Examining long-term motivational and behavioral outcomes of two physical activity interventions
Bibliographic record
Abstract
To examine possible impacts of two theory-based interventions – “Enhancing quality of life through exercise: A tele-rehabilitation approach (TEQ) and Active Living Lifestyles for individuals with SCI who use Wheelchair (ALLWheel)” – 12–18 months post-intervention on the satisfaction of psychological needs and motivation for leisure-time physical activity (LTPA), LTPA participation, and participation experience. A mixed-methods follow-up study. Community. Sixteen TEQ and six ALLWheel participants completed questionnaires and a semi-structured interview, 12–18 months after completing the interventions. TEQ intervention participants received a weekly LTPA counseling session with a trained kinesiologist through videoconferencing for 8 weeks. ALLWheel participants interacted with a peer mentor who provided LTPA counseling using smartphones for 10 weeks. The Psychological Need Satisfaction in Exercise, and the Treatment Self-Regulation Questionnaire were used as primary outcome measures. The LTPA barrier self-efficacy scale, the Measure of Experiential Aspects of Participation, and the 7-day LTPA Questionnaire for Adults with SCI were used as secondary outcome measures. A coding framework was created and deductive thematic analyses were used to analyze the qualitative data. Medium to large effects were found for autonomous motivation (TEQ), competence (TEQ and ALLWheel), and barrier self-efficacy (TEQ and ALLWheel). LTPA remained higher for the TEQ intervention group compared to the control group at follow-up, while an increase in moderate-to-vigorous LTPA was found in ALLWheel participants. Community-based tele-rehabilitation and virtual rehabilitation approaches, informed by theory, may assist adults with SCI in implementing LTPA over the long term.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".