EHealth Literacy in UK Teenagers and Young Adults: Exploration of Predictors and Factor Structure of the eHealth Literacy Scale (eHEALS)

Structural Validation and Measurement Invariance Testing of the Chinese Version of the eHealth Literacy Scale Among Undergraduates: Cross-Sectional Study

BACKGROUND

The eHealth Literacy Scale (eHEALS) was introduced in China in 2013 as one of the most important electronic health literacy measurement instruments. After a decade of development in China, it has received widespread attention, although its theoretical underpinnings have been challenged, thus demanding more robust research evidence of factorial validity and multigroup measurement properties.

OBJECTIVE

This study aimed to evaluate the Chinese version of the eHEALS in terms of its measurement properties.

METHODS

A cross-sectional survey was conducted in a university setting in China. Item statistics were checked for response distributions and floor and ceiling effects. Internal consistency reliability was confirmed with Cronbach α, split-half reliability, Cronbach α if an item was deleted, and item-total correlation. A total of 5 representative eHEALS factor structures were examined and contrasted using confirmatory factor analysis. The study used the item-level content validity index (I-CVI) and the average of the I-CVI scores of all items on the scale to assess the content validity of the dominance model. Furthermore, the validated dominance model was subsequently used to evaluate the relevance and representation of elements in the instrument and to assess measurement invariance across genders.

RESULTS

A total of 972 respondents were identified, with a Cronbach α of .92, split-half reliability of 0.88, and item-total score correlation coefficients ranging from 0.715 to 0.781. Cronbach α if an item was deleted showed that all items should be retained. Acceptable content validity was supported by I-CVIs ≥0.80. The confirmatory factor analysis confirmed that the 3-factor model was acceptable. The measurement model met all relevant fit indices: average variance extracted from 0.663 to 0.680, composite reliability from 0.810 to 0.857, chi-square divided by the df of 4.768, root mean square error of approximation of 0.062, standardized root mean squared residual of 0.020, comparative fit index (CFI) of 0.987, and Tucker-Lewis index of 0.979. In addition, the scale demonstrated error variance invariance (Δnormed fit index=-0.016, Δincremental fit index=-0.012, ΔTucker-Lewis index=0.005, Δcomparative fit index=-0.012, Δrelative fit index=0.005, and Δroot mean square error of approximation=0.005).

CONCLUSIONS

A 3-factor model of the Chinese version of the eHEALS fits best, and our findings provide evidence for the strict measurement invariance of the instrument regarding gender.

Adolescent pursuit of health information online during the COVID-19 pandemic: The roles played by eHealth literacy and psychological distress

COVID-19 has led to an increase in mental health problems for adolescents. In this study, we examined the factors related to the eHealth literacy of adolescents and how that impacted their pursuit of health information and mental health information online during the COVID-19 pandemic. We analyzed data from the 2020 Taiwan Communication Survey, which involved a total of 1,250 national representative adolescents who completed an online questionnaire. The results showed that two-thirds of adolescents reported searching for health information online, and about half of them reported searching for mental health information online during the COVID-19 pandemic. Multivariate analysis results indicated that adolescents who spent more time learning online, had higher levels of bonding social capital and self-determination, and had higher levels of parental active internet mediation were more likely to have higher levels of eHealth literacy. In addition, multivariate analysis results showed that adolescents who had higher levels of eHealth literacy and had higher depression and anxiety were more likely to seek health information and mental health information online. In conclusion, the levels of eHealth literacy and psychological distress of adolescents played a crucial role in their pursuit of health information and mental health information online during the COVID-19 pandemic.

The association among eHealth literacy, depressive symptoms and health-related quality of life among older people: A cross-section study

BACKGROUND

eHealth literacy can facilitate the uptake of benefits of health for older persons. The aim of this study was to examine the association of eHealth literacy with depression, health-related quality of life (HRQoL) among older persons.

METHODS

A survey of 6183 participants (aged 60 years and above) from 17 communities was conducted in June 2019. Participants answered questions related to basic information, eHealth literacy scale (eHEALS), geriatric depression scale and the short-form health survey (SF-36). Mediation model and a linear regression analysis were performed to explore the association between the eHEALS scores and related factors.

RESULTS

The mean score of eHEALS was 21.17 (SD = 8.25). eHEALS was significant higher in men, those with living in the city, those with high educated and stable income and those with living with children, as compared to their counterparts, respectively. Moreover, chronic diseases and depressive symptoms negatively associated with eHEALS, while actively obtaining health information and physical activity positively influenced eHEALS. Furthermore, depressive symptoms had direct and indirect effects on HRQoL, as mediated by eHealth literacy.

