Effects of Color and Lighting Temperature on Mood and Cognitive Performance
Megan B. Afifi, Elizabeth J. Krumrei-Mancuso*, and Janet Trammell* Department of Psychology, Seaver College, Pepperdine University
ABSTRACT. Research on the psychological effects of different design elements is important to interior designers and any individuals designing a space. No previous research has analyzed the interaction effects of color and lighting temperatures on mood, heart rate, and cognitive performance. The current study was conducted at Pepperdine University in a 2 x 2 randomized experiment. There were 78 participants aged 18–24 with a mean age of 18.85 ( SD = 1.20), including 53 women, 24 men, and 1 who did not indicate their gender. The study evaluated selfreported mood (Positive and Negative Affect Schedule), accuracy and reaction times (Stroop task), creative intelligence (Remote Associates Test), and heart rates (heart rate monitor). Participants completed these tasks in a room with either a warm (red) or cool (blue) background color and completed tasks once in warm lighting and once in cool lighting. We found that color and lighting temperatures had different effects on affect, creative intelligence, reaction times, and accuracy. Negative affect was lower in Warm Lighting x Cool Color and Cool Lighting x Warm Color conditions (p = .046). Accuracy was higher in the Cool Color condition (p = .01) and in the Cool Color x Warm Lighting condition (p = .047). Creative intelligence scores approached significance in being higher in cool than warm lighting (p = .05). No effects were found on heart rates (p = .62). These results can inform designers on how to use the design elements of color and lighting temperatures to promote certain desired psychological effects in a space.
Keywords: environmental psychology, interior design psychology, color and lighting temperature, mood, cognitive performance
Environmental psychology is a constantly evolving field of study that considers the relationships between design elements and psychological areas of functioning such as mood, arousal, and cognitive performance. Two primary elements of interior spaces are background color and lighting, and the way the two interact is of interest to designers to achieve the desired effect of a space. Often, the goal of the designer of an interior space is to create some ambient effect
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on a person’s emotional and cognitive state. However, design education programs often do not teach about the interactions between color and lighting in classes. This is a missed opportunity to explore the psychological and physiological effects that color and lighting interactions have on people in any given space.
The current study analyzed the relationship between warm (red) and cool (blue) background colors and warm (orangewhite) and cool (bluewhite) source lighting
temperatures, and how the interactions between these environmental elements affect people’s mood, cognitive performance, and heart rate. In this study, cognitive functioning refers to one’s mental abilities in areas such as learning, memory, problemsolving, and reasoning. Colors are described here as warm or cool based on hue and wavelength: cool colors like blue have a shorter wavelength, and warm colors like red are longer in wavelength. Similarly, cool lighting is described here as more bluewhite light, and warm lighting is described as orangewhite light.
Often, interior design programs teach color and lighting as separate design foundations, causing interior designers to be underprepared to understand how color and light intersect. In this paper, we rely on a phenomenological approach to color and lighting in which color and light intersect actively within the subjective experience of a person who inhabits a space (Poldma, 2009). As Poldma (2009) pointed out, when color and light act well together, this creates a positive spatial experience and an emotional resonance within the user of a space. Yet, given that it is within a person’s subjective experience that color and lighting interact to create a particular effect, it is necessary to study color and lighting together to understand how people experience color and light as interrelated concepts within a space. In agreement with Poldma (2009), unless designers can predict the color and lighting interaction effects that interior spaces will have on people, they will be partially blind to the ideal combinations that should be employed to achieve the intended effects of the design. The current study aims to contribute knowledge in this area.
The empirical framework of the current study focuses on how color hue and lighting temperature interact. Given that this has rarely been examined, we begin with a review of what is known about how color hue and lighting temperature individually influence people. Warm colors like red and yellow are generally understood to be more stimulating and arousing than cool colors like blue and green, and cool colors are generally more relaxing and calming than warm colors (Elliot, 2019; Roy et al. 2021; Wilms & Oberfeld, 2017). Similarly, in academic study environments, warm colors are generally found to be too stimulating and distracting; cool colors tend to work well as they are more calming and promote focus (Costa et al., 2018). On a simple proofreading exercise, however, red and white color conditions had enough of an arousing effect to promote performance more than the cool conditions did (Cha et al., 2020). In terms of lighting temperature, generally, people tend to prefer warmer and dimmer lighting, but although warmer, dimmer lighting may positively influence mood, it may also hinder performance on cognitive tasks (Knez & Kers, 2000).
The current study built on these previous findings to examine how the interaction of color and lighting
temperatures influences people. We evaluated the impact of various color and lighting temperature combinations on selfreported mood, task performance, and the physiological measure of heart rate. Previous studies have analyzed these components separately, but to our knowledge, none have analyzed the specific effects of these elements in tandem with each other. It is important to understand how color and lighting elements act together to affect mood and cognitive performance in people. Given the interaction between color and lighting that takes place within a person using a space, studying color and lighting together is imperative to understand their effects on people’s moods, physiology, creativity, task performance, and other experiences, within given spatial designs. With such knowledge, people—especially designers— can be more intentional in creating their desired experiences within given spaces.
Color
Color and Mood
A general trend seen with color temperature is that cool colors are preferable to spend time in, and incite feelings of calm more than warm colors (Costa et al., 2018). Stone (2001) found that positive mood was higher in participants who were in a blue room rather than a red room, but that mood did not differ significantly between those in a blue vs. a white room. Furthermore, blue was rated as more pleasant than either red or yellow in another study (ALAyash et al., 2015). Blue has also been rated as calmer and more interesting than warmer colors (Kaya & Epps, 2004). In agreement with these findings, people rated feelings of calmness (vs. restlessness) and peacefulness (vs. agitation) from highest to lowest in the order of cool, then achromatic, then warm colors (Yildirim et al., 2011). In addition, warmcolored interiors have the most positive effect on mood, followed by cool, then achromatic colors, and warm color interiors ranked higher in feelings of happiness and vividness than cool or achromatic colors (Yildirim et al., 2011). Warm color, then cool color, then achromatic color interiors were rated by participants in that order from most positive to most negative concerning high arousal, stimulation, and excitement (Yildirim et al., 2011).
Red was associated with higher anxiety and stress levels for participants who remained in a redcolored room; reports of symptoms of depression were more prominent in those who remained in a blue colored room for the duration of a task (Kwallek et al., 1988). This illustrates the arousing and nonarousing effects of different colors. In recent research, however, there have been contradictions, such as that cool colors are more arousing than warm colors, and that vivid blue is reported as having an awakening and activating effect on participants (ALAyash et al., 2015; Roy et al, 2021).
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Color and Cognitive Performance
In terms of cognitive performance, previous literature has indicated that warm colors enhance arousal and stimulation, and therefore can be more distracting than helpful on cognitive tasks (Elliot, 2019; Stone, 2001; Xia et al., 2016). Cool colors are more calming; therefore, they promote greater focus during cognitive tasks. Background colors (the color of the surrounding area in which the participant engaged in a task) either had a facilitating effect or no effect on cognitive task performance in a study by Xia et al. (2016). Accuracy was reported as higher in a blue background condition than in a red background condition, and the blue condition also enhanced simple creativity task performance more than red, which had little effect compared to the neutral (gray) color condition.
In a study where performance on a reportedly difficult reading task and a less difficult mathematics task were measured, Stone (2001) found that performance on the reading task was worse in a red environment than in a white environment, but performance on the reading task in a blue environment did not differ significantly from the red and white environments used in the study. Color did not significantly affect performance on the math task, but reading task performance was worst in the red environment. This illustrates the taskdependent nature of the relationship between color and cognitive performance and suggests that warm colors may inhibit performance on difficult tasks more so than less difficult tasks. Interestingly, some studies have reported that on easier, lowload cognitive tasks, cool colors are too relaxing and therefore do not assist in maintaining focus and concentration, causing worse performance (Elliot, 2019; Xia et al., 2016). This suggests, in congruence with other findings, that on a low cognitive load task, stimulation from warm colors does not hinder performance because not as much attention is required for the task. On higher cognitive load tasks, however, warm colors like red tend to be too distracting and hinder performance as they can draw attention away from the task at hand. The resulting distraction of warm colors takes up focus that could otherwise be more fully applied to performing better on the task. The lower distraction levels of cool colors allow for those resources to be more fully allocated to performance on more difficult tasks where they are needed. Therefore, determining what color temperature is more beneficial to the environment appears to depend on both the nature of the task difficulty and the desired level of stimulation.
Lighting
Lighting and Mood
Findings suggest that a positive mood is best preserved in warmer lighting; Zhu et al. (2019) found that
participants’ moods worsened more in cooler lighting conditions than in warmer lighting conditions. Knez and Kers (2000) found that, contrastingly, in younger adults, a negative mood was sustained more in a warmer lighting condition than in cooler lighting, but for older adults, a negative mood persisted in the cooler lighting condition. This finding partially contradicts some lighting theories that positive mood generally correlates more with warmer lighting than cooler, but this study reveals that the difference in effect may be attributed to age.
Lighting and Cognitive Performance
Compared to red and green lighting, white lighting proved to be rated higher on a usefulness scale, indicating that white lighting facilitated performance on more useful or productive activities, rather than hindering it (Odabaşioğlu & Olguntürk, 2015). Cognitive performance was found to be better in low, cool lighting than in low, warm lighting, and participants were slowest in processing a task measuring their inhibitory capacity (responding to red words flashing on a screen and ignoring black ones) and working memory under a dim, warm lighting source than in other lighting conditions (Zhu et al., 2019). They also found that participants performed best in high, cool light on a longterm memory task compared to other conditions, suggesting that cool lighting is best for promoting some aspects of cognitive performance like longterm memory. Accuracy scores on another task, however, were lower in cool than warm lighting. These findings support others that suggest that the effects of lighting temperature on cognitive performance are dependent on the type of task. Similarly, Stone (2001) found that color temperature affects cognitive performance differently depending on how high of a cognitive load the task requires.
The Current Study
To our knowledge, no previous studies have analyzed the interaction between background color and lighting temperatures on mood and cognitive performance. At the time of this study, enough research is available on the effects of color temperature and lighting temperature separately on mood and cognitive performance to understand the trends, however, there is no research on an integrated approach to color and lighting temperatures on these psychological effects. As the body of research on this topic is continuously growing, this will help inform designers about how to integrate design elements to best achieve the desired psychological effects of a designed space (Poldma, 2009). The current study contributes to the existing literature by replicating main effects and examining potential interactions between color and lighting temperatures on mood and cognitive performance levels. We examined this with a sufficient
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sample size in reallife contexts and provided evidence for what combinations of color and lighting work best for achieving better performance on cognitive tasks and striving towards net positive affect. All APA ethical standards were met in conducting this study, and approval was received from the Pepperdine University Institutional Review Board.
Hypotheses
To better integrate color and lighting interactions into discussions about design as Poldma (2009) points out is necessary, we analyzed their effects on mood, cognitive performance, and physical arousal. These are some of the main outcomes of interest when it comes to the experience of a designed space, and therefore our hypotheses are based on how color and lighting elements of design affect these measures both individually and together. Based on previous research, our hypotheses were as follows:
1. Mood was expected to be better in Cool Color and Warm Lighting conditions than in Warm Color and Cool Lighting conditions.
2. Warm Colors as well as Cool Lighting were expected to be more arousing and stimulating than Cool Colors and Warm Lighting (expressed as higher heart rates).
3. Performance on cognitive tasks was expected to be better in Cool Color and Cool Lighting conditions than in Warm Color and Warm Lighting conditions.
4. The interactions of Warm Color x Cool Lighting, Warm Color x Warm Lighting, Cool Color x Cool Lighting, and Cool Color x Warm Lighting conditions are expected to have different impacts on mood, heart rates, and cognitive performance levels in comparison with each other. As there is no established research on how specific interactions of these conditions affect our outcome variables, we predict that the conditions will have different effects on these outcomes from each other.
Hypothesis 4 helps to bring this body of research more in line with reallife settings, where color and lighting are both present in every space and interact in unknown ways to influence mood and cognition. It is important to better understand this relationship empirically to ensure that spaces are properly designed in reality.
Method
Participants
Participants of this study ( N = 78) were students at Pepperdine University. Participants were at least 18 years old and were determined not to be color blind by the online version of the Ishihara Color Blindness test.
An a priori power analysis of a 2 x 2 mixed ANOVA determined that 62 participants were needed to have 80% power to detect a medium sized effect (.15) with a .05 criterion of significance. The mean age was 18.85 (SD = 1.20), there were 53 (67.95%) women and 24 men (30.77%), and 1 participant who did not indicate their gender (1.28%). In terms of race, 38 (48.72%) participants identified as White/European American, 22 (28.21%) as Asian/Pacific Islander, 12 (15.38%) as Multiracial, 4 (5.13%) as Hispanic/Latino, and 2 (2.53%) as Black/African American. There were 48 (61.54%) firstyears, 16 (20.51%) secondyears, 7 (8.97%) thirdyears, 7 (8.97%) fourthyears, and students with majors of all eight major divisions offered at the school. This study made use of convenience sampling. Eligible participants received assignment credit in a psychology course for participating in this research. No participants dropped out after starting.
Internal consistency was calculated for scores on the Positive and Negative Affect Schedule (PANAS) and Remote Associates Test (RAT). Participants’ use of bluelight glasses was measured for exploratory analyses, however, only four participants reported wearing blue light glasses. Therefore, no additional analyses were conducted on this variable.
Design
This study made use of a 2 x 2 experimental design. One independent variable was color temperature which consisted of a warm color condition and a cool color condition that was examined between subjects with random assignment. Another independent variable was lighting temperature which consisted of a warm and cool lighting condition examined within subjects, counterbalanced for order effects. We examined the effects of color and lighting temperatures on mood (as measured by the PANAS), cognitive performance (as measured by the Stroop and RAT tasks), and heart rates (as measured by forearm heart rate monitors). These measures were analyzed withinsubjects to use participants as their own controls, rather than between subjects. We did not employ a withinsubjects design for the room color, as this change would be very noticeable to participants (unlike manipulating the warmth of the lighting). That is, if participants completed tasks in a red room and then came back to a blue room after the break, this may have been a threat to the validity of the design. Therefore, each participant completed experimental tasks and surveys in one color and both lighting conditions. For the color temperature variable, 47.4% were in the warm color condition (n = 37), and 52.6% were in the cool color condition (n = 41). Participants completed the experiment individually. Data collection stopped
after a predetermined sixweek period. Participants with missing data on certain scales and tasks were excluded only from analyses that involved those data.
Materials/Measures
Two questionnaires were administered through Qualtrics, and included an informed consent form, the mood survey, the Ishihara test, the Stroop task, and the RAT items for the trial condition and the experimental conditions. If a participant did not pass the Ishihara test, they were not given the experimental questionnaire.
Condition Materials
The Munsell Color Chart as used by the World Color Survey was used to select the condition colors. The warm color is described as G2 from the Munsell Color chart, and the cool color as H30. These colors were both high in saturation. The warm light had an illuminance factor of around 3,000K, and the cool light had an illuminance factor of around 6,000K.
The color conditions were created by using red and royal blue bulletin paper cut to the same size and fixed behind the computer. For lighting, two lamps with multiple brightness and temperature settings were used at their brightest setting to be set to the coolest setting in the cool lighting condition, and the warmest setting in the warm lighting condition. For the warm lighting condition, the computer screen was also set to a warm light setting to mitigate the contrasting effects of the blue light typically emitted by computer screens.
Ishihara Test
The Ishihara Test (computer version) was used to determine study eligibility by providing an indicator of color blindness. Potential participants were presented with an image of dots in one color forming two numbers inside a circle of dots in another color; the task was to identify the two numbers in the circle. This measure can only determine redgreen color blindness; failure to identify the numbers in the circle indicated possible redgreen colorblindness and exclusion from the study.
Positive and Negative Affect Schedule
The Positive and Negative Affect Schedule (PANAS) was used to measure participants’ state affect (Watson et al.,1988). The measure was adapted from its original to state, “indicate the extent you feel this way right now,” instead of “…the way you have felt over the past week” to measure state, rather than trait, affect. The scale measures 20 affect indicators, 10 measuring positive affect and 10 measuring negative affect, on a 5point scale to what degree they resonate with them ranging from 1 (very slightly or not at all) to 5 (extremely). The negative item “afraid” was left out by error and not collected from participants, so
the subscale scores were calculated from 10 positive and 9 negative scores in this study.
Scores were calculated by summing the scores on positive items into a positive affect score (ranging from 10–50, higher scores indicating a higher positive affect level) and those on negative items into a negative affect score (ranging from 9–45, higher scores indicating a higher negative affect level). The scale’s utility is promoted by the evidence of largescale normative data (Crawford & Henry, 2004). Our internal consistency analysis showed that Cronbach’s alpha was greater than .73 for positive and negative scales each time they were administered.
Reaction Time and Accuracy: Stroop Task
An online Stroop test from Hanover College was administered with 20 trials (one word per trial) per session, for a total of 40 trials per lighting condition (Hanover College, n.d.). The Stroop task was used to calculate attention to detail and cognitive interference by presenting color words in congruent colors (e.g., the word “blue” in blue text) and incongruent colors (e.g., the word “blue” in red text) and measuring participants’ reaction times and accuracy on congruent vs. incongruent trials. Reaction time scores were calculated by averaging the reaction times (in milliseconds) for each set and subtracting incongruent scores from congruent scores; higher scores indicate faster reaction times on incongruent items, even though mean scores tend to be negative due to incongruent trials having slower reaction times than congruent ones. Thus, a reaction time score of 300 indicates a slower reaction time average on incongruent than congruent trials by 300 milliseconds. Accuracy was calculated by averaging participants’ accuracy (1 for correct, 0 for incorrect) and subtracting incongruent scores from congruent scores. The higher the accuracy score, the more accurate participants were on congruent vs. incongruent items. Testretest reliability is sufficient for the Stroop task, though many different forms are used (Franzen, 1987). For the purposes of this experiment, an online form was used. Franzen (1987) recommended that participants have prior exposure to the task to ensure the learning curve asymptote is reached before the treatment is given, so a trial run of the Stroop task was administered to participants before the experimental conditions so that they knew how to complete it.
Creative Intelligence: Remote Associates Test (RAT)
The RAT was used to measure creative intelligence, following Xia et al. (2016). Items from this task were adapted from a collection of items from the Remote Associates Test of Creativity. Selected items were included in the Qualtrics survey and chosen to represent an equal distribution of
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difficulty from very easy to very hard. Two versions were created with the same distribution of difficulty, representing four “Very Easy,” four “Easy,” four “Medium,” four “Hard,” and four “Very Hard” items each. The versions were counterbalanced for the order completed in the two lighting conditions. According to Olteţeanu and Zunjani (2020), all internal consistency results for the visual RAT are above .75. Our results also showed strong internal consistency for Version 1 items (α = .84) and Version 2 items (α = .78).
Heart Rate
Heart rate monitors were placed on each participant’s desired forearm at the start of the experiment in the control condition. The Scosche Rhythm R+2.0: Advanced Waterproof & Dustproof Heart Rate Monitor Armband was used to monitor heart rates and the accompanying Rhythm SYNC mobile application was used by the researcher to record participants’ heart rates at the end of each set of tasks. Heart rates were recorded in beats per minute, and these data were reported and recorded in whole numbers and were not altered prior to analyses.
Demographic Survey
A demographic survey was included at the end of the Qualtrics survey. This was used to obtain information about age, sex, race, school year, school division, and whether participants were wearing bluelight glasses during the experiment.
Procedure
Upon agreeing to the terms of informed consent and passing the Ishihara Color Test, participants were asked to complete the PANAS and a trial run of the Stroop task in a room next to the experiment room. Here, participants were given forearm heart monitors and their base heart rates were recorded at the end of each set of tasks. Then, participants were led to a room with a desk and a laptop in one of the assigned color backgrounds and lighting temperature conditions. They were instructed to complete the Remote Associates Test and then proceeded to the Stroop task. They were asked to complete the PANAS at the end of the set of tasks, and there was a fiveminute break between tasks that took place outside of the room where the researcher or research assistant switched the lighting mode of the lamp and computer. Heart rates were recorded at the end of each set. Upon completion of the same tasks in the second lighting condition, participants were asked to complete a demographics survey, and then were thanked for their participation and dismissed. The average time to complete the study was about 45 minutes, taking around 15 minutes per experimental condition, 10 minutes to complete the trial, and a 5minute break to
counteract lighting effects. Each participant participated in the experiment once.
Results
Data was analyzed using the SPSS version 29. Data were not collected from six participants after they scored below the threshold of color blindness determined by the online Ishihara test. They were not included in the 78 participant count for analyses. Only one outlier
Positive Affect as a Function of Lighting and Color Temperature
Note. Positive affect as a function of lighting and color temperature. The error bars represent +/- 1 Standard Error. There were no differences in positive affect based on color or lighting and there was no interaction between color and lighting.
Negative Affect as a Function of Color and Lighting Temperature
Note. Negative affect as a function of color and lighting temperature. The error bars represent +/- 1 Standard Error. There was an interaction between color and lighting: in the warm lighting condition, scores on negative affect in the warm color were higher than in the cool color; in the cool lighting condition, scores on negative affect in the warm color were lower than those in the cool color. There were no main effects of color or lighting on negative affect.
