Common Experiences and Beliefs Among Highly Active, Older Adults
Bibliographic record
Abstract
Background: Research on correlates and determinants of physical activity has shown that age and motivation are associated with physical activity. Self-Determination Theory (SDT) provides a well-researched framework for understanding motivation, and proposes that the satisfaction of three primary psychological needs: autonomy, competence, and relatedness, fuels motivation for physical activity and promotes wellness.\nPurpose: Use SDT to identify experiences and beliefs that affect motivation for physical activity in older adults and provide a narrative approach to share their “movement stories.”\nMethods: Participants were recruited using nominated sampling and a public advertising campaign. Participants were at least 55-years old with International Physical Activity Questionnaire scores categorizing them as moderately-vigorously active. Data was collected using the Motives for Physical Activities Measure – Revised, Basic Psychological Need Satisfaction and Frustration Scale – General Measure, and via in-person interviews. Interviews were filmed and narratives created using Adobe. Interview scripts were analyzed by researchers and common themes coded.\nResults: Qualitative analysis showed participants expressed higher life satisfaction than frustration. Collectively, statements that expressed motivation were most common for competence (55), relatedness (33), autonomy (28), and interest/enjoyment (27). The least commonly mentioned motivation types were appearance (3) and fitness (13).\nConclusion: Overall, active older adults showed greater satisfaction over frustration with basic psychological needs. Motivational factors influencing PA varied greatly among participants, but they shared many common beliefs and experiences. It was shown that motivation stemmed most strongly from competence, interest, and relatedness and those promoting PA within this age group should focus on these domains.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".