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Currently, the rapid aging of global population, especially in low- and middle-income countries, is placing changing demands on health care systems. The preparation of the population for adequate eHealth literacy and good digital health is one of the challenges of social policy. The willingness to understand eHealth literacy and telemedicine use across different age groups of the population will help identify loopholes and bottlenecks in the implementation and help to develop appropriate solutions. Currently, studies on the status of eHealth literacy across different age ranges remain limited and scarce. In this study, we aimed to investigate the prevalence and factors associated with adequate eHealth literacy, including attitudes toward eHealth literacy and willingness to use telemedicine as an example of digital technology. We focused on the comparison between older people (aged ≥60 years) and younger adult groups in Thailand, a middle-income country. We conducted a cross-sectional, observational study from January 2021 to July 2021. A total of 400 participants who visited the outpatient department of Siriraj Hospital were recruited and completed questionnaires collecting demographic information, frequency of internet use, and devices used for accessing the internet. eHealth literacy was assessed using the eHAELS (eHealth Literacy Scale) questionnaire. We also explored the participants' attitude and willingness to use telemedicine. We applied univariable logistic regression analysis to elucidate the factors associated with eHealth literacy and willingness to use telemedicine. Our study revealed that the older participants had lower level of eHealth literacy compared to younger participants. Using an eHAELS score ≥26 points to define 'adequate eHealth literacy,' 74.0% (n=97) of older adults compared to 22.7% (n=61) of younger adults had inadequate eHealth literacy. Only 19.8% (n=26) of older adults, compared to 65.1% (n=175) of younger adults showed high levels of eHealth literacy defined by exploring each item using the eHEALS tool. The items with the lowest level of eHealth literacy among older adults pertained to confidence in finding and applying health information for self-care and in using information from the internet for making health decisions. In terms of attitude and interest toward telemedicine use, confidence in security, perceived convenience of telemedicine, and adequate eHealth literacy were the three strongest factors associated with willingness to use telemedicine, with odds ratios (ORs) of 5.90 (95% CI 3.43-10.15), 5.43(95% CI 3.12-9.43), and 4.45 (95% CI 2.60-7.62), respectively. Additionally, the younger adults were more likely to be interested in using telemedicine with an OR of 2.02 (95% CI 1.21-33.37). Our study addressed the low level of eHealth literacy, with more concerning figures among older adults compared to younger adults in a middle-income country. The willingness to adopt digital technologies related strongly to level of eHealth literacy. This information may be beneficial for guiding further improvements and promoting digital health in low- and middle-income settings facing the challenges of an aging population.

The rapid evolution of digital health technologies, particularly within the Web 3.0 framework, has underscored eHealth literacy (eHL) as a critical competency for patients engaging with digital health care platforms. Patients in sustained hospital stays, often in vulnerable conditions, face unique challenges in using eHealth tools effectively. However, existing eHL assessment tools are insufficient to address the intricate and dynamic demands of contemporary health care systems, especially for individuals under continuous hospital care. This study aimed to develop the Adult Inpatient eHealth Literacy Scale (AIPeHLS), a comprehensive, multidimensional tool grounded in the Lily Model, to evaluate eHL among adult inpatients within the context of digital health care innovations. The development of the AIPeHLS followed a systematic, multiphase process. Initial item pool generation was informed by a literature review and then refined using the Delphi method, resulting in a preliminary set of 53 items spanning 6 dimensions of the Lily Model. The scale was refined through a pilot survey among 100 individuals requiring inpatient care, followed by item analysis and exploratory factor analysis (EFA). Validation was achieved via a cross-sectional study with 532 participants, using confirmatory factor analysis (CFA) to verify the scale structure, alongside evaluations of convergent, discriminant, criterion-related, and content validity. Reliability was assessed using Cronbach α, Omega, and split-half reliability. The finalized AIPeHLS comprised 44 items across 6 dimensions: traditional literacy, information literacy, media literacy, health literacy, computer literacy, and scientific literacy, reflecting the skills necessary in the Web 3.0 context. Both EFA and CFA confirmed the 6-factor structure, demonstrating acceptable model fit indices (χ²=1974.654 (df=887), root mean square error of approximation=0.048, comparative fit index=0.957, normed fit index=0.925, and incremental fit index=0.957). The scale exhibited robust content validity, convergent and discriminant validity, criterion-related validity, and high internal consistency, with a Cronbach α of .965, Omega coefficient of 0.962, and a split-half reliability of 0.791 for the entire scale. The 44-item AIPeHLS was found to be a reliable and valid instrument for assessing eHL in adult inpatients in the evolving Web 3.0 context. Its comprehensive framework and strong psychometric properties make it an effective tool for health care providers to understand patients' digital health competencies and tailor interventions accordingly. For researchers, our findings provided opportunities to explore the relationship between eHL and health outcomes, while offering valuable insights into the development of more effective eHealth interventions and policies.

