Moderators Of A Multi-Component Physical Activity Behavior Change Intervention Effects On Fatigue, Depression, And Anxiety
Bibliographic record
Abstract
BACKGROUND: Fatigue, depression, and anxiety significantly reduce quality of life in breast cancer survivors (BCS). Identifying factors that predict symptom response to physical activity (PA) behavior change interventions may allow for more targeted interventions. PURPOSE: To determine demographic and medical factors that moderate the effects of a multi-component PA behavior change intervention (i.e., BEAT Cancer) on fatigue, depressive symptomatology, and anxiety in BCS. METHODS: In this multi-center randomized controlled trial, post-primary treatment BCS (N=222; Stage 0-III) were assigned to BEAT Cancer PA intervention or usual care (i.e., PA-related written materials) Fatigue Symptom Inventory (11-point, Likert scale (0=best; 10=worst) and Hospital Anxiety and Depression Scale were assessed at baseline, 3 months (immediately post-intervention) and 6 months. Moderators (baseline value of each outcome, age, income, marital status, cancer stage, months since diagnosis, cancer treatment, body mass index [BMI], and comorbidities) were assessed at baseline (BMI measured on-site; remaining factors self-reported). This study is a post-hoc exploratory analysis using linear regression to test hypothesized moderators. RESULTS: Participants with baseline fatigue interference ≥3 experienced greater improvements in fatigue interference (p = .020; -1.35 vs. -.42 for interference <3). Those with a history of radiation experienced greater reductions in depressive symptomatology (p = .013; -1.53 vs. 0.08 if no history of radiation). Finally, participants with <2 comorbidities or BMI <30 experienced greater reductions in anxiety (p = .010; -1.97 vs. -.26 for ≥ 2 comorbidities and p = .033; -1.66 vs. -.33 for BMI ≥ 30, respectively). No statistically significant moderators of the intervention effects on fatigue intensity were found. CONCLUSIONS: Findings indicate that BCS with higher baseline fatigue interference, history of radiation, <2 comorbidities, and BMI <30 may have a more favorable symptom response with a PA behavior change intervention. Future research is needed to identify etiologic mechanisms for lack of response (e.g., radiation therapy) and unmet needs of less responsive subgroups (e.g., multiple comorbidities, obesity).
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".