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      E-health literacy and associated factors among chronic patients in a low-income country: a cross-sectional survey

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          Abstract

          Background

          Chronic patients persistently seek for health information on the internet for medication information seeking, nutrition, disease management, information regarding disease preventive actions and so on. Consumers ability to search, find, appraise and use health information from the internet is known as eHealth literacy skill. eHealth literacy is a congregate set of six basic skills (traditional literacy, health literacy, information literacy, scientific literacy, media literacy and computer literacy). The aim of this study was to assess eHealth literacy level and associated factors among internet user chronic patients in North-west Ethiopia.

          Methods

          Institutional based cross-sectional study design was conducted. Stratified sampling technique was used to select 423 study participants among chronic patients. The eHealth literacy scale (eHEALS) was used for data collection. The eHEALS is a validated eight-item Likert scaled questionnaire used to asses self-reported capability of eHealth consumers to find, appraise, and use health related information from the internet to solve health problems. Statistical Package for Social science version 20 was used for data entry and further analysis. Multivariable logistic regression was used to examine the association between the eHealth literacy skill and associated factors. Significance was obtained at 95% CI and p < 0.05.

          Result

          In total, 423 study subjects were approached and included in the study from February to May, 2019. The response rate to the survey was 95.3%. The majority of respondents 268 (66.3%) were males and mean age was 35.58 ± 14.8 years. The multivariable logistic regression model indicated that participants with higher education (at least having the diploma) are more likely to possess high eHealth literacy skill with Adjusted Odds Ratio (AOR): 3.48, 95% CI (1.54, 7.87). similarly, being government employee AOR: 1.71, 95% CI (1.11, 2.68), being urban resident AOR: 1.37, 95% CI (0.54, 3.49), perceived good health status AOR: 3.97, 95% CI (1.38, 11.38), having higher income AOR: 4.44, 95% CI (1.32, 14.86), Daily internet use AOR: 2.96, 95% CI (1.08, 6.76), having good knowledge about the availability and importance of online resources AOR: 3.12, 95% CI (1.61, 5.3), having positive attitude toward online resources AOR: 2.94, 95% CI (1.07, 3.52) and higher level of computer literacy AOR: 3.81, 95% CI (2.19, 6.61) were the predictors positively associated with higher eHealth literacy level.

          Conclusion

          Besides the mounting indication of efficacy, the present data confirm that internet use and eHealth literacy level of chronic patients in this setting is relatively low which clearly implicate that there is a need to fill the skill gap in eHealth literacy among chronic patients which might help them in finding and evaluating relevant online sources for their health-related decisions.

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          Most cited references36

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          Sample size calculation in medical studies

          Optimum sample size is an essential component of any research. The main purpose of the sample size calculation is to determine the number of samples needed to detect significant changes in clinical parameters, treatment effects or associations after data gathering. It is not uncommon for studies to be underpowered and thereby fail to detect the existing treatment effects due to inadequate sample size. In this paper, we explain briefly the basic principles of sample size calculations in medical studies.
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            eHealth Literacy: Extending the Digital Divide to the Realm of Health Information

            Background eHealth literacy is defined as the ability of people to use emerging information and communications technologies to improve or enable health and health care. Objective The goal of this study was to explore whether literacy disparities are diminished or enhanced in the search for health information on the Internet. The study focused on (1) traditional digital divide variables, such as sociodemographic characteristics, digital access, and digital literacy, (2) information search processes, and (3) the outcomes of Internet use for health information purposes. Methods We used a countrywide representative random-digital-dial telephone household survey of the Israeli adult population (18 years and older, N = 4286). We measured eHealth literacy; Internet access; digital literacy; sociodemographic factors; perceived health; presence of chronic diseases; as well as health information sources, content, search strategies, and evaluation criteria used by consumers. Results Respondents who were highly eHealth literate tended to be younger and more educated than their less eHealth-literate counterparts. They were also more active consumers of all types of information on the Internet, used more search strategies, and scrutinized information more carefully than did the less eHealth-literate respondents. Finally, respondents who were highly eHealth literate gained more positive outcomes from the information search in terms of cognitive, instrumental (self-management of health care needs, health behaviors, and better use of health insurance), and interpersonal (interacting with their physician) gains. Conclusions The present study documented differences between respondents high and low in eHealth literacy in terms of background attributes, information consumption, and outcomes of the information search. The association of eHealth literacy with background attributes indicates that the Internet reinforces existing social differences. The more comprehensive and sophisticated use of the Internet and the subsequent increased gains among the high eHealth literate create new inequalities in the domain of digital health information. There is a need to educate at-risk and needy groups (eg, chronically ill) and to design technology in a mode befitting more consumers.
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              Development of the Digital Health Literacy Instrument: Measuring a Broad Spectrum of Health 1.0 and Health 2.0 Skills

