# The acceptability, adoption and feasibility of mobile health interventions for diabetes and hypertension care among Ghanaian healthcare workers

**Authors:** Pearl Aovare, Erik Beune, Felix P. Chilunga, Nicolas Moens, Eric P. Moll van Charante, Charles Agyemang

PMC · DOI: 10.1016/j.pecinn.2026.100456 · 2026-01-22

## TL;DR

The study examines how healthcare workers in Ghana use a mobile app for diabetes and hypertension care, finding it acceptable but facing challenges like poor connectivity and training needs.

## Contribution

The study provides new insights into mHealth adoption in low-resource settings by applying the TAM model and highlighting contextual barriers and solutions specific to Ghanaian healthcare workers.

## Key findings

- Healthcare workers found the AfyaPro app useful for reducing administrative burden and improving patient follow-up.
- Challenges included unstable internet, data entry workload, and limited patient access.
- Recommendations include decision-support tools, infrastructure improvements, and refresher training for sustainable adoption.

## Abstract

The study explored healthcare workers' experiences using the AfyaPro Connected Care app and identified key enablers and barriers to its adoption for diabetes and hypertension care in Ghana. The study applied the Technology Acceptance Model (TAM) to examine how perceptions of usefulness and ease of use of the app influence adoption and to address the gap in evidence on mHealth uptake by frontline providers in low- and middle-income country (LMIC) health systems.

A qualitative study was conducted with 20 healthcare workers from two healthcare facilities. Semi-structured interviews, guided by the TAM, explored perceptions of the app's usefulness, ease of use, and behavioral intention. The framework was appropriate for examining individual and contextual drivers of technology adoption in resource-constrained healthcare settings. Interviews were transcribed verbatim and analysed thematically.

Participants reported positive experiences with the app, noting reduced administrative burden, workflow integration, stronger patient-provider interaction and improved continuity of follow-up. The app enhanced access to specialist care, supported self-monitoring of blood pressure and glucose, and boosted confidence through its intuitive design and structured training. However, challenges persisted, including unstable power and internet connectivity, increased data entry workload, limited patient access and digital literacy, and restricted roles for junior staff. Participants recommended clearer roles, regular supervision, refresher training, and decision-support tools to improve sustainability and equitable adoption.

This study adopts a user-centered and context-sensitive approach based on provider experiences. It shows how mHealth tools can be fitted into Ghana's healthcare system, where challenges like limited infrastructure and digital literacy affect use. Innovation is seen as adapting tools and systems through digital literacy training, decision-support in provider workflows, and blended care models, helping to build a fairer and more sustainable health system.

Healthcare workers found the mHealth app feasible and acceptable. The findings highlight the potential of digital tools to improve chronic disease care in resource-limited settings. The study demonstrates how contextual factors in LMIC settings reshape key TAM constructs, with clear implications for mHealth policy, scale-up strategies, and refinement of technology adoption theory.

•Healthcare workers support Afyapro app for improved patient outcomes.•User-friendly app enhances health management and patient empowerment.•Challenges include connectivity, tech issues for elderly and systemic barriers.•Recommends decision-support tools, infrastructure fixes, and targeted training.

Healthcare workers support Afyapro app for improved patient outcomes.

User-friendly app enhances health management and patient empowerment.

Challenges include connectivity, tech issues for elderly and systemic barriers.

Recommends decision-support tools, infrastructure fixes, and targeted training.

## Linked entities

- **Diseases:** diabetes (MONDO:0005015)

## Full-text entities

- **Diseases:** diabetes (MESH:D003920), disease (MESH:D004194), hypertension (MESH:D006973)
- **Chemicals:** glucose (MESH:D005947)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Figures

1 figure with captions in the complete paper: https://tomesphere.com/paper/PMC12870867/full.md

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Source: https://tomesphere.com/paper/PMC12870867