Scales for measuring health literacy and numeracy have been broadly classified into performance-based (objective) and self-reported (subjective) scales. Both types of scales have been widely used in research and practice; however, they are not always consistent and may assess different latent constructs. Furthermore, an increasing number of objective measures have been developed, and it is unclear how many latent factors should be assumed. This study aimed to examine the psychometric properties and factor structure of items assessing objective health literacy across multiple scales and to clarify which aspects of objective health literacy would be correlated with subjective measures, as well as health behaviors and lifestyles. A total of 5 objective scales (72 items in total) were administered to Japanese-speaking adults (N=16,097; women: 7722/16,097, 48%; mean age 54.89, SD 16.46 years). The analyzed scales included items assessing the numeracy, comprehension, and application of health information, some of which were contextualized for specific diseases, such as diabetes and cancer. Participants' responses were submitted to exploratory factor analysis, and individual factor scores were calculated to test correlations with subjective health literacy, health behavior, and lifestyle. Exploratory factor analysis identified 3 factors, which were interpreted as conceptual knowledge, numeracy, and synthesis. The conceptual knowledge factor consisted of items about medical word comprehension. All numeracy items loaded onto the same factor, even when contextualized for different diseases. The synthesis factor was characterized by items assessing the ability to read and understand health-related information and make judgments on it using one's own knowledge. The identified factors showed high interfactor correlations (r values 0.53-0.64) and small-to-moderate correlations with subjective health literacy (r values 0.14-0.45). Additionally, each factor indicated small positive correlations with healthy diet and nutrition and lower substance use (r values 0.17-0.26). Our findings suggest that scales of objective health literacy have at least three latent constructs (ie, conceptual knowledge, numeracy, and synthesis) and that disease specificity is not psychometrically prominent. Each factor has some overlap with subjective health literacy, but overall, subjective and objective health literacy should be interpreted as independent constructs, given the small-to-modest correlations.

Individuals with serious mental illness increasingly use digital devices and the internet to access health information and services but often face challenges when navigating digital tools, which may limit the benefits they receive from online health resources and digital health care services. The objective of our study was to assess digital health literacy among individuals with serious mental illness and identify factors influencing this literacy. Participants were recruited, using convenience sampling, from 2 psychiatric clinics, 1 day-care center, and 4 halfway houses in Taipei, Taiwan, between May 2024 and February 2025. Self-reported data were collected using a survey that incorporated the eHealth Literacy Scale, the Attitudes Toward Computer/Internet Questionnaire, and the Mobile Device Proficiency Questionnaire. Generalized linear modeling was applied to identify factors associated with digital health literacy. Among 255 participants included in the analysis, 83.5% (n=213) reported owning at least 1 digital device. Digital health literacy was significantly lower among individuals who reported greater perceived difficulty in using digital tools (B=-1.533, 95% CI -2.350 to -0.717; P<.001) and higher distrust in online information (B=-0.986, 95% CI -1.916 to -0.056; P=.04). By contrast, greater mobile device proficiency (B=0.144, 95% CI 0.008-0.281; P=.04) and self-efficacy (B=1.777, 95% CI 0.376-3.177; P=.01) were positively associated with digital health literacy. Despite widespread device ownership, digital health literacy was varied and generally suboptimal among patients with serious mental illness. Perceived difficulty and distrust emerged as major barriers; proficiency and self-efficacy facilitated higher literacy. These findings highlight the need for mental health professionals to integrate tailored digital skills training, confidence-building strategies, and ongoing support into digital health interventions for individuals with serious mental illnesses.

