Standardization of the Continuing Care Activity Measure: A Multicenter Study to Assess Reliability, Validity, and Ability to Measure Change
Bibliographic record
Abstract
BACKGROUND: There is a lack of standardized mobility measures specific to the long-term care (LTC) population. Therefore, the Continuing Care Activity Measure (CCAM) was developed. OBJECTIVE: This study determined levels of reliability, validity for clinical utilization, and sensitivity to change of this measure. DESIGN: This was a prospective longitudinal cohort study among elderly people with primarily physical or medical impairments who were residing in LTC institutions that provide nursing home and more-complex care, with access to physical therapy services. METHOD: The CCAM, the Clinical Outcome Variables Scale (COVS), the Social Engagement Scale (SES) of the Resident Assessment Instrument-Minimum Data Set (RAI-MDS) 2.0 instrument, and the Resource Utilization Groups, version 3, (RUG-III) were administered by clinical and research physical therapists, with timing dictated by the study purpose. RESULTS: The participants were 136 residents of LTC institutions and 21 physical therapists. The CCAM interrater reliability (intraclass correlation coefficient [ICC]) was .97 (95% confidence interval=.91-1.00), and test-retest reliability (ICC) over a period of 1 week was .99 (95% confidence interval=.93-1.00). Over 6 months, the absolute change in total score was 5.88 for the CCAM and 4.26 for the COVS; the CCAM was 28% more responsive across all participants (n=105) and 68% more responsive for those scoring in the lower half (n=49). The minimal detectable difference of the CCAM was 8.6 across all participants. The CCAM correlated with the COVS, nursing care hours inferred from the RUG-III, and the SES. LIMITATIONS: Some participants were lost to follow-up. CONCLUSIONS: The CCAM is a reliable and valid tool to measure gross motor function and physical mobility for elderly people in LTC institutions. It discriminates among functional levels, measures individual functional change, and can contribute to clinical decision making.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".