The Performance Assessment of Self-Care Skills to Predict Adverse Events Post-Discharge
Bibliographic record
Abstract
Background. The Performance Assessment of Self-Care Skills (PASS) is a standardized assessment of the ability to perform daily activities. Purposes. This preliminary exploratory study aimed to 1) explore the ability of four PASS tasks to predict adverse events (readmissions and injuries) in older adults following hospitalization; 2) compare PASS's predictive validity to that of a generic tool (SMAF) and OT clinical judgement. Method.Twenty-two older patients were assessed in hospital at discharge and at home one week later. Adverse events were documented for six months post-discharge. Sensitivity and specificity analyses (ROC curves, Fisher's exact tests) were performed. Findings. Two PASS tasks (telephone, medication), the SMAF-Social and OT clinical judgement could identify individuals at risk of readmission (AUC > 0.7; p < 0.05). Implications. Using the PASS to assess more cognitively demanding tasks could be a promising way to predict adverse events after discharge, as a complement to clinical judgment.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".