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Association Between Health Literacy, eHealth Literacy, and Health Outcomes Among Patients With Long-Term Conditions: A Systematic Review Efrat Neter and Esther Brainin
by Hogrefe
Special Issue: Adjustment to Chronic Illness Original Articles and Reviews
Association Between Health Literacy, eHealth Literacy, and Health Outcomes Among Patients With Long-Term Conditions
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A Systematic Review
Efrat Neter and Esther Brainin
Department of Behavioral Sciences, Ruppin Academic Center, Emeq Hefer, Israel
Abstract: The objective of this paper is to synthesize and update findings from systematic review on health literacy and health outcomes among patients with long-term conditions, and extend the review to the digital domain. Health outcomes include clinical outcomes, processes of care, and health service use. Data sources are the following: (1) studies which appeared in two previous systematic reviews in 2004 and 2011 whose participants were people with long-term conditions or elderly (n = 54); (2) articles on health literacy and health outcomes identified in an updated 2011 –2016 search (n = 26); (3) articles on eHealth literacy and its association with health outcomes (n = 8). Strength of evidence was determined by a qualitative assessment of risk of bias, consistency, and directness. There was a lack of consistent evidence on the relationship between health literacy and clinical outcomes despite the consistent evidence on the association with mortality. There was low to insufficient evidence on the association between health literacy and self-rated health/function and emotional states of anxiety and depression, alongside high evidence on lack of association with quality of life. There was insufficient to low evidence on the association between health literacy and behavioral outcomes (medication adherence, other health behaviors) and finally also low to moderate evidence on the association between health literacy and use of health services such as hospitalization and emergency department. In the eHealth literacy domain, there were few studies reporting association with health behaviors and self-rated health with inconsistent results. In conclusion, it is advocated to examine performed heath literacy and eHealth literacy in large longitudinal studies.
Keywords: health literacy, eHealth literacy, health service use, health outcomes, processes of care
Health literacy is defined by the World Health Organization as “the cognitive and social skills which determine the motivation and ability of individuals to gain access to, understand and use information in ways which promote and maintain good health” (World Health Organization, 1998, p. 20). A definition by the Institute of Medicine focuses on similar capacities that serve making “appropriate health decisions” (Cutilli, 2007; Parker, Ratzan, & Lurie, 2003). This concept is elaborated by Nutbeam (2000, 2008) as being comprised of three types. The first, functional literacy, involves reading, writing, and basic communication skills that allow functioning effectively in everyday situations. Critical literacy involves critically
analyzing information and using information to exert greater control over life events and situations. Lastly, interactive literacy comprises of extracting information and deriving meaning from different forms of communication and to apply new information to changing circumstances. Rudd, Kirsch, and Yamamoto (2004) explicate health tasks that depend on health literacy: The range encompasses activities related to health promotion (e.g., purchase food), health protection (e.g., decide among product options and use products), disease prevention (e.g., undergo screening or diagnostic tests), health care and maintenance (e.g., calculate timing for medicine), and system navigation (e.g., locate facilities or apply for benefits).
Historically, the attending physician was the primary source supplying medical and medication-related information, but nowadays a wider range of information sources
is available to the public. These information sources include traditional media and electronic media, more specifically, the Internet (Hesse et al., 2005), and the literacy skill necessary to make use of these resources is labeled eHealth literacy. eHealth literacy encompasses basic literacy as well as information, media, health, computer and scientific literacies (the lily model; Norman & Skinner, 2006). Health literacy is measured through both performance and self-report. Screening tools for clinical settings such as Shortened Test of Functional Health Literacy in Adults (S-TOFHLA; Parker, Baker, Williams, & Nurss, 1995), Rapid Estimate of Adult Literacy in Medicine (REALM; Davis et al., 1993), and Newest Vital Sign (NVS; Weiss et al., 2005) measure performance (Kiechle, Bailey, Hedlund, Viera, & Sheridan, 2015), focusing on domains that are thought to be markers of an individual’s overall capacity (Baker, 2006). Comprehensive measures such as the Health Activity Literacy Scale (HALS; Rudd et al., 2004) that include tasks in various health domains (health promotion, protection, maintenance, disease prevention, system navigation) also exist, yet a recent review on the use of health literacy measures (Mackert, Champlin, Holton, Muñoz, & Damásio, 2014) found low use of these measures and called for the development of measures that can be administered remotely online. Self-report measures that relate both to the above health domains and also to the cognitive skills involved –seeking, understanding (basic literacy and numeracy), evaluating, and applying health information –also exist (e.g., Sørensen et al., 2012; European Health Literacy Scale).