FIGURE 1
FIGURE 2
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was detected using the Outlier Labeling Rule (Hoaglin et al., 1986) in the Heart Rate scale in the warm lighting condition. This outlier was deleted listwise. In cases where participants had missing data on the primary scales, they were excluded from analyses using these scales, but retained in other analyses (n = 4). To test our hypotheses, we conducted mixed repeated measures ANOVAs, with the withinsubjects factor of lighting (cool vs. warm) and the between subjects factor of color condition (cool vs. warm) on each of the six main outcome variables: positive affect, negative affect, Stroop reaction time, Stroop accuracy, RAT, and heart rate.
PANAS
A mixed repeated measures ANOVA was used to determine whether positive affect (PA) scores from the PANAS in warm and cool lighting (withinsubjects) were different in the warm and cool color conditions (between subjects). The main effect of color on PA was not significant F(1, 76) = 3.79, p = .06, η2 p = .05, indicating scores in the warm color (n = 37, M = 19.70, SD = 6.26) did not differ from scores in the cool color (n = 41, M = 23.04, SD = 9.03). The main effect of lighting on PA scores was also not significant F(1, 76) = 1.88,
Differences in Congruent and Incongruent Stroop Reaction Time as a Function of Color and Lighting Temperature
p = .17, η2 p = .02, indicating scores in warm lighting (n = 78, M = 21.79, SD = 8.08) were not different than those in cool lighting (n = 78, M = 21.12, SD = 7.94 ). The interaction effect of color and lighting on PA was not significant, F(1, 76) = 0.89, p = .34, η2p = .01, indicating that positive mood scores in the warm color condition within warm lighting (n = 37, M = 20.30, SD = 6.07) and cool lighting (n = 37, M = 19.11, SD = 6.47) were not different from in the cool color condition within warm lighting (n = 41, M = 23.15, SD = 9.42) and cool lighting (n = 41, M = 22.93, SD = 8.75), see Figure 1.
The mixed repeated measures ANOVA for negative affect (NA) revealed no main effects for color, F(1,76) < .01, p = .96, η2p < .01, indcating the warm color (n = 37, M = 13.28, SD = 4.54) did not differ from the cool color (n = 41, M = 13.33, SD = 4.31). Likewise, there were no main effects for lighting, F(1, 76) = 3.37, p = .07, η2 p = .04, indicating scores in warm lighting (n = 78, M = 13.64, SD = 4.23) did not differ from those in cool lighting (n = 78, M = 12.97, SD = 4.58). However, the interaction effect between color and lighting on NA scores was significant F (1, 76) = 4.10, p = .046, η2p = .05, indicating that, in the warm lighting condition, scores on negative affect in the warm color ( n = 37, M = 14.03, SD = 4.65) were higher than in the cool color (n = 41, M = 13.29, SD = 3.83), but in the cool lighting condition, scores on NA in the warm color condition (n = 37, M =12.54, SD = 4.36) were lower than those in the cool color condition (n = 41, M = 13.37, SD = 4.79); see Figure 2.
Stroop
Note. Differences in congruent and incongruent Stroop reaction time as a function of color and lighting temperature. Reaction Time scores were calculated by subtracting incongruent reaction time averages from congruent ones. As reaction times are typically slower on incongruent trials, this results in a negative number. These scores show how much slower reaction times were on incongruent vs. congruent trials. The error bars represent +/- 1 Standard Error. There were no effects of color or lighting on reaction time and there was no interaction of color and lighting.
Reaction time scores were calculated by subtracting reaction time averages on incongruent trials from congruent ones; the more negative the number, the slower reaction times were on incongruent compared to congruent trials. The repeated measures mixed ANOVA for reaction time on the Stroop task revealed no significant main effects for color, F(1, 73) = 0.98, p = .32, η2p = .01, indicating that the warm color (n = 37, M = 275.59, SD = 282.54) did not differ from the cool color (n = 41, M = 341.69, SD = 330.40). Likewise, there were no main effects of lighting, F(1, 73) = .07, p = .79, η2p = .001, indicating that the difference in reaction times between incongruent and congruent trials did not differ in the warm lighting condition (n = 75, M = 300.90, SD = 326.48) from the cool lighting condition (n = 75, M = 309.98, SD = 286.59). Finally, there was no significant interaction between color and lighting, F(1, 73) = 3.57, p = .06, η2p = .05, indicating that differences in reaction times in the warm colorcondition within warm lighting (n = 37, M = 234.55, SD = 240.06) and within cool lighting (n = 37, M = 316.63, SD = 317.46), and in the cool color condition within warm lighting (n = 38,
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FIGURE 3
M = 365.49, SD = 385.25) and cool lighting (n = 38, M = 303.51, SD = 257.14) were not significant, see Figure 3.
For accuracy scores in the Stroop task, errors were coded as a 0 and correct responses were coded as a 1, and incongruent scores were subtracted from congruent scores. Thus, the higher the accuracy score, the more accurate participants were on congruent vs. incongruent items. The main effect of color on accuracy was significant, F(1, 73) = 6.49, p = .01, η2p = .08, indicating that those in the cool color condition (n = 38, M = 0.14, SD = 0.33) were significantly more accurate than those in the warm color condition (n = 37, M = 0.02, SD = 0.14). The main effect of lighting on accuracy scores was not significant, F(1, 73) = 3.13, p = .08, η2p = .04, indicating that the differences in accuracy scores within warm lighting (n = 75, M = 0.10, SD = 0.28) and cool lighting (n = 75, M = 0.06, SD = 0.22) was not significant. The interaction effect of color and lighting on accuracy scores was also significant, F(1,73) = 4.08, p = .047, η 2 p = .05, such that the cool color was less accurate in the cool lighting condition ( n = 37, M = 0.11, SD = 0.04) than in the warm lighting condition (n = 38, M = 0.19, SD = 0.37), but the warm color was the same in the cool lighting condition (n = 37, M = 0.02, SD = 0.04) and warm lighting condition (n = 37, M = 0.01, SD = 0.04); see Figure 4.
RAT
A mixed ANOVA was conducted to determine the effects of color and lighting temperatures on summed scores on the RAT. The main effect of the betweensubjects factor of color on RAT scores was not significant, F(1, 75) = 0.02, p = .89, η2p = .00, indicating the warm color ( n = 36, M = 7.81, SD = 4.08) did not differ from the cool color (n = 41, M = 7.68, SD = 4.15). The main effect of the within subjects factor of lighting approached significance, F(1, 75) = 3.95, p = .05, η2p = .05, indicating RAT scores in warm lighting (n = 77, M = 7.35, SD = 3.97) were marginally lower than those in cool lighting (n = 77, M = 8.13, SD = 4.24). The interaction effect of color and lighting on RAT scores was not significant, F(1,75) = 2.85, p = .10, η2p = .04, indicating that scores did not differ significantly in the warm color condition within warm (n = 36, M = 7.75, SD = 4.12) and cool (n = 36, M = 7.86, SD = 4.15) lighting, and in the cool color condition within warm (n = 41, M = 7.00, SD = 3.85) and cool (n = 41, M = 8.37, SD = 4.36) lighting. Figure 5 shows the color and lighting interaction means of RAT scores.
Heart Rate
A mixed ANOVA was used to determine if heart rate
scores in warm and cool lighting were different in warm and cool colors. The main effect of color on heart rates was nonsignificant, F(1, 75) = 0.25, p = .62, η2p = .00, indicating the warm color (n = 36, M = 73.41, SD = 11.11) did not differ from the cool color (n = 41, M = 74.73, SD = 12.00). The main effect of lighting on heart rates, F(1, 75) = 0.91, p = .34, η2p = .01, was also not significant, indicating heart rates in warm lighting ( n = 77, M = 73.78, SD = 11.63) did not differ significantly from those in cool lighting (n = 77, M = 74.49, SD = 11.64). The interaction between color and lighting was also not significant, F(1, 75) < 0.00, p = .98, η2p < .00, indicating that the differences in heart rates in the warm color condition within warm ( n = 36, M = 73.11, SD = 11.41) and cool (n = 36, M = 73.81, SD = 11.09) lighting, and in the cool color condition within warm (n = 41, M = 74.37 SD = 11.93) and cool (n = 41, M = 75.10, SD = 12.21) lighting were not significant. Figure 6 shows the color and lighting interaction means of heart rates.
Differences in Congruent and Incongruent Stroop Accuracy as a Function of Color and Lighting Temperature
Note. Differences in congruent and incongruent Stroop accuracy as a function of color and lighting temperature. Accuracy scores were calculated by coding errors as a 0 and correct responses as a 1 and subtracting incongruent scores from congruent scores. Thus, the higher the accuracy score, the more accurate participants were on congruent vs. incongruent items. The error bars represent +/- 1 Standard Error. There was an interaction between color and lighting. Those in the cool color condition were less accurate in the cool lighting condition than in the warm lighting condition, but those in the warm color condition were no different in accuracy based on the lighting condition. There was also a main effect of color, such that those in the cool color condition were more accurate than those in the warm color condition.
FIGURE 4
Discussion
The current study analyzed how the color and lighting temperatures of a space affect people’s levels of positive and negative affect and cognitive performance. Positive and negative affect were measured using the PANAS, and cognitive performance was measured by creative intelligence scores from the RAT and reaction times and accuracy scores from the Stroop task.
Main Effects
Our first three hypotheses were designed to replicate previous findings on the individual effects of color or lighting, or to examine topics that had provided mixed results in previous research. We hypothesized that positive affect would be higher in cool color and warm lighting conditions, but this was not fully supported. No main effects of color or lighting on positive affect were found, and interaction effects were only significant for negative affect. Contrary to Zhu et al. (2019), positive mood was not found to be higher in warm than cool lighting, however, in agreement with Knez and Kers (2000), negative mood in younger adults was sustained more in warm than cool lighting.
We hypothesized secondly that arousal measured as increased heart rates would be higher in warm colors as well as cool lighting. This was not supported, as no main effects of color and lighting on heart rates were significant. Chen et al. (2022) similarly found that
Creative Intelligence Scores as a Function of Color and Lighting Temperature
lighting temperatures did not change participants’ heart rates significantly, but in contrast, Cha et al. (2020) found significant changes in heart rates in blue, white, and green color schemes. It should be noted that these changes occurred between only cool and achromatic color schemes, and not between warm and cool color schemes. These previous findings and the current findings provide interesting discourse and grounds for further research on the physiological effects of environmental color and lighting.
We hypothesized thirdly that cognitive performance would be better in cool color and cool lighting conditions than in warm color and warm lighting conditions. This was partially supported. Accuracy scores were indeed higher in the blue color than the red color conditions, congruent with Costa et al. (2018).
Creative intelligence was better promoted in cool than in warm light, as demonstrated by scores on the RAT being marginally higher in cool lighting than warm lighting. This supports the lighting aspect of Hypothesis 3. As color did not significantly affect RAT scores, different color temperatures may not affect creative intelligence compared to other areas of cognitive performance.
Interaction Effects
Our final hypothesis was formulated based on our primary theory that color and lighting interact together
Heart Rate as a Function of Color and Lighting Temperature.
Note. Creative intelligence scores as a function of color and lighting temperature. The error bars represent +/- 1 Standard Error. There was no effect of color or lighting on creative intelligence scores and there was no interaction between color and lighting.
Note. Heart rate as a function of color and lighting temperature. The error bars represent +/- 1 Standard Error. There was no effect of color or lighting on heart rate and there was no interaction between color and lighting.
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FIGURE 5
FIGURE 6
to impact the experiences of people who inhabit a space. We hypothesized lastly that the combinations of color and lighting temperatures would have different impacts on mood and cognitive performance levels, which was supported by our results, as color and lighting interacted in different ways to affect these aspects of mood, cognitive performance, and arousal differently.
Negative mood was higher in the Warm Lighting x Red Color condition than in the Warm Lighting x Blue Color condition. In cool lighting, negative mood was higher in the Blue Color condition than in the Red. This suggests that in an environment that is cool in both background color and lighting, and in one that is warm in both background color and lighting, negative mood is higher. It may then follow that having a combination of warm and cool temperatures in background color and lighting is preferable for low levels of negative mood than spaces that are all warm or cool. The slightly neutralizing effect of warm lighting on cool color tones and of cool lighting on warmer color tones may lead to a more neutral mood than combinations that are very cool or very warm all over. This relationship should be further explored. No significant interaction effects on heart rates were found. That accuracy scores in the blue color condition were higher in the warm lighting than cool lighting was contrary to Hypothesis 3, but the interaction effect supported Hypothesis 4. This indicates that a cool background color in combination with cool lighting did not assist participants in accuracy, but the environment with blue color and warm lighting did. This finding suggests that a combination of warm and cool temperatures better promotes accuracy than environments that are either all cool in color and lighting or all warm. Consistent with our results, Zhu et al. (2019) found that participants were less accurate in cool lighting than in warm. Unlike their other results, we did not find that reaction times were slower in warm light, and that overall performance was better in cool light. Although the results of their study did not include the interaction of color, it can still speak to the effect that cool lighting may not, in some circumstances, serve to improve one’s accuracy on a cognitive task. Our results further point to the taskdependent effects of color and lighting temperatures on various aspects of cognitive performance, as Elliot (2019), Stone (2001), and Xia et al. (2016) suggested. Our interaction effect regarding accuracy is unique to the body of research that aims to understand color and lighting temperature effects on cognitive performance. That accuracy was essentially the same in the red color condition between warm and cool lighting sparks debate about why these different interactions occurred. These results––from two measures of cognitive performance from the Stroop task alone––indicate how nuanced
the effects of color and lighting temperatures are. Interactions between color and lighting temperatures did not significantly affect score differences on the creative intelligence task, suggesting that there is indeed more nuance to the ways that warm and cool colors and lighting temperatures affect creative intelligence. Such findings regarding these different elements of cognitive performance are a basis for more indepth research on the complex relationship between specific cognitive tasks and how background color and lighting temperatures influence them, both alone and in combination. Whether warm colors and cool lighting provide the same distracting stimulation effect on mood as on cognitive functioning may prove fruitful for further research. That cool colors promoted positive emotions more so than warm colors is in accordance with Elliot (2019), Roy et al. (2021), Stone (2001), and Wilms & Oberfeld (2017). Neither lighting nor color temperature incited significant differences in heart rates, indicating that these factors may not influence physiological as much as psychological responses.
Implications
Results of this study can give a basic understanding of how two foundational elements of design–color and lighting–affect humans in psychological manners like mood and cognitive task performance. These results can be incorporated into educational settings especially, where certain aspects of cognitive performance should be supported. For example, if accuracy is important on a given task, it might be best to take tests or practice in a space with predominantly cool surrounding colors and under warm lighting. If creative intelligence and problemsolving are of the highest importance of the task at hand, cool lighting may be better for promoting such performance. Such findings can be implemented by teachers deciding the ideal setting in which to promote performance in students depending on the nature of the subject, and by students when practicing and promoting certain aspects of their own cognitive abilities. While especially important in a home environment, a reduced negative mood may serve as an asset in a school or office space as well. In classrooms, while cool lighting is commonly used to keep students awake and focused, warmer lighting and coolcolored backgrounds––or even cooler lighting in a warmercolored environment––may be more beneficial in promoting less negative mood in students. This may then motivate students to further engage in the learning process. For an individual completing any work in an office or home office where creative intelligence would be best promoted, opting for more cool lighting may prove beneficial.
These results can inform the design of residences, schools, study and work areas, offices, libraries, counseling
offices, and many other settings. The results of this study can be applied especially to spaces where mood and task performance are major factors. Humans spend their time in a variety of different settings where different levels of performance and comfort may be desired, and designing with intent can increase the effectiveness of these spaces. These findings can be applied to individual, educational, residential, occupational, and institutional settings.
Limitations
This study was conducted at Pepperdine University, a private, Christian, liberal arts college in California, which limits the generalizability of the results. In the setting where the study was conducted, the conditions were composed of a sheet of colored bulletin paper covering one wall of the room facing participants, and two desk lamps. While it is a strength of the study that the colors and lighting elements were represented in a reallife setting as opposed to via photos or videos, the color conditions were only present on the wall participants faced while completing tasks. Similarly, the lighting sources, while the main sources of light in the room, were different than having overhead lights in these temperatures that may be more representative of many other rooms where studying takes place. As participants spent a quite long amount of time in each condition (around 15 minutes in each lighting condition and around 30 minutes in front of either color condition), we believe that the color and lighting setup taking up most of the participants’ fields of vision was sufficient for analyzing the effects of the conditions. The time of day of participation in the experiment was not controlled. This could have led to variations in fatigue or stress levels in different participants that resulted from completing the experiment at different times of day. However, in theory, random assignment should have balanced any such effects between conditions The somewhat limited setup of the study may have contributed to the hypothesized effects on some mood, cognitive performance, and physiological measures not being found that are generally found in other studies.
Suggestions for Future Research
Future research on this topic can be conducted in a greater variety of settings, using a wider variety of color and lighting temperatures in between fully saturated red and blue colors and very cool and very warm lighting sources. Future research can also study participants in these settings for long periods to see what the longitudinal effects, rather than state effects, of certain elements of design are. Future studies on the topic of environmental psychology should explore the complexities that underlie the taskdependent effects
of color, lighting, and other primary design elements such as room layout and size. Future research should also study how color and lighting temperatures interact in different settings where the intended effects may be healing, rehabilitation, physical and cognitive stimulation, and other goals of interior spaces.
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Megan B. Afifi https://orcid.org/0000000191989501
Elizabeth J. KrumreiMancuso https://orcid.org/0000000161517845
Janet Trammell https://orcid.org/0000000203046974
This study was preregistered at https://osf.io/wb9dk. Data collection and analyses were sponsored by the Psychology Honors Program at Pepperdine University. We have no conflicts of interest to disclose.
Correspondence concerning this article should be addressed to Megan B. Afifi, Pepperdine University, 24255 Pacific Coast Hwy, Malibu, CA 90263. Email: meganafifi@gmail.com
Mental Health and Religiosity Among Sexual Minority Students at a Christian University
Danica P. Christy, Steven V. Rouse*, and Elizabeth J. Krumrei-Mancuso* Department of Psychology, Pepperdine University
ABSTRACT. University students are reporting increasing levels of psychological distress and suicidality. Consistent with the minority stress model, sexual minorities (SMs) are especially vulnerable; this is often heightened at religious universities that are nonaffirming of SM identities. We studied mental health and religiosity among 211 undergraduates at a religiously diverse, LGBTQ+ permitting, yet nonaffirming, university. SMs (n = 58) reported higher rates of suicidality (Z = 4.50, p < .001, ρ = .31) and psychological distress (t = 4.27, df = 209, p < .001, d = 0.66) than nonSMs. The correlation between intrinsic religiosity suicidality (ρ = .16, p = .02) was not moderated by SM identity. Similarly, the correlation between intrinsic religiosity and psychological distress (ρ = .18, p = .01) was not moderated by SM identity. Religious attendance correlated with higher rates of internalized homonegativity (ρ = .31, p = .02) and lower rates of identity superiority (ρ = .36, p = .005) for SMs. These findings highlight the complicated relationship between SM identity and religiosity. This study underscores the importance of offering affirming religious spaces for SM individuals and providing increased psychological support for SM students at religious universities.
Keywords: sexual minorities, religiosity, mental health, religious university, university students
In recent years, universities in the United States have witnessed increasing demand for mental health services and increasing rates of mental illness among university students. A review of two large, national studies performed across a 10year period found that depression, anxiety, nonsuicidal selfinjury, suicidal ideation, and suicide attempts increased markedly in university students between 2007 and 2018 (Duffy et al., 2019). Many of these increases were extreme. For example, in a national study of over 170,000 college students, severe depression, nonsuicidal selfinjury, suicide plans, and suicide attempts increased by over 100% in a decade.
These findings are especially concerning for communities that are at a higher risk of mental health
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struggles. The minority stress model theorizes that sexual minority (SM; this includes anyone identifying as gay, lesbian, bisexual, questioning, asexual, etc.) individuals are at a higher risk for psychological distress due to (a) external stressful experiences such as discrimination or violence, (b) expectations of these experiences, (c) concealment of sexual orientation, and (d) the internalization of negative societal expectations and attitudes (Meyer, 2013). Recent research has shown support for the minority stress model among SM students in university settings (Lipson et al., 2019; Riley et al., 2016; Wilson & Liss, 2022). This is especially true at religious universities (Klundt et al., 2021), where the occurrence of discrimination may be higher for SM students. Discrimination, bullying,
and microaggressions (i.e., subtle and indirect discrimination) can be detrimental to the mental health of SM students (Busby et al., 2020; Wolff et al., 2016).
Considering the large number of religiously affiliated universities in the United States, 883 as of 2015, these mental health risks are concerning (National Center for Educational Statistics, 2017). Among these religiously affiliated universities, many have policies against SM people, such as banning samegender relationships, statements opposing samegender marriages, and even outright banning of LGBTQ+ identifying students, faculty, and staff. These policies may heavily impact the experiences, and in turn, the mental health of their SM students (Woodford et al., 2018).
