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Community health workers (CHWs) found a mobile health (mHealth) app useful for hypertension management in Guatemala. Iterative feedback improved the app, highlighting needs for better training and addressing systemic challenges in resource-limited settings.

Keywords:
Guatemalacommunity health workersdigital healthhypertension managementmHealth appmobile healthnoncommunicable diseasesrural health

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Area of Science:

  • Global Health
  • Digital Health
  • Health Informatics

Background:

  • Hypertension management is a significant challenge in low- and middle-income countries (LMICs) due to limited healthcare resources.
  • Community health workers (CHWs) are vital for delivering care in these settings.
  • Mobile health (mHealth) tools can enhance chronic disease management when CHWs are involved in development.

Purpose of the Study:

  • To evaluate CHW feedback on a novel tablet-based mHealth tool for hypertension diagnosis and management.
  • To assess the usability, workflow integration, and cultural appropriateness of the mHealth tool from the CHW perspective.
  • To identify areas for iterative refinement of the mHealth app and hypertension program.

Main Methods:

  • A mixed-methods pilot study was conducted in rural Guatemala over 6 months with 6 CHWs.
  • Quantitative data collected via System Usability Scale and Likert surveys.
  • Qualitative data gathered through written surveys and focus group interviews in Spanish.

Main Results:

  • The mHealth app demonstrated good usability (average System Usability Scale > 70) and was perceived as useful and easy to use.
  • CHWs requested improved training, simplified medication regimens, and streamlined survey questions.
  • Key concerns included training adequacy, financial compensation, and cultural appropriateness of data collection.

Conclusions:

  • Iterative integration of CHW feedback is crucial for developing effective and culturally appropriate mHealth interventions in resource-constrained settings.
  • Addressing identified technical and systemic challenges can enhance future mHealth program implementations for chronic diseases.
  • Findings are exploratory due to small sample size and self-reported data, offering hypothesis-generating insights.