CONCLUSIONS

The eHEALS acts as a mediator between depressive symptoms and HRQoL. As eHealth literacy is a protector for older people, efforts to improve the older persons' eHealth literacy could help to maintain health status. Therefore, healthcare providers formulate effective programs to improve eHealth literacy for older persons, which can bring benefits for health ageing.

Development and psychometric evaluation of a new brief scale to measure eHealth literacy in people with type 2 diabetes

Background

The internet has become a major source of health information, and obtaining appropriate information requires various abilities and skills, labeled as electronic health literacy (eHealth literacy). The existing instruments for measuring eHealth literacy are outdated because they were developed during the Web 1.0 era, or not sufficiently sensitive for people with a specific condition or disease because they were designed to assess eHealth literacy over a broad range for a general population. Approximately one in ten adults worldwide live with diabetes. Health professionals have a responsibility to identify patients with low eHealth literacy to prevent them from obtaining misleading internet diabetes information.

Aims

The aims were to develop a condition-specific eHealth literacy scale for diabetes and to evaluate its psychometric properties among people with type 2 diabetes.

Methods

An instrument development design was used. This study recruited 453 people diagnosed with type 2 diabetes at the outpatient clinics of hospitals in 2021. Psychometric properties (internal consistency, measurement invariance, and content, structural, convergent, and known-groups validities) were analyzed.

Results

An expert panel assessed content validity. Exploratory factor analysis, exploratory graph analysis, and confirmatory factor analysis (CFA) for structural validity yielded a two-factor solution (CFI = 0.977, SRMR = 0.029, RMSEA = 0.077). Cronbach’s alpha and omega values were excellent for each factor (0.87–0.94). Multigroup CFA yielded configural and metric measurement invariance across the gender, age, and glycemic control status groups. Convergent validity with a comparator instrument to measure health literacy was supported by a moderate correlation, and known-groups validity determined using groups with different internet-use frequencies was satisfied with a high effect size.

Conclusion

A new condition-specific eHealth literacy scale for people with type 2 diabetes was developed, comprising 10 items. The scale exhibited good psychometric properties; however, test–retest reliability must be determined for the stability of the scale and cross-cultural validity is required among different languages. The brief scale has the merits of being feasible to use in busy clinical practice and being less burdensome to respondents. The scale can be applied in clinical trials of internet-based diabetes interventions for assessing the eHealth literacy of respondents.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12912-022-01062-2.

Factor Structure of the eHEALS

Abstract. The dimensionality of the eHEALS has been the subject of some controversy. Sample populations and language versions vary widely, as do the employed statistical methods to assess dimensionality. In previous research, we assessed the factor structure in two different samples testing 1 vs. 2 and 1 vs. 2 vs. 3 correlated factors. The objective of this reanalysis was to assess whether the 3-factor model fitted better than the 2- and 1-factor models. We analyzed data from a 2009 cross-sectional survey on health literacy in grade 12 ( n = 327) using CFA. All factor models of the eHEALS showed unsatisfactory model fit. A subsequent exploratory bifactor analysis confirmed multidimensionality and indicated that Item 2 was problematic. When this item was excluded from the correlated factor models, model fit improved, and the 3-factor model showed the best fit. The results in our sample of 12th-grade students offer some support to the German eHEALS having a 3-factor structure similar to the results from our previous research in women aged 50. The replicability of the fit pattern in a different sample and setting was limited by diverging results on Item 2.

Measuring health literacy: A systematic review and bibliometric analysis of instruments from 1993 to 2021

BACKGROUND

It has been about 30 years since the first health literacy instrument was developed. This study aimed to review all existing instruments to summarize the current knowledge on the development of existing measurement instruments and their possible translation and validation in other languages different from the original languages.

METHODS

The review was conducted using PubMed, Web of Science, Scopus, and Google Scholar on all published papers on health literacy instrument development and psychometric properties in English biomedical journals from 1993 to the end of 2021.

RESULTS

The findings were summarized and synthesized on several headings, including general instruments, condition specific health literacy instruments (disease & content), population- specific instruments, and electronic health. Overall, 4848 citations were retrieved. After removing duplicates (n = 2336) and non-related papers (n = 2175), 361 studies (162 papers introducing an instrument and 199 papers reporting translation and psychometric properties of an original instrument) were selected for the final review. The original instruments included 39 general health literacy instruments, 90 condition specific (disease or content) health literacy instruments, 22 population- specific instruments, and 11 electronic health literacy instruments. Almost all papers reported reliability and validity, and the findings indicated that most existing health literacy instruments benefit from some relatively good psychometric properties.

