Barriers and drivers to capacity-building in global mental health projects
Bibliographic record
Abstract
BACKGROUND: The global shortage of mental health workers is a significant barrier to the implementation and scale-up of mental health services. Partially as a result of this shortage, approximately 85% of people with mental, neurological and substance-use disorders in low- and middle-income countries do not receive care. Consequently, developing and implementing scalable solutions for mental health capacity-building has been identified as a priority in global mental health. There remains limited evidence to inform best practices for capacity building in global mental health. As one in a series of four papers on factors affecting the implementation of mental health projects in low- and middle-income countries, this paper reflects on the experiences of global mental health grantees funded by Grand Challenges Canada, focusing on the barriers to and drivers of capacity-building. METHODS: Between June 2014 and May 2017, current or former Grand Challenges Canada Global Mental Health grantees were recruited using purposive sampling. N = 29 grantees participated in semi-structured qualitative interviews, representing projects in Central America and the Caribbean (n = 4), South America (n = 1), West Africa (n = 4), East Africa (n = 6), South Asia (n = 11) and Southeast Asia (n = 3). Based on the results of a quantitative analysis of project outcomes using a portfolio-level Theory of Change framework, six key themes were identified as important to implementation success. As part of a larger multi-method study, this paper utilized a framework analysis to explore the themes related to capacity-building. RESULTS: Study participants described barriers and facilitators to capacity building within three broad themes: (1) training, (2) supervision, and (3) quality assurance. Running throughout these thematic areas were the crosscutting themes of contextual understanding, human resources, and sustainability. Additionally, participants described approaches and mechanisms for successful capacity building. CONCLUSIONS: This study demonstrates the importance of capacity building to global mental health research and implementation, its relationship to stakeholder engagement and service delivery, and the implications for funders, implementers, and researchers alike. Investment in formative research, contextual understanding, stakeholder engagement, policy influence, and integration into existing systems of education and service delivery is crucial for the success of capacity building efforts.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".