Digital health literacy: A concept analysis.

Objective: To elucidate the concept of digital health literacy by delineating its primary dimensions, origins and effects. Through this clarification, we seek to augment our understanding of the contemporary use of the concept of digital health literacy. Methods: Rodgers's concept analysis was employed to investigate digital health literacy as a context-influenced concept evolving with technological progress. Six databases (PubMed, Embase, CINAHL, RISS, KISS and DBpia) and Google Scholar were searched from 2006 to 2023, focusing on the terms 'digital health literacy', 'eHealth literacy' and 'mHealth literacy'. Of 2,819 papers, 32 were included in the analysis to identify the conceptual structure of digital health literacy. Results: The conceptual structure of digital health literacy was identified, and its evolution was traced. Currently, the four critical attributes are (a) goal-driven regulation, (b) information processing, (c) communication and (d) utilisation. Functional literacy, prior health knowledge and experience, and access to technology are antecedents, while positive health outcomes, increased perceived control and enhanced health-related quality of life emerged as consequences. Additionally, the concept was influenced by multilevel contextual factors. Conclusions: By enhancing our understanding of digital health literacy; standardising its terminology; and exploring the interactions among its antecedents, consequences and influencing factors, this study aims to reduce health disparities and promote equitable health in the digital era. The results of this foundational work, which establishes a basis for future research and policy development, provide clear pathways for developing targeted interventions and measurement tools of digital health literacy, ultimately contributing to better health practices.

Improving the eHealth literacy of older adults: A scoping review.

The World Health Organization stresses eHealth literacy's importance for effective health management, particularly among older adults, whose eHealth literacy is globally low and unequal. This scoping review aims to identify strategies to enhance their eHealth literacy. A literature search was performed in eight electronic databases until February 20, 2024, found 1629 records, with 24 meeting inclusion criteria. Most studies (8 of 17, 47.1 %) employed health behavior and learning theories. Interventions materials commonly utilized existing or self-designed websites or applications, with some U.S. studies incorporating standardized training materials. Outcome measures included information, psychological motivation, and behavioral change. The eHealth literacy scale was frequently used to assess eHealth literacy. Coach education combined with classroom exercises proved effective, and online health education was pivotal during the COVID-19 pandemic. Future research should focus on enhancing study design, utilizing comprehensive but concise assessment tools, tailoring interventions to theoretical frameworks, and prioritizing privacy and security.

Urban-Rural Differences in the Association of eHealth Literacy With Medication Adherence Among Older People With Frailty and Prefrailty: Cross-Sectional Study.

Background: With advances in science and technology and improvements in health literacy, more studies have focused on frailty prevention by promoting medication adherence, emphasizing the role of eHealth literacy. However, the association between eHealth literacy and medication adherence in frail older adults has not been well studied, and it is unknown whether urban-rural differences exist in this relationship. Objective: This study aims to examine the relationship between eHealth literacy and medication adherence in older people with different frailty statuses, emphasizing variations between rural and urban areas. Methods: Between November and December 2020, a total of 4218 urban and rural community members (aged ≥60 years) in China were recruited as participants using a multistage random sampling method. A face-to-face structured questionnaire survey was conducted to collect information on demographic characteristics, eHealth literacy (consisting of application, evaluation, and decision dimensions), and medication adherence. eHealth literacy was assessed using the Chinese version of the eHealth Literacy Scale developed by Norman and Skinner, and medication adherence was measured using the 4-item Morisky scale. We used a general descriptive analysis and stratified logistic regression models to examine how eHealth literacy is linked to medication adherence and urban-rural differences. Results: There were 4218 respondents, of which 2316 (54.9%) lived in urban areas and 1902 (45.1%) in rural areas, respectively. After adjusting for potential confounders, among participants with prefrailty, eHealth literacy was associated with medication adherence in urban areas in terms of less application (adjusted odds ratio [AOR] 1.16, 95% CI 0.82-1.63), less evaluation (AOR 1.29, 95% CI 0.92-1.81), and less decision ability (AOR 1.20, 95% CI 0.86-1.68); eHealth literacy was linked with medication adherence in the rural areas in terms of less application (AOR 1.10, 95% CI 0.56-2.13), less evaluation (AOR 1.05, 95% CI 0.61-1.79), and less decision ability (AOR 1.10, 95% CI 0.64-1.90). Among frail participants, less eHealth literacy (AOR 0.85, 95% CI 0.48-1.51), along with its dimensions, including less application (AOR 0.85, 95% CI 0.47-1.54), evaluation (AOR 0.89, 95% CI 0.50-1.57), and decision ability (AOR 0.99, 95% CI 0.55-1.76), were associated with medication adherence in urban areas; less eHealth literacy (AOR 0.89, 95% CI 0.48-1.65), along with its dimensions, including less application (AOR 1.23, 95% CI 0.62-2.44), evaluation (AOR 0.98, 95% CI 0.53-1.82), and decision ability (AOR 0.90, 95% CI 0.49-1.67), were associated with medication adherence in rural areas. Conclusions: The results of this study suggest that there is an association between eHealth literacy and medication adherence among older people with frailty and prefrailty. To promote medication adherence, eHealth literacy can be helpful in tailoring interventions.