CONCLUSION

This review highlighted that there were more than enough instruments for measuring health literacy. In addition, we found that a number of instruments did not report psychometric properties sufficiently. However, evidence suggest that well developed instruments and those reported adequate measures of validation could be helpful if appropriately selected based on objectives of a given study. Perhaps an authorized institution such as World Health Organization should take responsibility and provide a clear guideline for measuring health literacy as appropriate.

Need for cognition and burnout in teachers – A replication and extension study

Burnout has become more prevalent, mainly in social jobs, and there is evidence that certain personality traits protect against burnout. Only recently, studies have focused on investment traits like Need for Cognition (NFC), the stable intrinsic motivation to seek out and enjoy effortful cognitive activities. This study had three aims: First, the replication of findings by Grass et al. (2018), who investigated NFC and the burnout subscale reduced personal efficacy in student teachers, in a sample of 180 teachers. Second, investigating the role of perceived demands and resources in the context of NFC and burnout. And finally, creating an exploratory model for further research. The results indicated that unlike the student sample, the teachers’ association of NFC and reduced personal efficacy was mediated by self-control but not reappraisal. Teachers with higher NFC and self-control also had lower burnout because they experienced their resources as fitting to the demands.

Adolescents' self-efficacy and digital health literacy: a cross-sectional mixed methods study

BACKGROUND

The internet and social media are increasingly popular sources of health information for adolescents. Using online health information requires digital health literacy, consisting of literacy, analytical skills and personal capabilities such as self-efficacy. Appraising trustworthiness and relevance of online health information requires critical health literacy to discriminate between sources, critically analyse meaning and relevance, and use information for personal health. Adolescents with poor digital health literacy risk using misinformation, with potential negative health outcomes. We aimed to understand adolescents' contemporary digital health literacy and compared self-efficacy with capability.

METHODS

Adolescents (12-17 years) completed an eHEALS self-report digital health literacy measure, a practical search task using a think-aloud protocol and an interview to capture perceived and actual digital health literacy. eHEALS scores were generated using descriptive statistics, search tasks were analysed using an observation checklist and interviews were thematically analysed based on Social Cognitive Theory, focussing on self-efficacy.

RESULTS

Twenty-one participants generally had high self-efficacy using online health information but perceived their digital health literacy to be higher than demonstrated. They accessed online health information unintentionally on social media and intentionally via search engines. They appraised information medium, source and content using general internet searching heuristics taught at school. Information on social media was considered less trustworthy than websites, but participants used similar appraisal strategies for both; some search/appraisal heuristics were insufficiently nuanced for digital health information, sometimes resulting in misplaced trust or diminished self-efficacy. Participants felt anxious or relieved after finding online health information, depending on content, understanding and satisfaction. They did not act on information without parental and/or health professional advice. They rarely discussed findings with health professionals but would welcome discussions and learning how to find and appraise online health information.

CONCLUSIONS

Whilst adolescents possess many important digital health literacy skills and generally feel self-efficacious in using them, their critical health literacy needs improving. Adolescents desire increased digital health literacy so they can confidently appraise health information they find online and on social media. Co-designed educational interventions with adolescents and health providers are required.

How to predict the electronic health literacy of Chinese primary and secondary school students?: establishment of a model and web nomograms

Background

The internet has become an important resource for the public to obtain health information. Therefore, the ability to obtain and use such resources has become important for health literacy. This study aimed to establish a prediction model of Chinese students’ electronic health literacy (EHL) to guide government policymaking and parental interventions, identify the predictors of EHL in Chinese students using random forests, and establish a corresponding prediction model to help policymakers and parents determine whether primary and secondary school students have high EHL.

Methods

This is a cross-sectional study. From June to August 2021, a cluster sample survey was conducted with 1,300 students from seven primary and secondary schools in Shaanxi Province, China. We evaluated 1,235 primary and secondary school students using the e-health literacy scale. The data were divided into training and testing datasets in a 70:30 ratio for further analysis using random forest. The predictive accuracy of the score was measured using the area under the receiver operating characteristic curve. We also used decision curve analysis to determine the usefulness of the prediction model by quantifying the net benefits at different threshold probabilities in the validation dataset. 

