Previously submitted to: JMIR mHealth and uHealth (no longer under consideration since Jul 09, 2024)
Date Submitted: Apr 1, 2024
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Understanding the factors influencing adoption of mHealth in Rural Patients: A Case of Embu, Kenya
ABSTRACT
Background:
Kenya and other low-income countries face healthcare challenges such as affordability, access, and health worker shortages. Digital technologies have disrupted traditional service delivery in industries such as banking and retail. Significant changes have not yet affected healthcare. Technological advancements in healthcare may help to leapfrog barriers such as the cost of physical infrastructure.
Objective:
The study examined the influence of technical, social, and individual factors in adopting mHealth products in Embu, Kenya.
Methods:
A cross-sectional quantitative study using a structured close-ended questionnaire was conducted in Embu, Kenya, between August and December 2019. Correlation and regression analysis were used to determine the effect of the influential factors on adopting mHealth products.
Results:
207 (75%) randomly selected respondents over 18 years completed the survey, with the largest group (39.4%) aged between 35-44 years and 43% holding a Post-Secondary school diploma. Correlation analysis showed that social factors positively and significantly correlate to mHealth products' adoption (r(207) = .793, P < .05), reflecting a generally favourable view towards using mobile phones for seeking healthcare. Similarly, technical factors showed a significant correlation with mHealth adoption (r(207) = .931, P < .05), supported by widespread smartphone ownership and access to high-speed internet. Individual factors, including perceptions of the time-saving benefits of seeking healthcare services using a mobile phone, also demonstrated a positive correlation with the adoption of mHealth (r(207) = .708, P < .05).
Conclusions:
Our study underscores the significant relationship of social, technical, and individual factors in adopting mHealth products. Digital health implementers should leverage increasing access to technical factors such as the Internet, smartphones, good mobile network coverage, and high utilization of social media to facilitate the positive adoption of mHealth. Our research provided insights from Embu; however, expansive studies encompassing rural and urban demographics are required to enhance generalizability. Clinical Trial: N/A
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