"Nothing without connection"-Participant perspectives and experiences of mentorship in capacity building in Timor-Leste

PLOS Glob Public Health. 2024 Mar 8;4(3):e0002112. doi: 10.1371/journal.pgph.0002112. eCollection 2024.

Abstract

The literature on mentorship approaches to capacity building in global health is limited. Likewise, there are few qualitative studies that describe mentorship in capacity building in global health from the perspective of the mentors and mentees. This qualitative study examined the perspectives and experiences of participants involved in a program of health capacity building in Timor-Leste that was based on a side-by-side, in-country mentorship approach. Semi-structured interviews were conducted with 23 participants (including Timorese and expatriate mentors, and local Timorese colleagues) from across a range of professional health disciplines, followed by a series of member checking workshops. Findings were reviewed using inductive thematic analysis. Participants were included in review and refinement of themes. Four major themes were identified: the importance of trust and connection within the mentoring relationship; the side-by-side nature of the relationship (akompaña); mentoring in the context of external environmental challenges; and the need for the mentoring relationship to be dynamic and evolving, and aligned to a shared vision and goals. The importance of accompaniment (akompaña) as a key element of the mentoring relationship requires further exploration and study. Many activities in global health capacity building remain focused on provision of training, supervision, and supportive supervision of competent task performance. Viewed through a decolonising lens, there is an imperative for global health actors to align with local priorities and goals, and work alongside individuals supporting them in their vision to become independent leaders of their professions. We propose that placing mentoring relationships at the centre of human resource capacity building programs encourages deep learning, and is more likely to lead to long term, meaningful and sustainable change.

Grants and funding

The authors received no specific funding for this work.