Keeping community health workers in Uganda motivated: key challenges, facilitators, and preferred program inputs.

Abstract

In the face of global health worker shortages, community health workers (CHWs) are an important health care delivery strategy for underserved populations. In Uganda, community-based programs often use volunteer CHWs to extend services, including family planning, in rural areas. This study examined factors related to CHW motivation and level of activity in 3 family planning programs in Uganda. Data were collected between July and August 2011, and sources comprised 183 surveys with active CHWs, in-depth interviews (IDIs) with 43 active CHWs and 5 former CHWs, and service statistics records. Surveys included a discrete choice experiment (DCE) to elicit CHW preferences for selected program inputs. Service statistics indicated an average of 56 visits with family planning clients per surveyed CHW over the 3-month period prior to data collection. In the survey, new skills and knowledge, perceived impact on the community, and enhanced status were the main positive aspects of the job reported by CHWs; the main challenges related to transportation. Multivariate analyses identified 2 correlates of CHWs being highly vs. less active (in terms of number of client visits): experiencing problems with supplies and not collaborating with peers. DCE results showed that provision of a package including a T-shirt, badge, and bicycle was the program input CHWs preferred, followed by a mobile phone (without airtime). IDI data reinforced and supplemented these quantitative findings. Social prestige, social responsibility, and aspirations for other opportunities were important motivators, while main challenges related to transportation and commodity stockouts. CHWs had complex motivations for wanting better compensation, including offsetting time and transportation costs, providing for their families, and feeling appreciated for their efforts. Volunteer CHW programs in Uganda and elsewhere need to carefully consider appropriate combinations of financial and nonfinancial inputs for optimal results.