eHealth literacy is assessed most often by the self-report measure eHealth Literacy Scale (eHEALS; Norman & Skinner, 2006). It is the only measure used in more than one study (Karnoe & Kayser, 2015). The measure focuses on finding information on the Internet and assessing it. A broader self-report scale that also addresses generating information was just recently developed (Van der Vaart & Drossaert, 2017), while studies on performed eHealth literacy are scarce (Neter & Brainin, 2017; Van der Vaart et al., 2011). As electronic health resources in many forms (electronic health records, telehealth initiatives, mobile health-promoting applications, interactive health-related social media, and many online health information Websites) are changing many aspects of health care and health promotion, eHealth literacy is becoming increasingly vital in terms of health literacy. Moreover, the increased interaction with these resources, whether with health professionals, peers, or products, calls for evaluating users’ literacy in the digital health domain. Indeed, health literacy and eHealth literacy were found to be moderately associated (r = .36; Neter, Brainin, & Baron-Epel, 2015), sharing the skills of seeking and appraising/applying.
High attention is bestowed on patients’ health literacy because it is recognized as affecting the communication with healthcare providers and patients’ health outcomes (Baker et al., 2007; DeWalt, Dilling, Rosenthal, & Pignone, 2007; Paasche-Orlow & Wolf, 2007; Schillinger et al., 2002; Yin, Dreyer, Foltin, van Schaick, & Mendelsohn, 2007; Zamora & Clingerman, 2011). Poor health literacy has been reported as associated with various adverse health outcomes: navigation difficulties within the health system, inaccurate or incomplete reports related to medical history, missed doctor appointments, inaccurate use of medications in terms of timing (Baker et al., 2002; Baker, Parker, Williams, & Clark, 1998) or dosage (Baker et al., 1996), decreased rates of adherence to chronic illness regimens (Williams, Baker, Parker, & Nurss, 1998), and increased risk of hospitalization (Baker et al., 1998, 2002). Health literacy was also found to be associated with functioning in the digital domain, so that low health literacy (and related skills) are negatively related to the ability understand (Zikmund-Fisher, Exe, & Witteman, 2014), evaluate online health information and trust in online health information (Diviani, van den Putte, Giani, & van Weert, 2015). The findings on the association between health literacy and health outcomes persist after controlling for background characteristics such as socioeconomic status, age, and race (Schillinger et al., 2002), yet it is unclear what is the optimal strategy in adjusting for potential confounders (Bailey et al., 2014). On the one hand, it is argued that overadjustment could produce false-negative results of no association between health literacy and health outcomes when a true relationship actually exists (Bailey et al., 2014). On the other hand, findings on a major confounder such as intelligence indicate that much of the association between health literacy and health outcomes is accounted for by cognitive ability (Mõttus et al., 2014; Serper et al., 2014) to the point of viewing health literacy as a “domain-specific contextualized measure of basic cognitive abilities” (Reeve & Basalik, 2014). eHealth literacy is a more recent construct than health literacy, and much less research has examined its association with health outcomes (Karnoe & Kayser, 2015). Having the composite skills of eHealth literacy allows health consumers not only to increase the availability of health information (Knapp, Madden, Wang, Sloyer, & Shenkman, 2011; Milne et al., 2012; Muñoz, 2010; Neter & Brainin, 2012) but also to achieve positive health outcomes such as perceived or reported better communication with attending physician, enhanced use of medical insurance, health
behaviors, self-management of health needs, and understanding of the disease/condition (Mitsutake, Shibata, Ishii, & Oka, 2012; Neter & Brainin, 2012). A large number of reviews have been published on health literacy. Several of these reviews evaluated the association between health literacy and a broad spectrum of healthrelated outcomes, some including all populations (Berkman, Sheridan, Donahue, Halpern, Viera, et al., 2011; DeWalt, Berkman, Sheridan, Lohr, & Pignone, 2004) and some focusing on a particular segments of patients (caregivers, people with diabetes or cardiovascular diseases), tools or interventions (Bailey et al., 2014; Kiechle et al., 2015; T. W. Lee, Lee, Kim, & Kang, 2012; Taggart et al., 2012; Yuen, Knight, Ricciardelli, & Burney, 2016). The