Physical activity and depressive symptoms after breast cancer: Cross-sectional and longitudinal relationships.
Bibliographic record
Abstract
OBJECTIVE: The objective of this study was to examine the cross-sectional and longitudinal relationships between moderate-to-vigorous intensity physical activity (MVPA) and depressive symptoms in women after treatment for breast cancer. METHOD: Accelerometer data on MVPA and self-report data on frequency of depressive symptoms were collected five times at ∼ 3-month intervals from women (Mage at Time 1 = 55.01 ± 10.96 years) who had completed treatment for breast cancer 3 months prior to study inception. Data were analyzed using latent growth modeling with structured residuals. RESULTS: Levels of MVPA decreased, on average, by .52 min every 3 months (p < .001), whereas the frequency of depressive symptoms was stable. MVPA was inversely and significantly related cross-sectionally with depressive symptoms, but not longitudinally. Also, there was no evidence of a bidirectional predictive relationship between MVPA and depressive symptoms. CONCLUSION: Although higher levels of MVPA were associated with less frequent depressive symptoms cross-sectionally in women after treatment for breast cancer, MVPA did not predict frequency of depressive symptoms or vice versa. Common etiologic or shared risk factors underpinning the cross-sectional relationships between depressive symptoms and MVPA should be studied across the transition from treatment to survivorship. (PsycINFO Database Record
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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 | 0.005 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".