Seniors, Health Information, and the Internet: Motivation, Ability, and Internet Knowledge

Current status and influencing factors of activation of older patients with chronic disease

Objective

We aimed to investigate the status and influencing factors of activation of older patients with chronic disease.

Methods

We conducted a cross-sectional study, using the general information questionnaire, Patient Activation Measure, the Chinese version of the e-Health Literacy Scale, and the Health Empowerment Scale for the Elderly with Chronic Disease. By the convenience sampling method, 289 older patients with chronic disease were selected from January to April 2023 in a Class A tertiary hospital in Zhengzhou.

Results

The mean score of the Patient Activation Measure for older patients with chronic disease was 65.94 ± 13.35. The association of influencing factors such as religion, family income, health empowerment, e-health literacy, and patient activation was investigated.

Conclusion

The patient activation of older patients with chronic disease was at a middle level. Patients without religion and from high-income families tended to have a higher level of patient activation. Improving health empowerment and e-health literacy levels promotes patient activation and enhances their self-health management ability.

Topics Included in Health Literacy Studies in Asia: A Systematic Review

The study aimed to review general and specific health literacy studies in different countries in Asia to understand the progress of health literacy researches in the region. English-published studies with quantitative measurements of health literacy were collected through a systematic search in PubMed, Cochrane Library, Embase, and Web of Science, without publication dates limitation. A total of 156 articles on general health literacy, oral, mental, disease-specific health literacy, and eHealth literacy were collected. General health literacy was the most covered topic in 89 articles, followed by eHealth Literacy. Health literacy studies have been conducted in 16 countries and have been increasingly concerned in most of the countries in Asia. China had the largest number of articles, followed by Taiwan. Four studies had participants from more than one country. Education, age, health status, incomes, and living/residential area were significantly associated with health literacy levels in 156 studies, with the prevalence of 55.8%, 28.2%, 20.5%, 17.9%, and 10.9%, respectively. Lower health literacy was related to poorer health outcomes or lower quality of life in 71 studies.

Everyday Digital Literacy Questionnaire for Older Adults: Instrument Development and Validation Study

BACKGROUND

The need for digital literacy in aging populations is increasing in the digitalizing society. Digital literacy involves the identification, evaluation, and communication of information through various digital devices or relevant programs.

OBJECTIVE

The aims of this study were to develop an Everyday Digital Literacy Questionnaire (EDLQ), a digital literacy assessment scale, and subsequently evaluate its psychometric properties using a population of community-dwelling older adults in South Korea.

METHODS

The EDLQ was developed using an instrument development design. A nationwide survey was conducted, and the study included 1016 community-dwelling older adults (age ≥60 years). To evaluate the psychometric properties, the participants were randomly divided into 2 groups (n=508 each), and the internal consistency (Cronbach α and McDonald ω), structural validity (exploratory factor analysis and confirmatory factor analysis), hypothesis-testing construct validity using the eHealth Literacy Scale (eHEALS), and measurement invariance were analyzed.

RESULTS

Among the initial 30 items of the EDLQ, 22 items with a 3-factor solution had a total explained variance of 77%. The domains included "information and communication" (9 items), "content creation and management" (4 items), and "safety and security" (9 items). Confirmatory factor analysis was conducted with this 3-factor solution (χ2206=345.1; normed χ2206=1.7; comparative fit index=0.997; Tucker-Lewis index=0.997; root-mean-square error of approximation=0.036; standardized root-mean-square residual=0.050; composite reliability=0.903-0.959; average variance extracted=0.699-0.724; R2=0.616-0.773). Hypothesis-testing construct validity with the eHEALS revealed a strong correlation (r=0.75). Cronbach α and McDonald ω coefficients were .98 and 0.98, respectively. The fit indices for measurement invariance, including the configural, metric, and scalar invariance models, demonstrated a satisfactory fit to the data. Our findings suggest that the psychometric properties of the 22-item EDLQ are valid and reliable for assessing digital literacy among older Korean adults.

CONCLUSIONS

In this study, we developed a digital literacy measure with strong psychometric properties that made it suitable for assessing the digital literacy of community-dwelling older adults in Korea. To broaden its applicability, however, further assessment of its feasibility for use with different languages and cultures is necessary. Moreover, more empirical research on digital literacy and related factors in older adults can facilitate the development of personalized digital health care services and educational interventions in the digital society.

mHealth Self-Monitoring Model for Medicine Adherence of Patients With Diabetes in Resource-Limited Countries: Structural Equation Modeling Approach

BACKGROUND

The COVID-19 pandemic has led to serious challenges and emphasized the importance of using technology for health care operational transformation. Consequently, the need for technological innovations has increased, thus empowering patients with chronic conditions to tighten their adherence to medical prescriptions.

OBJECTIVE

This study aimed to develop a model for a mobile health (mHealth) self-monitoring system for patients with diabetes in rural communities within resource-limited countries. The developed model could be based on the implementation of a system for the self-monitoring of patients with diabetes to increase medical adherence.

METHODS

This study followed a quantitative approach, in which data were collected from health care providers using a questionnaire with close-ended questions. Data were collected from district hospitals in 3 South African provinces that were selected based on the prevalence rates of diabetes and the number of patients with diabetes treated. The collected data were analyzed using smart partial least squares to validate the model and test the suggested hypotheses.

