Personal Care Participation Assessment and Resource Tool: Clinical utility for inpatient rehabilitation
Bibliographic record
Abstract
BACKGROUND: Evidence supports validity of the Personal Care Participation Assessment and Resource Tool (PC-PART), but clinical utility remains unverified. PURPOSE: This study aimed to investigate occupational therapists' perceptions about the PC-PART's clinical utility for inpatient rehabilitation. METHOD: Using mixed methods, occupational therapists who had used the PC-PART as part of a research study in an inpatient rehabilitation setting completed a questionnaire (n = 9) and participated in a focus group (n = 6) to explore their perspectives about its clinical utility. Quantitative data were summarized and qualitative data analyzed using inductive thematic analysis. FINDINGS: Quantitative data highlighted both positive and negative aspects of the PC-PART's clinical utility. Five themes emerged from the qualitative data: nature of information gathered; familiarity with the instrument; perceived time and effort; item phrasing, interpretation, and presentation; and external influences on clinical use. IMPLICATIONS: The PC-PART was perceived to support gathering of clinically useful information, helpful to intervention and discharge planning. Recommendations for improving some item phrasing, operational definitions, and instructions were identified. Although standardized assessments were valued, use in routine practice was challenging, requiring a knowledge translation strategy.
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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 | 0.022 | 0.071 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".