social media plans for Black History Month and Women’s History Month. They also wrote about the work of Drs. Loretta Neal McGregor and Albee Mendoza for the Eye and presented a webinar on “Difficult Dialogues.”

Dr. Brien Ashdown started January 2020 as our first International Director, chairing the International Advisory Committee, and Psi Chi has been expanding internationally during the past year. We have added new chapters in coun­ tries where there were previously no Psi Chi chapters, such as Armenia, Italy, the United Arab Emirates, Turkey, and Great Britain. The International Advisory Committee (IAC) has been working diligently on expanding Psi Chi connections throughout the world by developing the International Partners in Leadership (IPALs) program connecting a U.S. and a non-U.S. chapter.

Chapters in Mexico, Guatemala, Arkansas, and Washington, D.C. pilot tested the program over fall 2020 and it will be launched April 2021 for all chapters. Through the use of technology, chapters from different parts of the world can meet each other, share resources and learn about psychology in other cultures. This focus on creating bridges between chapters fits nicely with former President Regan Gurung’s theme of “PsychEverywhere.”

Psychology is everywhere in the world and affects all facets of our lives. In addition, we have started working toward making materials available in languages other than English; some brochures and other materials are available in Spanish, and we have added Google translate on our webpages.

The IAC worked with the RAC, DAC, and Journal Editor to propose an important change to

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Psi Chi’s Response to COVID-19 | Harris O'Brien and Zlokovich

the Journal—allowing authors to include a second abstract in the language of their choice. The Board approved the proposal and our first article with an abstract in a second language, Chinese, appears in this same issue.

The fourth advisory committee is brand new.

Dr. Seungyeon Lee started January 2021 as our first Faculty Support Director, chairing the Faculty Support Advisory Committee (FSAC). She will be seeking out committee members to develop more resources and opportunities for all Psi Chi faculty members, whether or not they are faculty advisors of a chapter. One of the FSAC’s first tasks will be recommending to the Board how to spend $50,000 in support of psychology faculty that was generously donated to Psi Chi by the David and Carol Myers foundation. The FSAC will support our faculty

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members who do so much for the students both in and outside of the classroom!

Conclusion The staff, committees, Editor, Associate Editors, and Board, of Psi Chi have been working diligently to support students and faculty during COVID-19.

We have made videos for chapters to use for virtual inductions and graduations, video resources for each officer position and plan more webinars and podcasts in 2021. We hope you will check out all the new resources available to Psi Chi students, faculty, and alumni as well as apply for awards, grants and scholarships. Whether your involvement with your chapter continues online or you are able to return to your campus before graduating, rest assured that Psi Chi has resources to support you.

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Psi Chi Journal of Psychological Research 2020 Reviewers We sincerely appreciate the hard work on the part of the following individuals who each completed at least one review in 2020. Without the assistance of such dedicated professionals, Psi Chi Journal would not be able to function.—Debi Brannan (Editor) Glena Lynne Andrews George Fox University Trey Asbury Texas Woman's University Lara K. Ault Saint Leo University Angela Banitt Duncan Washburn University Daniel Wade Barrett Western Connecticut State University Susan E. Becker Colorado Mesa University Michelle Beddow Saginaw Valley State University Chris Bjornsen Longwood University Stefanie S. Boswell University of the Incarnate Word Karen Brakke Spelman College MaryAnne Britt Northern Illinois University Sheila Brownlow Catawba College Candice Burkett University of Montana Western Brittany Canfield California Southern University Mary Jo Carnot Chadron State College Bradley James Caskey Birmingham–Southern College Shawn R. Charlton University of Central Arkansas Sarah Cronin Bemidji State University Grace Deason University of Wisconsin–La Crosse Teddi S. Deka Missouri Western State University Fabiana DesRosiers Dominican College Kristen Ann Diliberto-Macaluso Berry College Melanie M. Domenech Rodríguez Utah State University Martin J. Downing Lehman College Gregory Scott Drury Stephen F. Austin State University Leslie G. Eaton State University of New York at Cortland Ryan Craig Ebersole Albany Medical Center Jared Franklin Edwards Southwestern Oklahoma State University Jorie H. Edwards Southwestern Oklahoma State University Mindy J. Erchull University of Mary Washington