RESULTS

Using variance-based structural equation modeling that leverages smart partial least squares, the analysis indicated that environmental factors significantly influence all the independent constructs that inform patients' change of behavior toward the use of mHealth for self-monitoring of medication adherence. Technology characteristics such as effort expectancy, self-efficacy, and performance expectancy were equally significant; hence, their hypotheses were accepted. In contrast, the contributions of culture and social aspects were found to be insignificant, and their hypotheses were rejected. In addition, an analysis was conducted to determine the interaction effects of the moderating variables on the independent constructs. The results indicated that with the exception of cultural and social influences, there were significant interacting effects on other independent constructs influencing mHealth use for self-monitoring.

CONCLUSIONS

On the basis of the findings of this study, we conclude that behavioral changes are essential for the self-monitoring of chronic diseases. Therefore, it is important to enhance those effects that stimulate the behavior to change toward the use of mHealth for self-monitoring. Motivational aspects were also found to be highly significant as they triggered changes in behavior. The developed model can be used to extend the research on the self-monitoring of patients with chronic conditions. Moreover, the model will be used as a basic architecture for the implementation of fully fledged systems for self-monitoring of patients with diabetes.

The impact of internet use on residents' happiness in China

Using data from the 2018 Chinese General Social Survey (CGSS), this study investigates the impact of internet use on residents' happiness. Empirical results show that internet use significantly enhances residents' happiness. Considering the possible endogeneity problem, a two-stage tool variable estimation is carried out with ownership of a mobile phone as the tool variable. After overcoming the endogenous problem and conducting a series of robustness tests, the conclusion is still valid. The action mechanism finds that social interaction frequency and socioeconomic status (SES) play significant mediating effects in the process of internet use affecting happiness. Specifically, internet use significantly increases the social interaction frequency of residents and enhances their SES. The improvement of social interaction frequency and SES will significantly increase residents' happiness. Therefore, this paper gives policy recommendations from the perspectives of regulating and deepening internet use, increasing the frequency of communication among residents, and improving their SES to better enhance their happiness.

Internet Use and Subjective Well-Being of the Elderly: An Analysis of the Mediating Effect Based on Social Capital

At present, the Internet has a profound impact on the lifestyle and ideas of the elderly and has an important impact on the subjective well-being of the elderly. Based on the data of 2020 China Family Panel Studies (CFPS), 4463 elderly people aged 60 years and above were selected in the empirical research, including 2321 males and 2142 females. The average age was 68.07 (SD = 5.75). The ordinary least square regression (OLS) model was used to test the effect of Internet use on the subjective well-being of the elderly; the structural equation model was used to analyze the influence path of social capital in the process of Internet use affecting the subjective well-being of the elderly, and the Sobel test is used to further verify the mediating effect of social capital. The results indicated the important positive effect of Internet use on the improvement of the subjective well-being of the elderly and confirms the mediating role of social capital in the process of Internet use affecting the subjective well-being of the elderly. Among them, the mediating effects of bonding social capital and bridging social capital accounted for 18.69% and 28.17%, respectively. It can be seen that the mediating effect of bridging social capital is significantly higher than that of bonding social capital. Marital status moderates the latter half of the mediation mechanism of "Internet use-bridging social capital-subjective well-being of the elderly", that is, "bridging social capital-subjective well-being of the elderly."

Online health information-seeking behaviour: an empirical study of managerial-level employees in Sri Lanka

Purpose

Over the past few years, the internet has expanded rapidly, and it has been considered a systematic way that consumers use to retrieve health-related information. However, the existing literature does not provide an articulated view of online health information-seeking behaviour through an in-depth understanding of users’ searching-related behaviour. The objectives of this study are to identify the factors affecting consumers’ health-related internet use and recognise the relationships between those specified and health-related internet use. Finally, the recommendations are made based on the findings.

Design/methodology/approach

An amalgamated model of technology acceptance model and health belief model was used to hypothesise health-related internet use behaviour, which is then tested using a cross-sectional survey of 287 Sri Lankan managerial-level employees. The covariance-based structural equation modelling with AMOS was used to check the study hypotheses.

Findings

Findings of this study depict five factors contributing to consumers’ health-related internet use as follows: perceived health risk towards chronic diseases consisting of perceived susceptibility and perceived severity; health consciousness; perceived usefulness of the internet; perceived ease of internet use; and attitude towards health-related internet use. As theorised, the internet’s perceived usefulness was positively and significantly related to consumers’ use of health-related internet and attitude towards health-related internet use. But as hypothesised, perceived ease of internet use did not directly affect consumers’ use of health-related internet. Further, findings reveal that health-related internet use is estimated by perceived health risk than health consciousness.

Originality/value

Findings reveal that Sri Lankan managerial-level employees have a reactive health behaviour driven by the perceived health risk and the desire to seek online health information.

