Multisource feedback systems for quality improvement in the health professions: Assessing occupational therapists in practice
Bibliographic record
Abstract
INTRODUCTION: The objective was to develop and psychometrically evaluate (feasibility, reliability, validity) a questionnaire-based multisource feedback (MSF) system for quality improvement (QI) for occupational therapists (OTs). METHODS: Surveys were developed for assessment of OTs by clients, co-workers, and themselves, respectively, using 5-point scales with an "unable to assess" category. A sample of 238 OTs participated. RESULTS: The number of respondents for the co-worker questionnaire was 2621, and for the client questionnaire it was 2881. The mean ratings ranged from 4 to 5 for each item on each scale. All of the instruments' full scales had very high Cronbach's alpha > 0.92. The factor analyses revealed a 7-factor solution (66.3% of the total variance) for the co-worker survey, and a 4-factor solution for the client questionnaire (73.2% of the variance). DISCUSSION: An MSF system employing surveys that have high reliability, validity, and feasibility was developed to provide feedback to OTs on core competencies and skills. It is suggested that similar MSF systems are feasible for health professionals in general.
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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 | 0.040 | 0.089 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| 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".