Evaluation of a new mental health liaison role in a rural health centre in Rocky Mountain House, Alberta: A Canadian story
Bibliographic record
Abstract
This paper describes the evaluation of a mental health liaison (MHL) role in a rural community in Alberta, Canada. The role provides advocacy, education, indirect and direct client intervention, and follow up. It was developed to eliminate gaps in mental health care and build collaborative cultures between the local hospital, physicians' offices, mental health clinics, and community agencies. Obtaining stakeholder feedback was an important step in assessing initial service impact while providing directions for role refinement and future programme development. A total of 116 questionnaires were distributed to physicians, hospital staff, and community mental health assessing stakeholder perception relating to various functions of the MHL. A 50% (n = 58) response rate was achieved with broad representation from different partners, including 75% of local physicians. The majority of respondents positively perceived the roles, functions, and impact of the MHL, including relationship development across the hospital community, improved access to services, and perceived improved client outcomes. The results reinforced that the MHL service meets a previously unmet need in this rural setting. Findings are being used to refine roles, provide local learning and resource development, understand issues relating to programme development in other areas, and develop client level outcomes relating to the services delivered.
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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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.020 | 0.004 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".