Health Information Orientation Profiles and Their Association with Knowledge of Antibiotic Use in a Population with Good Internet Access: A Cross-Sectional Study

Background: Poor knowledge of antibiotic use drives poor antibiotic practices, but little is known about the influence of health information orientation (HIO) on knowledge of antibiotic use in the general public. Methods: We conducted a nationally-representative population-wide cross-sectional study (November 2020−January 2021), on a proportionately stratified random sample of 2004 Singapore residents aged ≥21 years. Multivariable logistic regression analysis was performed to assess the association between HIO and knowledge of antibiotic use. Results: Forty percent of respondents had low-levels of HIO (LL-HIO); they tended to be younger, not currently married, and did not have family/friends working in the healthcare sector. Respondents with LL-HIO (aOR 1.82, 95% CI 1.32−2.51, p < 0.001) were 82% more likely to have poor knowledge of antibiotic use. In particular, older adults aged ≥50 years with LL-HIO (aOR 1.81, 95% CI [1.32−2.51], p < 0.001) were much more likely to have poor knowledge than their HL-HIO counterparts. They were also less likely to use the Internet to seek health information and had poor eHealth efficacy. Conclusion: LL-HIO is independently associated with poor knowledge of antibiotic use. Educational strategies on antibiotic use should disseminate a consistent message through both online and offline platforms, involving traditional and non-traditional healthcare and non-healthcare influencers.

Electronic health literacy and health-related outcomes among older adults: A systematic review

This review aims to identify, appraise, and synthesize research evidence of the association between electronic health (eHealth) literacy and health outcomes in older adults. English-written articles that presented the relationships between eHealth literacy and health-related outcomes in older adults were identified by searching five scientific databases (Web of Science, PubMed, Cochrane Library, APA PsycInfo, and EMBASE) hand-searching reference lists. Searches yielded 2993 studies after duplicates were removed, of which 24 publications were included in the final review. eHealth literacy was relatively low in older adults, and the eHealth Literacy Scale, developed by Norman and Skinner in 2006, was the most frequently used instrument in the included studies (21/24, 87.5%). The health-related outcomes associated with eHealth literacy were grouped into four categories: physical, behavioral, psychosocial, and cognitive. For behavioral (e.g., health-promoting behaviors, self-care, and medication adherence) and cognitive (e.g., health knowledge and health decision making) outcomes, the evidence was mostly consistent that eHealth literacy was positively associated with better outcomes. For physical (e.g., health-related quality of life) and psychosocial outcomes (e.g., anxiety and self-efficacy), the associations were less consistent, with some studies showing significant associations while others showed no associations. Most included studies were assessed as moderate quality. Overall, higher eHealth literacy is associated with more positive health behaviors and better health knowledge and attitude in older adults, however, the associations with some physical and psychosocial outcomes are less consistent. Clarifying the pathways of the relationships between eHealth literacy and some health-related outcomes is needed for further exploring their underlying mechanisms.

Online Health Information Seeking Behaviors Among Older Adults: Systematic Scoping Review

Background

With the world’s population aging, more health-conscious older adults are seeking health information to make better-informed health decisions. The rapid growth of the internet has empowered older adults to access web-based health information sources. However, research explicitly exploring older adults’ online health information seeking (OHIS) behavior is still underway.

Objective

This systematic scoping review aims to understand older adults’ OHIS and answer four research questions: (1) What types of health information do older adults seek and where do they seek health information on the internet? (2) What are the factors that influence older adults’ OHIS? (3) What are the barriers to older adults’ OHIS? (4) How can we intervene and support older adults’ OHIS?

Methods

A comprehensive literature search was performed in November 2020, involving the following academic databases: Web of Science; Cochrane Library database; PubMed; MEDLINE; CINAHL Plus; APA PsycINFO; Library and Information Science Source; Library, Information Science and Technology Abstracts; Psychology and Behavioral Sciences Collection; Communication & Mass Media Complete; ABI/INFORM; and ACM Digital Library. The initial search identified 8047 publications through database search strategies. After the removal of duplicates, a data set consisting of 5949 publications was obtained for screening. Among these, 75 articles met the inclusion criteria. Qualitative content analysis was performed to identify themes related to the research questions.

Results

The results suggest that older adults seek 10 types of health information from 6 types of internet-based information sources and that 2 main categories of influencing factors, individual-related and source-related, impact older adults’ OHIS. Moreover, the results reveal that in their OHIS, older adults confront 3 types of barriers, namely individual, social, and those related to information and communication technologies. Some intervention programs based on educational training workshops have been created to intervene and support older adults’ OHIS.

Conclusions

Although OHIS has become increasingly common among older adults, the review reveals that older adults’ OHIS behavior is not adequately investigated. The findings suggest that more studies are needed to understand older adults’ OHIS behaviors and better support their medical and health decisions in OHIS. Based on the results, the review proposes multiple objectives for future studies, including (1) more investigations on the OHIS behavior of older adults above 85 years; (2) conducting more longitudinal, action research, and mixed methods studies; (3) elaboration of the mobile context and cross-platform scenario of older adults’ OHIS; (4) facilitating older adults’ OHIS by explicating technology affordance; and (5) promoting and measuring the performance of OHIS interventions for older adults.

Exploring individuals’ adoption of COVID-19 contact-tracing apps: a mixed-methods approach

Purpose

During the challenging time of lockdown and isolation due to the coronavirus disease (COVID-19), contact-tracing apps have played a critical role in health communication and preventive healthcare. This study proposed and tested an extended technology acceptance model (TAM) with key health factors (i.e. health risk perception from COVID-19, health information orientation to COVID-19 and health consciousness) to understand individuals' adoption of COVID-19 contact-tracing apps.

