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Inequalities in the Use of eHealth Between Socioeconomic Groups Among Patients With Type 1 and Type 2 Diabetes: Cross-Sectional Study

AH. Hansen, M. Bradway, J. Broz, T. Claudi, Ø. Henriksen, SC. Wangberg, E. Årsand,

. 2019 ; 21 (5) : e13615. [pub] 20190529

Jazyk angličtina Země Kanada

Typ dokumentu časopisecké články, práce podpořená grantem

Perzistentní odkaz   https://www.medvik.cz/link/bmc20006322

BACKGROUND: The prevalence of diabetes and the use of electronic health (eHealth) are increasing. People with diabetes need frequent monitoring and follow-up of health parameters, and eHealth services can be highly valuable. However, little is known about the use of eHealth in different socioeconomic groups among people with diabetes. OBJECTIVE: The aim of this study was to investigate the use of 4 different eHealth platforms (apps, search engines, video services, and social media sites) and the association with socioeconomic status (SES) among people diagnosed with type 1 and type 2 diabetes mellitus (T1D and T2D, respectively). METHODS: We used email survey data from 1250 members of the Norwegian Diabetes Association (aged 18-89 years), collected in 2018. Eligible for analyses were the 1063 respondents having T1D (n=523) and T2D (n=545). 5 respondents reported having both diabetes types and thus entered into both groups. Using descriptive statistics, we estimated the use of the different types of eHealth. By logistic regressions, we studied the associations between the use of these types of eHealth and SES (education and household income), adjusted for gender, age, and self-rated health. RESULTS: We found that 87.0% (447/514) of people with T1D and 77.7% (421/542) of people with T2D had used 1 or more forms of eHealth sometimes or often during the previous year. The proportion of people using search engines was the largest in both diagnostic groups, followed by apps, social media, and video services. We found a strong association between a high level of education and the use of search engines, whereas there were no educational differences for the use of apps, social media, or video services. In both diagnostic groups, high income was associated with the use of apps. In people with T1D, lower income was associated with the use of video services. CONCLUSIONS: This paper indicates a digital divide among people with diabetes in Norway, with consequences that may contribute to sustaining and shaping inequalities in health outcomes. The strong relationship between higher education and the use of search engines, along with the finding that the use of apps, social media, and video services was not associated with education, indicates that adequate communication strategies for audiences with varying education levels should be a focus in future efforts to reduce inequalities in health outcomes.

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$a BACKGROUND: The prevalence of diabetes and the use of electronic health (eHealth) are increasing. People with diabetes need frequent monitoring and follow-up of health parameters, and eHealth services can be highly valuable. However, little is known about the use of eHealth in different socioeconomic groups among people with diabetes. OBJECTIVE: The aim of this study was to investigate the use of 4 different eHealth platforms (apps, search engines, video services, and social media sites) and the association with socioeconomic status (SES) among people diagnosed with type 1 and type 2 diabetes mellitus (T1D and T2D, respectively). METHODS: We used email survey data from 1250 members of the Norwegian Diabetes Association (aged 18-89 years), collected in 2018. Eligible for analyses were the 1063 respondents having T1D (n=523) and T2D (n=545). 5 respondents reported having both diabetes types and thus entered into both groups. Using descriptive statistics, we estimated the use of the different types of eHealth. By logistic regressions, we studied the associations between the use of these types of eHealth and SES (education and household income), adjusted for gender, age, and self-rated health. RESULTS: We found that 87.0% (447/514) of people with T1D and 77.7% (421/542) of people with T2D had used 1 or more forms of eHealth sometimes or often during the previous year. The proportion of people using search engines was the largest in both diagnostic groups, followed by apps, social media, and video services. We found a strong association between a high level of education and the use of search engines, whereas there were no educational differences for the use of apps, social media, or video services. In both diagnostic groups, high income was associated with the use of apps. In people with T1D, lower income was associated with the use of video services. CONCLUSIONS: This paper indicates a digital divide among people with diabetes in Norway, with consequences that may contribute to sustaining and shaping inequalities in health outcomes. The strong relationship between higher education and the use of search engines, along with the finding that the use of apps, social media, and video services was not associated with education, indicates that adequate communication strategies for audiences with varying education levels should be a focus in future efforts to reduce inequalities in health outcomes.
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$a Bradway, Meghan $u Norwegian Centre for eHealth Research, University Hospital of North Norway, Tromsø, Norway. Department of Clinical Medicine, University Hospital of North Norway, Tromsø, Norway.
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$a Broz, Jan $u Department of Internal Medicine, Second Faculty of Medicine, Charles University, Prague, Czech Republic.
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$a Claudi, Tor $u Department of Medicine, Nordland Hospital, Bodø, Norway.
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$a Henriksen, Øystein $u Faculty of Social Sciences, Nord University, Bodø, Norway.
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$a Wangberg, Silje C $u Department of Health and Care Sciences, Faculty of Health Sciences, UiT-The Arctic University of Norway, Narvik, Norway.
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$a Årsand, Eirik $u Norwegian Centre for eHealth Research, University Hospital of North Norway, Tromsø, Norway. Department of Clinical Medicine, UiT-The Arctic University of Norway, Tromsø, Norway.
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