Correlates of physical activity in a population-based sample of kidney cancer survivors: an application of the theory of planned behavior
Bibliographic record
Abstract
Background: Over half of kidney cancer survivors (KCS) are completely inactive and only a quarter are meeting physical activity (PA) guidelines. This highlights the need to identify and understand the determinants of PA in this understudied population. The purpose of this study is to determine the social cognitive correlates of PA intention and behavior in KCS using the Theory of Planned Behavior (TPB). Methods: All 1,985 KCS diagnosed between 1996 and 2010 in Alberta, Canada were mailed a self-report survey that consisted of the Godin Leisure Time Exercise Questionnaire and standard TPB items for intention, planning, perceived behavioral control (PBC), affective and instrumental attitudes, and descriptive and injunctive norms. Standard demographic and medical variables were also collected. Results: Completed surveys were received from 703 of 1,654 (43%) eligible KCS. The TPB was tested using structural equation modelling and demonstrated an adequate-to-good fit to the data [χ² = 256.88, p < .001; TLI = 0.97; CFI = 0.98; RMSEA = 0.06, 90% CI = 0.05-0.06]. There were significant pathways to PA from PBC (ß = 0.18, p = 0.02), planning (ß = 0.22, p < 0.01), and intention (ß = 0.31, p < 0.01); and to planning from intention (ß = 0.81, p < 0.01). In addition, there were significant model pathways to intention from instrumental attitude (ß = 0.28, p = 0.03), descriptive norm (ß = 0.09, p = 0.01), and PBC (ß = 0.52, p < 0.01). Overall, the TPB accounted for 69%, 63%, and 42% of the variance in intention, planning and PA, respectively. Conclusion: The TPB appears to be a useful model for explaining PA in KCS. All TPB constructs except injunctive norm and affective attitude were useful for explaining intention with PBC emerging as the largest correlate. Developing PA interventions based on the TPB may be effective in promoting PA in KCS and may lead to important improvements in health.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".