Exploring the equity impact of mobile health-based human immunodeficiency virus interventions: A systematic review of reviews and evidence synthesis

Abstract

Objective: While mobile health-based human immunodeficiency virus (HIV) interventions are often designed to promote health equity, systematic differences in the use of and access to mobile technologies may counteract that and widen treatment gaps. This systematic review applies an equity lens to investigate whether existing research provides adequate evidence on the ethical implications of mHealth technologies in HIV treatment and prevention.

Methods: This study included a two-stage methodology, consisting of (a) a systematic review of systematic reviews and (b) an evidence synthesis of primary studies. For the review of reviews we searched eight electronic databases, eight electronic journals and Google Scholar. We also screened reference lists and consulted authors of included studies. Primary studies were extracted from eligible reviews. We based our data extraction and analysis on the Place of residence, Race, Occupation, Gender/Sex, Religion, Education, Socioeconomic status, Social capital and other disadvantage related characteristics (PROGRESS-Plus) framework and the use of harvest plots, focusing on the socio-demographic distribution of mHealth effects.

Results: A total of 8786 citations resulted in 19 eligible reviews and 39 eligible primary studies. Existing reviews did not provide any analyses of the equity impacts of mobile health-based HIV initiatives. Information availability was higher in primary studies, predominantly suggesting no social gradient of mobile health-based HIV interventions. Overall, evidence remains weak and not sufficient to allow for confident equity statements.

Conclusions: Despite the negative force of socio-demographic inequities and the emerging nature of mobile health technologies, evidence on the equity implications of mobile health interventions for HIV care remains scarce. Not knowing how the effects of mobile health technologies differ across population subgroups inevitably limits our capacities to equitably adopt, adjust and integrate mobile health interventions towards reaching those disproportionally affected by the epidemic.

Keywords: Mobile health; eHealth; human immunodeficiency virus; inequalities; socioeconomic factors; telehealth.

Figure 1.

Preferred reporting items for systematic reviews and meta-analyses (PRISMA) flow diagram of screening and review process of systematic reviews. HIV: human immunodeficiency virus; m-Health: mobile health.

Figure 2.

Harvest plot of subgroup analysis results in primary studies. Each bar represents a primary study. Bar position represents the supported hypothesis. Bar color reflects the utilized human immunodeficiency virus (HIV) outcome measure (white = observation, grey = self-reported, black = objective measures). The numbers within each bar correspond to the study number provided by Supplemental Material Appendix C. The number above each bar represents study quality. A more detailed account of each harvest-plot element is provided by Table 1.

Figure 3.

Harvest plot of interaction effects results in primary studies. Each block represents a primary study; Bar position represents the supported hypothesis. Bar color reflects the utilized human immunodeficiency virus (HIV) outcome measure (white = observation, grey = self-reported, black = objective measures). The numbers within each bar represent the study citation, corresponding to the study numbers provided by Supplemental Material Appendix C. The number above each bar represents study quality. A more detailed account of each harvest-plot element is provided by Table 1.