SMs and Mental Health
A large body of literature supports the minority stress model’s prediction that SMs are at a higher risk of psychological distress than heterosexual individuals. A systematic review of 199 studies published between 2005 and 2014 revealed that the majority of these studies found higher rates of depression, attempted suicide, anxiety, alcohol and drug use, and other disorders in adult and adolescent SMs compared to non SMs (Plöderl & Tremblay, 2015). Additionally, a recent longitudinal study comparing rates of depression, anxiety disorders, suicidal ideation, substance abuse, and total mental health disorders found that sexual minorities reported significantly higher rates in all these categories compared to their heterosexual counterparts throughout the examined age range, 18 to 35 years of age (Spittlehouse et al., 2020). Both of these studies offer substantial support to the theory that SMs are at a higher risk of mental illness than heterosexuals.
These findings hold true among SM university students, who are at an even higher risk of mental illness than their heterosexual counterparts (Lipson et al., 2019; Wilson & Liss, 2022). A comparative study of 1,777 incoming firstyear students found that SM students reported significantly higher levels of depression, anxiety, and distress in comparison with heterosexual students both prior to and at the end of their first semester of college (Riley et al., 2016). Additionally, they experienced a greater increase in these symptoms over a threemonth period and greater experiences of stress than heterosexual students. This is likely because they are exposed to the same stressors as heterosexual students in addition to SMspecific challenges as they adjust to the college environment (Evans et al., 2017). Such research supports the minority stress model within a university setting by showing that SM university students are at risk of discrimination, stigma, and isolation, which in turn increases their risk of psychological distress.
Considering rates of mental illness have significantly increased among university students in general in recent years (Duffy et al., 2019), SM university students are especially vulnerable to negative mental health.
SMs, Mental Health, and Religiosity
Although religiosity is a protective factor for psychological distress in heterosexual individuals (Hackney & Sanders, 2003), the relationship between SMs’ mental health and religiosity is complex because religiosity acts as both a risk factor and a protective factor for SMs. Among SM individuals, religiosity is correlated with risk factors such as higher rates of alcohol abuse, anxiety, and internalized homophobia (Barnes & Meyer, 2012; Corbin et al., 2020; Wilkinson & Johnson, 2021). This may be because many religions, specifically religions that are nonaffirming of SMs, teach that samegender attraction and behaviors are sinful. However, religiosity also has positive impacts for SMs, such as offering belonging, providing social support, reducing health risks, and protection from psychological distress (Dyer, 2022; Lefevor et al., 2018; Wilkinson & Johnson, 2021).
Additionally, the literature provides support for religion acting as both a risk factor and a protective factor for suicidality. Although some studies have found that religiosity decreases the risk of suicidal ideation in SMs (Oh et al., 2022), others have found that religiosity increases the risk (Dyer, 2022; Lytle et al., 2018). A recent study attempted to explain this phenomenon by measuring religious attendance and religious beliefs separately (Park & Hsieh, 2023). They found that religious beliefs were associated with lower suicidality for lesbian, gay, and bisexual individuals. Conversely, religious attendance was associated with higher suicidality among lesbian, gay, and bisexual individuals. This suggests that SMs might be exposed to negative experiences at church, such as stigmatizing messages or microaggressions, that increase their risk of suicidality (Lomash et al., 2018).
SMs at Religious Universities
Understanding the complex relationship between religiosity and mental health for SM students is particularly relevant for SM students attending religious universities. Religious universities can offer unique challenges to SM students. Students at some of these universities experience institutionalized homophobia and marginalization (Woodford et al., 2018). Additionally, they experience personal victimizations and microaggressions, which may be more detrimental to mental health than blatant victimization (Woodford et al., 2014). They may also struggle with reconciling their faith and sexuality, internalized homophobia, and psychological distress (HeidenRootes et al., 2018; Klundt et al., 2021). Christy, Rouse, and Krumrei-Mancuso
A large study at Brigham Young University (BYU), a university affiliated with the Church of Jesus Christ of Latterday Saints, found that SM students reported lower quality of life and higher psychological distress than heterosexual students (Klundt et al., 2021). Additionally, they found that religiosity functioned as a positive influence for measured outcomes, such as decreasing rates of suicidality, for both heterosexual students and SM students. However, religion was a stronger positive influence for heterosexual students than SM students. Finally, they found that higher rates of religiosity were associated with higher rates of internalized homonegativity and lower rates of acceptance concerns. This study highlighted the complicated relationship between religiosity and mental health for SMs.
The reviewed research has consistently displayed increased mental health risks for SM students, which suggests the need for a support system for SM students at both religious and nonreligious universities. Some students have found this support through gendersexuality alliances (GSAs) if their university permits such an organization. Limited research shows that these organizations have been linked with positive outcomes for SM students. For example, a study of SM students at nonaffirming religiously affiliated universities found that being involved with a GSA was correlated with SM students having a more positive perception of their sexuality, less religious incongruence, and fewer struggles with their sexuality than SM students who were not associated with their GSA (Wolff et al., 2016).
Limitations in Literature
There are a few limitations of the existing literature. Due to the exploratory nature of these studies, some of the samples lacked racial diversity (HeidenRootes et al., 2018; Klundt et al., 2021; Wolff et al., 2016) or religious diversity (Klundt et al., 2021). There have been somewhat conflicting findings regarding religiosity, which may result from varying measures of religiosity from study to study. For example, religiosity is often measured by affiliation only or by a single item on the importance of religion, rather than a validated scale. These measurements fail to capture the multiple dimensions of religiosity and are overall poor measures of religiousness (Lefevor et al., 2022). Additionally, there is limited research on SM students at religious universities. Within that literature, there are few comparative studies between SM and heterosexual students. To our knowledge, comparative studies have only been conducted at universities where most of the population belongs to a single Christian denomination, which are not representative of religious universities as a whole.
Present Study
Considering the literature showing an increase in mental illness among university students, the heightened risk of mental health struggles for SM students at religiously affiliated universities, and the complicated relationship between religiosity and mental health for SM students, we investigated the relationship between religiosity and mental health in students at a religiously diverse, SM welcoming, but nonaffirming, religiously affiliated university. The present study relied on a widely used measure of religiosity and included a measure of SMspecific concerns. It is a modified replication of Klundt et al. (2021) who conducted a comparative study between SM students and heterosexual students. Despite their study’s strengths, Klundt et al. assessed students at BYU, which is religiously homogeneous (98% of BYU students are members of the Church of Jesus Christ of Latterday Saints), practices a religion that is dissimilar to many other Christian denominations, and has specific doctrines against samesex romantic behavior (Klundt et al., 2021).
To expand upon the work of Klundt et al. (2021), the purpose of the current study was to examine the relationship between psychological distress and religiosity of SM compared to heterosexual students at a religious university that is more representative of religious universities in the United States than BYU. First, the university from which we collected data has more religious diversity than BYU. Although our sample was 71% Christian, they identified with a variety of denominations. This means that the participants come from a variety of religious backgrounds and have likely been exposed to different religious doctrines regarding the LGBTQ+ community. Additionally, the university at which the present study took place does not have specific policies against homosexuality, therefore students are able to openly identify as LGBTQ+. This is in line with most Christian universities in the United States, with only 31% officially banning “homosexual acts or behavior” and 55% adopting nondiscrimination policies protecting lesbian, gay, and bisexual students (Coley, 2016; Coley, 2018). The university also has an official GSA that was approved in 2016. In 2014, 45% of Christian colleges in the United States had a GSA and this number has likely grown in recent years (Coley, 2016). However, the university retains a nonaffirming stance and explicitly denounces sexual behavior outside of a marriage between a man and a woman. Due to these characteristics, this study broadens the scope of Klundt et al.’s (2021) findings by more accurately representing the culture of religious universities in the United States.
Our hypotheses were as follows:
1. Based on the minority stress model (Meyers, 2013), SM students would report higher levels of
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psychological distress and suicidality than heterosexual students.
2. Similar to the findings of Wolff et al. (2016), students who experience samegender attraction and are involved in their university’s GSA would report having less difficulty accepting their sexuality and would report lower levels of incongruence between their religious beliefs and their sexuality than students who experience samegender attraction and are not involved in their university’s GSA (Wolff et al., 2016).
3. Based on previous research (Klundt et al., 2021), intrinsic religiosity, or strength of personal religious beliefs, would be predictive of lower levels of psychological distress and suicidality for both SM and heterosexual students, but the relationship would be weaker for SM students than heterosexual students.
4. Based on the findings of Klundt et al. (2021) intrinsic religiosity would be predictive of higher levels of identity concerns specific to LGBTQ+ students, such as internalized homonegativity, for students who experience samegender attraction.
Although Hypotheses 3 and 4 may seem to conflict with each other, multiple studies have documented higher rates of identity concerns specific to LGBTQ+ students without higher rates of psychological distress. Previous authors have proposed that this is because the protective characteristics of religion counteract the harmful impacts of homonegativity (Barnes & Meyer, 2012; Klundt et al., 2021).
Method
Procedure
Preregistrations of minimum sample sizes and primary analyses are available on the Open Science Framework (https://osf.io/yku45/). We obtained approval from the Pepperdine University Institutional Review Board and followed all APA ethical standards. Participants completed electronic consent forms prior to participating in our study. Participants were recruited through introduction to psychology classes ( n = 163). These participants received assignment credit in their class for participating. We recruited additional SM participants by sending a recruitment email to the university’s GSA email list and posting on the university’s GSA social media (n = 39). These students were compensated by being entered into a gift card raffle. Some participants chose not to receive class credit or be entered into the raffle (n = 9). Data were collected through an electronic, selfreport survey. The survey consisted of a demographic questionnaire and several psychological tests. Data collection occurred over a five week period. Any participants
who failed our validity item or had incomplete data (n = 13) were excluded from our analyses. An additional 12 participants were excluded from our analyses because they identified as heterosexual and reported same sex attraction. Although there is documentation of highly religious same sex attracted individuals who do not identify as LGBTQ+, this population is highly unique and may confound the results (Lefevor et al., 2020; Rosik et al., 2021). Participants who failed to complete all items within a single survey were excluded from analyses using that survey.
Participants
The sample consisted of 211 college students from a small liberal arts college on the West Coast. An a priori power analysis indicated that 156 total participants were needed to have 80% power to detect a mediumsized effect (d = 0.50) with a .05 criterion of significance. An additional a priori power analysis indicated that 60 SM participants were needed to have 80% power to detect a mediumsized effect (d = 0.65) with a .05 criterion of significance. The sample included 58 participants who identified with one or more SM identities. The survey was open to all undergraduate students over the age of 18. Participants’ ages ranged from 18 to 24 ( M = 19.00, SD = 1.14). Twentyeight percent of participants identified with at least one SM identity (n = 58) and 73% did not identify with an SM identity (n = 153). However, TABLE 1 Gender and Sexuality Demographics
Note. The total does not sum to 100% because participants were allowed to select more than
only 23.7% of the sample reported being attracted to the same gender (n = 50). These numbers were different because not all SM identifying people are attracted to their same gender (e.g., asexual and aromantic individuals may not experience any attraction or they may identify as heterosexual). Additional information on participants’ sexualities and gender identities can be found in Table 1. Participants who reported an SM identity without reporting samegender attraction were excluded from analyses using the Lesbian, Gay, and Bisexual Identity Scale. Sixty percent of SM participants were either active or somewhat active in the GSA (n = 35) and 40% of SM participants were not active in the GSA (n = 23). The sample consisted of 64.0% White (n = 135), 24.2% Asian American (n = 51), 18.5% Hispanic or Latinx (n = 39), 5.7% Black or African American ( n = 12), 3.8% Native Hawaiian or Pacific Islander (n = 8), 2.8% Middle Eastern (n = 6), 2.4% American Indian or Alaskan Native ( n = 5), and 1% did not respond (n = 2). Seventyone percent of participants identified as Christian, with a large variety in denominational affiliation. Additional religious demographics can be found in Table 2.
2 Religious Demographics
Measures
Counseling Center Assessment of Psychological Symptoms-34
The Counseling Center Assessment of Psychological symptoms 34 (CCAPS 34) is a 34 item survey that assesses mental health (Center for Collegiate Mental Health, 2019; Youn et al., 2015). It has seven subscales, (a) Depression, (b) Generalized Anxiety, (c) Social Anxiety, (d) Academic Distress, (e) Eating Concerns, (f) Hostility, and (g) Alcohol Use, and an overall psychological distress index. Previous research suggests the CCAPS34 has moderately high internal consistency (Cronbach’s alpha coefficients ranging from .76–.89 per subscale), high testretest reliability (r = .79–.87 for 1week testretest and r = .74–.86 for 2week testretest), and high validity when compared to previously validated measures of psychological distress (Correlations ranged from r = .52 to r = .78; Locke et al., 2012). The current study’s Cronbach’s alpha coefficients ranged from .69 to .90.
Duke University Religiosity Index
The Duke University Religiosity Index (DUREL) is a 5item survey that assesses religious attendance, private religious activity, and intrinsic religiosity (Koenig & Büssing, 2010). The first two dimensions, religious attendance and private religious activity, are single items scored on a 6point scale ranging from “More than once a week” to “Never” (e.g., “How often do you attend church or other religious meetings?”). The third dimension, intrinsic religiosity, is made up of three items scored on a 5point scale ranging from “Definitely true of me” to “Definitely not true” (e.g., “My religious beliefs are what really lie behind my whole approach to life”). Previous research suggests that the third dimension has high internal consistency (Cronbach’s alpha between .78 and .91; Storch, Roberti, et al., 2004), high twoweek testretest reliability (intraclass correlation coefficient of .91; Storch, Strawser, et al., 2004), and has been validated against other established measures of religiosity (r’s = .71–.85; Storch, Roberti, et al., 2004). The current sample’s internal consistency was .91. According to the recommendation of the authors, we examined each subscale separately rather than combining them into a single scale.
Lesbian, Gay, and Bisexual Identity Scale
The Lesbian, Gay, and Bisexual Identity Scale (LGBIS) is a 27item survey designed to measure identityrelated constructs among lesbian, gay, and bisexual people (Mohr & Kendra, 2011). Participants score each item on a 6point scale ranging from “disagree strongly” to “agree strongly.” We chose to adjust the wording of some items in order to increase the inclusivity of the scale. The changes include changing: “samesex” to “samegender,” “romantic relationships” to “romantic relationships TABLE
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and/or attractions,” and “LGB” to “LGBTQ+.” There are eight subscales: (a) Acceptance Concerns (e.g., “I often wonder whether others judge me for my sexual orientation”), (b) Concealment Motivation (e.g., “I prefer to keep my samegender romantic relationships and/ or attractions rather private”), (c) Identity Uncertainty (e.g., “I’m not totally sure what my sexual orientation is”), (d) Internalized Homonegativity (e.g., “If it were possible, I would choose to be straight”), (e) Difficult Process (e.g., “Admitting to myself that I’m an LGBTQ+ person has been a very painful process”), (f) Identity Superiority (e.g., “I look down on heterosexuals”), (g) Identity Affirmation (e.g., “I am glad to be an LGBTQ+ person”), and (h) Identity Centrality (e.g., “My sexual orientation is a central part of my identity”). Previous research suggests that the LGBIS has moderate to high internal consistency (Cronbach’s alpha estimates between .72 to .94) and testretest reliability in a 6week period (correlation coefficients for subscales ranged from .70 to .92; Mohr & Kendra, 2011). The current sample’s Cronbach’s alphas ranged from .79 to .91. The LGBIS was only administered to students who reported being attracted to people of the same gender.
Religious Incongruence Scale
This scale was designed to measure religious incongruence within lesbian, gay, and bisexual individuals (Wolff et al., 2016). It was developed to be administered alongside the LGBIS. It consists of two items (“I’ll never be fully accepted by God if I’m in a samegender relationship,” and “I can’t be true to my faith and be in a samegender relationship at the same time”). The Religious Incongruence scale had moderate interitem correlation (r = .57) and acceptable internal consistency (Cronbach’s alpha = .72; Wolff et al., 2016). The current sample’s Cronbach’s alpha was .65.
Suicidal Behavior Questionnaire-Revised
The Suicidal Behavior QuestionaireRevised (SBQR) is a 4item survey that measures the lifetime prevalence of suicidal attitudes, ideation, and previous as well as the possibility of future suicide attempts (Osman et al., 2001). Each item is scored on a 5, 6, or 7point scale with overall scores ranging from 0–18. In nonclinical high school and college samples, the authors proposed a score of 7 or higher as a cutoff point (Osman et al., 2001). Previous studies reported high internal consistency (Cronbach’s alpha = .97, Osman et al., 2001). The current study’s Cronbach’s alpha was .85.
Results
Analytic Procedures
We used the outlier labeling rule to identify outliers (Hoaglin, 1986). The only scale with outliers was the
substance and alcohol abuse scale. This scale was abnormally distributed and had 23 outliers. We ran the analyses with and without outliers. The statistical significance of the following results did not differ with or without outliers. Our results were significant both with and without outliers, so we present the results with the full sample included.
Descriptive statistics for each of the scales can be found in Table 3. Due to the abnormal distribution of some of our scales, we deviated from our OSF preregistration data analysis plan by using nonparametric alternatives.
Hypothesis 1
A between subjects t test found that psychological distress scores of SM students (M = 1.65, SD = 0.63) were significantly higher than heterosexual students ( M = 1.20, SD = 0.69; t = 4.27, df = 209, p < .001, d = 0.66). Additionally, a MannWhitneyWilcoxon U test found that suicidality scores of SM students
TABLE 3
Descriptive
Statistics of Study Variables
Note. Possible scores for psychological distress, depression, generalized anxiety, social anxiety, academic distress, eating concerns, hostility, and alcohol and drug abuse range from 0–4. Possible scores for suicidality range from 0–18. Possible scores for intrinsic religiosity range from 3–18. Possible scores for religious attendance and private religious practice range from 1–6. Possible scores for acceptance concerns, concealment motivation, identity uncertainty, internalized homonegativity, difficult process, identity superiority, identity affirmation, identity centrality, and religious incongruence range from 1–6.
( M Rank = 134.04) were significantly higher than heterosexual students ( M Rank = 92.92; Z = 4.50, p < .001, ρ = .31). These results support our hypothesis that SM students would report higher levels of psychological distress and suicidality than heterosexual students. As exploratory analyses, we ran a MANOVA and MannWhitneyWilcoxon U tests to determine whether scores on each of the psychological symptom (CCAP34) subscales differed between SM students and heterosexual students. The main effect of the MANOVA was statistically significant (F(4,206) = 4.97, p < .001). The betweensubjects effect was significant on depression (F(1,209) = 10.68, p < .001), (F(1,209) = 18.17, p < .001), and social anxiety (F(1,209) = 6.33, p =.01). There was not a significant effect for academic distress (F(1,209) = 1.45, p = .23).
MannWhitneyWilcoxon U tests found that the score rank difference between SM and heterosexual students on hostility (31.95, Z = 3.44, p < .001, ρ = .24) and substance and alcohol abuse (17.39, Z = 2.04, p = .04, ρ = .14) were significant, but differences on eating concerns (14.21, Z = 1.53, p = .13, ρ = .11) were not significant.
Hypothesis 2
Contrary to our second hypothesis, a MannWhitneyWilcoxon U test found that students who experience samegender attraction and are involved in the GSA (M Rank = 23.72) and students who experience samegender attraction and are not involved in the GSA (M Rank = 28.67) did not significantly differ on difficulty accepting their sexuality (Z = 1.16, p = .25, ρ = .17). An additional MannWhitneyWilcoxon U test found that students who experience samegender attraction and are involved in the GSA (M Rank = 25.88) and students who experience samegender attraction and are not involved in the GSA (M Rank = 24.83) did not significantly differ on incongruence between their religious beliefs and their sexuality (Z = 0.26, p = .80, ρ = .04). These results do not support our hypothesis that students who experience samegender attraction and are involved in the GSA would report having less difficulty accepting their sexuality and would report lower levels of incongruence between their religious beliefs and their sexuality than students who experience samegender attraction and are not involved in the GSA.
Hypothesis 3
To test our third hypothesis, we used two hierarchical regression analyses to examine whether intrinsic religiosity was predictive of lower levels of psychological distress and suicidality, respectively, and whether each of these relationships was moderated by SM status. In step one of the psychological distress model, we entered intrinsic
religiosity and SM status. Intrinsic religiosity (β = .06, p = .42) did not significantly predict psychological distress, but SM status (β = .27, p < .001) did significantly aid in the prediction of psychological distress. The overall model was significant (F[2,208] = 9.42, p < .001, R² = .08). When the interaction term was included in the second step, the overall model remained statistically significant (F[3,207] = 6.57, p < .001, R² = .09). However, the .01 change in R² values was not significant (F[1,207] = 0.89, p = .35) and the interaction term was not significant (β = .07, p = .35). This lack of interaction between intrinsic religiosity and SM status suggests that SM status does not moderate a relationship between intrinsic religiosity and psychological distress.
In step one of the suicidality model, we entered intrinsic religiosity and SM status. SM status (β = .32, p < .001) significantly aided in prediction, but intrinsic religiosity did not (β = .13, p = .13). The overall model was significant (F[2,203] = 15.61, p < .001, R² = .13). When the interaction term was included in the second step, the overall model remained statistically significant ( F [3,202] = 10.37, p < .001, R ² = .13). However, the < .001 change in R² values was not significant (F[1,202] = 0.04, p = .83) and the interaction term was not significant (β = .01, p = .83). This lack of interaction between intrinsic religiosity and SM status suggests that SM status does not moderate the relationship between intrinsic religiosity and suicidality. These two moderation analyses do not support our hypothesis that the relationship between intrinsic religiosity and wellbeing would be weaker for SM students than heterosexual students.
