Evaluating the impact of structured training programs for village health workers on healthcare delivery in resource-limited settings: Evidence from The Gambia

Abstract

Community health workers (CHWs) are critical in bridging healthcare gaps in underserved areas, particularly in resource-limited settings. In The Gambia, Village Health Workers (VHWs) play a pivotal role in primary healthcare delivery. Despite their significance, evidence on the effectiveness of structured training programs for VHWs remains sparse. This study evaluates the impact of a training program designed to enhance the knowledge and skills of VHWs in The Gambia, focusing on their capacity to address key community health needs. A retrospective quantitative design was employed, analyzing pre- and post-test scores from VHWs across three health regions in The Gambia. The training included 60 sessions on topics such as child health, nutrition, sanitation, and disease prevention. Data were analyzed using descriptive statistics, paired t-tests, and one-way ANOVA to assess improvements in knowledge and identify influencing factors like age, sex, and education level. The results revealed significant improvements in knowledge and practical skills, with mean post-test scores increasing by 26.32 points (p < 0.001) compared to pre-test scores. Age and education were significant predictors of performance, with older participants and those with secondary or tertiary education achieving higher post-test scores. No significant differences were observed based on sex, indicating the program’s inclusivity. These findings underscore the effectiveness of structured training programs in equipping VHWs with essential competencies to improve healthcare delivery. The study highlights the need for tailored approaches to address disparities in educational backgrounds and recommends ongoing capacity-building initiatives to sustain the impact. By strengthening VHW capacities, this intervention contributes to improving healthcare access and outcomes in The Gambia, offering valuable insights for similar programs in resource-limited settings.