Mapping Child Malnutrition and Measuring Efficiency of Community Healthcare Workers through Location Based Games in India
Arka Majhi, Aparajita Mondal, Satish B. Agnihotri

TL;DR
This paper presents a geospatial game-based approach to improve data collection efficiency and engagement among community healthcare workers in India for child malnutrition monitoring.
Contribution
It introduces a co-designed geospatial game method that enhances data collection accuracy and CHW engagement over traditional non-game approaches.
Findings
Game-based method significantly improved data collection efficiency (p<0.05).
Participants showed higher engagement and retention with the game.
The approach effectively maps hotspots and density distributions of child malnutrition.
Abstract
In India, Community Healthcare Workers (CHWs) serve as critical intermediaries between the state and beneficiaries, including pregnant mothers and children. Effective planning and prioritization of care and services necessitate the collection of accurate health data from the community. Crowdsourcing child anthropometric data through CHWs could establish a valuable repository for evidence-based decision-making and service planning. However, existing platforms often fail to maintain CHWs' engagement over time and across different spatial contexts, resulting in spatially misrepresented and outdated data. This study addresses these challenges by conducting a co-design exercise to develop innovative methods for collecting anthropometric data over time and space. The exercise involved analyzing data to create hotspot and density distribution maps. We implemented a trial of the developed…
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