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      Health literacy, digital literacy and eHealth literacy in Danish nursing students at entry and graduate level: a cross sectional study

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          Abstract

          Background

          The increasing number of people living with one or more chronic conditions imposes a growing demand on healthcare providers. One way to handle this challenge is by re-orientating the way care is provided, empower people and increase their ability to manage their condition. This requires, amongst other factors, sufficient level of health literacy (HL) and digital competences among both patients and the healthcare providers, who serve them. The focus of this study is the level of HL, digital literacy (DL), and eHealth literacy (eHL) in nursing students in Denmark.

          The objective was to examine the level of these three literacies in entry- and graduate-level nursing students and examine sociodemographic characteristics and self-rated health (SRH) associations.

          Methods

          A cross sectional study was conducted among 227 students at entry-level and 139 students at graduate-level from a nursing program. The survey consisted of the health literacy questionnaire (HLQ (nine scales)), the eHealth Literacy Assessment toolkit (eHLA (seven scales)), the eHealth Literacy Questionnaire (eHLQ (seven scales)), questions soliciting sociodemographic data, and a single item assessing the students’ SRH. Pearson’s chi-square test and the Mann-Whitney test were used to examine the differences in HL, DL, and eHL and between groups, and Kendall’s tau-b test to examine correlations between SRH and HL, DL, and eHL.

          Results

          The level of HL, DL and eHL tended to be higher among graduate-level students than in entry-level students and was satisfactory. Age, sex, country of origin, and parents’ educational level and occupational background influenced students’ HL levels. SRH was higher in students at the graduate level. Amongst entry-level students, SRH was positively associated to seven HLQ, four EHLA and four eHLQ, amongst graduate-level students, SRH was positively associated to seven HLQ and six eHLQ.

          Conclusions

          Educators must be aware of how sociodemographic factors affects students’ literacies and increase learning opportunities by mixing students when planning activities. Considering the higher SRH in graduate-level students, HL, DL, and eHL levels indicate that current curricula and study activities are appropriate, but there is still room for improvement.

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          Most cited references22

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          Measuring well-being rather than the absence of distress symptoms: a comparison of the SF-36 Mental Health subscale and the WHO-Five well-being scale

          The health status questionnaire Short‐Form 36 (SF‐36) includes subscales measuring both physical health and mental health. Psychometrically, the mental health subscale contains a mixture of mental symptoms and psychological well‐being items, among other things, to prevent a ceiling effect when used in general population studies. Three of the mental health well‐being items are also included in the WHO‐Five well‐being scale. In a Danish general population study, the mental health subscale was compared psychometrically with the WHO‐Five in order to evaluate the ceiling effect. Tests for unidimensionality were used in the psychometric analyses, and the sensitivity of the scales in differentiating between changes in self‐reported health over the past year has been tested. The results of the study on 9,542 respondents showed that, although the WHO‐Five and the mental health subscale were found to be unidimensional, the WHO‐Five had a significantly lower ceiling effect than the mental health subscale. The analysis identified the three depression symptoms in the mental health subscale as responsible for the ceiling effect. The WHO‐Five was also found to be significantly superior to the mental health subscale in terms of its sensitivity in differentiating between those persons whose health had deteriorated over the past year and those whose health had not. In conclusion, the WHO‐Five, which measures psychological well‐being, reflects aspects other than just the absence of depressive symptoms. Copyright © 2003 Whurr Publishers Ltd.
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            The Effect of Individual Factors on Health Behaviors Among College Students: The Mediating Effects of eHealth Literacy

            Background College students’ health behavior is a topic that deserves attention. Individual factors and eHealth literacy may affect an individual’s health behaviors. The integrative model of eHealth use (IMeHU) provides a parsimonious account of the connections among the digital divide, health care disparities, and the unequal distribution and use of communication technologies. However, few studies have explored the associations among individual factors, eHealth literacy, and health behaviors, and IMeHU has not been empirically investigated. Objective This study examines the associations among individual factors, eHealth literacy, and health behaviors using IMeHU. Methods The Health Behavior Scale is a 12-item instrument developed to measure college students’ eating, exercise, and sleep behaviors. The eHealth Literacy Scale is a 12-item instrument designed to measure college students’ functional, interactive, and critical eHealth literacy. A nationally representative sample of 525 valid college students in Taiwan was surveyed. A questionnaire was administered to collect background information about participants’ health status, degree of health concern, major, and the frequency with which they engaged in health-related discussions. This study used Amos 6.0 to conduct a confirmatory factor analysis to identify the best measurement models for the eHealth Literacy Scale and the Health Behavior Scale. We then conducted a multiple regression analysis to examine the associations among individual factors, eHealth literacy, and health behaviors. Additionally, causal steps approach was used to explore indirect (mediating) effects and Sobel tests were used to test the significance of the mediating effects. Results The study found that perceptions of better health status (t520=2.14-6.12, P<.001-.03) and greater concern for health (t520=2.58-6.95, P<.001-.003) influenced college students’ development of 3 dimensions of eHealth literacy and adoption of healthy eating, exercise, and sleep behaviors. Moreover, eHealth literacy played an intermediary role in the association between individual factors and health behaviors (Sobel test=2.09-2.72, P<.001-.03). Specifically, higher levels of critical eHealth literacy promoted students’ health status and their practice of multiple positive health behaviors, including eating, exercise, and sleep behaviors. Conclusions Because this study showed that eHealth literacy mediates the association between individual factors and health behaviors, schools should aim to enhance students’ eHealth literacy and promote their health behaviors to help them achieve high levels of critical eHealth literacy. Although some of the study’s hypotheses were not supported in this study, the factors that influence health behaviors are complex and interdependent. Therefore, a follow-up study should be conducted to further explore how these factors influence one another.
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              Assessing Competencies Needed to Engage With Digital Health Services: Development of the eHealth Literacy Assessment Toolkit