Abstract BackgroundIncreasing psychosocial burdens, such as stress and anxiety, underscore the need for accessible and effective prevention programs. Hybrid approaches, combining in-person and digital components, aim to reduce barriers and enhance flexibility. However, their effectiveness depends on participants’ eHealth literacy, which is associated with their ability to engage with digital tools. Understanding how psychosocial characteristics relate to eHealth literacy can provide insights for improving intervention design. ObjectiveThis study uses cluster analysis to explore the relationship between psychosocial characteristics and eHealth literacy in a hybrid mental health prevention program. By identifying distinct psychosocial profiles and analyzing their differences in eHealth literacy levels and patterns, this person-centered approach enables a nuanced understanding of eHealth literacy disparities beyond traditional variable-centered linear models. In addition, the study examines how sociodemographic variables are associated with eHealth literacy, providing insights into the role of psychosocial diversity in hybrid prevention programs. MethodsA cross-sectional study was conducted with participants of the RV Fit Mental Health intervention (January 2024–December 2024). Psychosocial characteristics, including anxiety, depression, optimism, pessimism, quality of life, self-efficacy, stress, and work ability, were assessed alongside eHealth literacy (eHealth Literacy and Use Scale [eHLUS], eHealth Literacy Scale [eHEALS]). To identify distinct psychosocial profiles, cluster analysis was used. A generalized linear model was applied to analyze associations between cluster membership, eHealth literacy, and sociodemographic variables. Finally, correlation matrices were used to further explore the relationships between psychosocial characteristics and eHealth literacy. ResultsA total of 173 participants were included. Four clusters were identified based on psychosocial characteristics. Significant associations were found between cluster membership and eHealth literacy, including the overall eHLUS score (PP ConclusionsThe cluster analysis identified distinct psychosocial profiles with varying levels of eHealth literacy, demonstrating that psychosocial characteristics are associated with eHealth literacy in diverse ways. These findings underscore the need to consider subgroup-specific needs in hybrid prevention programs. Certain groups may require additional support to effectively navigate eHealth tools. These findings emphasize the relevance of tailored intervention strategies that account for psychosocial diversity in eHealth engagement.

Hypertension represents an important global health challenge, closely linked to cardiovascular diseases and elevated premature mortality rates. Prehypertension, defined as elevated blood pressure not meeting the diagnostic criteria for hypertension, necessitates early intervention to prevent disease progression. Health literacy, defined as the capacity to comprehend and use health-related information, is a key determinant of health outcomes but has rarely been studied in the context of prehypertension prevention. This study investigated the association between health literacy and prehypertension in South Korean adults. Unlike prior research focusing on treatment adherence in diagnosed patients, this study used the most recent nationally representative data to explore how domain-specific health literacy is associated with prehypertension across various subgroups, identifying potential mechanisms for intervention. Data were obtained from the 2023 Korea National Health and Nutrition Examination Survey, a nationally representative cross-sectional study. A stratified, multistage clustered sampling design was used to invite participants. Adults aged 19 years and older (N=1873) who completed the Korean Health Literacy Index were included. Prehypertension was defined as a systolic blood pressure of 130 to 139 mm Hg or a diastolic blood pressure of 80 to 89 mm Hg. A multivariable survey-weighted logistic regression model was used to assess the associations between health literacy and prehypertension, adjusting for sociodemographic and health-related covariates. Of the 1873 participants, 319 (17.0%) had prehypertension, and 1098 (58.6%) showed low health literacy. After adjustment, those with low health literacy had a 43% higher likelihood of prehypertension (odds ratio 1.43, 95% CI 1.07-1.91) than those with high health literacy. Subgroup analyses revealed that the protective impact of health literacy is not uniform but is modulated by demographic contexts. The observed patterns may reflect three potential mechanisms: (1) motivation for and dependency on health information (eg, in women, middle-aged, lower education, and unemployed groups), (2) synergy between health literacy and resources (eg, in high-income, urban, married, and employer-insured groups), and (3) preventive efficacy in low-risk populations. Low health literacy was significantly associated with prehypertension, with variations across subgroups suggesting context-dependent mechanisms. Health literacy may serve as a modifiable determinant and compensatory resource for cardiovascular risk prevention, particularly in populations with limited access to health care. Targeted interventions that address domain-specific health literacy deficits are needed to reduce the prehypertension burden.