Hypothesis 4
For our final hypothesis, rho coefficients were used to analyze the relationship between intrinsic religiosity and LGBTQ+ identityspecific concerns among only those participants who reported samegender attraction. Intrinsic religiosity was not significantly related to any of the LGBIS scales. This does not support our hypothesis that intrinsic religiosity would be correlated with higher levels of LGBTQ+ identityspecific concerns, such as internalized homonegativity, for students who report samegender attraction. Additionally, two preregistered exploratory rho coefficients were used to analyze the relationship between LGBTQ+ identityspecific concerns and religious attendance and private religious practice. Religious attendance was significantly related with internalized homonegativity (ρ = .31, p = .02) and Identity Superiority scores (ρ = .36, p = .005). Private religious practice was significantly related with Identity Superiority scores (ρ = .28, p = .03).
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Discussion
The results supported our first hypothesis, that SM students would report higher levels of psychological distress and suicidality than their heterosexual counterparts. Additionally, exploratory analyses found that SM students reported higher levels on each of the CCAP subscales except for Academic Distress. These findings are consistent with the minority stress model (Meyer, 2013). Our results are also consistent with previous studies indicating that SM students, especially those on religious campuses, are at risk for psychological distress (HeidenRootes et al., 2018; Klundt et al., 2021). This speaks to the demand for increased mental health support for LGBTQ+ students.
The results did not support our second hypothesis, that students who reported samegender attraction and are involved in the university GSA would report having less difficulty accepting their sexuality and lower levels of incongruence between their religious beliefs and their sexuality than students who reported samegender attraction and are not involved in the university GSA. The inconsistency between this result and previous research may be because Wolff et al. (2016) compared students across a variety of nonaffirming religious universities, some of which did not allow the formation of GSAs. They theorized that universities that permitted GSAs were more accepting of SMs, in turn limiting the amount of marginalization faced by SM students. Therefore, the existence of a GSA on campus may have more influence than actual participation in the GSA. Additionally, students not involved in the GSA may experience social support from other communities outside of the GSA.
The results did not support our third hypothesis, that intrinsic religiosity would be predictive of lower levels of psychological distress and suicidality for both SM and heterosexual students, but the relationship would be weaker for SM students than heterosexual students. Although intrinsic religiosity had a somewhat weak relationship with psychological distress and suicidality, intrinsic religiosity was not predictive of lower levels of suicidality or psychological distress when entered in the regression model with SM status. This suggests that intrinsic religiosity is a weak protective factor for both SM and nonSM students. This contradicts the findings of Klundt et al. (2021), who found that religiosity was a stronger positive influence for nonSM students than SM students. This contradiction could be due to differences in our samples, such as differences in religious affiliation. However, the results of our study are promising as they indicate that intrinsic religiosity may be equally protective for both SM and nonSM students. The results did not support our final hypothesis, that intrinsic religiosity would
be predictive of higher levels of LGBTQ+ concerns, such as internalized homonegativity, for students who reported samegender attraction. However, exploratory analyses found that religious attendance was associated with more internalized homonegativity and less identity superiority. This is in line with previous research, which indicates that SMs who frequently attend church experience more negative feelings about their samegender attraction (Meanley et al., 2016). This is likely due to repeated exposure to antiLGBTQ+ sentiments in religious spaces.
Implications
The current study has many practical implications. This study highlights the complex relationship between religiosity, mental health, and identity acceptance for SM individuals. Although religious attendance was correlated with internalized homonegativity, intrinsic religiosity was found to be a protective factor for suicidality and psychological distress for both SM and heterosexual populations. This highlights the importance of offering affirming religious spaces for SM individuals. SM individuals are at an increased risk of suicidality (Plöderl & Tremblay, 2015), and it is important for SM individuals to be welcome in religious spaces that may provide them support.
Additionally, this study explores the need for increased psychological support for SM students at religious universities. SM students on average reported significantly higher rates of psychological distress, suicidality, depression, anxiety, and a multitude of other negative psychological symptoms. SM students could benefit from targeted mental health resources. Although this is true on all college and university campuses, it is especially important at religious institutions where SM students are at a higher risk of internalized homophobia and psychological distress (HeidenRootes et al., 2018; Klundt et al., 2021).
The current study has several limitations. Data were collected at a single university, limiting the generalizability of the findings. The sample lacked gender diversity, with 68.2% of the sample identifying as cisgender women, 27.5% of the sample identifying as cisgender men, and only 3.7% of the sample identifying as nonbinary or gender questioning. Although this study made an effort to include transgender and nonbinary individuals, a large majority of the sample identified as cisgender. Additionally, the data were selfreported at one timepoint, limiting our ability to make claims regarding causality or directionality.
Future research should explore SM and heterosexual individuals at a large variety of religious universities. It may be beneficial to study different institutional profiles of religiosity, LGBTQ+ acceptance, and conservatism to
Christy, Rouse, and Krumrei-Mancuso | LGBTQ+
contrast university atmospheres. Additionally, future research should explore the impact of intersectional identities, specifically at predominantly White and religiously affiliated institutions.
Despite the limitations of the current study, it contributes to the growing body of literature pertaining to SM students at religious universities. More specifically, it broadens the generalizability of previous studies, specifically Klundt et al. (2021). The study performed by Klundt et al. (2021) collected data from a religious university with an incredibly unique culture, extreme religious homogeneity, and little racial diversity. The similarities between the results of that study and the current study, especially regarding religiosity as a protective factor for suicidality for both heterosexual and SM students, despite differences in campus climates, suggest that this may be generalizable to a larger population. This research may be utilized to better inform academic institutions, specifically religiously affiliated institutions, about the increased need for psychological and religious support for SM students.
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Author Note
Steven V. Rouse https://orcid.org/0000000210805502
Elizabeth J. KrumreiMancuso https://orcid.org/0000000161517845
Danica Christy is now at the Department of Psychology, University of Nevada, Las Vegas.
To avoid any conflict of interest in the manuscript review process, Steve Rouse (who is a coauthor of this article and the editor of the journal) did not include his name on the first two versions of this manuscript, and the Associate Editor assigned to this manuscript did not know of his involvement; this was, however, disclosed to the Managing Editor for full transparency. Rouse recused himself from decisions about the publication of the manuscript, supporting the decision of the Associate Editor. Only after the manuscript was conditionally accepted was Rouse’s inclusion fully disclosed.
Positionality Statement: Danica Christy identifies as a White, cisgender lesbian. Steve Rouse identifies as a bisexual, White, cisgender man. Elizabeth Mancuso identifies as a heterosexual, White, cisgender woman. All three authors come from a Christian background. The authors acknowledge that their perspectives are influenced by these and other aspects of their identity and life experiences.
Transparent Change: We preregistered with an intention to use independentsample t tests. At the encouragement of a reviewer, we switched to using MANOVA for our analyses. This work was financially supported by Seaver College. Correspondence concerning this article should be addressed to Danica P. Christy. Email: danica.christy@unlv.edu
Internalized Stigma and Substance Use: Does Race Matter?
Anne Ferrari* and Mikaela Burch Division of Social Sciences, Mount Saint Mary College
ABSTRACT. Substance use disorders are some of the most stigmatized disorders compared to other mental health conditions. Little research has examined selfstigma felt by adolescents (ages 15–17) and young adults (ages 18–22) diagnosed with a substance use disorder, and less research has focused on how racial identity may exacerbate stigma. Using a betweensubjects design, the present study analyzed selfstigma of 133 adolescents and young adults using the Substance Abuse SelfStigma Scale. Oneway analyses of variance demonstrated that adolescents and young adults who did not identify as White reported significantly higher levels of stigma compared to their White peers on total scale measures of stigma, F (1, 131) = 104, p < .001, η² = .44, as well as subscales of selfdevaluation, F(1, 131) = 37.9, p < .001, η² = .22, fear of enacted stigma, F(1, 131) = 88.78, p < .001, η² = .40, and stigma avoidance/ values disengagement, F(1, 131) = 101.73, p < .001, η² = .43. The findings have important implications for the psychological wellness of adolescents and young adults diagnosed with substance use disorders.
Keywords: intersection, race, substance use, adolescents, drugs, stigma
According to the 2022 National Survey on Drug Use and Health, 17.3% of individuals aged 12 and over had a substance use disorder (SUD; Substance Abuse and Mental Health Services Administration, 2023) and people selfidentifying as multiracial (35.1%) reported the highest percentage of illicit drug use followed by Black (26.7%) individuals. Youth substance use represented a significant subset of the overall substance use problem; 27.8% of young adults ages 18–25 and 8.7% of adolescents ages 12–17 were diagnosed with an SUD (Substance Abuse and Mental Health Services, 2023). In addition, recent Monitoring the Future data found that, for the first time in many years, Black or African American 12th grade students reported higher levels of alcohol, nicotine, and prescription drug use than their White and Hispanic peers (Miech et al., 2023).
A person with an SUD may be subject to many deleterious effects, including increased levels of stigma (Yang et al., 2017). Although research has found that adults with SUDs experience higher levels of stigma than individuals with other psychiatric disorders (Barry et al., 2014), less research has examined stigma in adolescents or young adults, or how multiple stigmatizing identities, such as also being a member of a racially stigmatized group, may exacerbate stigma. The present study examined whether adolescents (ages 15–17) and young adults (ages 18–21) who do not identify as White and were in treatment for substance abuse disorder experienced more selfstigma than their White peers.
Stigma
People who misuse substances may experience psychological distress or impaired quality of life (Chang
Diversity badge earned for conducting research focusing on aspects of diversity.
et al., 2022; Earnshaw, 2020) because of social stigma. Stigma can exist in many forms, including social stigma and internalized selfstigma. Public stigma refers to society’s view of a condition, such as mental illness or drug addiction, and includes devaluation and discrimination toward those diagnosed (Brohan et al., 2011). Individuals with stigmatized conditions often become aware of the public’s negative attitudes and internalize them as selfstigma (Corrigan & Rao, 2012). Borenstein (2020) defined self stigma as internalized negative attitudes and shame that people may hold regarding an aspect of their condition, including mental illness or addiction.
Numerous studies have demonstrated the persistence of both public and selfstigma toward individuals with SUDs with consistent findings demonstrating higher levels for individuals with SUDs than those with other mental or physical illness conditions (Barry et al., 2014; Livingston et al., 2012; Luoma et al., 2013; Yang et al., 2017). Abusing substances has been found to cause individuals to be perceived as criminals (Chang et al., 2022) unsuitable marriage or work partners, undeserving of employment or housing (Barry et al., 2014), having weaker personalities (Chang, et al., 2022), and more dangerous (Schomerus et al., 2010; Yang et al., 2017) than those with a mental illness. In a review of qualitative research, Hammerlund et al. (2018) found that people with SUDs reported feelings of shame, guilt, and motivation to avoid the title of “addict” or “junkie.”
Stigma has the potential to harm many aspects of an individual’s wellbeing. It can create barriers for treatment and recovery (Adams & Volkow, 2020; Lannin et al., 2016) that can include bias from health care providers (van Boekel et al., 2013), internalized hopelessness about one’s convalescence (Corrigan et al., 2010) or internalized stigma toward helpseeking (Gutierrez et al., 2020; Smith et al., 2016). Selfstigma, or internalizing negative beliefs, has been found to impact wellbeing by lowering selfesteem and selfefficacy (Crapanzano et al., 2018; da Silveira et al., 2018; Ritsher & Phelan, 2004; Rusch et al., 2006), increasing isolation (Earnshaw et al., 2013), reducing social support (Earnshaw et al., 2013), and increasing suicidal ideation (Wastler et al., 2020). When public stigma is internalized, life goals may become more difficult to achieve, including employment (Sum et al., 2021), independent living, and meaningful relationships (Corrigan & Wassel, 2008; Earnshaw et al., 2013).
Although less research is devoted toward adolescents’ and young adults’ experiences of stigma, Adlaf et al. (2009) found that more than half of adolescents (7th–12th grade) reported that they would feel ashamed if friends discovered that someone in their family used
substances. In a study of young people (ages 18–25) with SUDs, Vatanasin and Dallas (2022) found that most participants (79%) reported a moderate amount of selfstigma with negative feelings and aimlessness. Similarly, Blyth et al. (2023) reported that 75% of participants ages 12–19 used stigmatizing language, such as “addict,” when describing their own or another person’s substance use. Adolescents and young adults are greatly impacted by awareness of public stigma, as the role of others is critical in the development of their own identities (Harter, 2012). Identity formation is a normal developmental milestone in adolescence, one that is shaped by social and cultural influences (Erikson, 1968). Identity formation is influenced not only by what the adolescent or young person believes themselves to be, but also what they believe others see them to be (Trieber & Booysen, 2021). Thus, many adolescents and young adults who struggle with substance use may internalize the negative stigma held by the public into their identities. This is even more concerning for adolescents and young adults who identify with more than one societally stigmatized group (Gibbons et al., 2010).
Intersection of Race With Stigma
Individuals with an SUD who are also members of other stigmatized groups, such as people of color, may face compounded or intersecting forms of stigma, as analyzed through an intersectional framework (Crenshaw, 1989; Earnshaw, 2020; Gary, 2005). The individual may feel the public’s stigma toward them for both identities: being a person who misuses substances and being nonWhite. Research has consistently shown that people of color experience public stigma in the form of discrimination leading to health, social, emotional, and economic disparities (Amaro et al., 2021; Centers for Disease Control and Prevention, 2023; Chen & Mallory, 2021; Macedo et al., 2019; Rivera, 2014). The intersection of race and ethnicity has also been demonstrated as a contributing factor toward stigma against individuals with SUDs. Kulesza et al. (2016) found that participants were more likely to associate Latinx individuals who inject drugs with deserving punishment rather than treatment, than they were for White individuals with an SUD. Similarly, Curry and CorralCamacho (2008) analyzed prison sentences for drugrelated crimes in Texas and found the probability of receiving prison time was greater for African American men than for White men. Zemore et al. (2009 reported that Hispanic individuals with SUDs endorsed greater levels of selfstigma than White individuals, and people of color held more stigmatizing views of former alcoholics than White individuals (Smith et al., 2010). Finally, in an examination of the effect of double stigma upon helpseeking
barriers in Black participants diagnosed with either a mental illness or addiction, Yu et al. (2022) found that racial stigma predicted helpseeking barriers through the effects of internalized stigma.
Given the increase in substance use by Black or African eighth graders, as demonstrated by the most recent Monitoring the Future research (Miech et al., 2023), it is important to examine how race may intersect the experience of stigma. We hypothesized that adolescents (ages 15–17) and young adults (ages 18–22) with SUDs who do not identify as White would have higher levels of selfstigma about their substance use than their White peers with SUDs.
Method
Participants
Participants consisted of 133 adolescents and young adults between the ages of 15 and 21 (M = 16) receiving outpatient treatment at various substance use recovery centers in the Northeastern United States. Of the 133 participants, 48% did not identify as White, and 52% identified as White. Of those not identifying as White, most identified as Black (51%) with Latinx (24%), Indian (3%), AfroCaribbean (6%), and mixed (16%) comprising the remainder. Fiftyfour percent of the participants identified as male and 46% as female. No participants identified as nonbinary.
Materials
Participants completed two scales. First, they completed a short demographic form, which asked participants to identify their race, age, and gender. Participants were provided a blank line to record their race, and were offered a second forced choice question, namely, whether they identified as White. Both age and gender were queried using open format questions. In addition to the short demographic form, the Substance Abuse Self Stigma Scale (SASSS) was used to measure the participants’ levels of selfstigma. The scale, developed by Luoma et al. (2013), is a selfreport survey that was designed to measure selfstigma in individuals who are misusing substances. The SASSS consists of three subsections with 8 items in Section 1 measuring selfdevaluation, 9 items in Section 2 measuring participants’ fear of enacted stigma, and 23 items in Section 3 measuring stigma avoidance and values disengagement (Luoma et al., 2013). Higher scores indicate greater levels of stigma. In the SASSS, ten items are reverse coded. Examples of items from Sections 1, 2, and 3 respectively are: “I have the thought that I can’t be trusted,” “a job interviewer wouldn’t hire me if I mentioned my substance history in a job interview,” and, “I avoid doing things where I would be blamed if it didn’t work out.” Participants were asked
to rate how much they agreed with the statement based upon a 5point scale, from 1 (never or almost never) to 5 (very often; Luoma et al., 2013). Luoma et al. (2013) reported an overall SASSS Cronbach alpha of .86. The present study found a Cronbach alpha of .83 for the overall SASSS scale.
Procedure
Data collection commenced in the fall semester of 2020 and continued until the fall semester of 2022. Substance use counseling agencies in the northeastern part of the Unites States that served adolescents and young people were solicited for data collection through contact with directors. Those that agreed to allow us to interview their clients did not have an Institutional Review Board, thus approval was obtained through the Institutional Review Board of the researchers’ institution, Mount Saint Mary College. Prior to the start of the study, participants were informed of the procedure, possible implications, and detrimental effects of the study, and informed consent was given. Participants were reminded that their participation was voluntary, they could discontinue the study at any time, for any reason, and that their responses would be anonymous. For adolescents under the age of 18, guardian informed consent as well as participant assent, was obtained. Data were collected via pen and paper and consisted of a demographic survey and the SASSS. Upon completion of the data collection, participants were debriefed inperson and presented with a 15minute Google Slides presentation about public figures who struggled with substance use issues and were able to overcome them. Chosen public figures for the presentation consisted of equal numbers of Black, White, and Hispanic individuals. At the end of the presentation, participants were encouraged to voice any additional thoughts or concerns about the present research.
Results
All 133 of the participants’ responses were coded into Statistical Product and Service Solutions (SPSS) version 16.0 for analysis and interpretation of the data. The independent variable consisted of participants’ identification as White or not White. The dependent variables consisted of the scores on the SASSS, which included total overall score and scores for each subscale of the instrument (i.e., Subscales 1= representing selfdevaluation, Subscale 2 = fear of enacted stigma, and Subscale 3 = stigma avoidance and values disengagement) for a total of 4 dependent variables. Oneway ANOVAs were performed for each dependent variable, resulting in four oneway ANOVAs in this betweensubjects design.
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The means and standard deviations for the overall SASSS scores as well as for the three subscales can be found by race (White and not White) in Table 1. Mean scores on the total scale as well as on each subscale were higher for participants not identifying as White than White participants, indicating higher levels of stigma. Participants not identifying as White reported a mean of 138.9 (SD = 24.8) on the total scale, whereas White participants’ mean was 98.6 (SD = 20.4). ANOVAs were performed to test for significant differences between total and subscale score means.
A oneway ANOVA on the dependent variable of Subscale 1 of the SASSS found a significant effect for race, F(1,131) = 37.9, p < .001, η² = .22 , with participants who did not identify as White scoring significantly higher on selfdevaluation than White participants. Because higher scores indicate greater stigma, participants not identifying as White reported greater stigma than White participants on selfdevaluation.
A oneway ANOVA on the dependent variable of Subscale 2 of the SASSS measuring fear of enacted stigma found a significant effect for race, F(1, 131) = 88.78, p < .001, η² = .40, with participants not identifying as White scoring significantly higher than White participants. Because higher scores indicate greater levels of stigma, participants not identifying as White reported greater levels of fear of enacted stigma than White participants.
A oneway ANOVA on the dependent variable of Subscale 3 of the SASSS measuring stigma avoidance/ values disengagement found a significant effect for race, F(1, 131) = 101.73, p < .001, η²= .43, with participants who did not identify as White scoring significantly higher than White participants. Because higher scores indicate greater levels of stigma, participants not identifying as White reported greater stigma avoidance and values disengagement than White participants.
A oneway ANOVA on the total SASSS scale found a significant effect for race, F(1, 131) = 104, p < .001, η² = .44, with participants who did not identify as White scoring significantly higher than White participants, indicating greater overall stigma being reported by those not identifying as White.
Discussion
Our hypothesis that adolescents (ages 15–17) and young people (ages 18–22) with SUDs who did not identify as White would report higher levels of selfstigma regarding their substance use than their White peers, was supported. Selfstigma of substance use was greater on all three subscales (i.e., selfdevaluation, fear of enacted stigma, stigma avoidance and values disengagement), as well as the entire scale, in adolescents and young people
who did not identify as White than it was for those who identified as White.
The present research has important health implications for individuals seeking care for SUDs. Chang et al. (2022) found that selfstigma levels remained unchanged over substance misuse treatment progression, most likely because the stigma was not addressed. For SUD clients identifying with historically marginalized groups, addressing stigma may take on even greater importance. Awareness of how multiple stigmas may influence adolescents and young people with SUDs can help create educational tools that explicitly reject racial stereotypes and provide appropriate racial role models that encourage greater access to psychological wellness.
Future research may wish to examine how stigma may impact treatment initiation and completion, especially for individuals who may possess stigma in compounded or intersecting forms. Although research examining the effect of stigma upon treatment seeking has found mixed results (Hammarlund et al., 2018), findings surrounding stigma from more than one source have been clearer. Multiple stigmas were found to have helpseeking implications, with adults (Acevedo et al., 2012; da Silveira et al., 2018; Hammarlund et al., 2018; Saloner & LeCook, 2013; Yu et al., 2022) and adolescents (Cumming et al., 2011) demonstrating that those who possess stigma from multiple sources are less likely to seek treatment for behavioral health disorders than those without.
