ArticleJMIR public health and surveillance2024
Digital Health Technology Use Across Socioeconomic Groups Prior to and During the COVID-19 Pandemic: Panel Study.
Article in JMIR public health and surveillance, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- A Mobile Virtual Reality-Based Intervention for Stress Reduction Among Young Adults: Pilot Randomized Controlled Trial.JMIR mHealth and uHealth · 2026Trial
- Digital Health Technology Use by Vietnamese Americans: Cross-Sectional Study.Asian/Pacific Island nursing journal · 2026Article
- Health equity and public acceptance of large language models in healthcare in China: A national population-based survey.PLOS digital health · 2026Article
- National Acceptance and Determinants of Immersive Extended Reality in Health Care in China: Cross-Sectional Study.Journal of medical Internet research · 2026Article
- Association of online health information exposure with disease awareness initial symptom severity in benign prostatic hyperplasia: a cross-sectional study.The Canadian journal of urology · 2026Article
- Privacy Policy Compliance of Mobile Sports and Health Apps in China: Scale Development, Data Analysis, and Prospects for Regulatory Reform.JMIR mHealth and uHealth · 2026Article
- Intention to Use Digital Health Among COPD Patients in Europe: A Cluster Analysis.Healthcare (Basel, Switzerland) · 2026Article
- Sleep in the age of technology: the use of sleep apps and perceived impact on sleep and sleep habits.Frontiers in psychology · 2026Article
- Digital health technologies for the management of sarcopenia in patients receiving maintenance hemodialysis: a narrative review.Frontiers in nutrition · 2026Review
- African digital health strategic plans analysis: key weaknesses in contextualization, intervention focus, and technological foresight.NPJ digital medicine · 2025Article
- Factors predicting eHealth literacy: A profile of California, USA.PEC innovation · 2025Article
- A Smartphone Is Not Enough: Telehealth Attendance and the Digital Divide.Health care science · 2025Article
- Examining the Influence of Demographic and Socioeconomic Factors on Disparities in Health Care App Usage: Protocol for a Systematic Scoping Review.JMIR research protocols · 2025Article
- Article
- A Method for Enabling Digital Health Technologies in Clinical and Translational Research at an Academic Medical Center.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2025Article
- Influencing public acceptance of artificial intelligence (AI) in healthcare delivery.Frontiers in digital health · 2025Article
- Digital access and health outcomes: The moderating role of socioeconomic status in health information seeking.Digital healthArticle
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Authors and funding
4 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundDigital technologies have become more important in the health care sector in the past decades. This transition from conventional to digital health care has been accelerated by the impact of the COVID-19 pandemic, which poses the risk of creating a "digital divide," inadvertently placing those who are older, economically disadvantaged, and have a lower level of education at a disadvantage.
objectiveThis study focuses on the influence of socioeconomic factors on the adoption of digital health technology in the Frisian population and how this relation is affected by the COVID-19 pandemic.
methodsIn 2019 and 2020, a panel study was conducted on digital health in the Frisian population in the Netherlands. In the survey, the use of digital health technology was operationalized in a broad sense, going beyond the care context by also including preventative health-promoting solutions generally available on the consumer market, such as wearables and lifestyle apps. First, to assess the influence of socioeconomic factors on the total use of digital health apps, a generalized linear model was fitted with use of digital health app as the dependent variable and socioeconomic factors as between-subject factors on the 2019 data. Second, to analyze whether the use of separate health apps increased from 2019 to 2020, we conducted chi-square tests on different digital health app types. Third, to examine the influence of COVID-19 on the use of digital health apps, a generalized linear mixed model was fitted with the use of digital health apps as the dependent variable, COVID-19 as the within-subject variable, and socioeconomic factors as between-subject factors.
resultsThe results indicated that prior to the COVID-19 pandemic, digital health technology use was higher in women, younger people, and those who are well educated and economically more privileged. Moreover, the percentage of people who reported using digital health technology rose from 70% (1580/2258) to 82.5% (1812/2197) due to the COVID-19 pandemic. This increase was significant for all separate types of digital health technology (all P<.001). In addition, we found the interaction effects of COVID-19 with age and education attainment, indicating that the lower total use among older people and people with lower education attainment became slightly less apparent from 2019 to 2020.
conclusionsThese findings on the influence of the COVID-19 pandemic on the digital divide indicated that the use of all types of digital health apps increased and that older individuals and people with a lower level of education caught up a little during COVID-19. Future research should gain more insight into this effect and examine whether it persists beyond the COVID-19 pandemic. Additionally, future endeavors should focus on vulnerable groups, ensuring they receive adequate attention to guarantee access to health care, preventative health-promoting solutions, and social services.
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