latest comprehensive review (Berkman, Sheridan, Donahue, Halpern, Viera, et al., 2011) judged the evidence on an association between health literacy and disease prevalence and severity (manifested in various clinical outcomes) as low, though the evidence on the association between health literacy and mortality was judged as high. They also inferred moderate evidence on the (negative) association between health literacy and increased use of health services, and low or insufficient evidence on processes of care as various health behaviors (Berkman, Sheridan, Donahue, Halpern, Viera, et al., 2011, pp. 101–102). As health literacy is most critical among people with long-term conditions, there is a special need to focus on them and examine its association with health outcomes across diseases, thus, the present review focuses on patients with long-term conditions and people over 65 years old (assumed to have long-term conditions). This is a population facing complex conditions requiring self-care which relies on either written materials or verbal instructions, both calling for literacy skills. The review includes studies reported in the two comprehensive reviews (Berkman, Sheridan, Donahue, Halpern, Viera, et al., 2011; DeWalt et al., 2004) as it pertains to patients with long-term conditions and older adults, using these reviews’ quality assessment. In addition, it includes studies on patients with long-term conditions and older adults published between 2011 and 2016, after these reviews were published. The current review focuses on outcomes most pertinent to patients with long-term conditions that go beyond knowledge and perceptions (e.g., perceived self-efficacy, similar to the review by Kiechle et al., 2015, p. 1540) to the following three major outcome categories: (1) patients’ outcomes (e.g., health status, functioning, well-being, health-related QoL, emotional states); (2) processes of care (e.g., patient behaviors/actions/adherence, patient–healthcare providers communication); and (3) health service outcomes (e.g., number of contacts with clinicians, hospitalization, emergency department use), viewed as a proxy measure of functional navigation (Paasche-Orlow & Wolf, 2007).
Only a single review was conducted on the association of eHealth literacy with health outcomes (Karnoe & Kayser, 2015), yet it examined many issues related to eHealth literacy; hence, the present work will conduct a systematic review focusing on health outcomes. Due to the limited amount of work accumulated thus far, community and primary care samples will be also included in the review, and not only patients with long-term conditions. The aims of the current work are therefore to (1) examine the association between health literacy and patients’ outcomes, processes of care, and health service utilization among patients with long-term conditions and (2) extend this review to the digital domain by examining the association between eHealth literacy and health outcomes, processes of care, and health service utilization, this time in a diverse population.
Methods
Materials and Search Procedures
Two literature searches were conducted. The first focused on empirical articles on health literacy and outcomes published between the years 2011 and 2016 and the second one on empirical articles on eHealth literacy and health outcomes published since 2000. A systematic search of peer-reviewed English-written empirical papers published between January 2011 and December 2016 was conducted in the following databases: CINHAL, Medline (including Cochrane Database of Systematic Reviews), PsycNet, ScienceDirect, Web of Science, and Wiley. A combination of two groups of key terms was used: health literacy and health outcomes. Additionally, manual searches of the reference lists were conducted. The search resulted in 206 papers. Two reviewers (EN/ NE) independently screened identified abstracts.
The systematic search of peer-reviewed English-written empirical papers on eHealth literacy and outcomes focused on papers published between January 2000 and December 2016. It was conducted on the following databases: CINHAL, Medline (including Cochrane Database of Systematic Reviews), PsycNet, ScienceDirect, Web of Science, and Wiley. We applied combinations of two groups of keywords: eHealth literacy (or digital health literacy) and outcomes. Additionally, manual searches of the reference lists were conducted. The search resulted in 130 papers. Two reviewers (EN/GT) independently screened identified abstracts. Lastly, articles appearing in the 2004 and 2011 comprehensive reviews on health literacy and health outcomes (Berkman, Sheridan, Donahue, Halpern, & Crotty, 2011; DeWalt et al., 2004) were all reviewed.