Deb Esty Baldwin Wallace University Shlomit Flaisher-Grinberg Saint Francis University Tifani Fletcher West Liberty University Andrew Sheldon Franklin Norfolk State University Azenett A. Garza Caballero Weber State University Rebecca Gilbertson University of Minnesota Duluth Jennifer M. Gonder Farmingdale State College Rupa Gordon Augustana College Heather Haas University of Montana Western Jonathan J. Hammersley Western Illinois University Thomas Fredrick Harlow University of Maryland Global Campus Sarah Herrmann Weber State University Karen Yvette Holmes Norfolk State University Marya T. Howell-Carter Farmingdale State College Robert Hymes University of Michigan–Dearborn Lori Elizabeth James University of Colorado– Colorado Springs Fanli Jia Seton Hall University Nancy Davis Johnson Queens University of Charlotte Marla Johnston Farmingdale State College April Jones Walden University Nancy J. Karlin University of Northern Colorado Emily Keener Slippery Rock University Allen Hayward Keniston University of Wisconsin—Eau Claire Jackie Kibler Northwest Missouri State University Casey Anne Knifsend California State University, Sacramento Penny Koontz Marshall University David S. Kreiner University of Central Missouri William John Lammers University of Central Arkansas

Marianne Elizabeth Lloyd Seton Hall University Stella G. Lopez University of Texas at San Antonio Amy Madewell Oklahoma State University Pam Marek Kennesaw State University Gina Mariano Troy University Tammy McClain West Liberty University Julie Guay McIntyre Russell Sage College Albee Mendoza Wesley College Cindy Miller-Perrin Pepperdine University Tara Mitchell Lock Haven University Betsy L. Morgan University of Wisconsin–La Crosse Walter Murphy Texas A&M University– Central Texas Daniele Nardi Ball State University Susan L. O'Donnell George Fox University Valerie Perez Wesley College Marilyn Petro Nebraska Wesleyan University Lindsay A. Phillips Albright College Dee Posey Washington State University Mark G. Rivardo Saint Vincent College Lisa Rosen Texas Woman's University Raylene Ross University of South Carolina David A. Saarnio Arkansas State University Nicholas Salter Hofstra University Donald Saucier Kansas State University Lauren Fruh VanSickle Scharff U. S. Air Force Academy Pamela Schuetze Buffalo State College Carl W. Scott University of St. Thomas Paul Scott Rockhurst University Katharine Suzanne Shaffer University of Baltimore Ayesha Shaikh Whittier College Leigh A. Shaw Weber State University

Madelynn D. Shell The University of Virginia's College at Wise David Bryan Simpson Valparaiso University Christina S. Sinisi Charleston Southern University Merry J. Sleigh Winthrop University Paul Curtis Smith Alverno College Fernanda Sofio Woolcott Princeton University Tammy L. Sonnentag Xavier University Shana Southard-Dobbs Lander University Kathryn Sperry Weber State University Crystal N. Steltenpohl University of Southern Indiana Rebecca Marie Stoddart Saint Mary's College Roxanne L. Sullivan Bellevue University Christy Teranishi Martinez California State University Channel Islands Leonell Torres-Pagan University of Puerto Rico Kimberli R. H. Treadwell University of Connecticut Dunja Trunk Bloomfield College Mary Utley Drury University Scott VanderStoep Hope College Allison A. Vaughn San Diego State University Taylor Wadian University of Cincinnati Blue Ash College Rebekah Wanic University of San Diego Kathleen West University of North Carolina at Charlotte Wayne Wilkinson Arkansas State University J. Austin Williamson Augustana College Jamie G. Wood Pittsburg State William D. Woody University of Northern Colorado Jason R. Young Hunter College Evan L. Zucker Loyola University New Orleans

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