Get In Motion: More than leisure-time physical activity participation
Bibliographic record
Abstract
Background: Get In Motion (GIM) is an evidence- and theory-based physical activity telephone counselling service for Canadian adults with a spinal cord injury (SCI). GIM sessions are based on the Health Action Process Approach (HAPA) model, with the counsellor facilitating behaviour change discussions over a 6-month time period. Previous research has shown GIM to be an effective service for increasing intentions and leisure-time physical activity (LTPA) behaviour among its clients. The purpose of the current study was to examine the secondary effects of the GIM on participation and quality of life among its clients. Methods: Clients’ (n=45; 50% males) demographics were collected over the phone, including age (51.46 ± 12.36 years), level of injury (50% with paraplegia), years post-injury (17.00 ± 17.51 years), upon enrolment. Secondary measures relating to participation and quality of life (i.e., Satisfaction with Life (SWL), autonomy and participation (AP), and self-efficacy of activities of daily living (ADLs)) were obtained at baseline and 6-months. Results: Using paired sample t-tests, a trend was found for positive changes in AP (p = .08) and ADL self-efficacy (p = .07) from baseline to 6-months, with clients reporting greater autonomy (5.16 to 5.49) and greater self-efficacy for accomplishing ADLs (3.92 to 4.28). No significant changes or trends were shown for SWL (p = .50). Conclusion: Overall, the GIM service seems to have a positive effect on some aspects of participation and QOL for its clients. To further increase clients’ life satisfaction, autonomy and participation, and ADL self-efficacy, it may be necessary to include other tools and strategies into GIM counselling sessions such as creating a more well rounded discussion which addresses social support networks, and sport or group activity participation. In the future, the long-term effects of the GIM service should be assessed along with the adoption of LTPA participation post-intervention.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".