Bibliographic record
Abstract
OBJECTIVE: To explore the views of community-care and mental health workers on barriers to the management of mental health problems in rural Western Australia, and how these could be addressed. DESIGN: Qualitative content analysis of semi-structured interviews. SETTING: Community and mental health services in Esperance. SUBJECTS: One hundred per cent of relevant mental health workers, 86% of community health professionals and representatives from a wide range of community organisations were interviewed (n = 38). MAIN OUTCOME MEASURES: The views of community-care and mental health workers on barriers to the management of mental health, and how these could be addressed. RESULTS: Barriers included confusion about the role of mental health services, limited after-hours access and help for those in situational crisis, communication problems between services, differences in working practices and difficulties in dealing with the stigma of mental illness in rural communities. Suggested solutions were an expansion of counselling services and multi-agency shared care with clinical streams for adults, those aged > 65 and children. CONCLUSION: This study revealed a number of barriers that are being addressed through a memorandum of understanding between services. WHAT IS ALREADY KNOWN: Initiatives to foster collaboration between rural mental health services and general practitioners have not included other providers of primary care. We wished to explore the views of community-care and mental health workers on barriers to the management of mental health problems in rural Western Australia and how these could be addressed. WHAT THIS STUDY ADDS: We identified a number of barriers to collaboration between mental health and community-based services, including poor communication, difficulties with referral and cultural differences between services. Of all these themes, the most significant was the lack of communication at individual, case management and organisational levels.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".