Associations Between Digital Skill, eHealth Literacy, and Frailty Among Older Adults: Evidence From China.

OBJECTIVES: Frailty is a common geriatric syndrome in older adults; however, its relationship with digital factors is underexplored. This study aimed to examine the association between digital skills, eHealth literacy, and frailty to provide insights for developing frailty interventions in the digital age. DESIGN: Cross-sectional study. SETTING AND PARTICIPANTS: Data were collected from a cross-sectional survey of older adults ≥60 years of age in China. METHODS: We used a digital skills questionnaire, the eHealth Literacy Scale, and the Tilburg Frailty Indicator to measure digital skill, eHealth literacy, and frailty, respectively. Linear regression and logistic models were established to explore the association between digital skill, eHealth literacy, and frailty. Finally, we used a structural equation model and the Karlson-Holm-Breen method to test the mediation. RESULTS: A total of 2144 older adults were included in this study. The rates of adequate digital skill, adequate eHealth literacy, and frailty were 4.1%, 11.9%, and 38.3%, respectively. Digital skill (ß = -0.108; 95% CI, -0.151 to -0.065) and eHealth literacy (ß = -0.153; 95% CI, -0.195 to -0.112) were negatively associated with frailty score (P < .05), and adequate digital skill (odds ratio, 0.367; 95% CI, 0.170-0.793) and adequate eHealth literacy (odds ratio, 0.455; 95% CI, 0.298-0.694) were associated with a lower prevalence of frailty. eHealth literacy had a mediating effect on the association between digital skills and frailty. CONCLUSIONS AND IMPLICATIONS: Better digital skill and eHealth literacy are associated with a lower prevalence of frailty among older adults. The association between digital skill and frailty was found to be completely mediated by eHealth literacy.

Designing Survey-Based Mobile Interfaces for Rural Patients With Cancer Using Apple's ResearchKit and CareKit: Usability Study.

BACKGROUND: Despite the increased accessibility and availability of technology in recent years, equality and access to health-related technology remain limited to some demographics. In particular, patients who are older or from rural communities represent a large segment of people who are currently underusing mobile health (mHealth) solutions. System usability continues to hinder mHealth adoption among users with nontraditional digital literacy. OBJECTIVE: This study aims to investigate if state-of-the-art mobile app interfaces from open-source libraries provide sufficient usability for rural patients with cancer, with minimal design changes and forgoing the co-design process. METHODS: We developed Assuage (Network Reconnaissance Lab) as a research platform for any mHealth study. We conducted a pilot study using Assuage to assess the usability of 4 mobile user interfaces (UIs) based on open-source libraries from Apple's ResearchKit and CareKit. These UIs varied in complexity for reporting distress symptoms. Patients with cancer were recruited at the Markey Cancer Center, and all research procedures were conducted in person. Participants completed the distress assessment using a randomly selected UI in Assuage with little to no assistance. Data were collected on participant age, location, mobile app use, and familiarity with mHealth apps. Participants rated usability with the System Usability Scale (SUS), and usability issues were documented and compared. A one-way ANOVA was used to compare the effect of the UIs on the SUS scores. RESULTS: We recruited 30 current or postsurgery patients with cancer for this pilot study. Most participants were aged >50 years (24/30, 80%), from rural areas (25/30, 83%), had up to a high school education (19/30, 63%), and were unfamiliar with mHealth apps (21/30, 70%). General mobile app use was split, with 43% (14/30) of the patients not regularly using mobile apps. The mean SUS score across the UIs was 75.8 (SD 22.2), with UI 3 and UI 4 achieving an SUS score ≥80, meeting the industry standard for good usability of 80. Critical usability issues were related to data input and navigation with touch devices, such as scale-format questions, vertical scrolling, and traversing multiple screens. CONCLUSIONS: The findings from this study show that most patients with cancer (20/30, 67%) who participated in this study rated the different interfaces of Assuage as above-average usability (SUS score >68). This suggests that Apple's ResearchKit and CareKit libraries can provide usable UIs for older and rural users with minimal interface alterations. When resources are limited, the design stage can be simplified by omitting the co-design process while preserving suitable usability for users with nontraditional technical proficiency. Usability comparable to industry standards can be achieved by considering heuristics for interface and electronic survey design, specifically how to segment and navigate surveys, present important interface elements, and signal gestural interactions.

Short-Term Effects of an eHealth Care Experiential Learning Program Among Patients With Type 2 Diabetes: Randomized Controlled Trial.