Identification
Screening
Record excluded (n = 141)
Records after duplicates removed (total: n = 164)
-Not chronic patient (n = 44)
-Not Health Literacy (n = 28)
-Not empirical (n = 48)
-Not English language (n = 2)
-Not quantitative (n = 4)
-Not Health Outcome (n = 15)
Included Studies included in review (n = 23)
Figure 1. PRISMA 2009 flow diagram for health literacy.
Reference lists screened and 3 additional studies included
Articles eligible for inclusion N = 26
Lastly, articles appearing in the 2004 and 2011 comprehensive reviews on health literacy and health outcomes (Berkman, Sheridan, Donahue, Halpern, & Crotty, 2011; DeWalt et al., 2004) were all reviewed.
Inclusion Criteria, Exclusion Criteria, and Data Abstraction
In the health literacy search, we (EN/NE) first selected publications which appeared in peer-reviewed journals (excluding dissertations, book chapters, qualitative studies, validation studies, narrative review articles, case reports, editorials, and letters). We then screened for empirical publications (1) which examined such outcomes as patients’ health-related outcomes, processes of care, and healthcare services use and (2) which were conducted on samples of patients with long-term conditions or older adults (Figure 1). Of the 164 identified studies (see Figure 1), 141 were excluded (44 for not including patients with long-term conditions, 28 on not being on health literacy, 48 on not being empirical, 2 for being written in a language other than English, 4 for not being quantitative, and 15 for not including a health outcome; Moher, Liberati, Tetzlaff, & Altman,
2009). In this stage, 23 articles meeting inclusion criteria were selected. Additional three articles were identified through review of the reference lists of the included articles; articles which did not employ multivariate analyses controlling for sociodemographic confounders were not included. There was an initial agreement between raters in 151 out of 164 studies (92% agreement). Discrepancies were resolved by a consensus method. Descriptive data were extracted by one researcher (EN) and then verified by the second researcher (NE).
The same procedure was applied in the eHealth literacy search except that samples from community and primary care settings were also included and statistical analyses were not inclusion criteria. Of the 130 identified studies (see Figure 2), 26 were duplicates, resulting in 104 screened studies. All 104 titles were screened, resulting in 56 studies whose abstracts were read. Reasons for exclusion of title or abstract were as follows: Twenty-nine on not being on eHealth literacy, 35 on not being empirical, 13 for not being quantitative, and 20 for not including a health outcome. In this stage, 7 articles meeting inclusion criteria were selected. One additional study was identified through the reference list of a review (Karnoe & Kayser, 2015).
Identification
Screening
Records after duplicates removed (total: n = 104)
Records assessed for eligibility (n = 104) Record excluded (n = 97)
Reasons for exclusion:
-Not eHealth Literacy (n = 29)
-Not empirical (n = 35)
-Not quantitative (n = 13)
-Not Health Outcome (n = 20)
Included Studies included in review (n = 7)
Figure 2. PRISMA 2009 flow diagram for eHealth literacy.
Coding, Data Synthesis, Data Analysis, and Quality Assessment Procedures
Findings on health literacy and outcomes are presented using three major outcome categories presented above: patients’ outcomes, processes of care, and health service outcomes. Studies which reported outcomes in more than one category are presented more than once, but their N was counted only once. The N of articles presenting results based on one study was counted once. Quality assessment of studies which appeared in the previous reviews was extracted (Berkman, Sheridan, Donahue, Halpern, Viera, et al., 2011). The data synthesis of the three outcome variables is presented in the Electronic Supplementary Material, ESM 1. Overall strength of the evidence for each outcome was qualitatively assessed using the Agency for Healthcare Research and Quality (AHRQ) guidance, by grading the strength of evidence as high, moderate, low, or insufficient on the basis of the potential risk of bias of included studies, consistency of effect across studies, directness of the evidence, and precision of the estimate (Owens et al., 2010). Risk of bias is assessed through two main elements: study design (RCT, observational; cross-sectional, prospective) and aggregate qualities, which in the current review relied
Articles eligible for inclusion N = 8
either on previous assessments of quality conducted in the previous reviews or on assessments conducted by the authors (EN and either NE or GT). Consistency is assessed by having the same direction of effect, the same sign of effect size, and narrow range of effect size; in the current review, it was assessed by the first parameter, as effect sizes were not computed. Directness refers to measuring the (ultimate) outcome of interest (i.e., direct) or alternatively measuring surrogate outcomes (i.e., indirect) or conducting indirect comparisons; in the current review, it addressed whether an ultimate outcome was measured. The last criterion, precision, refers to certainty surrounding the effect estimate, and as such an effect was not computed in the current review, this criteria was not employed. Thus, risk of bias, consistency, and directness were used in judging the overall strength of the evidence for each outcome.
