Distributions of actual usage sub-indices.

Community health systems are poised to play a prominent role in achieving universal health coverage in low- and middle-income countries, as demonstrated during the COVID-19 pandemic response. The advent of health information technology has provided an opportunity to optimize the community health space and improve efficiency. However, there is limited knowledge about the acceptance and usage of health information technology among community health workers, a prerequisite for scaled implementation. This study aimed to use the technology acceptance model (TAM) to predict the acceptance and usage of health information technology among CHWs, identify external factors, and understand the impact on community health systems. Specifically, we conducted semi-structured interviews with 170 community health workers who were recruited through both convenience and snowball sampling. We then performed response coding and cross-tabulation, correlation, and regression analysis. As a result, the TAM effectively predicted CHWs’ behavioral intention to use digital health tools. However, actual usage was not well predicted, and there was a mismatch between high behavioral intention and low actual usage. Access to smartphones emerged as a major determinant of actual usage, overshadowing other variables in the TAM. In conclusion, while CHWs show strong acceptance of digital health tools, structural barriers, particularly limited access to smartphones, hinder their actual use. These findings highlight the importance of addressing infrastructural inequities to enable the effective and equitable digitization of community health systems.