Effect of physical exercise intervention on daily sleep quality in women with breast cancer and severe psychological distress: a series of N-of-1 trials
Bibliographic record
Abstract
ObjectiveA good quality of sleep is essential within the context of breast cancer. Nonetheless, poor sleep quality is highly prevalent in breast cancer patients, particularly in women with psychological distress. Physical activity is recommended to improve sleep quality in the context of breast cancer. However, no previous physical activity intervention has been specifically tested to improve the sleep quality for women with breast cancer and psychological distress. Thus, the aim of this preliminary study was to examine the effects of a 12-week remote supervised physical activity intervention on daily self-reported sleep quality among women with breast cancer and severe psychological distress, at the individual level. MethodA series of N-of-1 trials with an A-B-A’ design was carried out with ecological momentary assessments. Phase A and A’ (2-week) represented pre- and post-intervention measures and phase B (12-week) represented the intervention phase. For the entire 16-week, participants received a daily prompt to report their sleep quality. The insomnia severity index was filled pre- and post-first phase A and end of phase B. Sixteen participants completed the treatment. ResultsA significant improvement of sleep quality was observed in 9 participants with moderate to large effects. However, the intervention was detrimental for the sleep quality in 2 patients. Paradoxically, the self-reported sleep disorder remained elevated at the end of intervention. ConclusionThis is the first study to show that physical activity is potentially effective in women with breast cancer and severe psychological distress. The findings justify extension to a randomized controlled trial.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".