Promoting physical activity in the spinal cord injury community through educating and empowering health care professionals: SCI Action Canada's Knowledge Mobilization Training series
Bibliographic record
Abstract
In 2011, SCI Action Canada developed an online training tool, the Knowledge Mobilization Training Series (KMTS), to enhance health care professionals' knowledge and confidence for promoting physical activity (PA) in the spinal cord injury (SCI) community. This study focuses on the first KMTS module - “Physical Activity Guidelines for Adults with SCI” (PAG-SCI). The purposes of this study were to examine the characteristics and participation pattern of the KMTS users, and to determine whether participation influenced users' social cognitions for promoting the PAG-SCI. The KMTS was advertised through SCI Action Canada’s community partners, ‘outreach events’, and website. Users (N=44, Mage=31.1±15.2 years, 66% female) completed a pre-module questionnaire examining attitudes, self-efficacy, and intentions for promoting the PAG-SCI. Eleven of the 44 users completed the same questionnaire following participation. Many users were employed as either rehabilitation therapists (25%) or health promoters (23%), and most (52%) reported working with up to 10 adults with SCI on a frequent basis. Approximately 39% of users viewed all five of the module sections (M=3.2±1.7); however, a decline in participation was seen, with less than half of users viewing the last three module sections. Separate repeated measures ANCOVAs, controlling for the number of sections viewed, showed a trend for an increase in users' attitudes for promoting the PAG-SCI (F(1,9)=3.37, p=.10, partial n2=.27). No significant changes or trends were found for self-efficacy or intentions (ps>.19, partial n2<.18). Future research is planned to examine users’ perceptions of KMTS in order to enhance user participation and cognitions for promoting PA.Acknowledgments: This study was funded by the Rick Hansen Institute.
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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 | 0.003 | 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 | 0.000 |
| Open science | 0.001 | 0.002 |
| 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".