Task-shifting in Mental Health Services: Extent, Impact and Challenges in Ghana
Bibliographic record
Abstract
Aim To examine the role and scope of practice of community mental health workers (CMHWs) as well as the impact and challenges associated with of work of CMHWs within Ghana's mental health delivery system. Methods A cross sectional survey of 11 psychiatrists, 29 health policy directors and 164 CMHWs as well as key informant interviews with 3 CMHWs, 5 psychiatrists and 2 health policy directors and three focus group discussions with 21 CMHWs. Results of quantitative data were analysed with SPSS version 20 whilst the results from qualitative data were analysed manually through thematic analysis. Results In addition to duties prescribed in their job descriptions, all the CMHWs identified several jobs that they routinely perform including jobs reserved for higher level cadres such as medication prescribing for which most of the CMHWs have no training. Some CMHWs reported they had considered leaving the mental health profession because of the stigma, risk, lack of opportunities for continuing professional development and career progression as well as poor remuneration. Almost all the stakeholders believed CMHWs in Ghana receive adequate training for the role they are expected to play although many identify some gaps in the training of these mental health workers for the expanded roles they actually play. All the stakeholders expressed concerns about the quality of the care provided by CMHWs. Conclusion The study highlights several important issues, which facilitate or hinder effective task-shifting arrangements from psychiatrists to CMHWs and impact on the quality of care provided by the latter. Disclosure of interest The author has not supplied his/her declaration of competing interest.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 source (direct Gemma or distilled Codex), 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".