Design/methodology/approach

A two-stage online survey was conducted to collect data on US individuals’ intention and actual use of COVID-19 contact-tracing apps. The sample comprises 288 valid responses. Partial least squares structural equation modeling (PLS-SEM) and fuzzy set/qualitative comparative analysis (fsQCA) were employed as the complementary approaches.

Findings

The findings from PLS-SEM revealed that health risk perception, health information orientation and perceived usefulness have positive net effects on behavioral intention, which, in turn, affects actual use. The results from fsQCA highlighted the explanatory power of the extended TAM to COVID-19 contact-tracing app adoption.

Originality/value

Although TAM is considerably effective in measuring technology acceptance, the phenomenon is highly context-driven. How technological and health factors simultaneously motivate the use of contact-tracing apps has not been well documented. The present study offers some implications for practitioners concerned about fostering the adoption of mobile health services in the time of COVID-19. Methodologically, this study is among the first to blend PLS-SEM and fsQCA to measure the explanatory power of a structural model.

Building on Evidence to Improve eHealth Literacy in Older Adults: A Systematic Review

This review aimed to provide information on ways to improve eHealth literacy in older adults by assessing current studies examining eHealth literacy. To achieve the aim, this review focused on what theories or theoretical frameworks were used in the studies, what factors were related to eHealth literacy, and what outcome variables were used in eHealth literacy interventions for older adults. Five electronic databases were searched to identify eligible studies. The Cochrane Handbook for Systematic Reviews of Interventions was followed to select relevant studies, and narrative synthesis was performed. Among a total of 27 studies, 13 described theories or theoretical frameworks. Credibility in Internet health information, knowledge, and experience were identified as modifiable factors related to eHealth literacy. The most frequently used outcome variable was eHealth literacy efficacy. Nurses who are interested in improving eHealth literacy in older adults should consider appropriate theoretical frameworks and multiple factors influencing eHealth literacy.

Mobile Health Apps and Health Management Behaviors: Cost-Benefit Modeling Analysis

BACKGROUND

Rising criticism about the risks associated with the use of mobile health apps necessitates a critical perspective to assess the use of these apps. A cost-benefit approach involving several moderating factors can be used to detect technology effects and individual-level push and pull factors related to health attitudes, lifestyle, and health management behaviors.

OBJECTIVE

We introduce a cost-benefit perspective to examine how health attitudes related to mobile health apps and health situational factors (health crises, health changes, and hospitalization) affect the likelihood of adopting lifestyle and health management behaviors among app users.

METHODS

The analysis is based on individuals' reported use of mobile health apps. The sample included 1495 US adults aged over 18 years who were contacted by landline or cellphone. A total of 50.96% (762/1495) of the participants were women. A set of logistic regression models was used to predict lifestyle and health management behaviors among users considering variations in the extent of use, health attitudes, health situation, and socioeconomic characteristics.

RESULTS

The findings indicate that the proposed models were reasonably adequate. In all, 88.76% (1327/1495) of the cases were correctly classified regarding lifestyle behaviors, but only 71.97% (1076/1495) of the cases were correctly classified regarding health management behaviors. Although a large percentage of individuals changed their attitudes following the use of mobile health apps, only a small proportion adopted health management behaviors. The use of mobile health apps affected up to 67.95% (1016/1495) of the users for consultation and 71.97% (1076/1495) of the users for decision making. The model was effective for 88.76% (1327/1495) of the cases regarding lifestyle behaviors but only 71.97% (1076/1495) regarding health management behaviors. The moderating effect of regular use of mobile health apps significantly affects lifestyle (Wald=61.795; B=2.099; P<.005) but not health management behaviors (Wald=12.532; B=0.513; P=.01). These results collectively indicate that the use of mobile health apps for health management is partially effective.

CONCLUSIONS

The use of mobile health apps is a main route to instigate the process of health empowerment and shape health attitudes. However, an accurate assessment of the effectiveness of mobile health apps necessitates distinguishing between lifestyle and health management behaviors and adopting a cost-benefit approach because individuals facing health concerns, such as a chronic disease, health emergency, health crisis, or health change, consider their affordances and situational effects. These moderators generate a push and pull framework in the decision-making process that balances the costs and benefits of use.

Three-factor structure of the eHealth Literacy Scale and its relationship with nurses' health-promoting behaviours and performance quality

AIMS

To examine the factorial validity of the eHealth Literacy Scale among hospital nurses and to investigate the associations of its components with health-promoting behaviours and nursing performance quality.

DESIGN

This cross-sectional study used survey data of 484 Korean hospital nurses, which were collected between March-May 2016.

METHODS

The three-factor structure was tested using confirmatory factor analyses. Multiple linear regression was conducted to test associations of the three components' scores with health-promoting behaviours and self-rated nursing performance quality.

RESULTS

The eHealth Literacy Scale supported a three-factor structure: awareness of internet health resources (awareness), having skills needed to access resources (skills), and the ability to evaluate the quality of internet health resources (evaluation). All the three components were significantly associated with higher quality of nursing performance and better interpersonal relations. Stress management, spiritual growth, and health responsibility were linked with evaluation or skills but physical activity and nutrition were not.

