Bibliographic record
Abstract
OBJECTIVES: This study examined the relationship between pain and mental health outcomes of depression and affect among survivors of breast cancer. The mediating role of physical activity was also tested. METHODS: Survivors of breast cancer (N=145) completed self-report measures of pain symptoms at baseline, wore an accelerometer for 7 days, and reported levels of depression symptoms and negative and positive affect 3 months later. Hierarchical linear regression analyses, controlling for personal and cancer-related demographics, were used to test the association between pain symptoms and each mental health outcome, as well as the mediation effect of physical activity. RESULTS: Pain positively predicted depression symptoms [F(6,139)=4.31, P<0.01, R=0.15] and negative affect [F(5,140)=4.17, P<0.01, R=0.13], and negatively predicted positive affect [F(6,139)=2.12, P=0.03, R=0.08]. Physical activity was a significant (P<0.01) partial mediator of the relationship between pain and depression and between pain and positive affect. DISCUSSION: Participation in physical activity is one pathway through which pain influences mental health. Efforts are needed to help survivors of breast cancer manage pain symptoms and increase their level of physical activity to help improve mental health.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".