The Effect of Group-Based Family Orientation to Community Mental Health Services
Bibliographic record
Abstract
INTRODUCTION: A simple initial family orientation session (IGS) focusing on what families might expect by way of treatment and with the provision of community resources if required was designed and implemented in a regional mental health service. The effects of the IGS were examined in terms of clinical measures that align closely with the provincially developed SMART goals for treatment and the nationally developed mental health theme of ‘recovery-oriented services’, as well as readmission rates and cumulative lengths of stay. METHODS: Employing clinical and registration data from a regional information and registration system, we examined readmission rates and cumulative lengths of both within and between groups exposed and unexposed to IGS over comparable time periods before and after November 2016. RESULTS: The IGS-exposed group had a greater reduction in admissions and cumulative length of stay compared to the unexposed group, with the greatest reduction in IGS-exposed emergency admissions. Clinical data indicated that both IGS-exposed and unexposed groups were similar. CONCLUSIONS: The findings support the hypothesis that changes in admission rates and overall days in service were potentially an effect of the IGS. The clinical measurement system and the IGS align closely with the provincially developed SMART goals for treatment and the nationally developed mental health theme of ‘recovery-oriented services’.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".