For the adolescent at a crucial stage of identity development, intersecting multiple dimensions of the self may become a more challenging task for those who have an SUD. Understanding one’s identity both as a person who misused substances and a person of color is not an easy feat. Assisting adolescents and young people in overcoming internalized stigma can contribute to the formation of a strong selfidentity necessary for future psychological wellness. Treiber and Booysen (2021) recommended that treatment of adolescents and young adults focus on deconstructing the “druggie” persona
TABLE 1
Means, Standard Deviations, and One-Way ANOVA Results by Race on SASSS Subsection and
Note aNIW = those not identifying as White. * p < .001
Scale Scores
as it has negative implications for overall wellbeing, potentially hampering the reconstruction of full identities for successful adulthood. A strong sense of identity empowers the adolescent for future adult success as an autonomous, resilient individual (Stephenson, 2023).
The present study had several limitations. First, our sample size was low; adolescents tend to be a challenging sample group due to the necessity of securing parental consent. Although many potential participants gave full assent, retrieval of guardian consent forms was an obstacle thereby reducing our overall dataset. The study also spanned a time when the Black Lives Matter movement was in full force, thus potentially exacerbating feelings of racial stigma in participants potentially creating a history threat to external validity. Future research should seek to replicate our findings with larger sample sizes.
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Author Note
Anne Ferrari
https://orcid.org/0000000214759697
Positionality Statement: Anne Ferrari identifies as a cisgender White female who is nondisabled. Mikaela Burch identifies as a heterosexual, cisgender African American and White woman. She is disabled. All authors acknowledge that their perspectives are influenced by their positions within these dimensions of identity. Correspondence concerning this article should be addressed to Anne Ferrari, Mount Saint Mary College, 330 Powell Ave, Newburgh, NY 12550. Email: Anne.Ferrari@msmc.edu
The Ideal Affect of Filipinx Americans
Audrienne Casidsid, William Peruel, Jonna-Lynn Alonso, and Christie Napa Scollon*
Department of Psychology, Western Washington University
ABSTRACT. Previous studies have found differences in ideal affect between East Asian populations and European American populations. However, no study has looked at the specific affective preferences of Filipinx Americans. Thus, the present study compared the ideal affect of Filipinx Americans and European Americans. Analyses revealed nearly identical ideal affect profiles between the Filipinx American and European American samples, p = .88, η2p = .00. Additionally, high arousal positive states were equally preferred to low arousal positive states in both the Filipinx American sample (p = .57, Cohen’s d = 0.06) and the European American sample (p = .83, Cohen’s d = 0.03). The results are consistent with the notion that religious influences shape ideal affect, whereas collectivism in this case did not (cf. Tsai et al., 2006). The results highlight the heterogeneity among collectivist Asian groups and underscore the need to examine the intersectionality of cultural influences on affect. More psychological research on Filipinx people is needed to unpack the experience of this unique culture.
Keywords: Filipinx American, ideal affect, HAP, LAP
ABSTRACTO
Estudios anteriores han encontrado diferencias en el afecto ideal entre las poblaciones del este de Asia y las poblaciones EuropeoAmericanas. Sin embargo, ningún estudio ha analizado las preferencias afectivas específicas de los Estadounidenses de origen Filipinx. Por lo tanto, el presente estudio comparó el afecto ideal de los Estadounidenses de origen Filipinx y los Estadounidenses de origen Europeo. Los análisis revelaron perfiles de afecto ideal casi idénticos entre las muestras Filipinxs Americanas y EuropeoAmericanas, p = .88, η2p = .00. Además, los estados positivos de alta excitación fueron igualmente preferidos a los estados positivos de baja excitación tanto en la muestra FilipinxAmericana ( p = .57, d de Cohen = 0.06) como en la muestra EuropeoAmericana (p = .83, d de Cohen = 0.03). Los Resultados son consistentes con la noción de que las influencias religiosas dan forma al afecto ideal, mientras que el colectivismo en este caso no lo hizo (cf. Tsai et al., 2006). Los resultados ponen de relieve la heterogeneidad entre los grupos colectivistas Asiáticos y subrayan la necesidad de examinar la interseccionalidad de las influencias culturales sobre el afecto. Se necesita más investigación psicológica sobre las personas Filipinx para desentrañar la experiencia de esta cultura única.
Diversity badge earned for conducting research focusing on aspects of diversity.
Casidsid, Peruel, Alonso, and Scollon | Filipinx
From pride to sorrow to anger to elation, many would argue that emotional experiences enrich the human experience. However, there are considerable cultural differences in the extent to which people would like to feel specific emotions. For instance, previous studies have shown that more individualistic cultures tend to value emotional experiences around enthusiasm and excitation, but collectivistic cultures tend to value feelings of calmness or relaxation much more than enthusiasm (Tsai, 2007). Differences in how much people value specific emotions can account, at least in part, for some of the differences in emotional experience.
Affect Valuation Theory
Psychologists and anthropologists have historically treated cultural differences in affect as a single construct (Mesquita et al., 1997; Wierzbicka, 1994). However, more current research on culture and emotions has suggested that people of different cultural backgrounds have different preferences for what emotions they want to feel. For instance, Eid and Diener (2001) found that individualistic and collectivistic cultures differed in norms regarding emotional experiences. Similarly, Tamir et al. (2016) found that people desired to feel different emotions based on how much those emotions aligned with their own values, which varied throughout different cultural regions.
Tsai’s affect valuation theory presents the idea of culture affecting emotional preferences by distinguishing between actual affect, the emotions people typically experience whether they like them or not, and ideal affect, the emotions people want to experience. Although ideal and actual affect may influence or reinforce one another, affect valuation theory predicts that they are two distinct constructs, along with the notion that culture influences ideal affect more than actual affect (Tsai et al., 2006). In other words, culture affects what emotions people would like to ideally feel.
Affect valuation theory breaks down commonly felt emotions into eight suboctants, differing across dimensions of valence and arousal. For example, the High Arousal Positive (HAP) octant includes feelings of excitement, enthusiasm, and strength. On the other end of the arousal dimension is the Low Arousal Positive (LAP) octant, which includes feelings of serenity and calm. The octants of HAP and LAP have received the most attention in culture and emotion literature because they have shown the most distinct and reliable cultural differences (e.g., Tsai et al., 2006; Tsai et al., 2007a; Tsai et al., 2007b).
East–West Differences in Ideal Affect
Research on affect valuation theory has exclusively relied on East–West comparisons, that is comparing scores on
ideal affect among East Asians and East Asian Americans to their White American counterparts. Consistently, this body of work has shown that East Asians value LAP more than HAP, whereas White Americans tend to value HAP over LAP (Tsai et al., 2006; Tsai et al., 2007a; Tsai et al., 2007b). If culture influences affect valuation, then it is important to understand how and why. Tsai has identified two potential factors that impact affect valuation.
First, interpersonal goals shape desired emotions, according to Tsai et al. (2007c). For instance, people in individualistic cultures typically prioritize influencing others’ behaviors to meet their needs as opposed to adjusting one’s own behavior to maximize group harmony. HAP emotions, such as enthusiasm, are instrumental to achieving influencing goals. Conversely, people from collectivistic cultures prioritize harmony in their social relationships and often adjust their own behavior to meet group needs. Thus, for them, LAP states such as serenity are instrumental to adjusting goals which maximize group harmony (Tsai et al., 2007c).
Second, previous studies have found religion to underpin preferences for ideal affective states. Tsai et al. (2007b) coded classical and contemporary texts from both Western and Eastern religious philosophies for frequency of HAP and LAP words. Christian texts such as the Bible tended to promote HAP states, and Eastern texts such as the Tao de Ching and the Bhagavad Gita tended to promote LAP states (Tsai et al., 2007b).
Filipinx Americans and Ideal Affect
Past research has only compared East Asian or East Asian American respondents to European Americans in their affect valuation (e.g. Tsai, 2007; Tsai et al., 2006; Tsai et al., 2007c). The present study extends Tsai’s research on affective valuation theory to examine the affect valuation of Filipinx Americans who occupy a unique cultural space. Traditionally speaking, the Filipinx people have more collectivistic values (Fuligni & Pederson, 2002). Furthermore, the values of kapwa, interconnectedness, and familial obligation, would mark the Philippines as a textbook example of collectivism (David, 2013). As such, Filipinx people likely prioritize adjusting goals over influencing goals in their interpersonal relationships. Based on this, we might expect Filipinx people to value LAP over HAP, similar to East Asians.
On the other hand, Philippine culture has been heavily impacted by nearly four hundred years of colonization, first by Spain, then later by the United States. Due to the effects of Spanish colonization, Christian values have been interwoven within the very fabric of Philippine culture. As such, about 65% of Filipinx Americans identify themselves as Catholic (Pew
Research Center, 2012). Additionally, Jasso et al. (2003) reported Filipinx immigrants as the second largest contributor of Catholic immigrants in the United States. Based on their religious affiliation, we might expect Filipinx Americans to value HAP more than LAP, as suggested by Tsai et al. (2007b).
Consequences of Affect Valuation
Are there any real consequences of affect valuation?
Bencharit et al. (2009) examined ideal affect in the context of job interviews and found that there are practical consequences of affect valuation. In a series of studies, they examined if (a) cultural differences in ideal affect impact the way job applicants present themselves, and (b) differences in emotional expression that are consistent with ideal affect determine who gets hired. Their results showed that job applicants who express affective states that match the ideal affect of the potential employer’s culture were more likely to get hired. To put this more concretely, someone hiring for an American company tends to perceive applicants who display HAP states such as engagement or enthusiasm as more competent (Paulhus et al., 2013; Wolf et al., 2016). Mismatches in ideal affect could be one reason Asian Americans are frequently overlooked for leadership positions, and other positions, unlike their European American peers. On the other hand, someone hiring for an East Asian organization perceives applicants who display calmness and serenity—both LAP states—as being more competent.
Tsai and colleagues have similarly demonstrated that ideal affect drives monetary donations on the microlending platform Kiva (Park et al., 2020). Donors from countries that value HAP give more money to Kiva applicants who display HAP in their profile pictures, whereas donors from countries that value LAP give more money to Kiva applicants who display LAP in their profile pictures.
TABLE 1
Sample Demographics
Research on affect valuation theory can also shed some light on the activities people participate in, which can have either positive or negative impacts to health and overall life satisfaction. According to Tsai (2007), one tenet of affect valuation theory is that people will try to reduce the gap between their actual and ideal affect by participating in specific mood producing activities aligned with their ideal affect. For instance, those who ideally want to feel HAP states, such as excitement and enthusiasm, are more likely to engage in challenging physical activities or use mood enhancing drugs than someone who values LAP states (Tsai et al., 2007, as cited in Tsai, 2007). In addition, this preference for HAP states may explain higher rates of stimulant drug abuse such as cocaine in America compared to those in China (United Nations Office for Drug and Crime, 2006). Thus, further research on affect valuation theory may extend to various domains, including work policy and rehabilitation practices.
Overview and Predictions
Reflecting findings from the existing literature, we expected that, for both the European American sample and the Filipinx American sample, ideal affect would differ from actual affect, replicating Tsai et al. (2006). Specifically, we predicted that ideal positive affect (PA) would be higher than actual PA, and ideal negative affect would be lower than actual negative affect.
Replicating past research, we expected European Americans to show an overall preference for HAP over LAP, and that European Americans would prefer HAP more than Filipinx Americans. Finally, Filipinx values can be classically characterized as being more on the collectivistic side. Yet, the religious preferences produced by centuries of colonization could have a lasting impact on ideal affect. Thus, we predicted that Filipinx Americans would prefer the LAP affective state more than European Americans. Additionally, we predicted that Filipinx Americans would prefer HAP states equally to LAP states.
Method
Participants
Approval to work with human participants was obtained through the Western Washington University Institutional Review Board before recruitment of participants. One hundred eighty undergraduate students participated in the study (106 Filipinx American and 74 European American). European American students were recruited through this university’s psychology human subjects pool in exchange for course participation credit. The subject pool consisted of students taking introductory level psychology courses. The sample of
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Filipinx Americans were part of a larger study, where eligible Filipinx Americans were compensated with a $10 Amazon gift card for completion of an online survey. Recruitment for the Filipinx American sample was done via word of mouth, social media outreach, and email correspondence with administrators of local Filipinx organizations. Table 1 shows the sample characteristics. In the Filipinx American sample, 72% of respondents identified as women, 23% identified as men, and 5% identified as nonbinary or did not provide their gender. In the European American sample, 73% of respondents identified as women, 16% identified as men, and 11% identified as nonbinary or did not provide their gender. The Filipinx American sample (n = 106) was larger than the European American sample (n = 74). The Filipinx American sample was also slightly older than the European American sample, t(150) = 9.59, p < .001, possibly due to the sampling procedure for our European American group.
Measures
We utilized the Affect Valuation Index (Tsai et al., 2006). This measure included items used to assess actual and ideal affect. Responses to the Affect Valuation Index have been shown to correspond to realworld behaviors, such as the hiring of job applicants (Bencharit et al., 2019) and making monetary donations (Park et al., 2020).
To measure actual affect, participants rated a list of 25 emotion words (e.g., enthusiastic) on how much they typically felt the emotion on average, using a scale of 1 (very slightly or not at all) to 5 (extremely or all of the time). Participants were also given an identical list of 25 emotion words to assess their ideal affect. Participants rated how they ideally would like to feel each emotion
Note. HAP = High Arousal Positive Affect; PA = Positive Affect; LAP = Low Arousal Positive Affect; LA = Low Arousal; LAN = Low Arousal Negative Affect; NA = Negative Affect; HAN = High Arousal Negative Affect; HA = High Arousal. Casidsid, Peruel, Alonso, and Scollon | Filipinx American
on average, using the same scale of 1 (very slightly or not at all) to 5 (extremely or all of the time). The items, and the order of these items, remained the same for both measures. Scores on suboctants were computed for both actual and ideal affect consisting of: higharousal positive (HAP), positive (PA), lowarousal positive (LAP), low arousal (LA), lowarousal negative (LAN), negative (NA), higharousal negative (HAN), and high arousal (HA).
Table 2 shows the means and standard deviations for each ideal and actual affect suboctant from the entire study population, the Filipinx American sample, and the European American sample. Table 3 displays the reliability coefficients for each subscale and the correlations between ideal and actual affect. Scores were aggregated between each scale, then ipsatized to account for individual cultural differences. We ipsatized participants’ ideal affect scores by computing Zscores for each participant’s response to each ideal affect item using the respective participant’s ideal affect mean and standard deviation, in effect removing betweenperson variance. The same was done for each actual affect item. Some participants were not included in the total sample size, due to incomplete responses or giving uniform answers to each question. Finally, attention check questions were included in the survey, to which all participants responded correctly.
Results
Overall, the data from this study did not support our predictions of a difference between the ideal affect profiles of Filipinx Americans and European Americans. However, the data did support our prediction that Filipinx Americans would equally prefer HAP states to LAP states.
TABLE 2
Means and Standard Deviations for Ideal and Actual Affect Octants
Ideal Versus Actual Affect
We ran a series of pairwise t tests to determine if ideal affect differed from actual affect (one for each octant), as shown in Table 4. For example, we compared ideal HAP to actual HAP, and ideal LAP to actual LAP. Tsai’s Affect Valuation Theory predicts that ideal affect and actual affect will differ, and we found this to be true in 6 out of 8 octants. Participants experienced less PA, HAP, and LAP than they ideally wanted to feel, all ts (179) > 15,
TABLE 3
Internal Consistency of Subscales and Correlations
(HAP)
Positive Affect (PA) Happy, satisfied, content
Low arousal positive (LAP) Calm, at rest, relaxed, peaceful (serene)
Low arousal (LA) Quiet, still, passive
Low arousal negative (LAN) Dull, sleepy, sluggish
Negative Sad, lonely, unhappy
High arousal negative (HAN) Fearful, hostile, nervous
High arousal Aroused, surprised, astonished
Note.* p < .05. ** p < .01.
Note. HAP = High Arousal Positive Affect; PA = Positive Affect; LAP = Low Arousal Positive Affect; LA = Low Arousal; LAN = Low Arousal Negative Affect; NA = Negative Affect; HAN = High Arousal Negative Affect; HA = High Arousal.
all ps < .001, all Cohen’s ds > 0.80. Similarly, participants also experienced more negative affect, HAN, and LAN than they ideally wanted to feel, all ts (179) > 14, all ps < .001, all Cohen’s ds > 0.50. There was no significant difference between ideal low arousal and actual low arousal, t(179) = 0.94, p = .20, Cohen’s d = 0.10, nor was there a significant difference between ideal high arousal and actual high arousal, t(179) = 6.89, p = .24, Cohen’s d = 0.11.
In an effort to make a comparison to past research, we conducted an identical analysis to Tsai et al. (2006). We performed a 2 (sample: Filipinx American vs. European American) x 2 (Ideal Affect: HAP vs. LAP) repeatedmeasures analysis of covariance (ANCOVA) on Ideal Affect ratings, controlling for actual HAP and actual LAP. The analysis was conducted on the ipsatized ideal affect ratings. We were primarily interested in whether there was an Ideal Affect x Sample interaction, as Tsai reported in her study comparing European Americans and East Asians (Tsai et al., 2006). In contrast to what was found with East Asian samples, we did not find a significant Ideal Affect x Sample interaction, F(1, 176) = 0.022, p = .88, η2p = .00, meaning the ideal affect profiles of the Filipinx American participants were on average nearly identical to the European American profiles (see Table 5). To help interpret this finding, we plotted the nonipsatized means by sample and octant in Figure 1. As shown in Figure 1, Filipinx Americans and European Americans in our sample were nearly identical in their ideal affect profiles.
Lastly, using a twotailed pairedsample t test, we examined if ideal HAP and ideal LAP differed for the Filipinx Americans and European Americans separately. Results revealed that ideal HAP and ideal LAP did not differ in the Filipinx American sample, t(105) = 0.58, p = .57, Cohen’s d = 0.06, nor in the European American sample, t(73) = 0.21, p = .83, Cohen’s d = 0.03. In other words, both groups equally preferred HAP and LAP states.
Discussion
In this study, we found evidence in support of our first hypothesis, which predicted that ideal affect would differ from actual affect, replicating Tsai et al. (2006). Specifically, our analyses revealed that ideal affect differed from actual affect in 6 out of the 8 affective octants.
In our study, participants felt fewer positive emotions than they ideally wanted to feel, and felt more negative emotions than they ideally wanted to feel, similar to what was found in previous studies examining affect valuation (Tsai et al., 2006).
Ideal Affect in Filipinx American and European American Cultures
We predicted that Filipinx Americans would prefer
FIGURE1
Filipinx Ideal Affect Vs. European American Ideal Affect
Filipinx American European American
Casidsid, Peruel, Alonso, and Scollon | Filipinx American Ideal Affect
HAP states equally to LAP states, given the prevalence of Catholicism in the Filipinx American population. Filipinx values are widely considered to be collectivistic, which would theoretically lead Filipinx Americans to value LAP states over HAP states (Tsai et al., 2007c). However, we suspected that the impacts of Spanish colonialism, specifically the transmission of the Catholic religion, would lead to an equal valuing of HAP states to LAP states, because Christian cultures have been found to endorse HAP states more often (Tsai et al, 2007b). These data did support our hypothesis, yielding some support for this claim.
Furthermore, given the pervasiveness of Christian values in American culture, we predicted that European Americans would prefer HAP more than Filipinx Americans. Additionally, considering the traditionally collectivistic values found in the Filipinx culture, we suspected that Filipinx Americans would prefer LAP more than European Americans. However, our data did not support these hypotheses. Instead, Filipinx Americans and European Americans showed nearly identical ideal affective profiles. This may be because 95 out of 106 Filipinx American respondents reported growing up in a Catholic household, prompting lower valuing of LAP states.
In conclusion, our findings lend support to the idea of actual affect (the emotions actually experienced) and ideal affect (the desired emotions) being distinct constructs. However, our sample varied from past research, which suggested that a culture whose values are predominantly collectivistic would tend to prefer LAP over HAP (Tsai et al., 2006). Instead, the ideal affective profiles for our European American sample and our Filipinx American sample were nearly identical, in that both groups equally preferred LAP and HAP states. This suggests that, compared to one’s cultural values of independence versus interdependence, one’s religion may be an equally strong, if not stronger, driver of ideal affect preferences.
These results also hold many potential implications for how Filipinx Americans behave. As previously mentioned, existing research on affect valuation has demonstrated that people will act in ways that will bring them closer to their ideal emotional state, such as engaging in different types of physical activity (Tsai et al., 2007, as cited in Tsai, 2007). We found that our sample of Filipinx Americans does value HAP states, suggesting that Filipinx Americans will also prefer to engage in activities that will evoke HAP. Furthermore, the ideal affect preferences of Filipinx Americans could have employmentrelated consequences, as previous studies have suggested that job applicants who express emotions that align with employers’ ideal affect preferences are
more likely to be hired (Bencharit et al., 2019). Our finding that Filipinx Americans equally value HAP and LAP states could mean that Filipinx American employers may equally prefer candidates who express enthusiasm and other similar emotions, as well as candidates who express low arousal emotions like calmness. Similarly, Park et al. (2020) found that ideal affect preferences impact how likely people are to donate money to others, as participants in their study were likely to donate more money to individuals on a donation website when their profiles showed facial expressions that matched participants’ ideal affective state. Because Filipinx Americans appear to value both HAP and LAP states equally, they may be equally likely to donate to individuals who express HAP and LAP emotions.