BACKGROUND: Type 2 diabetes is a chronic disease with a significant medical burden. eHealth care integrates medicine and technology to enhance the outcomes of such patients; however, adequate eHealth literacy (eHL) is necessary for that to happen. Fostering eHL is crucial for patients with diabetes to engage with eHealth care and receive quality care and timely support. Experiential learning theory can enhance patients' eHL and skills to use eHealth care technology in their daily care. OBJECTIVE: This study explored the effectiveness of an eHealth care experiential learning program in improving eHL, patient health engagement, and eHealth care use status among patients with type 2 diabetes in 3 months. METHODS: In this randomized controlled trial, patients under case management services from various clinics in Taiwan were randomly assigned to either the intervention group receiving the 6-session eHealth care experiential learning program or the control group receiving the usual care. Data were collected using structured questionnaires at 3 time points: pretest, postintervention, and 3 months after the intervention. Descriptive data were presented using frequency distribution, percentage, mean, and SD. The outcomes were analyzed using a generalized estimating equation method by intention-to-treat analysis. RESULTS: A total of 92 participants (46 in each group) were recruited in this study. Of these, 86 completed the course and follow-up evaluations with a mean age of 62.38 (SD 12.91) years. After completing the intervention, the intervention group had significantly higher posttest scores in eHL (ß=19.94, SE 3.52; P<.001), patient health engagement (ß=.28, SE 0.13; P=.04), and eHealth use (ß=3.96, SE 0.42; P<.001) than the control group. Furthermore, the intervention group maintained these significant improvements in eHL (ß=18.19, SE 3.82; P<.001) and eHealth use (ß=3.87, SE 0.49; P<.001) after 3 months. CONCLUSIONS: Participating in the eHealth care experiential learning program resulted in significant improvements in eHL, patient health engagement, and eHealth use among patients with type 2 diabetes. Our interventional program can inform future clinical practice and policies to strengthen self-management skills and facilitate the use of health technology in caring for patients with chronic diseases. TRIAL REGISTRATION: ClinicalTrials.gov NCT05180604; https://clinicaltrials.gov/ct2/show/NCT05180604.

Influence of eHealth Literacy and Health Promotion Behavior on Body Mass Index of Workers in the Public Sector.

Background: Adequate eHealth literacy and health promotion behavior (HPB) are important to achieve good health-related quality of life. There is limited information on the influence of eHealth literacy and HPB on body mass index (BMI) in our setting and among public service workers. Objectives: This study assessed the eHealth literacy, HPB, and BMI of public service workers and determined the influence of eHealth literacy and HPB on BMI. Design: A descriptive cross-sectional design was adopted. Methods: A simple random sampling technique was used to select 440 public service workers from civil service of redacted. A structured questionnaire was used to collect data on socio-demographics, eHealth literacy, and HPB. Weight and height were measured and BMI was calculated. Data were analyzed using frequency, percentage, mean, standard deviation, and logistic regression analysis. The significant level was set at 0.05. Results: More than one quarter (28.2%) of respondents had low eHealth literacy, and more than one third (42.5%) had inadequate (30.0% fair and 12.5% poor) HPB. An average (50.5%) had a level of obesity that ranged from preobesity to type 2 obesity. There was a significant association between eHealth literacy and HPB with the BMI of respondents at p < .05. Conclusion: There was inadequate eHealth literacy and HPB among public service workers. An average of the workers had a level of obesity that ranged from pre-obesity to type 2 obesity. There was a significant association between eHealth literacy and BMI and also between HPB and BMI of respondents. Community health professionals should assist public service workers to develop competencies and skills useful in evaluating health information on the Internet and applying such information to make informed decisions.

Developing an Educational Resource Aimed at Improving Adolescent Digital Health Literacy: Using Co-Design as Research Methodology.

BACKGROUND: Adolescence is a key developmental period that affects lifelong health and is impacted by adolescents regularly engaging with digital health information. Adolescents need digital health literacy (DHL) to effectively evaluate the quality and credibility of such information, and to navigate an increasingly complex digital health environment. Few educational resources exist to improve DHL, and few have involved adolescents during design. The co-design approach may hold utility through developing interventions with participants as design partners. OBJECTIVE: This project aimed to explore the co-design approach in developing an educational resource to improve adolescents' DHL. METHODS: Adolescents (12-17 years old) attended 4 interactive co-design workshops (June 2021-April 2022). Participant perspectives were gathered on DHL and the design of educational resources to improve it. Data generated were analyzed through content analysis to inform educational resource development. RESULTS: In total, 27 participants from diverse backgrounds attended the workshops. Insight was gained into participants' relationship with digital health information, including acceptance of its benefits and relevance, coupled with awareness of misinformation issues, revealing areas of DHL need. Participants provided suggestions for educational resource development that incorporated the most useful aspects of digital formats to develop skills across these domains. The following 4 themes were derived from participant perspectives: ease of access to digital health information, personal and social factors that impacted use, impacts of the plethora of digital information, and anonymity offered by digital sources. Initial participant evaluation of the developed educational resource was largely positive, including useful suggestions for improvement. CONCLUSIONS: Co-design elicited and translated authentic adolescent perspectives and design ideas into a functional educational resource. Insight into adolescents' DHL needs generated targeted educational resource content, with engaging formats, designs, and storylines. Co-design holds promise as an important and empowering tool for developing interventions to improve adolescents' DHL.

Sociodigital Determinants of eHealth Literacy and Related Impact on Health Outcomes and eHealth Use in Korean Older Adults: Community-Based Cross-Sectional Survey.

