Training and Maintaining System-Wide Reliability in Outcome Management
Bibliographic record
Abstract
The Child and Adolescent Functional Assessment Scale (CAFAS) is widely used for outcome management, for providing real time client and program level data, and the monitoring of evidence-based practices. Methods of reliability training and the assessment of rater drift are critical for service decision-making within organizations and systems of care. We assessed two approaches for CAFAS training: external technical assistance and internal technical assistance. To this end, we sampled 315 practitioners trained by external technical assistance approach from 2,344 Ontario practitioners who had achieved reliability on the CAFAS. To assess the internal technical assistance approach as a reliable alternative training method, 140 practitioners trained internally were selected from the same pool of certified raters. Reliabilities were high for both practitioners trained by external technical assistance and internal technical assistance approaches (.909-.995, .915-.997, respectively). 1 and 3-year estimates showed some drift on several scales. High and consistent reliabilities over time and training method has implications for CAFAS training of behavioral health care practitioners, and the maintenance of CAFAS as a global outcome management tool in systems of care.
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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 | 0.356 | 0.366 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".