The ideal affect preferences of Filipinx Americans
TABLE 4
Results of Paired-Samples t Tests Comparing Ideal Affect and Actual Affect
TABLE 5
Results of 2 (Sample: Filipinx American vs. European American) x 2 (Ideal Affect: HAP vs. LAP) Repeated-Measures ANCOVA Controlling for Actual HAP and Actual LAP
Note. HAP = High Arousal Positive Affect; LAP
may also have some practical consequences when it comes to the types of media that children from this population are shown. Tsai et al. (2007a) found that the most popular children’s books in the United States were more likely to have characters who expressed excitement, whereas characters from the most popular children’s books in Taiwan were more likely to have calm expressions. The results from our study suggest that children’s media popular among Filipinx Americans may have an equal representation of characters expressing HAP and LAP states.
Although this study was the first to examine the affective valuation of Filipinx Americans, it contains limitations that could potentially be addressed in future studies. One limitation of our study is that our analyses did not include demographic characteristics other than ethnicity, such as age or immigrant generation. By not considering these other aspects of participants’ identities, we were unable to observe potential relationships between those traits and participants’ affective experiences. This is especially pertinent based on the current study’s results, as it seems that, in our sample of Filipinx Americans, religious preference might have driven affective preferences just as much as ethnic background. To that end, we could not see how unique combinations of identities could potentially be related to different affective preferences and experiences, even within the same ethnic group. For instance, younger Filipinx Americans who are second generation immigrants may have different affective preferences to similarly aged Filipinx Americans who are first generation immigrants. Future studies can address this issue by including such demographic factors, in addition to ethnicity, in their analyses.
Another limitation was our measurement of religion. In our study, there was no indepth look into participants’ religiosity, as participants simply reported which religions they practice and which religions they were raised in. Future research on the effects of religion on affect valuation may seek to further operationalize religion by using more specific survey items that identify participants’ religious practices or identification with religious values. By doing this, we can have a stronger understanding of the relationship between religion and affect valuation.
All in all, these surprising findings illustrate the need to conduct further research on this unique yet underresearched population. In the field of affective research, future studies may explore the Filipinx American affective experience in comparison with other Asian populations, such as other Southeast Asians and East Asians, to further tease out the effects culture has on emotion on a narrower scale. Likewise, future
studies may compare the affective profile of Filipinx Americans to that of other populations impacted by Western colonization, such as Indigenous Americans. With further studies, we can add the voices and narratives of this underresearched population into the broader psychological literature, thereby improving the understanding of affect across cultures.
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Author Note
This research was conducted by three FilipinxAmericans who were born and raised in the West Coast region of the United States. We acknowledge our standpoint as members of the Filipinx diaspora who have primarily been educated within a Western epistemology. As members of our local Filipinx American communities, we have made the decision to use the term “Filipinx” instead of “Filipino" in this article based on our experiences interacting
within these communities, keeping with local norms of inclusivity. However, we acknowledge the discourse surrounding the usage of these two different terms, including the colonial background of “Filipinx,” and recognize that there are different contexts in which either term could be appropriate. As researchers and members of the diaspora, we value the usage of either term. Correspondence concerning this article should be addressed to Christie Napa Scollon. Email: christie.scollon@wwu.eduReferences
Casidsid, Peruel, Alonso, and Scollon | Filipinx American Ideal Affect
Quality Dating and Wellness Among a Religious College Student Population: A Mixed-Methods Approach
Robert R. Wright*1, Melissa Wilson1, Christian Nienstedt2, Carson Ewing3, Andres Rodriguez1, Cade Anderson1, Natalie Johnson1, and Lindsay Johnson1
1Department of Psychology, Brigham Young University–Idaho
2Department of Psychology, Alliant International University, Fresno
3Department of Educational Psychology, University of Utah
ABSTRACT. Growing concerns for loneliness, social isolation, and the health of young adults point to the importance of the dating context. This study aimed to identify and examine quality dating experience (QDE) and poor dating experience (PDE) relative to the wellbeing of religious college students identified as members of the Church of Jesus Christ of Latterday Saints, including gender differences. Focus group (n = 58) and online survey (n = 515) participants came from introductory psychology courses at a large religious institution. A mixed methods design was used to qualitatively identify quality and poor dating themes and then, using these themes, examine the dating experience using quantitative data from an online survey questionnaire. Focus group thematic analyses revealed patterns of gender similarity (e.g., compatibility, safety concerns, hyperfocus on marriage) and disparity (e.g., monetary value, date activity details) for both QDE and poor dating experience (PDE). Quantitative survey results highlighted substantial relationships between QDE, PDE, and wellness variables including mood, life satisfaction, depressive symptoms, anxiety, stress, loneliness, physical health symptoms, and perceived peer support. Interestingly, men had statistically stronger (p < .05) relationships between PDE and 3 health variables: depressive symptoms, peer support, and interpersonal conflict. This suggests that men may have more adverse health profiles than women when undergoing PDEs in a more traditional religious context. Results supported QDE and PDE as influential variables that go beyond the simple metric of dating frequency to capture a more comprehensive perspective of health among religious college students, including gender differences.
Keywords: quality dating, romantic, mixed method, religious, emerging adults
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Social relationships are an essential aspect of overall health and wellness. Perceived strong social relationships reduce mortality and extend life (HoltLunstad et al., 2010). Certain relationships, such as healthy marriages, offer enormous benefits, from adopting healthy behaviors and emotional regulation (Skoyen et al., 2013) to notable improvements in both the length and quality of life (Burleson et al., 2013; Manzoli & Villari, 2007). Moreover, social relationships with peers strongly influence health and wellness, particularly for emerging adults (Bryan et al., 2013), who frequently select future romantic partners and marital spouses from among their peers. Dating has often been used to foster good social relationships and companionship, including marriage (Bryan et al., 2013; Myers et al., 2005), especially within religious communities (Bartkowski et al., 2011). Relatedly, there is growing concern over declining marriage rates (CDC, 2023), as well as troubling trends of loneliness (U.S. Surgeon General, 2023) and social isolation related to death and disease (e.g., HoltLunstad et al., 2015). Dating and romantic involvement offer a potential remedy, particularly through positive or highquality experiences among emerging adults in religious college contexts where marriage is encouraged, and rates are generally higher (Parker & Stepler, 2017). Moreover, these contexts have substantial influence across the United States with more than 7,000 colleges and universities reporting a religious affiliation and providing education for millions of college students each year (NCES, 2023).
Despite potential disagreement regarding the definition of what exact interactions constitute a date, defining a quality date or a dating experience with high worth or value poses even more challenges. Indeed, the expectations of dating exert a strong influence on one’s assessment of dating experiences, particularly whether the expectations were met or not (e.g., Vannier & O’Sullivan, 2017, 2018). Moreover, this is impacted further by social factors such as gender (e.g., Paynter & Leaper, 2016), as well as religion (e.g., Langlais & Schwanz, 2017), making it imperative to consider these contextual factors by first taking a qualitative approach to define quality dating within a religious context (Charmaz, 1995). Furthermore, because social relationships are positively tied to many facets of health and wellbeing (cf., Newman & Roberts, 2013), quality dating experiences (QDEs) among religious adult college students are likely to show similar relationships with a wide range of wellness variables (e.g., physical, behavioral, mental). Despite these implications, few, if any, studies have investigated general QDEs as they relate to health and wellness within a religious context where marriage is often emphasized as a primary purpose of
dating, such as among members of the Church of Jesus Christ of Latterday Saints.
Quality Dating and Expectations
Dating is traditionally a Western societal practice to facilitate the identification of marriage partners (e.g., Huston et al., 1981; Myers et al., 2005), but this has been shaped over time by sociocultural values into a complex custom filled with expectations and beliefs (e.g., Buss at el., 2001). As part of this complexity, research has suggested that the average young adult holds strong dating expectations for an ideal type of relationship (Banker et al., 2010) and believes they should be looking for this kind of relationship in dating experiences with a potential partner. However, higher unrealistic expectations lead to more discontent and less devotion in relationships and are associated with lower relationship satisfaction, investment, and commitment (Vannier & O’Sullivan, 2017, 2018). Moreover, many express the belief and desire to meet a romantic partner organically, but they most often resort to nonorganic methods (e.g., online dating sites), often creating disappointment and dissatisfaction (Parker & Stepler, 2017; Portolan & McAlister, 2022). This is likely compounded further by the heavy emphasis many place on effective interpersonal communication in dating (Cohen, 2016) and the increased use of electronics and online dating forums in the wake of the COVID19 pandemic restrictions (Vogels & McClain, 2023; Wright et al., 2022). Furthermore, other studies have suggested substantial gender differences in dating expectations from women holding traditional standards that men should pay for and initiate dates (Paynter & Leaper, 2016) to men focusing more on physical and sexual aspects of dating than women (Bartoli & Clark, 2006; Buss et al., 2001; Ha et al., 2012).
Similarity theories offer some insight into understanding the complexity of how individuals endeavor to meet these dating expectations and have quality experiences. For example, the matching phenomenon states that, when selecting a potential mate, individuals choose those who “match” with them in level of desirability (Feingold, 1988; Tidwell et al., 2013). This applies to objective physical characteristics such as appearance and weight (Schafer & Keith, 1990) and attitudes and beliefs (e.g., Cramer et al., 1996; Regan, 1998), emphasizing the importance of perceived similarity over actual similarity (Reid et al., 2013; Tidwell et al., 2013). Indeed, Michinov and Monteil (2002) found that perceived similarities have a clear positive relationship to attraction, but dissimilarities have a more substantial negative impact. For instance, couples who participate in religious activities together have greater romantic relationship quality ( Langlais & Schwanz, 2017) and those with
higher religious attendance hold more traditional dating standards (Paynter & Leaper, 2016). Furthermore, in a study among religiously active college students, Wright et al. (2007) found support for the similarity principle in verbal communication, such that women were more attracted to men who verbally communicated similarly to them. Findings such as these suggest that religious context and beliefs should be considered alongside dating experience quality.
Religious Contextual Influence
Religious involvement can strongly influence selfperceptions, peer networks, and social behavior, which are directly related to dating (Smith, 2005). Moreover, among certain religious sects (e.g., conservative Protestants, Catholics), dating is a topic of central importance to religious observances such as marriage. Indeed, although not fully representative of all religious affiliations, Christian faiths embody nearly 66% of college graduates (Pew Research Center, 2023) and actively encourage marriage among their young adults through doctrine, culture, and practice. Many Christian young adults in college report feeling a cultural pressure to date for purposes of marriage (George, 2019). Moreover, those who are actively religious often approach dating more traditionally (e.g., marriage) whereas those who are not religiously active may date with other expectations (e.g., casual sex; Burdette et al., 2009; Weitbrecht & Whitton, 2020; Whitehead & Popenoe, 2000). This suggests that dating quality may mean something different to those who are actively religious due to the influence of religious beliefs and context.
For instance, among the Christian sect of the Church of Jesus Christ of Latterday Saints (previously known as Mormon, LDS), traditional gender roles (e.g., men pay for dates; Lever et al., 2015) and values (e.g., abstinence from premarital sex, marriage as the goal of dating to establish families) are encouraged with a particular focus on marriage as the goal for dating (Bartkowski et al., 2011). Indeed, young adults who are single (not married) in this faith often report it as a temporary state considering their goal to get married, which is advocated by the religion (Darrington et al., 2005). Furthermore, this focus on the importance of dating for marriage likely coincides with observed higher rates of marriage among this religiously active group (Bartkowski et al., 2011) and may correspond with a wide spectrum of health benefits. In support of this, a longitudinal study of over 25 years examining the health and mortality of members of this church highlighted that those who were married, among other conditions, had the lowest total death rates and longest life expectancies ever documented (Enstrom & Breslow,
2008). Furthermore, college students in this faith have demonstrated noteworthy links between positive health behaviors (e.g., diet, sleep, exercise) and improved health outcomes (e.g., depressive symptoms, anxiety, blood pressure; Wright et al., 2023; Wright, Nelson, et al., 2020), suggesting that positive social behaviors (e.g., QDE) may provide similar benefits. Collectively, these studies suggest that a population of religious young adults in college, particularly members of the Church of Jesus Christ of Latterday Saints, provides an opportunity to examine health and wellness relative to QDE.
Dating Quality and Wellness
Finally, quality romantic relationships have associations with a broad range of health and wellness indicators (cf., Burleson et al., 2013) especially for emerging adults (Braithwaite et al., 2010; GomezLopez et al., 2019). Much of the literature on dating and wellness among emerging adults at college has examined dating experience using relationship status as a proxy indicator rather than a direct measure of dating experience. For instance, in a large national sample, Kamp Dush and Amato (2005) reported that, even when relationship happiness was controlled, individuals in more committed dating relationships experienced a higher level of subjective wellbeing than those who dated infrequently or not at all. Considering a large sample of more than 1,600 emerging adult college students, Braithwaite et al. (2010) found that those in committed romantic relationships experienced greater wellbeing, fewer mental health problems (e.g., depression, anxiety), and were less likely to be overweight/obese than single students. In a large sample of undergraduate students, Whitton et al. (2013) reported that involvement in a committed relationship, as opposed to being single, was associated with fewer depressive symptoms, especially for college women. Moreover, college students in committed dating relationships are more likely to make better health decisions, decreasing their likelihood of participation in healthrisk behaviors such as problem alcohol use (e.g., Whitton et al., 2013) and increasing their likelihood of improvements in both nutrition and physical activity behaviors (e.g., Markey et al., 2007; Wright et al., 2023).
Going a step beyond simple relationship status, some studies suggest other factors such as gender and dating duration as important factors. For instance, one noteworthy study highlighted a stronger impact of a recent romantic relationship breakup (poor dating experience) on women’s emotional health than on men (Simon & Barrett, 2010), which is generally supported throughout the literature (GomezLopez et al., 2019). Another study examined positive romantic dating experiences from adolescence to young adulthood
and reported a decrease in depressive symptomology as positive dating experiences continue to occur longitudinally (Olson & Crosnoe, 2017). Among a large undergraduate student sample, Freeman et al. (2023) reported romantic duration as an important factor in dating quality, suggesting that greater duration is often part of greater quality. These studies along with other systematic reviews of this literature (GomezLopez et al., 2019; Kansky, 2018) highlight how positive dating and romantic relationships can be beneficial to college student health and wellness. However, few studies look at the quality of experiences with associated health and wellness in the nonmarital romantic dating setting, particularly within a religious context where ideals and goals for dating may influence differential profiles.
Current Study
The current study sought to identify QDEs along with its counterpart, poor quality dating experiences (PDEs), and then elucidate the relationship of these with health and wellness of a group of emerging adult college students who were members of the Church of Jesus Christ of Latterday Saints. Specifically, we proposed three research questions:
RQ1: What constitutes a QDEs or PDEs for men and women among religious college students?
RQ2: How does QDE and PDE relate to indicators of wellness among religious college students?
RQ3: Are the relationships in RQ1 and RQ2 different between men and women among religious college students?
To address these research aims, we employed a mixedmethod design, which incorporates the strengths of both qualitative and quantitative methods (Morgan, 2014). We employed focus group methodology where qualitative data was used to define QDE and PDE. We then developed quantitative measures of QDE and PDE from the findings of these focus groups to explore the relationships between health/wellness and dating experiences (quality and poor).
Method
QDE and PDE Measure Development
To determine what constitutes a QDE and differentiate this from PDE, we gathered qualitative data using focus group methodology. The main purpose of this approach was to identify emergent themes of descriptions of dating experiences to create representative quantitative measures. Our methodology followed Morgan’s (2014) recommendations and the method used by Wright et al. (2014). Before conducting these focus groups, we obtained permission from the institutional review board (IRB) for ethics compliance. Participants consisted of
58 men and women (64%) with an average age of 20.63 years ( SD = 2.21) and were mostly White ethnicity (88.1%) along with African Americans (3.4%), Hispanics (3.4%), and Multicultural (5.1%). Average lifetime dating experience was 4.97 years ( SD = 3.50), mean dating time at Brigham Young University–Idaho was 9.64 months (SD = 11.79), and the average number of inperson dates during the past three months was 5.09 (SD = 6.07). Among all participants, 52% reported being firstyears (38% were 1st semester 1styear students), 26% sophomores, 14% juniors, and 9% seniors. A total of four focus groups involved men participants (n = 21) and five focus groups were women participantsa (n = 37). All participants selfidentified as being members of the Church of Jesus Christ of Latterday Saints.
Focus groups were conducted across two semesters in the year 2022 and consisted of 5 to 10 participants each (see Morgan, 1996) who identified with male or female biological sex and were gendersegregated including moderators (members of the research team). Focus groups lasted for one hour following a semistructured format adapted from Morgan (1996). Moderators asked five scripted questions in each focus group and the semistructured nature of the interviews allowed interviewers to ask these questions in any order according to the flow of group discussion or ask additional questions relevant to participant comments. For the present purposes, we only focused on the questions regarding quality dating and dating concerns (i.e., PDEs), which were: “What is a quality date?” and “What are dating concerns for students at Brigham Young University–Idaho?” Audio recordings of each focus group were transcribed into text using the Trint program, available online.
We used conventional content analysis of each focus group following a threestep process to identify consistent or recurring themes (Hsieh & Shannon, 2005). First, based on recommended coding conventions (Charmaz, 1995), each corresponding pair of research assistants (who conducted the focus group) separately analyzed the transcript to identify commentary in which thematic elements seemed evident. Second, the pair met together and created a single version of the transcript with agreedupon thematic codes within their focus groups. Following which, all research members of the same sex met together to integrate and develop descriptions of the thematic labels created. To reduce potential bias, research assistants did not compare or examine themes yielded from focus groups of the other sex.
To verify the reliability of the themes, six coders, who were not part of the theme development process (three for each sex), were asked to label the manuscript sections using the labels identified. All were trained independently and instructed to identify the presence
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Dating Religious Health and Wellness | Wright, Wilson, Nienstedt, Ewing, Rodriguez, Anderson, Johnson, and Johnson
or absence of each code in the descriptions. Kappa coefficients were calculated and averaged across all three coders for each thematic code to determine interrater reliability. This provided a more accurate estimate as chance agreement is factored out by subtracting out the possibility that the coders would agree based on their tendency to select a certain code. Following recommendations by McHugh (2012) and Wright et al. (2014), coefficient values were considered acceptable with at least a moderate level of agreement (κ > .40).
In response to “What is a quality date?” the men focus groups produced six thematic codes that all demonstrated acceptable interrater reliability, and the women focus groups yielded three thematic codes all with acceptable interrater reliability (see Table 1). In response to our question, “What are dating concerns for students at Brigham Young University–Idaho?”, men focus groups yielded six thematic codes with five demonstrating acceptable interrater reliability (see Table 2). Women focus groups, on the other hand, produced four emergent themes, all with acceptable interrater reliability
TABLE 1
Quality Dating Experience Focus Group Emergent Themes
What is a quality date?
The date is enjoyable as the two people are friends before the date and can be friends after the date
Quality over Quantity 0.73 93% 6 (14%) Quality date is better than several dates
Communication 0.59 84% 11 (25%) Communication is natural between the individuals/it is easy to communicate with the other person
Socially Comfortable 0.56 86% 8 (18%) It is comfortable to be around the other person on a date/the other person is capable socially
Compatibility 0.44 87% 6 (14%) The two individuals on the date are compatible with one another/aspects of each individual work well with the other Women Only
Activity 0.81 95% 9 (16%) What you spend your time doing (including what you do on a first verses second date) will determine whether a date is quality
Personal Character 0.59 79% 27 (47%) The personality or character traits a person has is important (examples: respectful, chivalrous, well-mannered, supportive); not necessarily physical traits
Connection 0.57 79% 21 (37%) How the two people interact and connect will determine whether a date is quality; this may include similar interests, friendly conversation, open communication, shared beliefs, and mutual growth
Note. Kappa and percent agreement values are averages across all three coder comparisons.
(see Table 2). Next, we created genderspecific measures of QDE and PDE based on the emergent themes from the focus groups (see Appendix A and B).
Participants and Procedure
Following IRB approval for the quantitative online questionnaire portion of the current study, participants for the quantitative questionnaire portion of our study were solicited from introductory psychology courses on campus by email invitation. Interested students followed a link (via Qualtrics), whereupon they provided consent and completed an online questionnaire regarding college student life, including experiences related to their dating experiences and various aspects of their health and wellness. Data were collected during three semesters from 2022 to 2023. Student participants were given course credit for their participation and were allowed to select between several options for this course credit. Participants (n = 515) were an average of 20.12 years (SD = 2.34) and comprised mostly of women (60.6%), and most were White (83.9%) with Hispanic (3.5%), Black (2.1%), Asian American (1.9%), and Native American (0.6%) also represented. Education level was mostly firstyear students (62.9%) or sophomores (24.3%), and 71.1% were single with 28.9% reporting being in a dating relationship (not marriage). Finally, participants reported being currently enrolled in an average of 12.51 (SD = 2.15) credits, and many were employed part (40.6%) or fulltime (3.9%). All participants selfidentified as being members of the Church of Jesus Christ of Latterday Saints.