CONCLUSION

Strategies to enhance eHealth literacy among nurses could improve nurses' health and further patient care. Training to build nurses' self-efficacy to evaluate internet health information could improve eHealth literacy and should be developed and examined.

IMPACT

To improve nurses' health and patient care, training programs to build nurses' self-efficacy to access and evaluate internet health information should be developed.

Internet health information education for older adults: A pilot study

This study aimed to develop internet health information education program, and to explore the program's feasibility and preliminary effects. We made use of an intervention mapping approach and adopted as conceptual framework the information-motivation-behavioral skills model to develop the program. We evaluated the feasibility and the impact of the education program using a single-group pretest-posttest design using generalized equation estimation. Eleven older adults participated in the classes from January 25 to February 22, 2019. Each outcome of the behavioral theory-based components of the program-computer/Web knowledge (p < .001), attitude toward internet-based health information (p = .002), eHealth literacy score (p < .001), searching performance scores (p < .001), and level of understanding of internet-based health information (p = .002)-showed significant improvement immediately after the intervention. This pilot study reveals that a behavior theory-based education program for utilizing internet-based health information is an effective way to increase older adults' eHealth literacy.

Self-assessed health among older people in Europe and internet use

BACKGROUND

About ten years ago, an age-related digital divide was identified, where 'the elderly' denoted a group of people at risk of losing the benefits of a digital society. The aims of this work are to find a relationship between self-assessed health and internet use by older people in European countries and to ascertain whether this relationship differs in countries with a more developed eHealth policy.

MATERIALS AND METHODS

An ordered logistic regression is estimated for all countries in the sample and for two countries subsets which differ in their eHealth performance. Individual data is collected by SHARE. The classifying criterion of eHealth performance is based on the 'eHealth' policy dimension of the indicator used to construct the Digital Economy and Society Index. The average marginal effects are computed for the variable of internet use.

RESULTS

Results show that older people who use the internet tend to report better health status. This relationship however may not hold for low levels of health and it is stronger in countries with low eHealth performance.

CONCLUSION

Policy measures on eHealth not only contribute to people's health but also help to alleviate critical situations such as the one created by the Covid-19 pandemic.

How does family support work when older adults obtain information from mobile internet?

Purpose

More and more older adults begin to use the mobile internet to obtain information. However, the quality of information obtained through mobile internet by older adults is hard to be guaranteed. The purpose of this paper is to study the role of family support when older adults obtain information from mobile internet.

Design/methodology/approach

This study conducted a survey of 263 older adults who owned mobile internet devices such as smartphones or tablet PCs. The theory hypotheses are tested using partial least squares techniques.

Findings

For older adults, family support is the influencing factor of mobile internet literacy improvement. Family emotional support has stronger impacts on the improvement both of mobile internet skill literacy and of mobile internet information literacy than family cognitive support has. Furthermore, the improvement of both mobile internet skill literacy and of mobile internet information literacy hs positive impacts on the quality improvement of obtained information by older adults.

Practical implications

This paper gives advice on how family members can support older adults during their obtaining information from mobile internet to improve their mobile internet literacy and quality of obtained information.

Originality/value

This study examines the factors that influence mobile internet literacy and quality of obtained information among older adults from the perspective of family support in the Chinese mobile internet context. The research results enrich the internet literacy theory and the information quality theory.

The Reliability and Validity of the Telephone-Based and Online Polish eHealth Literacy Scale Based on Two Nationally Representative Samples

Adequate ehealth literacy is one of the key instruments safeguarding people against unreliable health-related information obtained from the Internet. This paper presents an assessment of the reliability and the validity of a Polish version of the ehealth literacy scale (Pl-eHEALS). The assessment was carried out on the basis of two nationally representative samples of the Polish population. In the first survey of adults at least 50 years old, the technique of computer-assisted telephone interviewing (CATI) was applied. In the second survey of young adult women (18-35 years old), the technique of computer-assisted web interviewing (CAWI) was used. The reliability and the validity of the Pl-eHEALS was analyzed. There were no floor or ceiling effects revealed in either sample. The Cronbach's alpha coefficients were 0.90 and 0.88, and Guttman split-half coefficients were 0.89 and 0.81, respectively. Exploratory factors analysis revealed single factor models in both cases. The sum of squared loadings in the first survey was 6.090 and accounted for 58.72% of the variance. In the second survey, the sum was 5.927 and was responsible for 55.06% of the variance. Hypothesis testing showed that, for older adults, higher ehealth literacy was prevalent in the respondents who used the Internet more frequently. Among young adult women, higher readiness to use the Internet as a primary source of health-related information and to undertake specific internet health-related activities was associated with higher ehealth literacy. The analysis reported in this paper confirmed the reliability and the validity of the instrument. It should be stressed that, prior to this study, there was no validated Polish version of the eHEALS that could be used with Polish-speaking respondents.

Patients' health literacy in relation to the preference for a general practitioner as the source of health information

Background

For many patients, the general practitioner (GP) is the most important point of contact for obtaining information about a wide range of health topics. However, patients with different characteristics may seek health information from different sources, such as friends or the internet. The relationship between patient characteristics and preferences for information sources is understudied. We investigate which information sources are used by patients for health-related questions and how this relates to patients’ sociodemographics, health, and health literacy.

