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      Health App Use and Its Correlates Among Individuals With and Without Type 2 Diabetes: Nationwide Population-Based Survey

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          Abstract

          Background

          Evidence suggests that mobile health app use is beneficial for the prevention and management of type 2 diabetes (T2D) and its associated complications; however, population-based research on specific determinants of health app use in people with and without T2D is scarce.

          Objective

          This cross-sectional study aimed to provide population-based evidence on rates and determinants of health app use among adults with and without T2D, thereby covering a prevention perspective and a diabetes management perspective, respectively.

          Methods

          The study population included 2327 adults without a known diabetes diagnosis and 1149 adults with known T2D from a nationwide telephone survey in Germany conducted in 2017. Rates of smartphone ownership and health app use were estimated based on weighted sample proportions. Among smartphone owners, determinants of health app use were identified for both groups separately in multivariable logistic regression models. Sociodemographic factors, diabetes-related factors or indicators, psychological and health-related factors, and physician-provided information were selected as potential determinants.

          Results

          Among participants without known diabetes, 74.72% (1690/2327) were smartphone owners. Of those, 49.27% (717/1690) used health apps, most often to improve regular physical activity. Among participants with T2D, 42.26% (481/1149) were smartphone owners. Of those, 41.1% (171/481) used health apps, most commonly to target a healthy diet. Among people without known diabetes, determinants significantly (all P values <.05) associated with an increased likelihood of health app use compared with their reference group were as follows: younger and middle age of 18 to 44 or 45 to 64 years (odds ratios [ORs] 3.89; P<.001 and 1.76; P=.004, respectively), overweight or obesity (ORs 1.58; P<.001 and 2.07; P<.001, respectively), hypertension diagnosis (OR 1.31; P=.045), former or current smoking (ORs 1.51; P=.002 and 1.58; P<.001, respectively), perceiving health as very good (OR 2.21; P<.001), other chronic diseases (OR 1.48; P=.002), and having received health advice from a physician (OR 1.48; P<.001). A slight or high perceived diabetes risk (ORs 0.78; P=.04 and 0.23; P<.001, respectively) was significantly associated with a decreased likelihood of health app use. Among people with T2D, younger and middle age (18-64 years; OR 1.84; P=.007), female gender (OR 1.61; P=.02), and using a glucose sensor in addition or instead of a glucose meter (OR 2.74; P=.04) were significantly positively associated with health app use.

          Conclusions

          In terms of T2D prevention, age, diabetes-related risk factors, psychological and health-related factors, and medical health advice may inform app development for specific target groups. In addition, health professionals may encourage health app use when giving advice on health behaviors. Concerning T2D management, only a few determinants seem relevant for explaining health app use among people with T2D, indicating a need for more future research on which people with T2D use health apps and why.

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          Most cited references44

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          Type 2 diabetes in adolescents and young adults

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            The global economic burden of diabetes in adults aged 20-79 years: a cost-of-illness study.

            Differences in methods and data used in past studies have limited comparisons of the cost of illness of diabetes across countries. We estimate the full global economic burden of diabetes in adults aged 20-79 years in 2015, using a unified framework across all countries. Our objective was to highlight patterns of diabetes-associated costs as well as to identify the need for further research in low-income regions.
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              Who Uses Mobile Phone Health Apps and Does Use Matter? A Secondary Data Analytics Approach