Measures
Dating Experience Constructs
First, building on the themes generated in our focus groups, we created two 10item genderspecific measures regarding QDE (see Appendix A) for the past three months on a 5point Likert scale (1 = strongly disagree, 5 = strongly agree) with higher values meaning greater quality. Both exhibited acceptable internal consistency (αs = .89, .92, respectively). Next, to capture the inverse of quality dating, we constructed two measures (8 items for men, 12 items for women) of PDE (see Appendix B) on the same timeframe and agreement scale as above with higher values representing poorer dating experiences. Both measures demonstrated acceptable internal consistency (αs = .83, .84). Dating frequency was captured by a single item asking how often they went on dates during the past three months.
Mental Wellness Constructs
Second, we assessed mental health and wellness with a variety of measures. Affect was captured using an
Wright, Wilson, Nienstedt, Ewing, Rodriguez, Anderson, Johnson, and Johnson | Quality Dating Religious Health and Wellness
eightitem measure of mood on a fivepoint frequency scale (1 = not at all, 5 = extremely) regarding how much a mood adjective described their mood over the past month along positive (i.e., happy, alert, enthusiastic, relaxed; α = .62) and negative (i.e., sad, irritable, bored, nervous; α = .68) dimensions (Wright et al., 2017). Acute depressive symptoms during the past week were assessed using the Center for Epidemiologic Studies Depression (CES D) 5 item measure (Bohannon et al., 2003) on a 4 point scale (1 = rarely or none of the time; 4 = most or all of the time; α = .77). Anxiety over the past three months was assessed using a 4 item measure on a 5 point frequency scale (1 = never, 5 = very often; α = .82; Butz & Yogeeswaran, 2011). Perceived stress was captured using seven items from the Perceived Stress Scale (Cohen et al., 1983) on a 5point frequency scale (1 = never, 5 = very often; α = .84). Using a 7point agreement scale (1 = strongly disagree, 7 = strongly agree), satisfaction with life (Diener et al., 1985) was queried with five items (α = .87) and body appreciation (i.e., body image) was assessed on a 7point agreement scale (1 = not at all true, 7 = very true) using the 13item Body Appreciation Scale (Avalos et al., 2005; α = .94).
Social Wellness Constructs
Regarding social health and wellness, perceived loneliness during the past month was assessed using the 3item Short Loneliness Scale (Hughes et al., 2004) on a 5point frequency scale (1 = never, 5 = all the time; α = .81 ). Social support was examined from both perceptual and behavioral perspectives. For the perceptual perspective, we first asked participants to indicate the number of close friends they felt they had (i.e., people that you feel at ease with, can talk to about private matters, and can call on for help). For peer specific social support, we used eight items on a 7 point agreement scale (1 = strongly disagree , 7 = strongly agree) regarding perceptions of social support from peers (Wood et al., 2004; α = .71). Then, to capture perceptions of general social support, we used the Interpersonal Support Evaluation List (ISEL; Cohen & Hoberman, 1983), which is a 12item measure on a 4point agreement scale (1 = definitely false, 4 = definitely true) of perceived availability of social support within one’s general social contacts (α = .86) Measurement of behavioral social support involved an 8item measure of social integration (i.e., inperson social interactions) on a daily frequency scale (α = .74) in the past month (Twenge et al., 2017). Interpersonal conflict with others in general was assessed using six items (Wright et al., 2017) on a 5point frequency scale (1 = never, 5 = very often) for the past 3 months (α = .87). Finally, as other potential indicators of social wellness, we queried daily
time spent on social media as well as time spent on screens. For daily time spent on social media, we asked participants to indicate how much time they spent on all social media each day during the past month on a sliding scale (0 to 10 hours). Daily time spent viewing a screen (screen time) used four items (Wright et al., 2022) to create a sum score of daily screen time on a typical day during the past month on a smartphone, tablet, computer, and television.
Physical Wellness Constructs
Lastly, physical wellness was assessed with the single item EuroQol Fifth Dimension (Kind et al., 2005) measure of overall subjective health so participants rated their own health on a scale from 0 (worst physical health) to 100 (best physical health). Physical health symptoms were measured using Spector & Jex’s (1998) 18item Physical Symptom Inventory (e.g., headache, fatigue) during the past 30 days. To capture sedentary behavior on a typical day, we used a 10item adapted version of the Sedentary Behavior Questionnaire (Rosenberg et al., 2010) on a 9point scale (0 = none, 9 = 6 hours or more) with 10 behaviors (e.g., watching television, playing video games, sitting in a car).
TABLE 2
Dating Experience Focus Group Emergent Themes
Men Only
are dating concerns fors tudents at Brigham Young UniversityIdaho?
What are dating concerns for students at Brigham Young University–Idaho?
Meeting with a potential partner may be unsafe
Major differences may exist between yourself and a potential partner
Dating with the exclusive purpose/priority of marriage
The other person is or will be rude/treats you or others poorly
Getting rejected from potential partners for a period of time or more than once Fear of Investment
5 (13%) Fear of getting too involved or being committed to a potential partner for an extended period of time
Women Only
11 (20%) The feeling one has about whether they are safe in the presence of another person
Concern that someone only wants to get married because everyone else is doing it or because it is the norm
The negative characteristics that a person displays; examples include deceitful, manipulative, isolating, pushy, possessive Lack of Communication
Failure of dating partners to adequately communicate expectations for the dating relationship because they don’t want to appear too eager or for some other reason
Note. Kappa and percent agreement values are averages across all three coder comparisons.
Data Analysis
First, as our data were genderspecific, we analyzed differences between women and men in terms of both QDE and PDE using independentsamples t tests and Cohen’s d main effects. Next, we examined relationships between these dating experience variables and the health and wellness indicators using correlation analysis. Moreover, we applied a Fisher’s transformation of Pearson’s r to z to enable a statistical comparison of the genderspecific correlations, as this standardizes correlation coefficients for direct comparison. Similarly, for subsequent t tests on differences between women and men in these correlations, this transformation enables detection of significant differences due to this standardization. To protect against possible Type I error, which may be inflated by conducting multiple significance tests, we applied Bonferroni’s correction (which reduces the alpha level to be considered statistically significant) for the t tests on differences between women and men in correlation strength. Finally, we explored a few alternative explanations for the observed results by examining differences in other demographic variables age, dating frequency, and relationship status (single versus dating relationship).
Results
Means, standard deviations, and other descriptive information for study variables are listed in Tables 3 and 4.
Participants reported an average of 7.80 (SD = 10.30) dates in the past 3 months, and increased dating frequency was significantly related to increased positive affect, life satisfaction, general social support, and social integration as well as decreased perceived loneliness. However, these relationships were rather modest, suggesting that dating frequency alone may not be a good predictor of wellness in this context. Moreover, both age and number of credits enrolled were not significantly related to dating frequency, QDE, or PDE.
Regarding our created measures of Quality Dating Experience (QDE) and Poor Dating Experience (PDE), the correlations between them were negative for both men and women (r = .42, .52, respectively), providing support of their theoretical inverse relationship. Moreover, dating quality experience did not significantly differ between men ( M = 3.84, SD = 0.62) and women ( M = 3.88, SD = 0.66), t(487) = 0.52, p = .50, d = 0.05. However, PDE differed significantly, t(491) = 5.42, p < .001, d = 0.49) as women (M = 2.64, SD = 0.58) reported PDEs more frequently than men (M = 2.33, SD = 0.68). Moreover, QDE was reported significantly higher than PDE for both men, t(392) = 23.37, p < .001, d = 2.36, and women, t(586) = 24.21, p < .001, d = 2.00. As might be expected, dating frequency was positively correlated with QDE for both men and women, but significantly more so for women (see Table 4). Moreover, dating frequency
TABLE 3
Correlation Matrix for Study Variables Across Entire Sample
7.
8.
9. Loneliness
10. Number Close Friends
Note * p < .001; Dating Quality and Poor Dating Experience variables are not reported here, but in Table 4 because they are gender specific. Internal consistency estimates (Cronbach’s α) are listed on the diagonal. Dating frequency is according to prior 3 months. Social media time, screen time, and sedentary behavior are in minutes per day..
Wright, Wilson, Nienstedt, Ewing, Rodriguez, Anderson, Johnson, and Johnson | Quality Dating Religious Health and Wellness
was negatively correlated with PDE for both men and women, though this relationship was stronger for women. Thus, women reported PDEs more frequently and exhibited a stronger relationship between quantity and quality of dates than men.
Next, we examined health and wellness across and women and men relative to their dating experience (see Table 4). In general, relationships between the QDE and PDE were in the expected direction (poorer wellness associated with lower QDE) and were in the same direction for men and women, suggesting similar relationships between these variables regardless of gender. Among the mental wellness variables, all were significantly (p < .05) related in the expected directions to the QDE and PDE (except negative mood and QDE), with poorer health being generally associated with lower QDE. However, in terms of differences, men generally exhibited stronger significant relationships than women for the wellness variables associated with the QDE and PDE. Satisfaction with life, depressive symptoms, and body appreciation were the strongest, and depressive symptoms demonstrated a significantly stronger (p < .05) relationship with PDE for men than women.
Furthermore, the social and physical wellness indicators were generally related to the QDE and PDE in the expected directions for both men and women, though not all were significant (see Table 4). Perceived loneliness, general social support, and interpersonal conflict exhibited the strongest relationships with the PDE for both women and men. However, peer support and interpersonal conflict manifested significant gender differences with men reporting a statistically stronger association than women. Interestingly, daily social media time and daily screen time demonstrated small and nonsignificant associations, suggesting that electronic media use may not have much of a relationship with the evaluation of one’s dating experience. Similarly, physical wellness variables exhibited small or inconsequential correlations with the QDE and PDE, though these were also in the expected directions, overall. Collectively, these results suggest that dating experiences likely are similarly related for both women and men with the notable exceptions of dating frequency being stronger for women whereas depressive symptoms, peer social support, and interpersonal conflict were more strongly related for men.
Finally, we explored alternative explanations including age, dating frequency, and relationship status differences that could offer competing explanations for the results. First, although age significantly differed between men ( M = 20.92, SD = 2.04) and women (M = 19.60, SD = 2.38) t(513) = 6.46, p < .001, d = 0.57, it was not significantly related to the QDE or PDE,
suggesting that age was not a confounding variable. Second, both women and men reported similar frequency of dating activity in the past 3 months with men at an average of 7.00 dates (SD = 10.32) and women at 8.32 dates (SD = 10.27) t(477) = 1.38, p = .17, d = 0.13, suggesting that observed differences between men and women on the QDE and PDE are likely not related to differences in dating frequency. Third, we investigated the difference between being single and being in a dating relationship (not married but dating one person more exclusively than others). Generally, across both men and women, those in a current dating relationship scored significantly higher on the QDE and lower on the PDE than those who were not (see Table 5), which would be expected. Thus, these results suggest that, although being in a current committed dating relationship may play a role in
Correlations for QDE and PDE With Wellness Variables Across Genders
Body Appreciation
Loneliness
Number
Peer Support
Subjective Health
Sedentary Behavior
Note * p < .05; ** p < .01; QDE = Quality Dating Experience; PDE = Poor Dating Experience. Fisher’s r to z transformations were conducted on the Pearson r values to enable appropriate comparisons for statistical significance and reported here. Δ represents the transformed correlation value difference between men and women, such that a negative value represents a stronger absolute value for women and vice versa. Bonferroni corrections were applied for difference testing of the correlation values. Social Media Time and Screen Time are both in terms of daily minutes.
TABLE 4
the perceived dating experience (higher ratings of QDE), age and frequency of dating are likely not confounding variables in the current analyses of QDE and PDE.
Discussion
Using a mixedmethods approach, the current study examined expectations and perceptions regarding QDE and PDE among a religious college student emerging adult population of members of the Church of Jesus Christ of Latterday Saints. Focus groups revealed similar and contrasting perspectives between women and men for dating experiences, supporting the qualitative approach in elucidating specific themes that were central and defining for the dating experience as a college student in a religious context. Next, upon creating measures of QDE and PDE from these themes, a large quantitative survey uncovered relationships between both dating experience variables and several wellness factors, suggesting a connection between one’s dating experience and overall wellness. Finally, both similar and unique patterns were observed between women and men, which further suggests a need to consider gender as an important characteristic in perceptions of the quality of one’s dating experience.
First, for Research Question 1, focus groups uncovered several dating experience themes that were similar for both women and men in this religious context while noting some differences. The quality dating themes of compatibility, friendship, socially comfortable, and friendship elicited from the men focus groups were similar in content to personal character and connection in the women focus groups. These similar findings support the matching phenomenon’s (Feingold, 1988; Tidwell et al.,
TABLE 5
Differences in Relationship Status Across Genders on the QDE and PDE
2013) assertion that similarity produces attraction and, by extension, quality experiences. However, notable differences were also evident, particularly between the men’s theme of monetary value and the women’s theme of activity, highlighting a potential difference of focus, likely due to genderrelated expectations (e.g., Paynter & Leaper, 2016) and norms such as an expectation for men to pay for dates (Lever et al., 2015). Interestingly, some potential themes were not identified including physical attraction (Ha et al., 2012), dating outcome, and shared religious activity (Langlais & Schwanz, 2017), which may be a unique finding within a religious dating context where these may be assumed or deemed socially unacceptable to report.
The PDE themes demonstrated some congruence between women and men, particularly regarding safety and a concern for getting married too quickly. This is interesting in a religious dating environment where dating should lead to marriage (Myers et al., 2005), suggesting that dating safety remains a concern along with the worry that dating may elicit marriage prematurely. Moreover, notable gender differences revolved around communication. Whereas men reported being rejected and receiving rudeness from potential dating partners, women identified a lack of communication. It may be that men receive negative communication and women do not receive enough communication when defining PDE, which is in line with prior research emphasizing the role of communication in dating (Cohen, 2016; Wright et al., 2007). Finally, it is interesting to note that only one of the themes identified across both questions for both women and men (fear of investment) failed to achieve at least a moderate level of interrater agreement, suggesting that the remaining themes are likely prominent within this religious college student dating context.
Second, for Research Question 2, QDE and PDE was related to many wellness variables and more strongly than dating frequency. Particularly strong correlations emerged across the genders for perceptions of loneliness, satisfaction with life, depressive symptoms, peer, and general social support, suggesting that both women and men experienced feelings of isolation from the social context under conditions of less QDE. This finding underscores the importance of dating experiences in this population, particularly considering recent increasing trends in loneliness and social isolation (e.g., HoltLunstad et al., 2015; U.S. Surgeon General, 2023) even among this same religious population (Wright et al., 2018). Moreover, the connection between poor dating and poorer wellness may be rooted in the social ideal that successful social integration in a religious context mandates quality social interactions, particularly
Wright, Wilson, Nienstedt, Ewing, Rodriguez, Anderson, Johnson, and Johnson | Quality Dating Religious Health and Wellness
with the other sex. However, it is also feasible that those who already experience poorer mental health elicit poorer dating experiences or are apt to perceive them as such. Regardless, these results suggest that perceptions of dating quality experience can be used as a proxy indicator of wellness, particularly for mental health, and that using a simple metric of dating frequency may be failing to capture a more comprehensive perspective.
Third, for Research Question 3, our results highlighted some notable differences between women and men. Although this may be expected in a religious dating context that emphasizes differing traditional gender roles, significant differences highlighted the stronger association of PDE for men’s wellness compared to women, contrary to other studies (GomezLopez et al., 2019; Simon & Barrett, 2010). A potential explanation for the constructs of depressive symptoms, perceived peer social support, and interpersonal conflict exhibiting this stronger pattern for men than women may involve traditional dating expectations for gender roles espoused in many religious contexts. For instance, in this context, men are generally expected to ask women on dates, plan the activities, and pay for the date (Lever et al., 2015). Women, on the other hand, are expected to either accept or decline and then participate in the planned activities. Thus, a PDE may reflect how well the man is able to succeed in his gender role expectations and, by extension, lead to increased depressive symptoms, conflict with others, and a decrease in perceptions of peer acceptance and support.
Supporting this explanation of gender roles, dating frequency had a stronger association with dating quality experience for women than men, suggesting that frequency of dates for women may lead to increased dating quality experience or vice versa. Indeed, according to these gender role expectations, men are freer to increase their dating frequency but less able to control the quality of the dating experience, as this involves further interpersonal interaction. Women, on the other hand, have less freedom to increase their dating frequency, but more decision latitude during the dating experience as they engage interpersonally. Thus, as dating frequency increases for women, this may engender a sense of increased quality, or women who have greater QDEs may also be drawing more dating opportunities in the future. Furthermore, building on these findings, mental health practitioners, educators, and even religious leaders may need to be sensitive to some of these expressed gender differences in dating. For instance, in a more traditional religious setting, an acknowledgement of these unique perceived gender roles, social pressures, and social identity of the genders within the dating context may help these stakeholders to support young adults. This may be
particularly important in fostering healthy relationships and promoting overall wellbeing within the context of their religious beliefs and community settings. Finally, some wellness variables and alternative explanations may not be important when considering dating quality experience. Despite studies highlighting the importance of social media, electronic media use, and screen time in this population (e.g., Wright et al., 2018; Wright, Schaeffer, et al., 2020; Wright et al., 2024) and others (Twenge et al., 2017) regarding social and mental health, our study failed to uncover a relationship. This may be due to screen time, electronic media, and social media becoming more mainstream among emerging adults rather than a novel distraction or impediment to the dating experience, an interpretation further supported by the nonsignificant relationship with dating frequency. Moreover, our findings suggest that gender differences in frequency of dating and age are likely not viable competing explanations for these observed differences in the dating quality experience. However, dating relationship status mattered, such that those who are in a current dating relationship reported better quality dating experience. This is to be expected, as one does not exclusively date someone until it has already been determined that some amount of compatibility or desirability exists in the potential relationship. In fact, this further supports the idea that dating is performing its adaptive function in this traditional religious context, as dating quality with one person should be predictive of future marriage potential.
Potential Limitations and Future Research
This investigation has some potential limitations. First, the crosssectional study design precludes any causal conclusions, as temporal primacy was not established. Moreover, using correlations limits inferential conclusions, though we applied Fisher’s transformation before making any direct statistical comparisons, and we used Bonferroni corrections to decrease chances of Type I error. Second, despite using a mixedmethod design that builds on the strengths of both qualitative and quantitative data, the limitations of both are also possible. For instance, the focus groups might have limited generalizability along with the resulting quantitative measures. However, our conduction of multiple gendersegregated focus groups until the point of data saturation partially mitigates this concern. Third, other factors not included in these analyses (e.g., personality) may attenuate or moderate these findings, such that those who are more extraverted or neurotic may demonstrate differential patterns of relationships between dating and corresponding health. Finally, sample characteristics may pose difficulties in generalizing these results to other populations beyond
the traditional college student setting such as those of lower socioeconomic status or different cultural perspectives. Moreover, the current study espoused heteronormative and cisgender assumptions related to dating within a sample of members of the Church of Jesus Christ of Latterday Saints, which may not always be the supported (Klundt et al., 2021).
Despite these potential limitations, insights from this study offer some direction for future research. First, although it seems plausible that the quality of dating experience may cause wellness outcomes, the reverse is also plausible, such that those who have poorer wellness may elicit or cause more dating frustrations. Future research examining dating quality over time could address this issue while also controlling for several other potentially confounding variables (e.g., interactions prior to dating, personality characteristics). Second, future studies could restrict examination to only those who are single or in an exclusive dating relationship to identify potentially unique or more nuanced elements of quality dating at each of these two distinct dating stages. Third, future research could explore the validity of our created measures (QDE, PDE) among other single college students at other conservative or religious campuses. Indeed, comparison to another religious or nonreligious college campus could provide further interesting insights into how well these generalize in other contexts and populations (e.g., sexual minorities). Going a step further, future research might examine the predictive validity of our created measures in following college students who score high on the QDE (and low on the PDE) in dating relationships to determine whether they are predictive of other behavioral outcomes such as engagement or marriage. Moreover, building on the concept that personality characteristics influence the dating process, future studies could examine how personality may account for the observed relationships between dating experiences and health. Finally, sophisticated methodological designs could be implemented to study QDE and PDE using inlab observations (Galliher et al., 2008) from a dyadic perspective (Kenny & Acitelli, 1994).
In conclusion, using a mixedmethods design to investigate dating quality experience among single college students at a religious institution of higher education, we identified emergent themes of QDE and PDE, created measures, and uncovered consistent relationships between quality dating experience and better overall wellness. Thus, this work provides a building block in understanding a context in which to potentially address the growing national challenges in marriage, social isolation, and loneliness by targeting dating experiences among college students within a religious context.
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Author Note
Robert R. Wright https://orcid.org/0000000241017840
Christian Nienstedt https://orcid.org/0000000196546734
Carson R. Ewing https://orcid.org/0000000255354864
This research was supported by internal funding from Brigham Young University–Idaho for student and facultydirected research. We would like to thank (in alphabetical order) Samuel Chambers, Annie Harrison, Spencer Heindel, Keegan Hokanson, Maren Layton, Stephanie Merrick, Shelby W. Morgan, Sara Mouser, and Lavear Whitney for their assistance throughout the conduction of this study. The authors declare no conflict of interest. The data that we used for the current study are available from the corresponding author, upon reasonable request.
