A market test of a tailored physical activity handbook for people with spinal cord injury
Bibliographic record
Abstract
Physical activity (PA) information is in high demand but scarcely available to people with spinal cord injury (SCI). To meet this demand, effective informational resources are needed. Research suggests that tailored messages increase the relevance of PA information. The purpose of this study was to market test a tailored PA handbook among people with SCI (n = 11, 72.7% men, Mage = 43.2 ± 9.5, Myears post injury = 13.7 ± 10.7). Participants completed a baseline questionnaire assessing functional ability and social cognitions (e.g., barrier self-efficacy, outcome expectancies). Participants were randomly assigned to receive a PA handbook tailored to baseline information (n = 6) or a generic PA handbook (n = 5). The usability, appeal, and relevance of the handbook were assessed at 2 weeks. The groups were compared using t-tests and Cohen's d effect sizes. The tailored handbook was read more thoroughly than the generic handbook (t = -2.086, df = 9, p = 0.067, d = -1.22). Despite being a similar length, participants in the generic condition expressed greater concern about the length of the handbook (t = 1.990, df = 9, p = 0.078, d = 1.21). The tailored handbook was also rated as being more enjoyable, easier to read, and was considered to have more relevant and novel content compared to the generic handbook (d > 0.60). Results provide some evidence for using tailored messages when creating informational resources regarding PA for the SCI population.Acknowledgments: Heather Gainforth (Recruitment), Rebecca Bassett (Recruitment), and the Social Sciences and Humanities Research Council of Canada (Funding)
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".