JMIR Publications

ABSTRACT

Background:

Mobile health (mHealth) holds promise for enhancing patient care, yet attrition in its use remains a major barrier. Low retention rates limit its potential impact, while barriers to accessing or adopting mHealth vary across populations and countries. These difference in utilization of mHealth may exacerbate health inequalities, contributing to the digital health divide.

Objective:

We aimed to conduct a systematic review and meta-analysis to investigate the factors associated with inequalities in mHealth utilization across different implementation phases, including access, adoption, adherence, and maintenance.

Methods:

This systematic review and meta-analysis analyzed mHealth research from 2000 to May 30, 2024, using databases such as PubMed and ProQuest. Eligible studies included smartphones, mHealth apps, wearables, and inequality indicators across four mHealth phases: access, adoption, adherence, and maintenance. Excluded studies were non-peer-reviewed, opinion-based, or not in English. Extracted data included study characteristics, target populations, health outcomes, and inequality factors like age, gender, socioeconomic status, and digital literacy. Factors were categorized using a digital health equity framework (biological, behavioral, sociocultural, digital, healthcare system, and physical domains). Meta-analyses were performed using a random-effects model for factors reported in at least three studies, with heterogeneity assessed by the I² statistic.

Results:

Among 1,990 studies, 62 met inclusion criteria, and 33 underwent meta-analysis. Phases of mHealth utilization were access (37.1%), adoption (75.8%), adherence (14.5%), and maintenance (3.2%). Access improved with higher education (OR = 2.53; 95% CI = 1.29–4.97) and income (OR = 2.72; 95% CI = 1.17–6.29). Adoption was similarly influenced by education (OR = 2.07; 95% CI = 1.58–2.70) and income (OR = 2.17; 95% CI = 1.32–3.57) but negatively affected by older age (OR = 0.38; 95% CI = 0.15–0.97). Comorbidities increased adoption (OR = 1.50; 95% CI = 1.33–1.69). Race, gender, and health literacy showed minimal impact.

Conclusions:

Inequalities in mHealth utilization reflect interconnected barriers across its phases. While access and adoption have been studied, adherence remains underexplored, highlighting the need for longitudinal research. Addressing inequalities requires targeted interventions to improve digital health literacy, affordability, and trust to support equitable, sustained use.