Psychosocial correlates of physical activity intentions and behaviour in young and middle age adult cancer survivors: An application of an integrated model
Bibliographic record
Abstract
A theoretical model integrating the Theory of Planned Behaviour (TPB) and the Self-Determination Theory (SDT) was used to examine the influence of autonomous motives on physical activity intentions and behaviours in 104 adult (24-44 years) cancer survivors. Survivors of breast (44%), lymphoma (35%), testicular (15%), and colorectal (6%) cancer completed a mailed survey that included measures of behavioural regulation, TPB, physical activity, medical, and demographic variables. Results showed that survivors who met current physical activity guidelines reported better affective ( p= .001), and instrumental attitudes ( p= .002), subjective norm ( p= .012), perceived control ( p =.002), intentions ( p .000), identified regulations ( p .000), and intrinsic motivation ( p p p 0.01) making the only significant unique contributions. Further analysis showed that intention, perceived control, and identified regulation explained 24% of the variance in physical activity behaviour with identified regulation (s=.40, p Acknowledgments: I wish to acknowledge Dr. Chris Blanchard for his feedback on the data analyses.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".