Family history of cancer as a cue to action for physical activity behaviour and beliefs
Bibliographic record
Abstract
Objective: Examine if family history of cancer serves as a cue to action prompting adults to assess their personal risk of cancer, consider the consequences, and engage in physical activity (PA) if they believe it will reduce their risk.Design: Cross-sectional survey of adults with and without a close relative with cancer.Main Outcome Measures: Health Belief Model (HBM) constructs of perceived cancer vulnerability, perceived cancer severity, response effectiveness of PA, self-efficacy for PA, and barriers to PA, and moderate-to-vigorous intensity PA (MVPA).Results: Perceived barriers and self-efficacy correlated with MVPA in both groups (p < .05), and perceived vulnerability and response effectiveness correlated with MVPA in participants with a close relative with cancer (p < .05). In multiple regression analyses, HBM constructs accounted for 18.5% and 8.3% of the variability in MVPA among participants with and without a close relative with cancer, respectively. Participants with a close relative with cancer had greater perceived vulnerability to cancer compared to participants without a close relative with cancer (p < .001).Conclusion: Adults with and without a close relative with cancer may be differentially influenced by HBM constructs, and as a result may respond differently to PA interventions and public health messaging.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".