Explaining adherence to contrasted physical activity and nutrition scenarios in post-treatment childhood cancer patients: A cross-sectional study using variables from the Theory of Planned Behavior
Bibliographic record
Abstract
Children diagnosed with cancer are vulnerable to long-term health issues. Engaging in physical activity (PA) and adopting a healthy diet could mitigate these risks. This study aimed to understand the role of variables from the Theory of Planned Behavior (TPB) in adherence to healthy/unhealthy PA and nutrition scenarios. Through convenience sampling, four ad hoc questionnaires measuring variables from the TPB were completed by 96 parents of children diagnosed with cancer in paper format or via a secure online platform to assess attitude, perceived behavioral control (PBC), subjective norms (SN), and intention. We performed a MANOVA and multiple linear regressions. We found an effect of behavior domain (F(3, 4828.66) = 6.467, p < 0.001, ηp2 = 0.004), and scenario (F(3, 152.86) = 76.495, p < 0.001, ηp2 = 0.600). Intention was a complete intermediary variable between attitude/SN and healthy nutrition. Attitude, PBC, and intention are promising targets for PA and nutrition behaviors. SN should also be targeted for nutrition behaviors.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".