“You can because you do and you do, because you can”: Using interpretative description to examine what it means to be a physically literate adult living with multiple chronic conditions
Bibliographic record
Abstract
AIMS: Physical literacy is an emerging strategy to increase participation in movement activities for children and youth, however little is known about how to frame physical literacy for aging adults. The purpose of this qualitative study was to explore how adults with multiple chronic conditions describe physically literacy for adults and to understand the needs, preferences, barriers, and facilitators to acquiring and maintaining physical literacy despite fluctuations in health status. METHODS: Sixteen semi-structured interviews were conducted with working and retired teachers in Ontario, Canada, with varying self-identified physical activity levels and are living with 2 or more chronic conditions. A semi-structured interview guide was used to conduct the interviews. Thematic analysis was used to analyze the data. RESULTS: Participants identified 5 themes when describing physical literacy for adults: understanding one's body, conscious commitment to movement, access to and knowledge of rehabilitation health resources, valuable physical activities, and confident problem solver. Results indicate that when acquiring physical literacy for adults, there are important new constructs, such as self-management and the awareness of rehabilitation strategies to maintain mobility, that differ from the traditional physical literacy model. CONCLUSIONS: To improve function and mobility outcomes for adults living with chronic conditions, programs should be guided by a physical literacy framework that addresses the needs unique to aging adults, such as understanding the changes that occur with aging, self-monitoring mobility changes and participating in rehabilitation strategies.
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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 | 0.028 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.018 |
| Scholarly communication | 0.005 | 0.009 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| 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".