Physical Activity and Psychological Health in Breast Cancer Survivors: An Application of Basic Psychological Needs Theory
Bibliographic record
Abstract
OBJECTIVE: The role of psychological need satisfaction in terms of understanding the mechanisms through which leisure-time physical activity (LTPA) is associated with psychological health in breast cancer survivors who have recently completed treatment was examined. METHODS: Adopting a longitudinal two-wave design, female breast cancer survivors (N = 144) completed self-report instruments of LTPA, psychological need satisfaction, and psychological health at two points separated by 3 months. The first test administration period was 6 months following the completion of primary treatment. RESULTS: Change score analyses demonstrated that greater LTPA across the 3-month period was associated with greater perceptions of well-being (rs ranged from .17 to .20) and lower ill-being (rs ranged from -.06 to -.21). Results of multiple mediation analyses demonstrated that psychological need fulfillment underpinned the LTPA-well-being relationship only. CONCLUSIONS: Collectively these findings indicate that increased engagement in LTPA represents one factor associated with greater psychological health in breast cancer survivors, with fulfilling the psychological need for relatedness most salient in understanding this relationship. Continued investigation into the mechanisms associated with reductions in ill-being in breast cancer survivors appear justified.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".