              Background With the digitization of health care and the wide availability of Web-based applications, a broad set of skills is essential to properly use such facilities; these skills are called digital health literacy or eHealth literacy. Current instruments to measure digital health literacy focus only on information gathering (Health 1.0 skills) and do not pay attention to interactivity on the Web (Health 2.0). To measure the complete spectrum of Health 1.0 and Health 2.0 skills, including actual competencies, we developed a new instrument. The Digital Health Literacy Instrument (DHLI) measures operational skills, navigation skills, information searching, evaluating reliability, determining relevance, adding self-generated content, and protecting privacy. Objective Our objective was to study the distributional properties, reliability, content validity, and construct validity of the DHLI’s self-report scale (21 items) and to explore the feasibility of an additional set of performance-based items (7 items). Methods We used a paper-and-pencil survey among a sample of the general Dutch population, stratified by age, sex, and educational level (T1; N=200). The survey consisted of the DHLI, sociodemographics, Internet use, health status, health literacy and the eHealth Literacy Scale (eHEALS). After 2 weeks, we asked participants to complete the DHLI again (T2; n=67). Cronbach alpha and intraclass correlation analysis between T1 and T2 were used to investigate reliability. Principal component analysis was performed to determine content validity. Correlation analyses were used to determine the construct validity. Results Respondents (107 female and 93 male) ranged in age from 18 to 84 years (mean 46.4, SD 19.0); 23.0% (46/200) had a lower educational level. Internal consistencies of the total scale (alpha=.87) and the subscales (alpha range .70-.89) were satisfactory, except for protecting privacy (alpha=.57). Distributional properties showed an approximately normal distribution. Test-retest analysis was satisfactory overall (total scale intraclass correlation coefficient=.77; subscale intraclass correlation coefficient range .49-.81). The performance-based items did not together form a single construct (alpha=.47) and should be interpreted individually. Results showed that more complex skills were reflected in a lower number of correct responses. Principal component analysis confirmed the theoretical structure of the self-report scale (76% explained variance). Correlations were as expected, showing significant relations with age (ρ=–.41, P<.001), education (ρ=.14, P=.047), Internet use (ρ=.39, P<.001), health-related Internet use (ρ=.27, P<.001), health status (ρ range .17-.27, P<.001), health literacy (ρ=.31, P<.001), and the eHEALS (ρ=.51, P<.001). Conclusions This instrument can be accepted as a new self-report measure to assess digital health literacy, using multiple subscales. Its performance-based items provide an indication of actual skills but should be studied and adapted further. Future research should examine the acceptability of this instrument in other languages and among different populations.
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                Author and article information

                Contributors
                birukkirubel@gmail.com
                Journal
                BMC Med Inform Decis Mak
                BMC Med Inform Decis Mak
                BMC Medical Informatics and Decision Making
                BioMed Central (London )
                1472-6947
                6 August 2020
                6 August 2020
                2020
                : 20
                : 181
                Affiliations
                [1 ]GRID grid.449044.9, ISNI 0000 0004 0480 6730, Health Informatics Department, Medicine and Health science college, , Debre Markos University, ; Debre Markos, Ethiopia
                [2 ]GRID grid.59547.3a, ISNI 0000 0000 8539 4635, Health Informatics Department, College of Medicine and Health science, , University of Gondar, ; Gondar, Ethiopia
                [3 ]GRID grid.463530.7, ISNI 0000 0004 7417 509X, Faculty of Health & Social Sciences, Science center Health & Technology, , University of South-Eastern Norway, ; Notodden, Norway
                [4 ]GRID grid.463530.7, ISNI 0000 0004 7417 509X, School of Business, Institute of Business, History & Social Sciences, , University of South-Eastern Norway, ; Notodden, Norway
                Author information
                http://orcid.org/0000-0002-7411-1411
                Article
                1202
                10.1186/s12911-020-01202-1
                7407428
                32762745
                f469b6a8-5237-4bb3-aa43-042f084206cc
                © The Author(s). 2020

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 24 January 2020
                : 23 July 2020
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100007866, College of Medicine and Health Sciences, University of Gondar;
                Funded by: CBMP Project UOG
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2020

                Bioinformatics & Computational biology
                ehealth literacy,chronic patients,ehealth,low income country,electronic health

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