How capacity building of district health managers has been designed, delivered and evaluated in sub-Saharan Africa: a scoping review and best fit framework analysis

OBJECTIVES: We aimed to understand how capacity building programmes (CBPs) of district health managers (DHMs) have been designed, delivered and evaluated in sub-Saharan Africa. We focused on identifying the underlying assumptions behind leadership and management CBPs at the district level. DESIGN: Scoping review. DATA SOURCES: We searched five electronic databases (MEDLINE, Health Systems Evidence, Wiley Online Library, Cochrane Library and Google Scholar) on 6 April 2021 and 13 October 2022. We also searched for grey literature and used citation tracking. ELIGIBILITY CRITERIA: We included all primary studies (1) reporting leadership or management capacity building of DHMs, (2) in sub-Saharan Africa, (3) written in English or French and (4) published between 1 January 1987 and 13 October 2022. DATA EXTRACTION AND SYNTHESIS: Three independent reviewers extracted data from included articles. We used the best fit framework synthesis approach to identify an a priori framework that guided data coding, analysis and synthesis. We also conducted an inductive analysis of data that could not be coded against the a priori framework. RESULTS: We identified 2523 papers and ultimately included 44 papers after screening and assessment for eligibility. Key findings included (1) a scarcity of explicit theories underlying CBPs, (2) a diversity of learning approaches with increasing use of the action learning approach, (3) a diversity of content with a focus on management rather than leadership functions and (4) a diversity of evaluation methods with limited use of theory-driven designs to evaluate leadership and management capacity building interventions. CONCLUSION: This review highlights the need for explicit and well-articulated programme theories for leadership and management development interventions and the need for strengthening their evaluation using theory-driven designs that fit the complexity of health systems.