Increasing Occupational Performance in Adults with Serious Mental Illness: A Train the Trainer Model
Bibliographic record
Abstract
People living with a serious mental illness experience functional limitations that interfere with their ability to live meaningful and productive lives (Kelly & McKenna, 2004; Perese, 2007). Adults with a serious mental illness have the ability to move beyond their role as a patient and recreate a new life as an active participant in their recovery process (Krupa et al„ 2009). Psychosocial rehabilitation programs can facilitate recovery in adults with a serious mental illness (Roe et ah, 2007).\nThe project developers worked with a community mental health program to teach staff how to integrate key concepts from occupational therapy in mental health including task analysis, grading of activities, and the use of the Canadian Occupational Performance Measure assessment into their client services. The outcome of this workshop seminar was that Buckelew staff members were provided with a better understanding of occupation-based strategies they can use with adults with a serious mental illness and to demonstrate the role occupational therapists can have in a mental health setting. The workshop demonstrated that occupational therapy has a lole in consultation and training in community mental health.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".