Background: eHealth literacy is an essential skill for pursuing electronic health information, particularly for older people whose health needs increase with age. South Korea is now at the intersection of a rapidly digitalizing society and an increasingly aged population. eHealth literacy enables older people to maximize the effective use of emerging digital technology for their health and quality of life. Understanding the eHealth literacy of Korean older adults is critical to eliminating the gray digital divide and inequity in health information access. Objective: This study aims to investigate factors influencing eHealth literacy in older Korean adults and its impact on health outcomes and eHealth use. Methods: This was a cross-sectional survey. Community-dwelling older adults 65 years and older in 2 urban cities in South Korea were included. eHealth literacy was measured by the eHealth Literacy Scale. Ordinal logistic regression was used to analyze factors associated with eHealth literacy and multivariate ANOVA for the impact of eHealth literacy on health outcomes and eHealth use. Results: In total, 434 participants were analyzed. A total of 22.3% (97/434) of participants had high eHealth literacy skills. Increasing age, higher monthly income, and time spent on the internet were significantly associated with eHealth literacy (P<.001), and social media users were 3.97 times (adjusted odds ratio 3.97, 95% CI 1.02-15.43; P=.04) more likely to have higher skill. Higher eHealth literacy was associated with better self-perceived health and frequent use of digital technologies for accessing health and care services (P<.001). Conclusions: Disparity in socioeconomic status and engagement on the internet and social media can result in different levels of eHealth literacy skills, which can have consequential impacts on health outcomes and eHealth use. Tailored eHealth interventions, grounded on the social and digital determinants of eHealth literacy, could facilitate eHealth information access among older adults and foster a digitally inclusive healthy aging community.

The relationship between peer support and sleep quality among Chinese college students: the mediating role of physical exercise atmosphere and the moderating effect of eHealth literacy.

Background: Poor sleep quality has emerged as a prevalent health issue among college students. This study aims to explore the mechanism of sleep quality among college students by constructing a moderated mediation model. Methods: The Peer Support Scale, Physical Exercise Atmosphere Scale, eHealth Literacy Scale and Pittsburgh Sleep Quality Index were used to conduct a survey and analysis on 1,085 questionnaires, which were distributed among students from four universities in the northwest, northeast and central regions of China. Results: (1) A significant pairwise correlation exists between peer support, physical exercise atmosphere, eHealth literacy and sleep quality (P < 0.001); (2) Physical exercise atmosphere plays a mediating role between peer support and sleep quality, with a mediating effect accounting for 28.08%; (3) eHealth literacy can significantly moderate the strength of the relationships between peer support and exercise atmosphere, between peer support and sleep quality, and between physical exercise atmosphere and sleep quality. This study revealed the relationship between peer support and sleep quality among college students and its influencing mechanism, and provided theoretical and practical basis for improving college students' sleep quality from the perspectives of peer support, physical exercise atmosphere, and eHealth literacy.

Exploring the acceptance of robotic assisted surgery among the Indian population: An empirical investigation.

Background: Technology has completely transformed healthcare, starting with X-ray machines and MRIs to telehealth and robotic surgeries to e-health records. The launch of minimally invasive surgery (MIS) serves as a milestone in medical history, offering benefits such as smaller incisions, shorter hospital stays, and faster recovery, making it a preferred surgical option. This study mainly explores patients' willingness to adopt robot-assisted surgery (RAS) technology in a surgical intervention and is assessed in the backdrop of the Technology Acceptance Model (TAM). Methods: This research project employs a post-positivist research philosophy and a cross-sectional research design. A structured, pre-tested questionnaire was used to collect data from 280 respondents. Results: The results revealed that trust had a significant impact on Perceived Usefulness (ß = 0.099) and Perceived Ease of Use (ß = .157), and eHealth literacy had a significant impact on Perceived Ease of Use (ß = 0.438) and Perceived Usefulness (ß = 0.454). Additionally, Perceived Usefulness partially influenced behavioral intention (ß = 0.123), and attitude had a significant influence on behavioral intention (ß = 0.612). The analysis revealed an insignificant impact of eHealth literacy on Perceived Usefulness (ß = 0.067). The Standard Root Mean Square Residual (SRMR) value was <0.8. Mediation analysis also revealed partial mediation between the constructs. The SRMR rating of this model is 0.067, indicating that it fits the data well. Conclusion: This study revealed that a patient's intention will be high if he or she believes that RAS is beneficial in treating his or her ailment. In comparison, information related to RAS is clearly known, and it does not directly affect selection intention. eHealth literacy is a significant antecedent to patients' behavioral intention. Hence, the healthcare industry must devise strategies to promote the acceptance of RAS at all levels.

Associations Between Sociodemographic Characteristics, eHealth Literacy, and Health-Promoting Lifestyle Among University Students in Taipei: Cross-Sectional Validation Study of the Chinese Version of the eHealth Literacy Scale.