Results
Description of Analyzed Studies
and 26 from the updated search, encompassing 65,065 participants (some of the studies are reported in several articles). The majority of studies were based in the USA; other original studies took place in Asia and Europe. The measures used in the studies were mostly S-TOFHLA (n = 26) and TOFHLA (n = 13), followed by the REALM (n = 26). Few studies used self-reported items or self-constructed scales. Nearly all studies assessed functional literacy and controlled for background variables. The eHealth literacy analysis included only 8 studies published mostly in Asia and North America. The earliest study examining such associations was from 2011. The studies encompassed 5,076 participants. A list of all articles included in the review appears in ESM 2.
Health Literacy and Health Outcomes
The outcomes are grouped into three main categories: patients’ outcomes, processes of care outcomes, and health service outcomes. Patients’ outcomes included diverse outcomes such as clinical (biochemical/biometric indicators), self-rated health and function, quality of life, and emotional condition. The clinical indicators were diverse, including CD4 count and viral load in the case of HIV, glycemic control among patients with diabetes, cancer stage, blood pressure (among patients with hypertension, diabetes, or HIV), anticoagulation control, infections and kidney function among patients with renal disease and complications following surgery. The most prevalent clinical indicator was glycemic control. Most studies (with few exceptions; Mancuso, 2010; Schillinger et al., 2002) adjusted for background variables (quality ranged from fair to good), and this feature did not distinguish between studies that found an association to those which did not report an association between health literacy and the clinical indicator. Most were cross-sectional (n = 21) or retrospective (n = 3), but several (n = 7) were prospective. Overall, evidence on the relationship between health literacy and clinical indicators was inconsistent across studies (association in 13 studies out of 31), and the heterogeneity did not permit the estimation of an effect. Studies did not differ in directness (all used direct assessments of outcomes). Therefore, this evidence was rated insufficient.
The evidence on perceived function and health was somewhat more consistent: 17 studies measured either self-rated health, function, limitations, or morbidity; 12 reported a positive association (with health and function) or negative (with limitations and morbidity), whereas 5 reported no association. All the latter were assessed as fair quality, whereas studies that reported an association were either of fair or of good quality. Again, studies did not differ in
directness, all measuring the outcomes of interest directly. Due to lack of consistency and prevalent use of cross-sectional design, this evidence on association between health literacy and perceived function/health was rated as low to insufficient.
The evidence on the association between health literacy and quality of life was unequivocally consistent: no association. Most studies were cross-sectional (n = 5), while two were prospective. The evidence on the association between health literacy and emotional states was less consistent: 7 of the 10 studies reported negative association, while only two found no association and one found a positive unexpected association. Again, there was no relation to quality as most studies controlled for confounds and studies did not differ in directness, all measuring the outcome of interest. The evidence was judged to be low to insufficient due to its inconsistency and high prevalence of cross-sectional design. The evidence on mortality was consistent and based on four good prospective studies including several thousand participants, all reporting a negative association between health literacy and mortality. The strength of the evidence was thus judged to be high, based on low risk for bias (i.e., design, number of participants in studies) and consistency. Processes of care included behavioral outcomes. The most prevalent behavior studied was medication adherence (n = 20), with most studies being cross-sectional (n = 14) or retrospective (n = 2) and few prospective (n = 4), while all studies controlled for background variables and did not differ in directness. Most studies (n = 14) found a positive association between health literacy and medication management/adherence, with three of the four prospective studies reporting such an association. No studies reported negative association. Due to the high risk for bias embodied in the design and relatively high consistency, the evidence was rated as low.