Methods

A stratified and population-based survey was conducted to investigate health information sources within the German population over 35 years (n = 4144). Sociodemographics, use of technology, health-related indicators, and health literacy (including self-efficacy and action planning), as well as questions regarding the ratings of multiple health-related information sources, were investigated in personal interviews and analyzed using logistic regression.

Results

In our study, GPs were the most important source of information for the patients, followed by medical specialists, pharmacists and the internet. Patient age and number of illnesses were associated with the choice of information source. Furthermore, action planning and self-efficacy for acquiring health knowledge were associated with the selected source of information.

Conclusions

Information provider appears to be an important role for GPs, particularly among old and chronically ill patients. GPs should have the specific capabilities to fill this role and should be trained and referred to accordingly. Self-efficacy and action planning for acquiring health knowledge are important patient factors doctors can use for brief inventions during consultations.

Health Literacy in Web-Based Health Information Environments: Systematic Review of Concepts, Definitions, and Operationalization for Measurement

Background

Health literacy research seems to lack a consensus on what aspects to include into literacy in the context of health and on how to operationalize these concepts for measurement purposes. In addition to health literacy, several other concepts, such as electronic health (eHealth) literacy and mental health literacy, have been developed across disciplines. This study examines how these different concepts are used when studying health-related competencies in Web contexts.

Objective

This study systematically reviews health literacy concepts and definitions and their operationalization in studies focused on Web-based health information environments.

Methods

A systematic literature search was conducted in April 2016 in 6 electronic databases with a limitation to articles in English published between January 2011 and April 2016. Altogether, 1289 unique records were identified and screened according to the predefined inclusion criteria: (1) original, peer-reviewed research articles written in English; (2) the topic of the article concerned literacy in the context of health; (3) informants of the study were lay people, not health professionals or students of the field; and (4) the focus of the study was placed on an Web-based information environment. In total, 180 full texts were screened, of which 68 were included in the review. The studies were analyzed with an emphasis on the used health literacy concepts and measures.

Results

On the basis of the included studies, several concepts are in use when studying health-related literacy in Web environments, eHealth literacy and health literacy being the most common ones. The reviewed studies represent a variety of disciplines, but mostly medical sciences. Typically, quantitative research methods are used. On the basis of the definitions for health literacy, 3 thematic categories were identified: general and skill-based, multidimensional, and domain-specific health literacy. Most studies adopted a domain-specific concept, followed by the ones that used a general and skill-based concept. Multidimensional concepts occurred least frequently. The general health literacy concepts were usually operationalized with reading comprehension measures, the domain-specific concepts with self-efficacy measures, and multidimensional concepts with several types of measures. However, inconsistencies in operationalization were identified.

Conclusions

The results show that in studies conducted in Web-based information environments, several different health literacy concepts are in use, and there is no clear consensus on the definitions for these concepts. Future studies should place emphasis on the conceptual development of health literacy in Web contexts to gain better results on operationalization for measurement. Researchers are encouraged to provide clear operational definitions for the concepts they use to ensure transparency in reporting.

Proposing a Transactional Model of eHealth Literacy: Concept Analysis

Background

Electronic health (eHealth) literacy was conceptualized in 2006 as the ability of internet users to locate, evaluate, and act upon web-based health information. Now, advances in eHealth technology have cultivated transactional opportunities for patients to access, share, and monitor health information. However, empirical evidence shows that existing models and measures of eHealth literacy have limited theoretical underpinnings that reflect the transactional capabilities of eHealth. This paper describes a conceptual model based on the Transactional Model of Communication (TMC), in which eHealth literacy is described as an intrapersonal skillset hypothesized as being dynamic; reciprocal; and shaped by social, relational, and cultural contexts.

Objective

The objective of our study was to systematically examine eHealth literacy definitions, models, and measures to propose a refined conceptual and operational definition based on the TMC.

Methods

Walker and Avant’s concept analysis method was used to guide the systematic review of eHealth literacy definitions (n=10), rating scales (n=6), models (n=4), and peer-reviewed model applications (n=16). Subsequent cluster analyses showed salient themes across definitions. Dimensions, antecedents, and consequences reflected in models and measures were extracted and deductively analyzed based on codes consistent with the TMC.

Results

Systematic review evidence revealed incongruity between operational eHealth literacy included in definitions compared with literacies included within models and measures. Theoretical underpinnings of eHealth literacy also remain dismal. Despite the transactional capabilities of eHealth, the role of “communication” in eHealth literacy remains underdeveloped and does not account for physical and cognitive processing abilities necessary for multiway transactions.

Conclusions

The Transactional Model of eHealth Literacy and a corresponding definition are proposed. In this novel model, eHealth literacy comprises a hierarchical intrapersonal skillset that mediates the reciprocal effect of contextual factors (ie, user oriented and task oriented) on patient engagement in health care. More specifically, the intrapersonal skillset counteracts the negative effect of “noise” (or impediments) produced by social and relational contexts. Cutting across health and technology literacies, the intrapersonal skillset of eHealth literacy is operationalized through four literacies that correspond with discrete operative skills: (1) functional (ie, locate and understand); (2) communicative (ie, exchange); (3) critical (ie, evaluate); and (4) translational (ie, apply).

