Personal goal-setting among women living with breast cancer: protocol for a scoping review
Bibliographic record
Abstract
BACKGROUND: Breast cancer and its treatment can have many physical and psychological effects on affected women. Women's personal goals may provide insight into their priorities and motivations in the context of breast cancer. Incorporating personal goal-setting into support and care interventions may have an effect on psychological well-being. This protocol describes our scoping review methods, the aim of which is to examine and map the existing evidence on personal goal-setting among women with a breast cancer diagnosis. METHODS: Our scoping review will search for published, full-length articles, where personal goal-setting is a major component of the study, and the study population is females with breast cancer. MEDLINE, PsycInfo, CINAHL, EMBASE, the Cochrane Library, and AMED databases will be searched. Two independent reviewers will conduct all screening and extract data. Descriptive information about the studies, participants, any interventions, measurement tools, outcomes, and results will be reported. DISCUSSION: The results from this review will chart the literature, contributing to optimizing the incorporation of personal goal-setting approaches into effective interventions for the care and support of women with breast cancer.
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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 | 0.086 | 0.078 |
| Meta-epidemiology (narrow) | 0.005 | 0.006 |
| Meta-epidemiology (broad) | 0.011 | 0.014 |
| Bibliometrics | 0.015 | 0.014 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.079 | 0.013 |
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".