Disparity between Physical Capacity and Participation in Seniors with Chronic Disease
Bibliographic record
Abstract
UNLABELLED: Consistently low rates of physical activity are reported for older adults, and there is even lower participation if a chronic disease is present. PURPOSE: To explore the predictors of physical capacity and participation in older community-dwelling individuals living with multiple chronic diseases. METHODS: This was a descriptive cross-sectional investigation of physical capacity (physiological potential) and physical activity participation (recorded engagement in physical activity). Multiple regression and odds ratios were used to investigate determinants of physical capacity (6-min walk test) and physical activity participation (Physical Activity Scale for Individuals with Physical Disabilities Questionnaire; pedometer steps per day). RESULTS: Two hundred community-dwelling ambulatory participants living with two or more chronic diseases were assessed. Sixty-five percent (65%) were women, and the mean age was 74 +/- 6 yr (range 65-90 yr). Mobility (timed up and go) was a consistent determinant across all three primary outcomes. For the 6-min walk test, determinants included mobility, BMI, grip strength, number of medications, leg strength, balance, and Chronic Disease Management Self-Efficacy Scale (r2 = 0.58; P = 0.000). The determinants for the self-reported participation measure (Physical Activity Scale for Individuals with Physical Disabilities Questionnaire) was mobility (r2 = 0.04; P = 0.007). For the mean daily pedometer steps, the determinants included mobility, body mass index (BMI), age, and Chronic Disease Management Self-Efficacy Scale (r2 = 0.27; P = 0.000). There were higher risks for inactivity associated with impairments compared with the presence of a chronic disease. In addition, more than a third of participants had sufficient physical capacity but did not meet minimal recommendations of physical activity. CONCLUSION: This study suggests that it is easier to predict an individual's physical capacity than their actual physical participation.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".