BACKGROUND: The popularization of the internet and rapid development of mobile devices have led to an increased inclination and opportunities to obtain health-related information online. The eHealth Literacy Scale (eHEALS), widely used for measuring eHealth literacy, assesses an individual's ability to search, understand, appraise, and use eHealth information. However, the Chinese version of the eHEALS multiple-factor model remains to be validated, and the correlation between eHEALS and the health-promoting lifestyle profile (HPLP) among university students is rarely explored in Taiwan. OBJECTIVE: This study aimed to examine the fit, validity, and reliability of the Chinese eHEALS multiple-factor model and to clarify the predictive effects of eHEALS on the HPLP among university students. METHODS: University students in Taipei, the capital of Taiwan, were recruited, and 406 valid questionnaires including sociodemographic characteristics, eHEALS, and HPLP responses were collected. Confirmatory factor analysis was performed to validate the Chinese eHEALS. Independent sample t test, 1-way ANOVA, and multiple linear regression analyses were conducted to examine the relationship between sociodemographic variables and the HPLP. Pearson product-moment correlation and binary logistic regression analyses were performed to ascertain the predictive effects of eHEALS on the HPLP. RESULTS: The Chinese eHEALS exhibited an optimal fit when delineated into the search, usage, and evaluation 3-factor model (comparative fit index=0.991, Tucker-Lewis index=0.984, root mean square error of approximation=0.062), and its validity and reliability were confirmed. The mean eHEALS score of university students was 3.17/4.00 (SD 0.48) points, and the score for the evaluation subscale was the lowest (mean 3.08, SD 0.56 points). Furthermore, there were significant sex, institution orientation, daily reading time, daily screen time, primary information channel, and perceived health status differences in the HPLP: male participants (t404=2.346, P=.02), participants attending general university (t404=2.564, P=.01), those reading ≥1 hour daily (F2,403=17.618, P<.001), those spending <3 hours on mobile devices or computers daily (F2,403=7.148, P<.001), those acquiring information from others (t404=3.892, P<.001), and those with a good perceived health status (F2,403=24.366, P<.001) had a significantly higher score. After adjusting for sociodemographic variables, the eHEALS score remained an independent predictor of the HPLP. Compared to students with relatively high eHEALS scores, those with relatively low eHEALS scores had a 3.37 times risk of a negative HPLP (adjusted odds ratio [OR]=3.37, 95% CI 1.49-7.61), which could explain 14.7%-24.4% of the variance (Cox-Snell R2=0.147, Nagelkerke R2=0.244, P=.004). CONCLUSIONS: There is room for improvement in eHealth literacy among university students in Taipei. eHEALS may be used to screen students who require HPLP improvement, thereby providing appropriate eHealth literacy training programs, particularly those targeting evaluation literacy. Additionally, the 3-factor model of the Chinese eHEALS used in this study results in more definite scale content, thus increasing the practicality and applicability of this scale in health-promoting studies.

Digital Health Literacy and Its Association With Sociodemographic Characteristics, Health Resource Use, and Health Outcomes: Rapid Review.

BACKGROUND: Digital health literacy has emerged as a critical skill set to navigate the digital age. OBJECTIVE: This review sought to broadly summarize the literature on associations between digital health literacy and (1) sociodemographic characteristics, (2) health resource use, and (3) health outcomes in the general population, patient groups, or parent or caregiver groups. METHODS: A rapid review of literature published between January 2016 and May 2022 was conducted through a search of 4 web-based databases. Articles were included on the basis of the following keywords: "measured digital health literacy," "digital literacy," "ehealth literacy," "e-health literacy," "electronic health literacy," or "internet health literacy" in adult populations; participants were from countries where English was the primary language; studies had to be cross-sectional, longitudinal, prospective, or retrospective, and published in English. RESULTS: Thirty-six articles met the inclusion criteria. Evidence on the associations between digital health literacy and sociodemographic characteristics varied (27/36, 75% included studies), with higher education (16/21, 76.2% studies that examined the association) and younger age (12/21, 57.1% studies) tending to predict higher digital health literacy; however, other studies found no associations. No differences between genders were found across the majority of studies. Evidence across ethnic groups was too limited to draw conclusions; some studies showed that those from racial and ethnic minority groups had higher digital health literacy than White individuals, while other studies showed no associations. Higher digital health literacy was associated with digital health resource use in the majority of studies (20/36, 55.6%) that examined this relationship. In addition, higher digital health literacy was also associated with health outcomes across 3 areas (psychosocial outcomes; chronic disease and health management behaviors; and physical outcomes) across 17 included studies (17/36, 47.2%) that explored these relationships. However, not all studies on the relationship among digital health literacy and health resource use and health outcomes were in the expected direction. CONCLUSIONS: The review presents mixed results regarding the relationship between digital health literacy and sociodemographic characteristics, although studies broadly found that increased digital health literacy was positively associated with improved health outcomes and behaviors. Further investigations of digital health literacy on chronic disease outcomes are needed, particularly across diverse groups. Empowering individuals with the skills to critically access and appraise reliable health information on digital platforms and devices is critical, given emerging evidence that suggests that those with low digital health literacy seek health information from unreliable sources. Identifying cost-effective strategies to rapidly assess and enhance digital health literacy capacities across community settings thus warrants continued investigation.

Age Differences in Electronic Mental Health Literacy: Qualitative Study.

