Colon cancer information as a source of exercise motivation
Bibliographic record
Abstract
Using a Protective Motivation Theory (PMT) framework, this study examined whether colon cancer is a meaningful source of exercise motivation. Participants were (N = 173) teaching and school staff randomly assigned into one of three treatment conditions: PMT present, PMT absent (attention control) and no information (non-contact control). Two separate DVD videos were developed (one incorporating the four major components of PMT; perceived vulnerability (PV), perceived severity (PS), response efficacy (RE) and self-efficacy (SE) featured colon cancer and exercise information while the other DVDs featured cancer and nutritional information). Following treatment, participants completed questionnaires which assessed their beliefs towards colon cancer and exercise as well as their intentions to do more exercise. Two weeks later (T1), self-reported measures of exercise behaviour were assessed and then repeated at 1 month (T2). Only physically inactive participants were used in subsequent analyses (n = 72). Results indicated that compared to the two control groups, the PMT present group scored significantly higher on RE and intention to engage in more exercise (p-values = 0.001). A trend effect in the expected direction also was noted for T1 exercise behaviour (p = 0.09). RE, SE and PV made significant and unique contributions to exercise intention scores, explaining 44% of the response variance. Intention was the only variable to show an association with T1 exercise behaviour, explaining 10% of the response variance. Overall, these findings suggest that a single exposure of media intervention grounded in theory can influence people's beliefs, motivation and initial behaviour.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".