Analysing 3429 digital supervisory interactions between Community Health Workers in Uganda and Kenya: the development, testing and validation of an open access predictive machine learning web app.

Background: Despite the growth in mobile technologies (mHealth) to support Community Health Worker (CHW) supervision, the nature of mHealth-facilitated supervision remains underexplored. One strategy to support supervision at scale could be artificial intelligence (AI) modalities, including machine learning. We developed an open access, machine learning web application (CHWsupervisor) to predictively code instant messages exchanged between CHWs based on supervisory interaction codes.

Exploring supervision for volunteer community health workers in Mukono District, Uganda: An exploratory mixed-methods study.

Community Health Worker (CHW) supervision is an under-researched area. This mixed-methods study engaged key stakeholders involved in CHW supervision in Mukono District, Uganda including CHWs (=14), District Health Office officials (=5), NGO programme managers (=3) and facility-based health staff (=3). Our study aimed to explore how supervision is currently conceptualised and delivered in this setting, the desired qualities of a potential supervisor, as well as the challenges regarding supervision and potential solutions to address these.

Training, supervision and performance of Community Health Workers in the delivery of ear and hearing care to 321 community members in rural Uganda.

Objectives: Community Health Workers are one way to address the shortage of ear and hearing care specialists in low-resource settings. However, there are few reports evaluating training and service delivery by Community Health Workers.

Design, Setting And Participants: We trained 13 Community Health Workers in primary ear and hearing care in Mukono District, Uganda.

Exploring perceptions, barriers, and enablers for delivery of primary ear and hearing care by community health workers: a photovoice study in Mukono District, Uganda.

Background: Hearing loss is a prevalent but neglected disease, especially in low- or middle-income countries. The role of Community Health Workers (CHWs) to deliver primary ear and hearing care has been explored in several studies from a technical standpoint, but understanding perceptions, barriers, and enablers of such an approach from the perspective of CHWs themselves through a health equity lens has been less well documented.

Methods: This qualitative study used photovoice to explore the views and experiences of CHWs in the Seeta Nazigo Parish of Mukono District in the delivery of ear and hearing care in the community.

'We are the people whose opinions don't matter'. A photovoice study exploring challenges faced by community health workers in Uganda.

Understanding the experiences of community health workers (CHWs) through the use of participatory visual methods (PVMs) has been relatively underexplored. One such PVM is photovoice, which involves the capture of photographic images related to issues of social importance. In this study, we explore challenges faced by eight CHWs in Mukono District, Uganda through the use of photovoice.