Barriers and drivers to service delivery in global mental health projects
Bibliographic record
Abstract
BACKGROUND: Research in global mental health (GMH) has previously documented how contextual factors like political instability, poverty and poorly-funded health infrastructure continue to compromise effective and equitable mental health service delivery. There is a need to develop more feasible and evidence-based solutions through implementation research. This paper, one in a series pertaining to implementation in GMH projects worldwide, focuses on implementation factors influencing mental health service delivery. METHODS: This is a qualitative study carried out as part of a Theory of Change-driven evaluation of Grand Challenges Canada's (GCC's) Global Mental Health portfolio. Purposive sampling was used to recruit twenty-nine GCC grantees for interviews. A semi-structured interview schedule was used to guide the interviews which were recorded and subsequently transcribed. Transcripts were double-coded and analyzed in NVivo 11 using framework analysis. This paper reports results related to detection and treatment of mental illness, mental health promotion and prevention of mental illness. RESULTS: Key barriers included: lack of appropriate human resources and expertise for service delivery; lack of culturally appropriate screening tools and interventions; and difficulties integrating services with the existing mental health system. Formative research was a key driver facilitating the cultural adaptation of mental health detection, treatment, promotion and preventative approaches. Recruiting local providers and utilizing mHealth for improving screening, monitoring and data management were also found to be successful approaches in reducing workforce burden, improving sustainability, mental health literacy, participant engagement and uptake. CONCLUSIONS: The study identifies a number of key barriers to and drivers of successful service delivery from the perspective of grantees implementing GMH projects. Findings highlight several opportunities to mitigate common challenges, providing recommendations for strengthening systems- and project-level approaches for delivering mental health services. Further, more inclusive research is required to inform guidance around service delivery for successful implementation, better utilization of funding and improving mental health outcomes among vulnerable populations in low-resource settings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".