Similar consistency was found in other diverse healthrelated behaviors such as physical exercise, vaccinations, cancer screening, self-care, appointment keeping, or using an inhaler. The studies were in diverse patient populations: patients with diabetes, asthma, CAD, transplantation, and elderly people. Ten studies reported on a positive association between health literacy and uptake of at least one health-promoting behavior, while five studies reported no association. Again, all studies conducted multivariate analyses where confounds were taken into account and did not differ in directness (all assessed direct outcomes). All the studies that reported no association were of fair quality, and four of them were cross-sectional, while there were three good studies (among the 10) which found a positive association. Here, too, the evidence on the association was rated as low to insufficient in strength. Health service outcomes included mostly use of emergency department and hospitalization. Among the twelve studies,
three were judged as good and all three reported a negative association between health literacy and health service use; all the studies reporting no association (n = 3) were of fair quality, and overall eight of the twelve studies reported a negative association between health literacy and services use, so that adequate literate patients consumed less services. All studies measured the outcome directly. Due to the inconsistency and risk of bias in the design (high prevalence of cross-sectional), the evidence was judged as low to moderate in strength.
eHealth Literacy and Health Outcomes
Studies on eHealth literacy have for the most part (two exceptions) used the eHEALS measure and were cross-sectional (see also Karnoe & Kayser’s review, 2015). Quality assessment of the studies was evaluated using four criteria: study’s N and the representativeness of the sample [representative sample (= 4), N 500 (= 3), 250 > N < 500 (= 2), N < 250 (= 1)]; use of theoretical framework (yes = 1, no = 0), the measure being used (4 = performance, 3 = validates self-report, 1 = proxy (use) or 1-item self-report); and the design (3 = prospective or experimental, 1 = cross-sectional, 1 = multivariate analysis, could be added). Overall quality ranged from 0 to 11, with 1–5 = poor, 6–9 = fair quality, and 10–11 = good quality. There was inter-rater agreement in 30 out of the 32 evaluations (93.8%). A Cohen’s κ calculated on the overall quality score (categories: poor, fair, and good, 8 agreements out of 8 in all studies) was 1.00, p < .005 with a standard error of 0.00. Of the eight studies examining association of eHealth literacy with a health outcome, only two studies surveyed patients with long-term conditions (lung cancer survivors, HIV) while the rest examined college student and community adults. The health outcome was most often health behaviors (n = 6); in four of the studies, high eHealth literacy was found to be associated with health-promoting behaviors, while in one study, it was found to be positively associated with health-compromising behavior (risk behaviors related to HIV), and in one study, it was found as not associated with the health behavior (HPV vaccination). Self-rated health was examined in two studies and found not associated with health literacy in both cases. The strength of the evidence on both findings was judged to be moderate to low: On the one hand, the findings exhibited relative consistency and high directness (i.e., measuring the ultimate outcome of interest, albeit through self-reports), while on the other hand, there was a considerable risk of bias (expressed in small amount of studies, nonrepresentative samples, small Ns, and cross-sectional design) (Table 1). A complete list of studies used in this review is available in ESM 2.
Discussion
The present review focused on patients with long-term conditions who continuously have to manage their health and for whom health literacy can be a critical resource. The review concentrated mostly on concrete outcomes –clinical indicators, behaviors, healthcare use, while also including patients’ outcomes such as perceived health and function, quality of life, and emotional conditions. The health outcomes associated with health literacy –spanning from emotional responses and quality of life, to clinical markers and to morbidity and mortality –present a complex and intriguing picture.
Summary of Findings and Theoretical Frameworks
The only two domains with high strength of evidence concerned quality of life and mortality; in the former, there was consistently no association with health literacy, and in the latter, there was a consistent negative association. There was insufficient to low strength of evidence regarding all the other outcomes. Clinical outcomes were clearly with high heterogeneity, barring an inference on the state of the evidence beside one of insufficient evidence. Other outcomes –emotional conditions, perceived health and function, behaviors, and health service use –though with less heterogeneity, did not present a consistent direction in the association and exhibited high risk of bias mainly due to prevalence of cross-sectional design, in spite of the high directedness (Owens et al., 2010). These findings mostly reiterate those of previous reviews (Al Sayah, Majumdar, Williams, Robertson, & Johnson, 2013; Bailey et al., 2014; Berkman, Sheridan, Donahue, Halpern, Viera, et al., 2011). For example, the Berkman, Sheridan, Donahue, Halpern, and Crotty (2011) review, which examined studies across many populations, and the review of Al Sayah et al. (2013), which focused on people with diabetes, both also reported inconsistent results in the association between health literacy and clinical outcomes, leading the authors to conclude that the evidence on these outcomes is insufficient (Berkman, Sheridan, Donahue, Halpern, Viera, et al., 2011, p. 103) or weak (Al Sayah et al., 2013). The evidence of health behaviors was judged by these previous reviews to be low to insufficient, just as our evaluation indicated. They concluded the evidence on healthcare utilization to be moderate, whereas we concluded the evidence to be low to moderate; the difference in the evaluation stemmed probably from addition of studies that also added inconsistency in the direction of the results. In summary, the current review then further replicates previous reviews: The findings are similar among long-term patients across different diseases.
