Social Cognitive Constructs Did Not Mediate the BEAT Cancer Intervention Effects on Objective Physical Activity Behavior Based on Multivariable Path Analysis
Bibliographic record
Abstract
BACKGROUND: Most breast cancer survivors do not meet physical activity recommendations. Understanding mediators of physical activity behavior change can improve interventions designed to increase physical activity in this at-risk population. PURPOSE: Study aims were to determine the 3-month Better Exercise Adherence after Treatment for Cancer (BEAT Cancer) behavior change intervention effects on social cognitive theory constructs and the mediating role of any changes on the increase in accelerometer-measured physical activity previously reported. METHODS: Post-treatment breast cancer survivors (N = 222) were randomized to BEAT Cancer or usual care. Assessments occurred at baseline, 3 months (M3), and 6 months (M6). Adjusted linear mixed model analysis of variance determined intervention effects on walking self-efficacy, outcome expectations, goal setting, and perceived barrier interference at M3. Path analysis determined mediation of intervention effects on physical activity at M6 by changes in social cognitive constructs during the intervention (i.e., baseline to M3). RESULTS: BEAT Cancer significantly improved self-efficacy, goals, negative outcome expectations, and barriers. Total path analysis model explained 24 % of the variance in M6 physical activity. There were significant paths from randomized intervention group to self-efficacy (β = 0.15, p < .05) and barriers (β = -0.22, p < .01). Barriers demonstrated a borderline significant association with M6 physical activity (β = -0.24, p = .05). No statistically significant indirect effects were found. CONCLUSIONS: Although BEAT Cancer significantly improved social cognitive constructs, no significant indirect effects on physical activity improvements 3 months post-intervention were observed (NCT00929617).
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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 | 0.006 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".