BACKGROUND: Electronic mental health literacy (eMHL) is critical for accessing and effectively using digital mental health resources. However, there is a paucity of research on how eMHL varies across age groups. OBJECTIVE: This study aimed to investigate differences in eMHL among young, middle-aged, and older adults; provide insights into the needs, behaviors, and attitudes of different age groups in relation to digital mental health resources; and ultimately, inform the improvement of mental health services. METHODS: A qualitative investigation was conducted to examine the differences in eMHL across different age demographics in the Chinese population in 2023. The study sample comprised 3 distinct age groups: 18-34 years, 35-64 years, and 65 years and older. Participants were recruited through purposive sampling to ensure a diverse representation of the population. Data were collected through semistructured one-on-one interviews, which allowed for in-depth exploration of individual experiences and perceptions. The gathered data were subsequently subjected to rigorous thematic analysis to enable the identification and interpretation of recurring patterns and themes. RESULTS: The principal outcomes derived from these interviews were synthesized into 5 distinct dimensions: emotional needs, use of digital mental health resources, assessment of digital mental health information, engagement with social media to regulate emotions, and coping strategies. These dimensions were uniformly observed across the 3 age groups. CONCLUSIONS: We identified differences in knowledge, skills, and attitudes regarding the use of web-based information for managing mental health problems between the 3 age groups. The findings highlight the importance of age-specific strategies for improving eMHL.

eHealth Literacy and Web-Based Health Information-Seeking Behaviors on COVID-19 in Japan: Internet-Based Mixed Methods Study.

BACKGROUND: During the COVID-19 pandemic, much misinformation and disinformation emerged and spread rapidly via the internet, posing a severe public health challenge. While the need for eHealth literacy (eHL) has been emphasized, few studies have compared the difficulties involved in seeking and using COVID-19 information between adult internet users with low or high eHL. OBJECTIVE: This study examines the association between eHL and web-based health information-seeking behaviors among adult Japanese internet users. Moreover, this study qualitatively shed light on the difficulties encountered in seeking and using this information and examined its relationship with eHL. METHODS: This cross-sectional internet-based survey (October 2021) collected data from 6000 adult internet users who were equally divided into sample groups by gender, age, and income. We used the Japanese version of the eHL Scale (eHEALS). We also used a Digital Health Literacy Instrument (DHLI) adapted to the COVID-19 pandemic to assess eHL after we translated it to Japanese. Web-based health information-seeking behaviors were assessed by using a 10-item list of web sources and evaluating 10 topics participants searched for regarding COVID-19. Sociodemographic and other factors (eg, health-related behavior) were selected as covariates. Furthermore, we qualitatively explored the difficulties in information seeking and using. The descriptive contents of the responses regarding difficulties in seeking and using COVID-19 information were analyzed using an inductive qualitative content analysis approach. RESULTS: Participants with high eHEALS and DHLI scores on information searching, adding self-generated information, evaluating reliability, determining relevance, and operational skills were more likely to use all web sources of information about COVID-19 than those with low scores. However, there were negative associations between navigation skills and privacy protection scores when using several information sources, such as YouTube (Google LLC), to search for COVID-19 information. While half of the participants reported no difficulty seeking and using COVID-19 information, participants who reported any difficulties, including information discernment, incomprehensible information, information overload, and disinformation, had lower DHLI score. Participants expressed significant concerns regarding "information quality and credibility," "abundance and shortage of relevant information," "public trust and skepticism," and "credibility of COVID-19-related information." Additionally, they disclosed more specific concerns, including "privacy and security concerns," "information retrieval challenges," "anxieties and panic," and "movement restriction." CONCLUSIONS: Although Japanese internet users with higher eHEALS and total DHLI scores were more actively using various web sources for COVID-19 information, those with high navigation skills and privacy protection used web-based information about COVID-19 cautiously compared with those with lower proficiency. The study also highlighted an increased need for information discernment when using social networking sites in the "Health 2.0" era. The identified categories and themes from the qualitative content analysis, such as "information quality and credibility," suggest a framework for addressing the myriad challenges anticipated in future infodemics.

Measuring electronic health literacy in the context of diabetes care: psychometric evaluation of a Persian version of the condition-specific eHealth literacy scale for diabetes.

BACKGROUND: The rise of the internet and social media has led to increased interest among diabetes patients in using technology for information gathering and disease management. However, adequate eHealth literacy is crucial for protecting patients from unreliable diabetes-related information online. OBJECTIVE: To examine the psychometric characteristics and explore the preliminary validity of the Persian version of the Condition-specific eHealth Literacy Scale for Diabetes (Persian CeHLS-D) to assess eHealth literacy in the context of diabetes care. METHODS: After adapting, translating, examining content validity, and pilot testing the questionnaire, it was administered to 300 patients with type 2 diabetes mellitus (T2DM). Construct validity was assessed through confirmatory factor analysis, convergent and known-groups validity. The internal consistency (Cronbach's alpha), composite reliability and maximum reliability, and test-retest correlation were assessed. RESULTS: Factor analysis supported the hypothesized two-factor model with 10 items, and the standardized factor loadings ranged from 0.44 to 0.86 (P-values < 0.001). Cronbach's alpha and test-retest correlation were good for each factor. Convergent validity was confirmed by significant correlations of Persian CeHLS-D with diabetes health literacy, perceived usefulness and importance of using the internet for health information, internet anxiety, and perceived physical and mental health. Know-groups validity determined using groups with different internet-use frequencies, and different attitudes towards providing online healthcare services, were satisfied. CONCLUSION: This study demonstrated the Persian CeHLS-D as a reliable and valid measure of eHealth literacy among patients with T2DM in Iran. Its satisfactory psychometric properties support its use in research and clinical settings to assess eHealth literacy and inform interventions.

eHealth Literacy and the Use of NHS 111 Online Urgent Care Service in England: Cross-Sectional Survey.