Results

We found that 33.6% of students had high EHL. The univariate analysis showed that age (P < 0.001), grade (P < 0.001), employment status (P < 0.001), household location (P < 0.001), parental phubbing behavior (P < 0.001), and general self-efficacy (P < 0.001) were significantly associated with EHL. A random forest classification model was developed with the training dataset (872 students), and seven variables were confirmed as important: age, grade, employment status, father education level, game time, parental phubbing behavior, and general self-efficacy. The validation of the model showed good discrimination, with an area under the curve of 0.975 in the training dataset and 0.738 in the testing dataset. The model was translated into an online risk calculator, which is freely available (https://xietao.shinyapps.io/DynNomapp/).

Conclusions

In this study, an intuitive tool to predict the EHL of Chinese primary and secondary school students was developed and validated.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-13421-4.

eHealth literacy of patients attending a primary care clinic in Malaysia and its associated factors: A cross-sectional study

BACKGROUND

People are overloaded with online health information (OHI) of variable quality. eHealth literacy is important for people to acquire and appraise reliable information to make health-related decisions. While eHealth literacy is widely studied in developed countries, few studies have been conducted among patients in low- and middle-income countries (LMICs).

OBJECTIVE

We aimed to determine the level of eHealth literacy in patients attending a primary care clinic in Malaysia and its associated factors.

METHODS

A cross-sectional study using a self-administered questionnaire was conducted in an urban primary care clinic. We used a systematic random sampling method to select patients aged 18 years and above who attended the clinic. The eHealth literacy scale (eHEALS) was used to measure eHealth literacy.

RESULTS

A total of 381 participants were included. The mean eHEALS was 24.4 ± 7.6. The eHEALS statements related to skills in appraising OHI were scored lower than statements related to looking for online resources. Higher education level of attending upper secondary school (AOR 2.53, 95% CI 1.05-6.11), tertiary education (AOR 4.05, 95% CI 1.60-10.25), higher monthly household income of >US$470 (AOR 1.95, 95% CI 1.07-3.56), and those who had sought OHI in the past month (AOR 1.95, 95% CI 1.13-3.36) were associated with a higher eHealth literacy level.

CONCLUSIONS

This study found a low eHealth literacy level among primary care patients in Malaysia. While the patients were confident in searching for OHI, they lacked skills in appraising them. Our findings inform the interventions for improving eHealth literacy in LMICs, especially educating the public about OHI appraisal.

Digitization and Health in Germany: Cross-sectional Nationwide Survey

Background

Digital technologies are shaping medicine and public health.

Objective

The aim of this study was to investigate the attitudes toward and the use of digital technologies for health-related purposes using a nationwide survey.

Methods

We performed a cross-sectional study using a panel sample of internet users selected from the general population living in Germany. Responses to a survey with 28 items were collected using computer-assisted telephone interviews conducted in October 2020. The items were divided into four topics: (1) general attitudes toward digitization, (2) COVID-19 pandemic, (3) physical activity, and (4) perceived digital health (eHealth) literacy measured with the eHealth Literacy Scale (eHEALS; sum score of 8=lowest to 40=highest perceived eHealth literacy). The data were analyzed in IBM-SPSS24 using relative frequencies. Three univariate multiple regression analyses (linear or binary logistic) were performed to investigate the associations among the sociodemographic factors (age, gender, education, and household income) and digital technology use.

Results

The participants included 1014 internet users (n=528, 52.07% women) aged 14 to 93 years (mean 54, SD 17). Among all participants, 66.47% (674/1014) completed up to tertiary (primary and secondary) education and 45.07% (457/1017) reported a household income of up to 3500 Euro/month (1 Euro=US $1.18). Over half (579/1014, 57.10%) reported having used digital technologies for health-related purposes. The majority (898/1014, 88.56%) noted that digitization will be important for therapy and health care, in the future. Only 25.64% (260/1014) reported interest in smartphone apps for health promotion/prevention and 42.70% (433/1014) downloaded the COVID-19 contact-tracing app. Although 52.47% (532/1014) reported that they come across inaccurate digital information on the COVID-19 pandemic, 78.01% (791/1014) were confident in their ability to recognize such inaccurate information. Among those who use digital technologies for moderate physical activity (n=220), 187 (85.0%) found such technologies easy to use and 140 (63.6%) reported using them regularly (at least once a week). Although the perceived eHealth literacy was high (eHEALS mean score 31 points, SD 6), less than half (43.10%, 400/928) were confident in using digital information for health decisions. The use of digital technologies for health was associated with higher household income (odds ratio [OR] 1.28, 95% CI 1.11-1.47). The use of digital technologies for physical activity was associated with younger age (OR 0.95, 95% CI 0.94-0.96) and more education (OR 1.22, 95% CI 1.01-1.46). A higher perceived eHealth literacy score was associated with younger age (β=–.22, P<.001), higher household income (β=.21, P<.001), and more education (β=.14, P<.001).