Three-Factor Structure of the eHealth Literacy Scale Among Magnetic Resonance Imaging and Computed Tomography Outpatients: A Confirmatory Factor Analysis

BACKGROUND

Electronic health (eHealth) literacy is needed to effectively engage with Web-based health resources. The 8-item eHealth literacy scale (eHEALS) is a commonly used self-report measure of eHealth literacy. Accumulated evidence has suggested that the eHEALS is unidimensional. However, a recent study by Sudbury-Riley and colleagues suggested that a theoretically-informed three-factor model fit better than a one-factor model. The 3 factors identified were awareness (2 items), skills (3 items), and evaluate (3 items). It is important to determine whether these findings can be replicated in other populations.

OBJECTIVE

The aim of this cross-sectional study was to verify the three-factor eHEALS structure among magnetic resonance imaging (MRI) and computed tomography (CT) medical imaging outpatients.

METHODS

MRI and CT outpatients were recruited consecutively in the waiting room of one major public hospital. Participants self-completed a touchscreen computer survey, assessing their sociodemographic, scan, and internet use characteristics. The eHEALS was administered to internet users, and the three-factor structure was tested using structural equation modeling.

RESULTS

Of 405 invited patients, 87.4% (354/405) were interested in participating in the study, and of these, 75.7% (268/354) were eligible. Of the eligible participants, 95.5% (256/268) completed all eHEALS items. Factor loadings were 0.80 to 0.94 and statistically significant (P<.001). All reliability measures were acceptable (indicator reliability: awareness=.71-.89, skills=.78-.80, evaluate=.64-.79; composite reliability: awareness=.89, skills=.92, evaluate=.89; variance extracted estimates: awareness=.80, skills=.79, evaluate=.72). Two out of three goodness-of-fit indices were adequate (standardized root mean square residual (SRMR)=.038; comparative fit index (CFI)=.944; root mean square error of approximation (RMSEA)=.156). Item 3 was removed because of its significant correlation with item 2 (Lagrange multiplier [LM] estimate 104.02; P<.001) and high loading on 2 factors (LM estimate 91.11; P<.001). All 3 indices of the resulting 7-item model indicated goodness of fit (χ²₁₁=11.3; SRMR=.013; CFI=.999; RMSEA=.011).

CONCLUSIONS

The three-factor eHEALS structure was supported in this sample of MRI and CT medical imaging outpatients. Although further factorial validation studies are needed, these 3 scale factors may be used to identify individuals who could benefit from interventions to improve eHealth literacy awareness, skill, and evaluation competencies.

Health Literacy and Use and Trust in Health Information

There is a need to investigate which health information sources are used and trusted by people with limited health literacy to help identify strategies for addressing knowledge gaps that can contribute to preventable illness. We examined whether health literacy was associated with people's use of and trust in a range of potential health information sources. Six hundred participants from a GfK Internet survey panel completed an online survey. We assessed health literacy using the Newest Vital Sign, the sources participants used to get health information, and the extent to which participants trusted health information from these sources. We performed multivariable regressions, controlling for demographic characteristics. Lower health literacy was associated with lower odds of using medical websites for health information and with higher odds of using television, social media, and blogs or celebrity webpages. People with lower health literacy were less likely to trust health information from specialist doctors and dentists, but more likely to trust television, social media, blogs/celebrity webpages, friends, and pharmaceutical companies. People with limited health literacy had higher rates of using and trusting sources such as social media and blogs, which might contain lower quality health information compared to information from healthcare professionals. Thus, it might be necessary to enhance the public's ability to evaluate the quality of health information sources. The results of this study could be used to improve the reach of high-quality health information among people with limited health literacy and thereby increase the effectiveness of health communication programs and campaigns.

Health literacy in the eHealth era: A systematic review of the literature

OBJECTIVES

This study aimed to identify studies on online health service use by people with limited health literacy, as the findings could provide insights into how health literacy has been, and should be, addressed in the eHealth era.

METHODS

To identify the relevant literature published since 2010, we performed four rounds of selection-database selection, keyword search, screening of the titles and abstracts, and screening of full texts. This process produced a final of 74 publications.

RESULTS

The themes addressed in the 74 publications fell into five categories: evaluation of health-related content, development and evaluation of eHealth services, development and evaluation of health literacy measurement tools, interventions to improve health literacy, and online health information seeking behavior.

CONCLUSION

Barriers to access to and use of online health information can result from the readability of content and poor usability of eHealth services. We need new health literacy screening tools to identify skills for adequate use of eHealth services. Mobile apps hold great potential for eHealth and mHealth services tailored to people with low health literacy.

PRACTICE IMPLICATIONS

Efforts should be made to make eHealth services easily accessible to low-literacy individuals and to enhance individual health literacy through educational programs.

Exploring the Measurement Properties of the eHealth Literacy Scale (eHEALS) Among Baby Boomers: A Multinational Test of Measurement Invariance

BACKGROUND

The eHealth Literacy Scale (eHEALS) is one of only a few available measurement scales to assess eHealth literacy. Perhaps due to the relative paucity of such measures and the rising importance of eHealth literacy, the eHEALS is increasingly a choice for inclusion in a range of studies across different groups, cultures, and nations. However, despite its growing popularity, questions have been raised over its theoretical foundations, and the factorial validity and multigroup measurement properties of the scale are yet to be investigated fully.