BACKGROUND: Many health care systems have used digital technologies to support care delivery, a trend amplified by the COVID-19 pandemic. "Digital first" may exacerbate health inequalities due to variations in eHealth literacy. The relationship between eHealth literacy and web-based urgent care service use is unknown. OBJECTIVE: This study aims to measure the association between eHealth literacy and the use of NHS (National Health Service) 111 online urgent care service. METHODS: A cross-sectional sequential convenience sample survey was conducted with 2754 adults (October 2020-July 2021) from primary, urgent, or emergency care; third sector organizations; and the NHS 111 online website. The survey included the eHealth Literacy Questionnaire (eHLQ), questions about use, preferences for using NHS 111 online, and sociodemographic characteristics. RESULTS: Across almost all dimensions of the eHLQ, NHS 111 online users had higher mean digital literacy scores than nonusers (P<.001). Four eHLQ dimensions were significant predictors of use, and the most highly significant dimensions were eHLQ1 (using technology to process health information) and eHLQ3 (ability to actively engage with digital services), with odds ratios (ORs) of 1.86 (95% CI 1.46-2.38) and 1.51 (95% CI 1.22-1.88), respectively. Respondents reporting a long-term health condition had lower eHLQ scores. People younger than 25 years (OR 3.24, 95% CI 1.87-5.62) and those with formal qualifications (OR 0.74, 95% CI 0.55-0.99) were more likely to use NHS 111 online. Users and nonusers were likely to use NHS 111 online for a range of symptoms, including chest pain symptoms (n=1743, 70.4%) or for illness in children (n=1117, 79%). The users of NHS 111 online were more likely to have also used other health services, particularly the 111 telephone service (χ12=138.57; P<.001). CONCLUSIONS: These differences in eHealth literacy scores amplify perennial concerns about digital exclusion and access to care for those impacted by intersecting forms of disadvantage, including long-term illness. Although many appear willing to use NHS 111 online for a range of health scenarios, indicating broad acceptability, not all are able or likely to do this. Despite a policy ambition for NHS 111 online to substitute for other services, it appears to be used alongside other urgent care services and thus may not reduce demand.

Electronic Health Literacy Scale-Web3.0 for Older Adults with Noncommunicable Diseases: Validation Study.

BACKGROUND: In the current digital era, eHealth literacy plays an indispensable role in health care and self-management among older adults with noncommunicable diseases (NCDs). Measuring eHealth literacy appropriately and accurately ensures the successful implementation and evaluation of pertinent research and interventions. However, existing eHealth literacy measures focus mainly on individuals' abilities of accessing and comprehending eHealth information (Web1.0), whereas the capabilities for web-based interaction (Web2.0) and using eHealth information (Web3.0) have not been adequately evaluated. OBJECTIVE: This study aimed to examine the reliability, validity, and measurement invariance of the eHealth Literacy Scale-Web3.0 (eHLS-Web3.0) among older adults with NCDs. METHODS: A total of 642 Chinese older adults with NCDs (mean age 65.78, SD 3.91 years; 55.8% female) were recruited in the baseline assessment, of whom 134 (mean age 65.63, SD 3.99 years; 58.2% female) completed the 1-month follow-up assessment. Baseline measures included the Chinese version of the 24-item 3D eHLS-Web3.0, the Chinese version of the 8-item unidimensional eHealth Literacy Scale (eHEALS), and demographic information. Follow-up measures included the 24-item eHLS-Web3.0 and accelerometer-measured physical activity and sedentary behavior. A series of statistical analyses, for example, Cronbach α, composite reliability coefficient (CR), confirmatory factor analysis (CFA), and multigroup CFA, were performed to examine the internal consistency and test-retest reliabilities, as well as the construct, concurrent, convergent, discriminant, and predictive validities, and the measurement invariance of the eHLS-Web3.0 across gender, education level, and residence. RESULTS: Cronbach α and CR were within acceptable ranges of 0.89-0.94 and 0.90-0.97, respectively, indicating adequate internal consistency of the eHLS-Web3.0 and its subscales. The eHLS-Web3.0 also demonstrated cross-time stability, with baseline and follow-up measures showing a significant intraclass correlation of 0.81-0.91. The construct validity of the 3D structure model of the eHLS-Web3.0 was supported by confirmatory factor analyses. The eHLS-Web3.0 exhibited convergent validity with an average variance extracted value of 0.58 and a CR value of 0.97. Discriminant validity was supported by CFA results for a proposed 4-factor model integrating the 3 eHLS-Web3.0 subscales and eHEALS. The predictive validity of the eHLS-Web3.0 for health behaviors was supported by significant associations of the eHLS-Web3.0 with light physical activity (ß=.36, P=.004), moderate to vigorous physical activity (ß=.49, P<.001), and sedentary behavior (ß=-.26, P=.002). Finally, the measurement invariance of the eHLS-Web3.0 across gender, education level, and residence was supported by the establishment of configural, metric, strong, and strict invariances. CONCLUSIONS: The present study provides timely empirical evidence on the reliability, validity, and measurement invariance of the eHLS-Web3.0, suggesting that the 24-item 3D eHLS-Web3.0 is an appropriate and valid tool for measuring eHealth literacy among older adults with NCDs within the Web3.0 sphere.