Study, year (Reference) eHealth literacy instrument Study sample Design and grade Outcome and association Variables used in
multivariate analysis
(Blackstock et al., 2016) eHEALS Women (n = 63); US Cross-sectional: Fair
(Britt, Collins, Wilson, Linnemeier, & Englebert, 2015) eHEALS College students (n = 396), US Cross-sectional: Fair
(Hsu, Chiang, & Yang, 2014) eHLS 1
College students (n = 525), Taiwan Cross-sectional: Fair
(Milne et al., 2012) eHEALS Lung cancer survivors (n = 83), Canada (Mitsutake et al., 2012) eHEALS General adult sample (n = 2,970), Japan Cross-sectional: Poor Cross-sectional: Fair
(Mitsutake, Shibata, Ishii, & Oka, 2016) eHEALS General adult sample (n = 2,115), Japan
(Neter & Brainin, 2012) eHEALS General adult sample (n = 1,289), Israel Cross-sectional: Fair
Cross-sectional: Fair HIV transmission SRH risk behaviors; positively associated Age, income, SRH Health behavior: HPV vaccination, no association –
Health behaviors; PA, nutrition and sleep are positively associated Quality of life, SRH; no association Colorectal cancer knowledge, screening behavior; positive association Health behaviors; PA, nutrition are positively associated SRH, no association Perceived control as mediator to intentions Health status, health concerns
Age, marital status, education
Socio-economic, Internet use frequency
(Xie, 2011) Tasks Older adults (n = 146), US Experimental: Fair Reported self-care, increased following instruction Note. eHEALS = eHealth Literacy Scale; SRH = Self-Rated Health; PA = Physical Activity.
Still, this pattern of results presents an obvious question: How is health literacy associated with mortality in a consistent manner yet not associated consistently with intermediate health outcomes, be they clinical, behavioral, emotional, or perceptual?
The answer seems to be initially methodological and then leading to theoretical conceptualization. Earlier reviews (Al Sayah et al., 2013; Bailey et al., 2014; Berkman, Sheridan, Donahue, Halpern, Viera, et al., 2011) and many empirical studies grappled with the issue of confounding factors or misestimating the relationship between health literacy and outcomes. These reviewers present and sometimes demonstrate (Berkman, Sheridan, Donahue, Halpern, & Crotty, 2011) the conflict as one between addressing confounders, on the one hand, to overadjustment by including other variables than background characteristics (e.g., self-care, treatment regimen, health status), thus producing possible false-negative results of no association between health literacy and health outcomes. Note that there were hardly findings in an opposite direction: The heterogeneity is between no association and an association in one direction (positive or negative, depending on the outcome).
Overadjustment not only masks findings, but it also creates a theoretical chaos: Variables that could be conceptualized of as mediators or moderators are analyzed as confounders. A recent review on health literacy and health
outcomes among patients with diabetes presented a framework incorporating sociodemographic determinants of health literacy, moderators such as social-cognitive factors and processes of care and clinical health outcomes (Bailey et al., 2014). The authors also noted that most of the mediators and moderators were understudied. It seems that the community of researchers in the health literacy domain needs to move beyond variables and constructs to an overall framework or multilevel theory, possibly similar to WHO’s five dimensions of adherence (Sabate, 2003). Though conceptual models on determinants and outcomes of health literacy were proposed (Paasche-Orlow & Wolf, 2007), the field did not seem to adopt them by examining the models in a longitudinal design that affords inferring about pathways. It is clear that the domain of health literacy could greatly benefit from inclusion of health literacy performance assessment tools in large longitudinal studies, e.g., longitudinal studies on midlife and aging such as Survey of Health, Ageing and Retirement in Europe (SHARE, http://www.share-project.org), English Longitudinal Study of Aging (ELSA, http://www.elsa-project.ac.uk), Midlife in the United States: A National Longitudinal Study of Health and Well-being (MIDUS, http://midus.wisc.edu).