The use of digital health technology in diabetes self-care is increasing, making eHealth literacy an important factor to consider among people with type 1 diabetes. There are very few studies investigating eHealth literacy among adults with type 1 diabetes, highlighting the need to explore this area further. The aim of this study was to explore associations between eHealth literacy and demographic factors, disease-specific factors, and well-being among adults with type 1 diabetes. The study used data from a larger cross-sectional survey conducted among adults with type 1 diabetes in Sweden (N=301). Participants were recruited using a convenience sampling method primarily through advertisements on social media. Data were collected between September and November 2022 primarily through a web-based survey, although participants could opt to answer a paper-based survey. Screening questions at the beginning of the survey determined eligibility to participate. In this study, eHealth literacy was assessed using the Swedish version of the eHealth Literacy Scale (Sw-eHEALS). The predictor variables, well-being was assessed using the World Health Organization-5 Well-Being Index and psychosocial self-efficacy using the Swedish version of the Diabetes Empowerment Scale. The survey also included research group-developed questions on demographic and disease-specific variables as well as digital health technology use. Data were analyzed using multiple linear regression presented as nested models. A sample size of 270 participants was required in order to detect an association between the dependent and predictor variables using a regression model based on an F test. The final sample size included in the nested regression model was 285. The mean Sw-eHEALS score was 33.42 (SD 5.32; range 8-40). The model involving both demographic and disease-specific variables explained 31.5% of the total variation in eHealth literacy and was deemed the best-fitting model. Younger age (P=.01; B=-0.07, SE=0.03;95% CI -0.12 to -0.02), lower self-reported glycated hemoglobin levels (P=.04; B=-0.06, SE=0.03; 95% CI -0.12 to 0.00), and higher psychosocial self-efficacy (P<.001; B=3.72, SE=0.53; 95% CI 2.68-4.75) were found associated with higher Sw-eHEALS scores when adjusted for demographic and disease-specific variables in this model. Well-being was not associated with eHealth literacy in this study. The demographic and disease-specific factors explained the variation in eHealth literacy in this sample. Further studies in this area using newer eHealth literacy tools are important to validate our findings. The study highlights the importance of development and testing of interventions to improve eHealth literacy in this population for better glucose control. These eHealth literacy interventions should be tailored to meet the needs of people in varying age groups and with differing levels of psychosocial self-efficacy.

Tailoring is an important strategy to improve uptake and efficacy of medical information and guidance provided through eHealth interventions. Given the rapid expansion of eHealth, understanding the design rationale of such tailored interventions is vital for further development of and research into eHealth interventions aimed at improving health and healthy behavior. This systematic review examines the use of health literacy concepts through tailoring strategies in digital health interventions (eHealth) aimed at improving health and how these elements inform the overall design rationale. A systematic search of PubMed, PsycINFO, Web of Science, and ACM databases yielded 31 eligible randomized trials that focused on adult health improvement through eHealth interventions. Eligible studies compared tailored versus nontailored eHealth interventions for adults, excluding non-English papers and those addressing solely readability or targeting populations with accessibility barriers. Data extraction focused on study characteristics, health literacy components, tailoring methods, and design rationales, with study quality evaluated using Quality Assessment for Diverse Studies (QuADS) by independent reviewers. Most interventions applied both cognitive and social health literacy concepts and predominantly used content matching as a tailoring strategy. Of all studies using content matching, most used one or more supporting theories as well as end-user data to inform the content matching. While choices for individual intervention components were mostly explicated, detailed descriptions of the design process were scarce, with only a few studies articulating an underlying narrative that integrated the most important chosen components. While tailored eHealth interventions demonstrate promise in enhancing health literacy and the trial design of the interventions overall was of good quality, inconsistent documentation of design rationales impedes replicability and broader application of the used eHealth concepts. This calls for more detailed reporting on the design choices of the intervention in efficacy studies, so that reported outcomes can be easier connected to choices made in the design of the eHealth intervention.