              Background To achieve full potential in user-oriented eHealth projects, we need to ensure a match between the eHealth technology and the user’s eHealth literacy, described as knowledge and skills. However, there is a lack of multifaceted eHealth literacy assessment tools suitable for screening purposes. Objective The objective of our study was to develop and validate an eHealth literacy assessment toolkit (eHLA) that assesses individuals’ health literacy and digital literacy using a mix of existing and newly developed scales. Methods From 2011 to 2015, scales were continuously tested and developed in an iterative process, which led to 7 tools being included in the validation study. The eHLA validation version consisted of 4 health-related tools (tool 1: “functional health literacy,” tool 2: “health literacy self-assessment,” tool 3: “familiarity with health and health care,” and tool 4: “knowledge of health and disease”) and 3 digitally-related tools (tool 5: “technology familiarity,” tool 6: “technology confidence,” and tool 7: “incentives for engaging with technology”) that were tested in 475 respondents from a general population sample and an outpatient clinic. Statistical analyses examined floor and ceiling effects, interitem correlations, item-total correlations, and Cronbach coefficient alpha (CCA). Rasch models (RM) examined the fit of data. Tools were reduced in items to secure robust tools fit for screening purposes. Reductions were made based on psychometrics, face validity, and content validity. Results Tool 1 was not reduced in items; it consequently consists of 10 items. The overall fit to the RM was acceptable (Anderson conditional likelihood ratio, CLR=10.8; df=9; P=.29), and CCA was .67. Tool 2 was reduced from 20 to 9 items. The overall fit to a log-linear RM was acceptable (Anderson CLR=78.4, df=45, P=.002), and CCA was .85. Tool 3 was reduced from 23 to 5 items. The final version showed excellent fit to a log-linear RM (Anderson CLR=47.7, df=40, P=.19), and CCA was .90. Tool 4 was reduced from 12 to 6 items. The fit to a log-linear RM was acceptable (Anderson CLR=42.1, df=18, P=.001), and CCA was .59. Tool 5 was reduced from 20 to 6 items. The fit to the RM was acceptable (Anderson CLR=30.3, df=17, P=.02), and CCA was .94. Tool 6 was reduced from 5 to 4 items. The fit to a log-linear RM taking local dependency (LD) into account was acceptable (Anderson CLR=26.1, df=21, P=.20), and CCA was .91. Tool 7 was reduced from 6 to 4 items. The fit to a log-linear RM taking LD and differential item functioning into account was acceptable (Anderson CLR=23.0, df=29, P=.78), and CCA was .90. Conclusions The eHLA consists of 7 short, robust scales that assess individual’s knowledge and skills related to digital literacy and health literacy.
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                Author and article information

                Contributors
                lk@sund.ku.dk
                Journal
                BMC Nurs
                BMC Nurs
                BMC Nursing
                BioMed Central (London )
                1472-6955
                10 April 2020
                10 April 2020
                2020
                : 19
                : 22
                Affiliations
                [1 ]Faculty of Health, Department of Nursing and Nutrition, University College Copenhagen, Copenhagen N, Denmark
                [2 ]GRID grid.5254.6, ISNI 0000 0001 0674 042X, Department of Public Health, Section of Health Service Research, , University of Copenhagen, ; Øster Farimagsgade 5, 1353 Copenhagen, Denmark
                Article
                418
                10.1186/s12912-020-00418-w
                7149891
                32308559
                cc47118b-0cd3-4591-b00c-d407896fe6a7
                © 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
                : 22 September 2019
                : 31 March 2020
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2020

                Nursing
                health literacy,digital literacy,ehealth literacy,self-rated health,nursing students,hlq,ehlq,ehla
                Nursing
                health literacy, digital literacy, ehealth literacy, self-rated health, nursing students, hlq, ehlq, ehla

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