Social determinants of health and their relation to suboptimal health status in the context of 3PM: a latent profile analysis.

Background: Suboptimal health is identified as a reversible phase occurring before chronic diseases manifest, emphasizing the significance of early detection and intervention in predictive, preventive, and personalized medicine (PPPM/3PM). While the biological and genetic factors associated with suboptimal health have received considerable attention, the influence of social determinants of health (SDH) remains relatively understudied. By comprehensively understanding the SDH influencing suboptimal health, healthcare providers can tailor interventions to address individual needs, improving health outcomes and facilitating the transition to optimal well-being. This study aimed to identify distinct profiles within SDH indicators and examine their association with suboptimal health status. Method: This cross-sectional study was conducted from June 16 to September 23, 2023, in five regions of China. Various SDH indicators, such as family health, economic status, eHealth literacy, mental disorder, social support, health behavior, and sleep quality, were examined in this study. Latent profile analysis was employed to identify distinct profiles based on these SDH indicators. Logistic regression analysis by profile was used to investigate the association between these profiles and suboptimal health status. Results: The analysis included 4918 individuals. Latent profile analysis revealed three distinct profiles (prevalence): the Adversely Burdened Vulnerability Group (37.6%), the Adversity-Driven Struggle Group (11.7%), and the Advantaged Resilience Group (50.7%). These profiles exhibited significant differences in suboptimal health status (p < 0.001). The Adversely Burdened Vulnerability Group had the highest risk of suboptimal health, followed by the Adversity-Driven Struggle Group, while the Advantaged Resilience Group had the lowest risk. Conclusions and relevance: Distinct profiles based on SDH indicators are associated with suboptimal health status. Healthcare providers should integrate SDH assessment into routine clinical practice to customize interventions and address specific needs. This study reveals that the group with the highest risk of suboptimal health stands out as the youngest among all the groups, underscoring the critical importance of early intervention and targeted prevention strategies within the framework of 3PM. Tailored interventions for the Adversely Burdened Vulnerability Group should focus on economic opportunities, healthcare access, healthy food options, and social support. Leveraging their higher eHealth literacy and resourcefulness, interventions empower the Adversity-Driven Struggle Group. By addressing healthcare utilization, substance use, and social support, targeted interventions effectively reduce suboptimal health risks and improve well-being in vulnerable populations. Supplementary Information: The online version contains supplementary material available at 10.1007/s13167-024-00365-5.

Exploring behavioral intention to use telemedicine services post COVID-19: a cross sectional study in Saudi Arabia.

Introduction: While telemedicine offers significant benefits, there remain substantial knowledge gaps in the literature, particularly regarding its use in Saudi Arabia. This study aims to explore health consumers' behavioral intention to use telemedicine examining the associated factors such as eHealth literacy and attitudes toward telemedicine services. Methods: A cross-sectional observational study was conducted to collect data on demographics, health status, internet skills, attitudes toward telemedicine, and eHealth literacy. An online survey was administered at two large public gatherings in Riyadh. The eHEALS-Pl scale was used to measure perceived eHealth literacy levels, and data analysis was performed using SPSS (IBM Corp. United States). Results: There were 385 participants, with an equal distribution of genders. The largest age group was 18-20 years old (57%). Nearly half of the participants were neither employed nor students, while 43% had access to governmental hospitals through employment. 71% reported proficiency in using the internet. Health-wise, 47% rated their health as excellent, and 56% did not have medical insurance. 87% expressed a high likelihood of using telemedicine if offered by a provider. Participants were categorized based on their eHealth Literacy scores, with 54% scoring low and 46% scoring high. Overall, participants showed positive attitudes toward telemedicine, with 82% agreeing that it saves time, money, and provides access to specialized care. About half of the participants perceived the process of seeing a doctor through telemedicine video as complex. Both eHealth Literacy and attitudes toward telemedicine showed a statistically significant association with the intention to use telemedicine (p < 0.001). There was a positive and significant correlation between eHealth Literacy and attitudes (ρ =0.460; p < 0.001). Multivariate ordinal regression analysis revealed that the odds for a high likelihood of intention to use telemedicine significantly increased with positive attitudes (p < 0.001). Mediation analysis confirmed the significant mediating role of attitudes toward telemedicine in the relationship between eHealth Literacy and the intention to use telemedicine. Conclusion: The findings underline the importance of enhancing health literacy and consumer attitudes toward telemedicine, particularly during the healthcare digital transformation we are experiencing globally. This is crucial for promoting increased acceptance and utilization of telemedicine services beyond the COVID-19 pandemic.