Impact of Illness on Electronic Health Use (The Seventh Tromsø Study - Part 2): Population-Based Questionnaire Study
Autor: | Andrius Budrionis, Kassaye Yitbarek Yigzaw, Rolf Wynn, Luis Marco-Ruiz, Sunday Oluwafemi Oyeyemi, Johan Gustav Bellika |
---|---|
Jazyk: | angličtina |
Rok vydání: | 2020 |
Předmět: |
Adult
Male medicine.medical_specialty 020205 medical informatics social media Psychological intervention Health Informatics 02 engineering and technology Disease Logistic regression search engines 03 medical and health sciences 0302 clinical medicine Disability benefits Surveys and Questionnaires 0202 electrical engineering electronic engineering information engineering eHealth medicine Humans 030212 general & internal medicine mobile apps Original Paper VDP::Medisinske Fag: 700::Helsefag: 800::Samfunnsmedisin sosialmedisin: 801 business.industry Odds ratio Middle Aged Telemedicine Cross-Sectional Studies Research Design Family medicine Chronic Disease Household income Female internet VDP::Medical disciplines: 700::Health sciences: 800::Community medicine Social medicine: 801 business |
Zdroj: | Journal of Medical Internet Research |
Popis: | Background Patients who suffer from different diseases may use different electronic health (eHealth) resources. Thus, those who plan eHealth interventions should take into account which eHealth resources are used most frequently by patients that suffer from different diseases. Objective The aim of this study was to understand the associations between different groups of chronic diseases and the use of different eHealth resources. Methods Data from the seventh survey of the Tromsø Study (Tromsø 7) were analyzed to determine how different diseases influence the use of different eHealth resources. Specifically, the eHealth resources considered were use of apps, search engines, video services, and social media. The analysis contained data from 21,083 participants in the age group older than 40 years. A total of 15,585 (15,585/21,083; 73.92%) participants reported to have suffered some disease, 10,604 (10,604/21,083; 50.29%) participants reported to have used some kind of eHealth resource in the last year, and 7854 (7854/21,083; 37.25%) participants reported to have used some kind of eHealth resource in the last year and suffered (or had suffered) from some kind of specified disease. Logistic regression was used to determine which diseases significantly predicted the use of each eHealth resource. Results The use of apps was increased among those individuals that (had) suffered from psychological problems (odds ratio [OR] 1.39, 95% CI 1.23-1.56) and cardiovascular diseases (OR 1.12, 95% CI 1.01-1.24) and those part-time workers that (had) suffered from any of the diseases classified as others (OR 2.08, 95% CI 1.35-3.32). The use of search engines for accessing health information increased among individuals who suffered from psychological problems (OR 1.39, 95% CI 1.25-1.55), cancer (OR 1.26, 95% CI 1.11-1.44), or any of the diseases classified as other diseases (OR 1.27, 95% CI 1.13-1.42). Regarding video services, their use for accessing health information was more likely when the participant was a man (OR 1.31, 95% CI 1.13-1.53), (had) suffered from psychological problems (OR 1.70, 95% CI 1.43-2.01), or (had) suffered from other diseases (OR 1.43, 95% CI 1.20-1.71). The factors associated with an increase in the use of social media for accessing health information were as follows: (had) suffered from psychological problems (OR 1.65, 95% CI 1.42-1.91), working part time (OR 1.35, 95% CI 0.62-2.63), receiving disability benefits (OR 1.42, 95% CI 1.14-1.76), having received an upper secondary school education (OR 1.20, 95% CI 1.03-1.38), being a man with a high household income (OR 1.67, 95% CI 1.07-2.60), suffering from cardiovascular diseases and having a high household income (OR 3.39, 95% CI 1.62-8.16), and suffering from respiratory diseases while being retired (OR 1.95, 95% CI 1.28-2.97). Conclusions Our findings show that different diseases are currently associated with the use of different eHealth resources. This knowledge is useful for those who plan eHealth interventions as they can take into account which type of eHealth resource may be used for gaining the attention of the different user groups. |
Databáze: | OpenAIRE |
Externí odkaz: |