Believability of messages about preventing breast cancer and heart disease through physical activity
Bibliographic record
Abstract
BACKGROUND: The purpose of this research was to examine the relationships of self-reported physical activity to involvement with messages that discuss the prevention of heart disease and breast cancer through physical activity, the explicit believability of the messages, and agreement (or disagreement) with specific statements about the messages or disease beliefs in general. METHODS: A within subjects' design was used. Participants (N = 96) read either a breast cancer or heart disease message first, then completed a corresponding task that measured agreement or disagreement and confidence in the agreement or disagreement that 1) physical activity 'reduces risk/does not reduce risk' of breast cancer or heart disease, 2) that breast cancer or heart disease is a 'real/not real risk for me', 3) that women who get breast cancer or heart disease are 'like/not like me', and 4) that women who get breast cancer or heart disease are 'to blame/not to blame'. This task was followed by a questionnaire measuring message involvement and explicit believability. They then read the other disease messages and completed the corresponding agreement and confidence task and questionnaire measures. Lastly, participants completed a questionnaire measuring physical activity related attitudes and intentions, and demographics. RESULTS: There was no difference in message involvement or explicit believability of breast cancer compared to heart disease messages. Active participants had a higher confidence in their agreement that physical activity is preventive of heart disease compared to breast cancer. Multinomial regression models showed that, in addition to physical activity related attitudes and intentions, agreement that physical activity was preventive of heart disease and that women with heart disease are 'like me' were predictors of being more active compared to inactive. In the breast cancer model only attitudes and intentions predicted physical activity group. CONCLUSIONS: Active women likely internalized messages about heart disease prevention through physical activity, making the prevention messages more readily available within memory, and active women may therefore process such information differently. The study of how health-related beliefs are created and are related to perceptions of prevention messages is a rich area of study that may contribute to more effective health promotion.
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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 | 0.009 | 0.058 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".