Profile of Physical Activity Levels in Community-Dwelling Older Adults
Bibliographic record
Abstract
PURPOSE: To examine relationships between selected sociodemographic, health-related and environmental factors and levels of physical activity in older adults across three age groups. METHODS: Seven hundred sixty-four older adults (mean age = 77.4 +/- 8.6 yr) from a midsize Canadian city completed a self-administered questionnaire under researcher supervision. Level of physical activity was determined using the Physical Activity Scale for the Elderly (PASE). Correlates of physical activity were examined using previously validated questionnaires. The findings pertaining to personal and environmental factors are presented. RESULTS: Overall, significantly higher mean PASE scores were seen in those individuals in the following categories: male (P < 0.001), married or common-law (P < 0.001), not living alone (P < 0.001), not living in senior's housing (P < 0.001), higher levels of education (P < 0.001) and higher incomes (P < 0.001). Better physical health showed significant positive associations (P < 0.001) with PASE score. Individuals reporting at least four or more chronic health conditions had significantly lower PASE scores than those reporting no chronic conditions (P < 0.001). Significantly lower PASE scores were also reported in those using domestic services (P < 0.001). Higher PASE scores were related to the presence of hills, biking and walking trails, street lights, various recreation facilities, seeing others active and unattended dogs (P < 0.001 to P < 0.05). CONCLUSION: An understanding of the factors that influence physical activity behavior in older adults is critical to developing effective intervention strategies that will address the problem of physical inactivity in this population, and in doing so, improve the health status and quality of life of the older adult, while having a significant impact on healthcare expenditures.
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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 | 0.000 | 0.001 |
| 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 | 0.000 | 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".