              Background Mobile phone use and the adoption of healthy lifestyle software apps (“health apps”) are rapidly proliferating. There is limited information on the users of health apps in terms of their social demographic and health characteristics, intentions to change, and actual health behaviors. Objective The objectives of our study were to (1) to describe the sociodemographic characteristics associated with health app use in a recent US nationally representative sample; (2) to assess the attitudinal and behavioral predictors of the use of health apps for health promotion; and (3) to examine the association between the use of health-related apps and meeting the recommended guidelines for fruit and vegetable intake and physical activity. Methods Data on users of mobile devices and health apps were analyzed from the National Cancer Institute’s 2015 Health Information National Trends Survey (HINTS), which was designed to provide nationally representative estimates for health information in the United States and is publicly available on the Internet. We used multivariable logistic regression models to assess sociodemographic predictors of mobile device and health app use and examine the associations between app use, intentions to change behavior, and actual behavioral change for fruit and vegetable consumption, physical activity, and weight loss. Results From the 3677 total HINTS respondents, older individuals (45-64 years, odds ratio, OR 0.56, 95% CI 0.47-68; 65+ years, OR 0.19, 95% CI 0.14-0.24), males (OR 0.80, 95% CI 0.66-0.94), and having degree (OR 2.83, 95% CI 2.18-3.70) or less than high school education (OR 0.43, 95% CI 0.24-0.72) were all significantly associated with a reduced likelihood of having adopted health apps. Similarly, both age and education were significant variables for predicting whether a person had adopted a mobile device, especially if that person was a college graduate (OR 3.30). Individuals with apps were significantly more likely to report intentions to improve fruit (63.8% with apps vs 58.5% without apps, P=.01) and vegetable (74.9% vs 64.3%, P<.01) consumption, physical activity (83.0% vs 65.4%, P<.01), and weight loss (83.4% vs 71.8%, P<.01). Individuals with apps were also more likely to meet recommendations for physical activity compared with those without a device or health apps (56.2% with apps vs 47.8% without apps, P<.01). Conclusions The main users of health apps were individuals who were younger, had more education, reported excellent health, and had a higher income. Although differences persist for gender, age, and educational attainment, many individual sociodemographic factors are becoming less potent in influencing engagement with mobile devices and health app use. App use was associated with intentions to change diet and physical activity and meeting physical activity recommendations.
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                Author and article information

                Contributors
                Journal
                JMIR Diabetes
                JMIR Diabetes
                JD
                JMIR Diabetes
                JMIR Publications (Toronto, Canada )
                2371-4379
                Apr-Jun 2020
                20 May 2020
                : 5
                : 2
                : e14396
                Affiliations
                [1 ] Institute for Medical Sociology and Rehabilitation Science Charité – Universitätsmedizin Berlin Berlin Germany
                [2 ] Department of Epidemiology and Health Monitoring Robert Koch Institute Berlin Germany
                [3 ] Cologne Center for Ethics, Rights, Economics, and Social Sciences of Health Cologne Germany
                [4 ] Preventive Cardiology and Medical Prevention, Department of Cardiology University Medical Centre Johannes Gutenberg University Mainz Germany
                [5 ] Federal Center for Health Education (BZgA) Office for National Education and Communication on Diabetes Mellitus Cologne Germany
                Author notes
                Corresponding Author: Lena M Stühmann lena.stuehmann@ 123456charite.de
                Author information
                https://orcid.org/0000-0003-0550-389X
                https://orcid.org/0000-0003-2919-450X
                https://orcid.org/0000-0002-9413-2148
                https://orcid.org/0000-0003-1399-6874
                https://orcid.org/0000-0003-2304-9248
                https://orcid.org/0000-0002-0477-1369
                https://orcid.org/0000-0002-1902-7567
                https://orcid.org/0000-0001-7492-7210
                Article
                v5i2e14396
                10.2196/14396
                7270854
                32432555
                aa790756-3f0b-4830-a638-8d3498e49f7d
                ©Lena M Stühmann, Rebecca Paprott, Christin Heidemann, Jens Baumert, Sylvia Hansen, Daniela Zahn, Christa Scheidt-Nave, Paul Gellert. Originally published in JMIR Diabetes (http://diabetes.jmir.org), 20.05.2020.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Diabetes, is properly cited. The complete bibliographic information, a link to the original publication on http://diabetes.jmir.org/, as well as this copyright and license information must be included.

                History
                : 15 April 2019
                : 23 June 2019
                : 17 November 2019
                : 5 February 2020
                Categories
                Original Paper
                Original Paper

                mobile app,smartphone,diabetes mellitus,type 2 diabetes,risk factors,health-related behavior,health promotion

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