Endocrine-disrupting chemicals, such as parabens, are commonly found in personal care products (PCPs). Exposure to parabens is linked to several significant health risks, such as reproductive disorders, breast cancer, infertility, and hormone imbalances. Women are particularly vulnerable to these effects due to their higher use of PCPs containing parabens. Despite these risks, Canada lacks regulatory frameworks for the use of parabens in PCPs, relying instead on consumer awareness for reducing exposure. Previous studies have highlighted that many women remain unaware of parabens, exhibiting low risk perception and limited knowledge, which restricts behavior change toward safer choices. To address this gap, this project developed the Paraben-Free & Me educational toolkit using the integrate, design, assess, and share framework. Toolkit development methodology involved empathizing with target users, defining specific behaviors, grounding the data in the health belief model, ideating implementation strategies, prototyping, gathering user feedback, and building a minimum viable product. The Paraben-Free & Me toolkit includes multimedia resources such as blog posts, interactive quizzes, videos, podcasts, and forums aimed at increasing knowledge, risk perceptions, and health beliefs and facilitating paraben-free behaviors. This toolkit shows potential to inform women about endocrine-disrupting chemicals, reduce exposures, and improve health outcomes.

Digital health services (DHS) are an increasingly integral part of health care services. Understanding users' abilities to engage with DHS is crucial to ensuring that health technology meets their needs. Assessing digital health literacy (DHL) and health technology readiness can help identify the strengths and weaknesses of DHL in different subgroups. This study aimed to assess DHL and health technology readiness among people with epilepsy or multiple sclerosis (MS) and, accordingly, identify and categorize them into distinct subgroups or profiles. In addition, we aimed to investigate respondents' use of DHS in managing their chronic condition and differences in DHL and health technology readiness between DHS users and nonusers. An electronic survey was distributed to people with epilepsy or MS with the help of patient organizations. The questionnaire included the Finnish version of the Readiness and Enablement Index for Health Technology. The subgroups of respondents were identified using k-means cluster analysis. Nonparametric tests were used to compare health technology readiness among identified subgroups. Respondents (N=289) had mid- to high-level scores in all the dimensions describing DHL and health technology readiness. A total of 4 distinct profiles emerged with different strengths and weaknesses in their DHL and health technology readiness. There was a significantly higher proportion of DHS users among the 2 profiles with the highest DHL, profile 1 (62/81, 76.5%) and profile 2 (59/80, 74.7%), compared with the profile with the lowest DHL, profile 4 (20/50, 40%; P<.001). In contrast, those with the lowest confidence in their DHL had higher emotional distress, reported lower confidence in the support from their health care providers, and had a smaller proportion of DHS users. In addition, the DHS users had significantly higher DHL levels in 6 of the 7 dimensions, as well as higher confidence in the support they received from their health care providers (mean 2.71, SD 0.72; P=.01) compared with nonusers (mean 2.42, SD 0.90) and in social support for health (mean 2.81, SD 0.71; P=.02), compared with nonusers (mean 2.54, SD 0.85). Identifying subgroups with distinct profiles, characterized by different strengths and weaknesses in their DHL and health technology readiness, is crucial in ensuring the development of responsive and inclusive DHS to meet the needs of all users, particularly those requiring support in using DHS. In addition, the nonusers had lower confidence in the support they received from their health care provider than the users. Further research is needed to understand this difference.