Empowerment-Led Guided Self-Help Intervention for Symptom Burden in Breast Cancer Women Treated With Ovarian Function Suppression: A Randomized Trial Protocol
Bibliographic record
Abstract
Background: Ovarian function suppression (OFS) treatment causes breast cancer patients' estrogens to fall rapidly to postmenopausal levels, and the 5-year treatment duration and 28-day treatment cycles place a heavy physical and psychological symptom burden on them, which in turn directly or indirectly affects the survival benefit. Managing symptom burden early in treatment is critical, but OFS-related studies have yet to be seen. Self-management is essential for patients' symptom burden. However, self-help management is hampered by patients' lack of knowledge, skills, motivation, etc. Guided self-help intervention (GSH) provides a feasible approach. Empowerment theory is a promising theoretical framework to guide self-management. Methods: A prospective two-arm parallel randomized controlled single-blind clinical trial will be conducted to investigate the effect of symptom burden GSH based on empowerment theory in breast cancer patients in the early stages of OFS treatment. A block randomization method is used to allocate 144 patients to either the control or intervention group. The program is conducted according to the OFS return-to-hospital treatment cycle. The intervention group will receive a total of two rounds and five sessions of empowering GSH, lasting at least 15 weeks in total; the control group will receive only usual nursing care. Symptom burden and related metrics will be assessed at baseline and 1, 3, and 6 months after OFS treatment, and changes between and within groups will be explored. This paper adhered to the SPIRIT and CONSORT guidelines. Conclusion: These results will help to validate the GSH in symptom burden management for breast cancer patients in OFS treatment early stages. It enriches its symptom burden management research and may provide implications for the whole cycle of OFS treatment patients.
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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 | 0.010 | 0.009 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.041 | 0.004 |
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".