Task shifting of mental health care services in Ghana: ease of referral, perception and concerns of stakeholders about quality of care
Bibliographic record
Abstract
OBJECTIVES: To examine the perceptions of stakeholders about the ease of referral of patients from community mental health workers (CMHWs) to psychiatrists in Ghana and the level of stakeholder concerns about the quality of care provided to these community health cadres. DESIGN: A cross-sectional survey. PARTICIPANTS: Eleven psychiatrists, 26 health policy directors and 164 community mental health workers, including 71 (43.3%) community psychiatric nurses, 19 (11.6%) clinical psychiatric officers and 74 (45.1%) community mental health officers. METHODS: We administered three separate, self-administered, semi-structured questionnaires to the study participants. RESULTS: Although many respondents including almost all CMHWs perceive that it is easy for them to refer difficult cases to a psychiatrist who will usually see such patients in a timely manner, less than a quarter of these health cadres reported that they always or often refer patients to see a psychiatrist. The majority of CMHWs were of the opinion that patients, psychiatrists and other healthcare workers have concerns about the quality of care they provide, sentiments that were echoed by all psychiatrists and over half of all the health policy directors. CONCLUSION: There is also a need for policy directors to educate CMHWs about their roles and to clarify referral pathways so that cases that are difficult to manage will be appropriately referred to psychiatrists or appropriately trained and incentivized district medical doctors for further management.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".