Correspondence concerning this article should be addressed to Robert R. Wright, Department of Psychology, Brigham Young University–Idaho, 210 West 4th South Rexburg, ID 834602140. Telephone: 2084964085. Email: wrightro@byui.edu
Wright, Wilson, Nienstedt, Ewing, Rodriguez, Anderson, Johnson, and Johnson | Quality Dating Religious Health and Wellness
APPENDIX A
Quality Dating Experience (QDE) Measures
Men Only
1. Make me feel socially comfortable
2. Are okay with a cheap or creative dating activity
3. Communicate well with me
4. Create a connection with me through communication
5. I have interacted with beforehand in another context
6. Are not someone I have just met
7. Have similar standards/morals
8. Have shared interests
9. Are fun to be around
10. Have a personality that is compatible with mine
Women Only
1. Are gentlemen
2. Engage in dating activities with me that are fun and enjoyable.
3. Have a personality that I find interesting/attractive
4. Are respectful
5. Engage in dating activities with me that are appropriate for getting to know them
6. Have similar standards/morals.
7. Are supportive of me
8. Communicate to me the planned dating activity(ies) beforehand.
9. Have shared interests.
10. I feel a connection with.
APPENDIX B
Poor Dating Experience (PDE) Measures
Men Only
1. I feel uncomfortable or uneasy while I am on a date with someone.
2. I see “red flags” (e.g., warning signs) while I am on a date with someone.
3. I feel that my dating partner(s) pressure me to get married too quickly.
4. Those I date are rude or impolite
5. Those I date (or want to date) reject my efforts to date them
6. Investing my time and energy into dating is just not worth it
7. I feel unsafe while I am on a date with someone.
8. Major personal differences arise between me and those I date
Women Only
1. I feel like those I date act or become possessive.
2. According to my dating partner(s), getting married quickly is the norm.
3. I date those who I do not know very well.
4. I feel like those I date try to isolate or separate me from others.
5. I see “red flags” (e.g., warning signs) while I am on a date with someone.
6. I feel uncomfortable or uneasy while I am on a date with someone.
7. I feel unsafe while I am on a date with someone.
8. When I go on dates, I feel the conversation is one-sided.
9. I feel uncomfortable when those I date are unclear about their expectations of me.
10. I feel like those I date try to manipulate me.
11. I am concerned that people I date are not straightforward about their intentions.
12. I feel that my dating partner(s) pressure me to get married too quickly.
Race Differences in Stressor-Related Negative Affect and Daily Rumination
Jessica M. Blaxton* and Sydney Dobrzynski Department of Psychology, Metropolitan State University
ABSTRACT. This study investigated race differences in the withinperson relationships among daily reports of rumination, stress, and negative affect (NA). Past research illustrating that the withinperson relationship between stress and NA predicts longterm outcomes has emphasized the importance of early intervention for those with stronger daily relationships between stress and NA. We examined whether withinperson increases in daily rumination exacerbate the relationship between daily stress and NA. Further, we explored whether the exacerbating effect of daily rumination on the relationship between daily stress and NA is greater for People of Color (POC) compared to White participants. Participants ( N = 92) completed a global questionnaire with demographic information and 2 weeks of daily questionnaires assessing daily reports of perceived stress, NA, and rumination. We analyzed the data using multilevel modeling to parse betweenperson effects from the withinperson relationships among daily stress, NA, and daily rumination. Results revealed that withinperson increases in daily rumination and daily perceived stress related to greater daily NA. Greater overall stress and rumination related to greater daily NA. POC reported greater daily NA compared to White participants. The twoway interaction model indicated that daily withinperson rumination exacerbated the relationship between daily perceived stress and daily NA. Results suggest that POC may benefit from interventions and preventive strategies aimed at increasing wellbeing in general and decreasing NA. In addition, introducing strategies to prevent increases in daily rumination on high stress days can be particularly helpful in reducing NA.
Keywords: daily stress, daily negative affect, people of color, daily rumination
Understanding how the daily relationship between stress and negative affect (NA) fluctuates and differs depending on contextual, daily variables (e.g., rumination), and person level variables (e.g., race) can inform preventative care and interventions aimed at uplifting and maintaining well being among those most at risk. Studies have consistently illustrated a strong, positive relationship
between daily stress and NA (Blaxton et al., 2022; Colgan et al., 2019; Montpetit et al., 2010; Mroczek & Almedia, 2004; Stawski et al., 2008), termed stressor related negative affect (SRNA; Stawski et al., 2019). The strength of this relationship significantly predicts chronic physical health conditions and affective distress levels up to 10 years later (Charles et al., 2013; Piazza, 2013). The significant findings emphasize the
Diversity badge earned for conducting research focusing on aspects of diversity.
importance of early intervention for the wellbeing of those with particularly strong relationships between daily stress and NA (Montpetit et al., 2010). Moreover, stress and coping theory suggests that a person’s perception of stress and the way they cope with that stress can affect their response to the stressor (Folkman & Lazarus, 1986). The physiological impact of stress depends on a variety of factors including contextual, historical, cumulative, and acute stress processes (Epel et al., 2018). Indeed, research has shown that contextual factors not only influence SRNA (Blaxton et al., 2022), but also the longterm effects of the daily SRNA (Blaxton et al., 2022; Brose et al., 2011; Charles et al., 2013; Parrish et al., 2011; Piazza, 2013). Rumination specifically results in increased perceptions of the severity of stress (Watkins & Roberts, 2020). Thus, days of greater rumination may relate to a stronger daily stressNA relationship, which could highlight a potential pathway for reducing daily SRNA. In addition, some individuals may be particularly susceptible to experiencing greater SRNA and greater rumination due to contextual circumstances. Because People of Color (POC) experience greater discrimination than White people (Dalessandro et al., 2023), we explored whether SRNA is stronger for POC and whether the potentially exacerbating effect of daily rumination on the daily stressNA relationship is also stronger for POC.
Daily Rumination in Relation to Daily Stress and Negative Affect Research has shown that greater rumination relates to greater stress (Catalino et al., 2017; Genet & Siemer, 2012; Pavani et al., 2016; Sladek et al., 2020) and greater NA (Catalino et al., 2017; Genet & Siemer, 2012; Pavani et al., 2016). Specifically, daily stress and cortisol levels increase on days when people ruminate more than usual (Sladek et al., 2020). Participants ruminated 1.5 standard deviations above their mean score on days of greater than usual stress, which related to higher waking cortisol levels the next day (Sladek et al., 2020). Thus, yesterday’s daily rumination can affect tomorrow’s stress, and greater rumination may exacerbate the negative effects of stress.
Not only does daily rumination have a strong positive relationship with daily stress (Sladek et al., 2020), but greater rumination also influences NA (Catalino et al., 2017; Genet & Siemer, 2012; Pavani et al., 2016). For example, rumination amplifies NA with unnatural life stressors produced in lab settings (Genet & Siemer, 2012). In everyday life, individuals who tend to ruminate more on a daytoday basis also show greater NA, and this relationship is stronger for individuals experiencing greater overall daily stress (Catalino et al., 2017). Thus,
a combination of stressful experiences and high levels of rumination relate to greater levels of NA (Catalino et al., 2017; Genet & Siemer, 2012; Pavani et al., 2016). These chronically higher levels of NA can lead to worse physiological health and less satisfaction with social relationships (Pavani et al., 2016). In addition, consistent levels of rumination predict symptoms of depression and anxiety up to a year later (Pavani et al., 2016). Thus, rumination appears to intensify and maintain NA levels in short and longterm situations (Pavani et al., 2016). These findings indicate significant betweenperson relationships among rumination, stress, and NA. Although betweenperson findings do not necessarily relate to the withinperson level (Brose et al., 2010), we hypothesized that greater daily rumination exacerbates the relationship between daily stress and NA within individuals as well.
Racial Differences in Stress and Negative Affect
POC experience greater stress and NA, and may thus also experience greater daily SRNA (Bergeman et al., 2020; Ong et al., 2009). Indeed, among a sample of Mexican adolescents, racial discrimination reported over the course of the last year predicted daily stress levels (Zeiders, 2017). In addition, NA ratings were higher than the person’s mean NA scores on days with more discriminatory acts or stressors reported and even higher on days when other stressors occurred, like work or family matters, compared to the days reported with only discrimination related stressors (Ong et al., 2009). Discrimination historically causes significantly higher levels of perceived stress in marginalized groups, including groups based on race, gender, and people with different sexual orientations (Dalessandro et al., 2023). Data show that lifelong stressors of discrimination cause major depressive disorders and generalized anxiety disorders, comparable to the levels that come with traumatic events such as military combat, sexual assault, and physical assault (Ong et al., 2009). For example, African Americans report increased perceived stress compared to White Americans and are more likely to have severe, longterm, depression (Ojebuoboh et al., 2022). This chronic stress predicts more physiological health problems in the future, including cardiovascular disease (Ong et al., 2009).
Epel et al. (2018) explained that stress encompasses a complex process involving interactions between individual and environmental factors, historical and current events, and psychological and physiological reactivity. The authors provided a model to understand stress that highlights how stressor exposures across the life course and captured at difference timescales influence habitual responding and stress reactivity. Understanding stress
Race, Daily Stress, and Daily Rumination |
Blaxton and Dobrzynski
as a process involves recognizing the cumulative effects of stress over time and the interaction between acute stress responses and chronic stressors. For example, chronic stressors, like discrimination, can increase the frequency and severity of daily stressors and amplify emotional and physiological responses to these stressors. This cumulative stress exposure can then lead to longterm health impacts, such as increased inflammation, accelerated aging, and higher risk of disease. Because the strength of the daily relationship between stress and NA also predicts longterm health (Charles et al., 2013; Piazza, 2013), daily SRNA may illustrate one potential pathway for increased stress perceptions among POC (Bergeman et al., 2020). Multilevel modeling allowed us to study stress as a process and compare participants to themselves, situating them within their own context (Hoffman, 2009). Thus, by focusing on the withinperson relationships among daily SRNA and rumination, we examined whether POC experience greater SRNA. We furthered explore whether daily rumination amplifies SRNA more for POC compared to White participants.
Purpose of the Current Study
The purpose of the current study was threefold. First, we hypothesized that daily rumination exacerbates the relationship between daily stress and NA. Second, we hypothesized that POC experience an exacerbated relationship between daily stress and NA. Finally, we explored whether the exacerbating effect of daily rumination on the relationship between daily stress and NA is greater for POC compared to White participants.
Method
Participants and Procedure
Descriptive statistics and intercorrelations among the measured variables are presented in Table 1. The participants included 92 individuals from a convenience sample at Metropolitan State University in St. Paul, Minnesota. After the study was approved by the
Institute’s Human Subjects Review Board, participants were recruited from psychology classes and provided informed consent via Qualtrics. Participants completed a global data questionnaire, identifying race and ethnicity for the current study. Participants then completed nightly questionnaires over the course of 14 days, which assessed daily stress, daily NA, and daily rumination. The dataset included a total of 776 days out of the possible 1,288 days. Consequently, 40% of the data were missing. We do control for the total number of missing days for each participant in the analyses.
Measures
Positive and Negative Affect Schedule (PANAS)
Participants reported NA using the NA subscale from the Positive and Negative Affect Schedule (Watson et al., 1988). The questions used displayed 14 NA items that participants rated on a 5point scale containing the response items not at all, a little, moderately, quite a bit, and extremely. For example, participants were asked to respond to, “Today I felt guilty,” using the 5point scale. If more than two responses were missing from the reported questionnaire, the total NA score was coded as missing. If fewer than two questions were missing from the reported questionnaire, the missing data point was substituted with the mean score of NA for the participant for that day. Individuallevel reliability across the 14 days of the study was .86 (see Bonito et al., 2012; Nezlek, 2017, for computational details).
Perceived Stress Scale
Participants reported answers for stress each night using the 10 item Perceived Stress Scale (Cohen & Williamson, 1988). The questions were modified to reflect their perceived stress over the course of the day they reported. Specifically, the original Perceived Stress Scale asks participants to report their feelings of stress over the last month, but we asked participants to report their feelings of stress over the course of that day, which is consistent with previous research using the Perceived Stress Scale to assess daily SRNA (Blaxton et al., 2023). The questionnaire was rated on a 4point scale containing the response options strongly disagree, disagree, agree, and strongly agree. For example, participants responded to, “I was upset today because of something the happened unexpectedly,” using the 4point scale. If more than two questions were missing from the reported questionnaire, the participant’s stress score was coded as missing for that day. Questionnaires missing fewer than 20% substituted the mean score for the missing day. Individuallevel reliability across the 14 days of the study was .74 (see Bonito et al., 2012; Nezlek, 2017 for computational details).
TABLE 1
Daily Rumination Measure
Participants reported their levels of rumination by answering four questions and rating them on a scale of 0–100 (Slavish et al., 2018). For example, participants responded to “Today, how often did you experience a train of thought that was difficult to get out of your head?” If only one question was missing from the reported answers, the mean for the other three scores was substituted for the missing item. If more than one question was missing, the daily rumination score was coded as missing. Individuallevel reliability across the 14 days of the study was .79 (see Bonito et al., 2012; Nezlek, 2017, for computational details).
Analytic Approach
We analyzed the data with multilevel modeling, where Level 1 included daily scores (i) for each participant, which were nested in Level 2 average scores (j). To effectively parse the within person effects from the betweenperson effects, we person mean centered each Level 1 variable (Wang & Maxwell, 2015). The main effects equation was:
NAij = b0j + b1j(day-1) + b2j(stressij – stressj) + b3j(ruminationij – ruminationj) + eij
b0j = g00 + g01(POC) + g02(stress ) + g03(rumination ) + u0j
b1j = g10 + u01
b2j = g20 + u02
b1j = g30 + u03
Level 1 includes the effect of time (day) to control for its effect on daily NA as well as withinperson fluctuations in daily stress (g20) and daily rumination (g30). Level 2 includes the betweenperson effects of whether the participant was a POC ( g 10), average stress levels ( g 20), and average rumination levels ( g 30) over the 14 days of data collection. Although we do not show it in the equation for the sake of simplicity, we also controlled for total number of missing days and age at Level 2. The SAS Proc Mixed procedure with maximum likelihood allowed us to analyze the data to test the aims of our study. We first examined the main effects model (Model 1) to test whether greater daily stress relates to greater daily NA among the participants. Next, we added the possible Level 1 and crosslevel twoway interactions to the model between daily stress and daily rumination. ( g 40), POC and daily stress ( g 21), and POC and daily rumination (g31) to examine whether daily rumination exacerbates the relationship between daily stress and daily NA as well as whether POC experience an exacerbated relationship between daily stress and daily NA compared to White participants. Finally, we created the threeway interaction model by including the crosslevel interaction between daily stress, daily rumination, and POC (g41) to examine whether the exacerbating effect of
daily rumination on the daily stressNA relationship is greater for POC compared to White participants.
Results
Demographic Results
The participants (N = 92) ranged in age from 17–65 (M = 31.71; SD = 11.93). Seventythree participants reported their gender with 12 reporting a gender identity of man, 58 of women, and three of “Another Gender Identity.” The participants (N = 76) who reported their race/ethnicity included 43 people who identified as White and 33 that identified as a POC. More specifically, 54% of the participants identified as White, 20% identified as Black, 18% identified as Asian, 4% identified as Hispanic, 3% identified as Middle Eastern, and 1% identified as American Indian/Alaskan Native. The 72 participants who reported income included 45 participants with above $25,000 a year. The other 27 participants reported an income of $25,000 or less. Among the 92 participants, there were 512 days missing in total, causing 39.75% of the possible data to be missing. We analyzed whether there were demographic differences in any of the variables of interest. Results revealed that older adults reported less NA (b = 0.23, p = .02), less overall stress (b = 0.10, p = .03), and less rumination (b = 0.61, p = .007) compared to younger adults. There were also differences in age between POC and White participants (t = 2.78; p = .007), with more White participants being older (n = 42; M age = 34.81; SD age = 12.73) compared to POC (n = 28; M age = 27.07; SD age = 8.98). Finally, a greater amount of missing data among the participants did predict greater perceived stress (b = 0.35, p < .001), greater NA (b = 0.48, p = .02), and greater rumination (b = 1.09, p = .03). Because age and number of missing days related to both the independent and dependent variables, we controlled for age and number of missing days in the multilevel models.
Results From Analytic Models
Results revealed that 58% of the variance in daily NA exists between participants (t00 = 73.07, z = 6.00, p < .001) and withinperson fluctuations explain 42% of the variance in daily NA ( s 2 = 53.66, z = 18.49, p < .001; Nezlek, 2001). The main effects model revealed that within person increases in daily rumination ( g 30 = 0.18, p < .001) and daily perceived stress (g20 = 0.72, p < .001) related to greater daily NA. Greater overall stress ( g 02 = 0.80, p < .001) and rumination ( g 03 = 0.19, p < .001) related to greater daily NA. In addition, POC reported greater daily NA (M = 28.49, SD = 12.46) compared to White individuals (g01 = 2.83, p = .02; M = 24.09, SD = 5.90). The twoway interaction model that included three interactions between
Blaxton
Dobrzynski
Race, Daily Stress, and Daily Rumination |
Blaxton and Dobrzynski
daily stress and daily rumination, POC status and daily stress, and POC status and daily rumination indicated that daily withinperson rumination exacerbated the relationship between daily perceived stress and daily NA ( g 40 = 0.01, p < .001; see Figure 1). The twoway interactions between POC and daily stress (g21) as well as POC and daily rumination (g31) were not significant. The threeway interaction between POC, daily stress, and daily rumination (g41) was also not significant.
Discussion
Results from the study emphasized the importance of situating SRNA in the context of the individual experiencing that SRNA to best inform interventions and preventative care strategies. Specifically, the results expanded upon previous SRNA research (Blaxton et al., 2022; Colgan et al., 2019; Montpetit et al., 2010; Mroczek & Almedia, 2004; Stawski et al., 2008), indicating that college students also experience significant SRNA. Moreover, they illustrated that days of greater rumination are also days of greater SRNA, suggesting that targeting rumination may be one pathway to reduce stress reactivity. Finally, results indicated that POC experience greater daily NA overall compared to White participants. Although many individuals would likely benefit from interventions and preventive care strategies aimed at developing resilience to stress, lowering NA, and promoting wellbeing, our study indicated that POC experience greater daily NA than White individuals. This finding adds to the literature that highlights differences in daily wellbeing between POC and White individuals (Dalessandro et al., 2023; Ong et al., 2009). Previous
research has indicated that greater discrimination relates to poorer daily wellbeing (Ong et al., 2009; Zeiders, 2017). Epel et al. (2018) explained that stress results from an interplay of a variety of contextual factors both within and outside the individual. Experiencing greater daily NA compared to White individuals may reflect the negative effects from longterm, historical discrimination. Interventions and preventive care strategies focusing on increasing wellbeing in general among POC, including reducing social discrimination, may be particularly beneficial.
The lack of support for all hypotheses may be due to the high amount of missing data; however, we do control for missingness in the analyses. Notably, individuals with a greater amount of missingness tended to report greater stress, NA, and rumination. Including more participants in the sample might increase the power of the study and increase the likelihood of capturing participants with higher scores on the variables of interest. In addition, future research can examine whether SRNA and rumination differ based on specific racial differences, rather than just POC compared to White participants. Finally, because past research has indicated that individuals higher in trait acceptance show less overall daily rumination, one potential pathway for reducing the relationship between daily rumination and SRNA may be through increasing acceptance (Catalino et al., 2017). Thus, future research can examine how a JustInTime intervention, aimed at increasing acceptance in response to a momentary increase in daily stress, may reduce the exacerbating effect of daily rumination on daily SRNA.
In sum, results from the current study showed that POC do illustrate greater daily NA compared to White participants; however, we do not have evidence that POC experience the relationship between SRNA and rumination differently than White participants. We do see that increases in daily rumination relate to an exacerbated relationship between daily stress and NA, suggesting that targeting daily rumination may be an effective way to reduce SRNA.
References
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FIGURE 1
Daily Stress and Daily Rumination
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Author Note
Jessica M. Blaxton https://orcid.org/0000-0002-6548-9826
Sydney Dobrzynski is now in the Psychology Department at Augsburg University.
Positionality Statement: Jessica identifies as a heterosexual, cisgender White woman. Jessica is nondisabled. Sydney identifies as a nonheterosexual cisgender White woman, who is disabled according to the Americans with Disabilities Act. The authors acknowledge that their identities influence their perspectives.
Public Significance Statement: This research indicates that People of Color experience greater daily NA compared to White participants. In addition, people experience greater stressor related NA when they ruminate more than they typically do, suggesting that targeting daily rumination may be one way to reduce the longterm ramifications of daily stress reactivity.
Neither I nor any member of my immediate family have a significant financial arrangement or affiliation with any product or services used or discussed in my paper, nor any potential bias against another product or service.
Correspondence concerning this article should be addressed to Jessica Blaxton, Psychology Department, Metropolitan State University, St. Paul, MN 55108. Email: Jessica.blaxton@metrostate.edu
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