Explaining the impact of mHealth on maternal and child health care in low- and middle-income countries

BACKGROUND: Despite the growing global application of mobile health (mHealth) technology in maternal and child health, contextual factors, and mechanisms by which interventional outcomes are generated, have not been subjected to a systematic examination. In this study, we sought to uncover context, mechanisms, and outcome elements of various mHealth interventions based on implementation and evaluation studies to formulate theories or models explicating how mHealth interventions work (or not) both for health care providers and for pregnant women and mothers.

METHOD: We undertook a realist synthesis. An electronic search of five online databases (PubMed/Medline, Google Scholar, Scopus, Academic Search Premier and Health Systems Evidence) was performed. Using appropriate Boolean phrases terms and selection procedures, 32 articles were identified. A theory-driven approach, narrative synthesis, was applied to synthesize the data. Thematic content analysis was used to delineate elements of the intervention, including its context, actors, mechanisms, and outcomes. Abduction and retroduction were applied using a realist evaluation heuristic tool to formulate generative theories.

RESULTS: We formulated two configurational models illustrating how and why mHealth impacts implementation and uptake of maternal and child health care. Implementation-related mechanisms include buy-in from health care providers, perceived support of health care providers' motivation and perceived ease of use and usefulness. These mechanisms are influenced by adaptive health system conditions including organization, resource availability, policy implementation dynamics, experience with technology, network infrastructure and connectivity. For pregnant women and mothers, mechanisms that trigger mHealth use and consequently uptake of maternal and child health care include perceived satisfaction, motivation and positive psychological support. Information overload was identified as a potential negative mechanism impacting the uptake of maternal and child health care. These mechanisms are influenced by health system conditions, socio-cultural characteristics, socio-economic and demographics characteristics, network infrastructure and connectivity and awareness.

CONCLUSION: Models developed in this study provide a detailed understanding of implementation and uptake of mHealth interventions and how and why they impact maternal and child health care in low- and middle-income countries. These models provide a foundation for the 'white box' of theory-driven evaluation of mHealth interventions and can improve rollout and implementation where required.