Validation of the Mandarin Version of the Activity Measure for Post-Acute Care (AM–PAC) “6-Clicks” Among Patients in Acute Rehabilitation
Bibliographic record
Abstract
IMPORTANCE: A standardized functional measure that can be used across rehabilitation care settings in Taiwan is urgently needed. OBJECTIVE: To generate a Mandarin version of the Activity Measure for Post-Acute Care (AM-PAC) "6-Clicks" for patients in acute care. DESIGN: Mixed-methods study with a cross-sectional design. SETTING: Acute care wards of three teaching hospitals in Taiwan. PARTICIPANTS: A sample of 231 neurological patients in acute care (62.3% female; mean age = 63.2 yr, standard deviation = 14.6). OUTCOMES AND MEASURES: The 6-Clicks consist of three subscales: Basic Mobility, Daily Activity, and Applied Cognition. They were translated into Mandarin, and their internal consistency, test-retest reliability, interrater reliability, and convergent validity were tested. RESULTS: All subscales of the Mandarin version of the 6-Clicks showed good internal consistency (α = .97-.98). Test-retest and interrater reliabilities were excellent for all subscales (intraclass correlation coefficients >.8). Convergent validity was supported by strong correlations of the Basic Mobility and Daily Activity subscales with the Barthel Index (r = .73 and .72, respectively) and between the Applied Cognition subscale and the Montreal Cognitive Assessment (r = .82). CONCLUSION: Our results provide psychometric evidence supporting the use of the Mandarin version of the 6-Clicks in acute care settings in Taiwan. WHAT THIS ARTICLE ADDS: This study confirms the appropriateness of the use of the Mandarin version of the AM-PAC "6-Clicks" with patients in acute rehabilitation, making it a valuable addition to validated measures available for use by occupational therapists in Taiwan.
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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 | 0.007 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".