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Meta-Analysis
. 2020 Feb 6;22(2):e11613.
doi: 10.2196/11613.

Adherence to Electronic Health Tools Among Vulnerable Groups: Systematic Literature Review and Meta-Analysis

Jelena Arsenijevic #  1 , Lars Tummers #  1 , Niels Bosma  2
Affiliations
Meta-Analysis

Adherence to Electronic Health Tools Among Vulnerable Groups: Systematic Literature Review and Meta-Analysis

Jelena Arsenijevic et al. J Med Internet Res. .

Abstract

Background: Electronic health (eHealth) tools are increasingly being applied in health care. They are expected to improve access to health care, quality of health care, and health outcomes. Although the advantages of using these tools in health care are well described, it is unknown to what extent eHealth tools are effective when used by vulnerable population groups, such as the elderly, people with low socioeconomic status, single parents, minorities, or immigrants.

Objective: This study aimed to examine whether the design and implementation characteristics of eHealth tools contribute to better use of these tools among vulnerable groups.

Methods: In this systematic review, we assessed the design and implementation characteristics of eHealth tools that are used by vulnerable groups. In the meta-analysis, we used the adherence rate as an effect size measure. The adherence rate is defined as the number of people who are repetitive users (ie, use the eHealth tool more than once). We also performed a meta-regression analysis to examine how different design and implementation characteristics influenced the adherence rate.

Results: Currently, eHealth tools are continuously used by vulnerable groups but to a small extent. eHealth tools that use multimodal content (such as videos) and have the possibility for direct communication with providers show improved adherence among vulnerable groups.

Conclusions: eHealth tools that use multimodal content and provide the possibility for direct communication with providers have a higher adherence among vulnerable groups. However, most of the eHealth tools are not embedded within the health care system. They are usually focused on specific problems, such as diabetes or obesity. Hence, they do not provide comprehensive services for patients. This limits the use of eHealth tools as a replacement for existing health care services.

Keywords: digital health; disparities in health care; eHealth; meta-analysis.

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Conflict of interest statement

Conflicts of Interest: None declared.

Figures

Figure 1
Figure 1
Searching strategy for PubMed I.
Figure 2
Figure 2
Results from meta-analysis-effect size adherence rate.
Figure 3
Figure 3
Funnel plot corresponding to Begg’s test (pseudo 95% confidence limits).
Figure 4
Figure 4
Regression line related to the Egger test.
See this image and copyright information in PMC

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