The few studies on eHealth literacy and health outcomes do not allow inference. The field is clearly young. The paucity of studies on eHealth literacy and health outcomes compelled including all samples and not only those
focusing on patients with long-term conditions. The eHealth field clearly needs to produce more studies examining whether the digital promise in the health domain is being realized in terms of better outcomes for those who are more skilled in using the Internet for health purposes. Concurrently, the field needs, just as the field of health literacy, a conceptual framework (Norgaard et al., 2015). It should be noted that both health literacy and eHealth literacy were measured almost exclusively by validated tools, a finding reiterating recent reviews of health literacy measurement (Nguyen, Paasche-Orlow, & McCormack, 2017) and on eHealth literacy measures (Karnoe & Kayser, 2015).
Limitations and Summary
This review harbors several limitations. First, searches were limited to articles published in English. Second, the authors used the search term “health literacy,” assuming it is a widely used and accepted term rather than using all the search terms associated with the official query (mostly the names of the scales, e.g., “test of functional health literacy” or “rapid estimate of adult literacy”). Third, the findings on health literacy were briefly reported, taking into account the detailed description in previous publication (Berkman, Sheridan, Donahue, Halpern, Viera, et al., 2011). Fourth, the current review did not include in the review the control groups of RCT intervention studies; this could have added more studies, yet the decision was similar to other reviews that examined these studies separately (see Berkman, Sheridan, Donahue, Halpern, Viera, et al., 2011). An additional limitation is that few evidence concerning oral health literacy (speaking and listening skills) and outcomes exit and could be incorporated in a review. Lastly, the authors, similar to other systematic reviews (Bailey et al., 2014; Berkman, Sheridan, Donahue, Halpern, & Crotty, 2011; DeWalt et al., 2004; Kiechle et al., 2015; Taggart et al., 2012; Yuen et al., 2016), refrained from conducting a meta-analysis due to considerable heterogeneity in the samples, diseases, measures, and outcomes. Future studies could focus on either a disease or a population (e.g., caregivers) and conduct a quantitative analysis.
Despite these limitations, this review adds to the literature as it summarizes findings across different long-term conditions on a wide range of outcomes and its interpretation focuses on the conceptual level. Implications from this review go beyond a call to clinicians and educators to provide easily understood information and reduce complexity; the call is for an ecological model to be tested in longitudinal designs, or even better include the tools of health literacy and eHealth literacy (preferably performed and not self-reports) in already running longitudinal studies in the health domain.
Electronic Supplementary Materials
The electronic supplementary material is available with the online version of the article at https://doi.org/10.1027/ 1016-9040/a000350
ESM 1. Table (.pdf) Synthesis of reviews (2004, 2011) and new literature search (2011–2016) on health literacy and outcome among patients with long-term conditions. ESM 2. Text (.pdf) List of studies included in the review.
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Funding This study has been supported by the Ministry of Science and Technology, Israel to Efrat Neter (http://dx.doi.org/10.13039/ 501100006245, 3-10840).
Efrat Neter Department of Behavioral Sciences Ruppin Academic Center Beit 3 Emeq Hefer Israel neter@ruppin.ac.il
Efrat Neter (PhD) is a behavioral scientist, working at the Behavioral Sciences Department at Ruppin Academic Center. Her research interests are primarily: (1) health behavior –antecedents, decision-making, promotion, and change (including RCTs), and particularly attempting to translate laboratory findings into largescale population interventions; (2) health information search on the Internet and particularly eHealth literacy; and (3) self-management of chronic medical conditions such as multiple sclerosis, where she studies self-care behaviors and medication adherence.
Esther Brainin (PhD) is a senior lecturer at the Department of Behavioral Sciences at Ruppin Academic Center in Israel. Brainin explores a wide range of topics linked to how information and communication technologies (ICT) lead to social change. For the past 20 years, she has conducted both empirical and theoretical studies in the intersection of technology and society, the digital divide and partial usage of the Internet, and the relationship between Internet usage, social stratification, and individuals’ empowerment.
