Mapping the extent of the literature and psychometric properties for the Physical Activity Scale for the Elderly (PASE) in community-dwelling older adults: a scoping review
Bibliographic record
Abstract
BACKGROUND: Identifying valid and accessible tools for monitoring and improving physical activity levels is essential for promoting functional ability and healthy aging. The Physical Activity Scale for the Elderly (PASE) is a commonly used and recommended self-report measure of physical activity in older adults. The objective of this scoping review was to map the nature and extent to which the PASE has been used in the literature on community-dwelling older adults, including the evidence for its psychometric properties. METHODS: Seven electronic databases (MEDLINE (Ovid), Embase (Ovid), AMED (Ovid), Emcare (Ovid), CINAHL (EBSCO), Ageline (EBSCO)) were searched from inception to January 25, 2023. Studies were included if physical activity was part of the aim(s) and measured using the PASE, participants had a mean age of 60 years or older and lived in the community, and papers were peer-reviewed journal articles published in English. Pairs of independent reviewers screened abstracts, full-texts, and extracted data. Where possible, weighted mean PASE scores were calculated for different subgroups based on age, sex, and clinical population. RESULTS: From 4,124 studies screened, 232 articles from 35 countries met the inclusion criteria. Most studies were cross-sectional (60.78%), completed in high-income countries (86.4%) and in North America (49.57%). A variety of clinical conditions were included (n = 21), with the most common populations being osteoarthritis (n = 13), Parkinson's disease (n = 11), and cognitive impairment (n = 7). Psychometric properties of ten versions of the PASE were found. All versions demonstrated acceptable test-retest reliability. Evidence for construct validity showed moderate correlations with self-reported physical activity, fair to moderate with accelerometry derived activity and fair relationships with physical function and self-reported health. Pooled means were reported in graphs and forest plots for males, females, age groups, and several clinical populations. CONCLUSION: The PASE was widely used in a variety of clinical populations and geographical locations. The PASE has been culturally adapted to several populations and evaluated for its reliability and convergent validity; however, further research is required to examine responsiveness and predictive validity. Researchers can use the weighted mean PASE scores presented in this study to help interpret PASE scores in similar populations. OSF REGISTRATION: osf.io/7bvhx.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".