Exercise Preferences for People with Osteoporosis, Identifying Barriers, Facilitators, Needs and Goals of Exercise
Bibliographic record
Abstract
Purpose: It is challenging for many people with osteoporosis to initiate and adhere to an exercise program. Currently there is little evidence on exercise preferences of people with osteoporosis, yet these factors may contribute to improved exercise adherence. Therefore, this project surveyed patients with osteoporosis to understand their exercise preferences, barriers, needs, and goals. Methods: The Personalized Exercise Questionnaire (PEQ) was used to gain insight into the barriers, facilitators, and goals related to exercise. Participants were recruited from a subspecialty metabolic bone disorder clinic, within the Greater Toronto Area, in Ontario, with a large population of osteoporotic patients. Data collection took place, inside the clinic, from December 2018 to June 2019 Results: Data on a total of 287 surveys were collected. The sample was 90% female with a mean age of 67 (SD: 10.7) years. Most participants preferred to exercise in the morning (n=208, 75%), on their own time (n=180, 65%), with exercise that were easy to perform (n=151, 55%), slow paced (n=133, 48%), and easy to remember (n=117, 43%). Home (n=171, 62%) was the most preferred location to exercise. The most important goal for the participants was to improve strength (n=241, 84%) and the least important goal was to reduce falls (n=129, 45%). Time was the most common barrier reported in 30% of participants and followed by pain in 23% of the participants. Conclusion: This study provides insight into participant preferences for exercise. The major finding was between men and women were where they preferred to exercise. Men preferred to exercise at home or at the gym, and women preferred to exercise at home or outdoors.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".