Conclusions

Internet users in Germany expect that digitization will affect preventive and therapeutic health care in the future. The facilitators and barriers associated with the use of digital technologies for health warrant further research. A gap exists between high confidence in the perceived ability to evaluate digital information and low trust in internet-based information on the COVID-19 pandemic and health decisions.

eHealth Literacy Instruments: Systematic Review of Measurement Properties

Background

The internet is now a major source of health information. With the growth of internet users, eHealth literacy has emerged as a new concept for digital health care. Therefore, health professionals need to consider the eHealth literacy of consumers when providing care utilizing digital health technologies.

Objective

This study aimed to identify currently available eHealth literacy instruments and evaluate their measurement properties to provide robust evidence to researchers and clinicians who are selecting an eHealth literacy instrument.

Methods

We conducted a systematic review and meta-analysis of self-reported eHealth literacy instruments by applying the updated COSMIN (COnsensus-based Standards for the selection of health Measurement INstruments) methodology.

Results

This study included 7 instruments from 41 articles describing 57 psychometric studies, as identified in 4 databases (PubMed, CINAHL, Embase, and PsycInfo). No eHealth literacy instrument provided evidence for all measurement properties. The eHealth literacy scale (eHEALS) was originally developed with a single-factor structure under the definition of eHealth literacy before the rise of social media and the mobile web. That instrument was evaluated in 18 different languages and 26 countries, involving diverse populations. However, various other factor structures were exhibited: 7 types of two-factor structures, 3 types of three-factor structures, and 1 bifactor structure. The transactional eHealth literacy instrument (TeHLI) was developed to reflect the broader concept of eHealth literacy and was demonstrated to have a sufficient low-quality and very low-quality evidence for content validity (relevance, comprehensiveness, and comprehensibility) and sufficient high-quality evidence for structural validity and internal consistency; however, that instrument has rarely been evaluated.

Conclusions

The eHealth literacy scale was the most frequently investigated instrument. However, it is strongly recommended that the instrument's content be updated to reflect recent advancements in digital health technologies. In addition, the transactional eHealth literacy instrument needs improvements in content validity and further psychometric studies to increase the credibility of its synthesized evidence.

Evaluating the psychometric properties of the eHealth Literacy Scale in Brazilian adults

OBJECTIVE

To translate and adapt the eHealth Literacy Scale for the cultural reality of Brazil and to evaluate the psychometric properties of its Brazilian Portuguese version.

METHODS

The instrument was translated and adapted to Brazilian Portuguese and applied to a sample of 502 individuals from 18 to 80 years old who lived in the surrounding areas of six Family Health Units of a city in the countryside of the state of São Paulo, Brazil. The data was evaluated using exploratory and confirmatory factor analysis, item response theory, and instrument reliability measures (Cronbach's alpha and McDonald's omega).

RESULTS

The eHealth Literacy Scale - Brazilian version (eHEALS-Br) presented an excellent internal consistency (α = 0.95 e ω = 0.95), with only one dimension and an explained variation of 81.79%.

CONCLUSIONS

The Brazilian version of the instrument showed excellent psychometric properties to measure the levels of digital health literacy in adults from the country.

COVID-19 Misinformation Online and Health Literacy: A Brief Overview

Low digital health literacy affects large percentages of populations around the world and is a direct contributor to the spread of COVID-19-related online misinformation (together with bots). The ease and 'viral' nature of social media sharing further complicate the situation. This paper provides a quick overview of the magnitude of the problem of COVID-19 misinformation on social media, its devastating effects, and its intricate relation to digital health literacy. The main strategies, methods and services that can be used to detect and prevent the spread of COVID-19 misinformation, including machine learning-based approaches, health literacy guidelines, checklists, mythbusters and fact-checkers, are then briefly reviewed. Given the complexity of the COVID-19 infodemic, it is very unlikely that any of these approaches or tools will be fully effective alone in stopping the spread of COVID-19 misinformation. Instead, a mixed, synergistic approach, combining the best of these strategies, methods, and services together, is highly recommended in tackling online health misinformation, and mitigating its negative effects in COVID-19 and future pandemics. Furthermore, techniques and tools should ideally focus on evaluating both the message (information content) and the messenger (information author/source) and not just rely on assessing the latter as a quick and easy proxy for the trustworthiness and truthfulness of the former. Surveying and improving population digital health literacy levels are also essential for future infodemic preparedness.