OBJECTIVE

The objective of our study was to examine the factorial validity and measurement invariance of the eHEALS among baby boomers (born between 1946 and 1964) in the United States, United Kingdom, and New Zealand who had used the Internet to search for health information in the last 6 months.

METHODS

Online questionnaires collected data from a random sample of baby boomers from the 3 countries of interest. The theoretical underpinning to eHEALS comprises social cognitive theory and self-efficacy theory. Close scrutiny of eHEALS with analysis of these theories suggests a 3-factor structure to be worth investigating, which has never before been explored. Structural equation modeling tested a 3-factor structure based on the theoretical underpinning to eHEALS and investigated multinational measurement invariance of the eHEALS.

RESULTS

We collected responses (N=996) to the questionnaires using random samples from the 3 countries. Results suggest that the eHEALS comprises a 3-factor structure with a measurement model that falls within all relevant fit indices (root mean square error of approximation, RMSEA=.041, comparative fit index, CFI=.986). Additionally, the scale demonstrates metric invariance (RMSEA=.040, CFI=.984, ΔCFI=.002) and even scalar invariance (RMSEA=.042, CFI=.978, ΔCFI=.008).

CONCLUSIONS

To our knowledge, this is the first study to demonstrate multigroup factorial equivalence of the eHEALS, and did so based on data from 3 diverse nations and random samples drawn from an increasingly important cohort. The results give increased confidence to researchers using the scale in a range of eHealth assessment applications from primary care to health promotions.

The Association Between Perceived Health Status and Health Information Communication Channels

Varying types of health information sources may influence health outcomes, but not much is known about their impact. The purpose of our study was to explore the association between health information sources and individuals' health status. A total of 14,966 participants who responded to the Annenberg National Health Communication Survey between 2005 and 2012 were included. Controlling for demographics, comorbidities, communication patterns, and socioeconomic status, we utilized regression analysis to examine the relationship between sources of health information and perceived health status. Included in the study were a total of 8,103 females and 6,863 males between 18 and 101 years old (M = 49.14, SD = 16.13). Health information from the Internet and pharmaceutical companies was significantly associated with better health status (p < .05), whereas information from social media, health care apps, news outlets, and health care companies was not. Information from the Internet was significantly associated with better health status, suggesting that health information from the Internet may have benefits. However, use of social media and health care apps did not relate to better health status, which may indicate that these sources are not as useful to consumers or that these sources have not yet saturated the health information marketplace.

Emerging Ethical Issues in Digital Health Information

The problems of poor or biased information and of misleading health and well-being advice on the Internet have been extensively documented. The recent decision by the Internet Corporation for Assigned Names and Numbers to authorize a large number of new generic, top-level domains, including some with a clear connection to health or healthcare, presents an opportunity to bring some order to this chaotic situation. In the case of the most general of these domains, “.health,” experts advance a compelling argument in favor of some degree of content oversight and control. On the opposing side, advocates for an unrestricted and open Internet counter that this taken-for-granted principle is too valuable to be compromised, and that, once lost, it may never be recovered. We advance and provide evidence for a proposal to bridge the credibility gap in online health information by providing provenance information for websites in the .health domain.

Epidemiological profile of Dupuytren's disease in Taiwan (Ethnic Chinese): a nationwide population-based study

BACKGROUND

The epidemiologic profile of ethnic Chinese patients with Dupuytren's disease is unknown. We therefore investigated the epidemiology of Dupuytren's disease using Taiwan's National Health Insurance Research Database.

METHODS

Patients who filed claims for treatment for Dupuytren's disease between January 2000 and December 2011 were identified in the database. Age- and gender-specific incidences were estimated by dividing the incidence number by population data.

RESULTS

We identified 1,078 patients with Dupuytren's disease (681 men, 397 women; male/female ratio: 1:1.72). The annual incidence rate ranged from 0.39-0.63/10(5) for men and 0.14-0.44/10(5) for women. A trend analysis revealed a rising trend in the annual incidence from 2001 to 2011 (p = 0.0199). The prevalence rate increased steadily from 0.46/10(5) in 2000 to 4.52/10(5) in 2011 (p = 0.0186). The mean age at onset was significantly higher in men than in women (60.7 ± 18.4 vs. 53.7 ± 15.5 years). Peak age at onset for men was 70-79 (28.1%) and for women was 50-59 (33.5%). Men > 60 years old had higher incidence rates than did women (incidence rate ratios: 2.0, 4.5, and 6.6 for those 60-69, 70-79, and ≥ 80, respectively). Hypertension (29.6%), diabetes mellitus (21.9%), hyperlipidemia (14.8%), ischemic heart disease (10.5%), and chronic obstructive pulmonary disease (8.0%) were the most common comorbidities.

CONCLUSIONS

The incidence and prevalence of Dupuytren's disease and the male/female ratio were significantly lower in ethnic Chinese than in Western ethnic groups. Moreover, the age at onset was significantly lower in ethnic Chinese women. However, the incidences of three comorbidities (hypertension, diabetes mellitus, and hyperlipidemia) were similar to those in other ethnicities.