Feasibility and acceptability of study methods and psychosocial interventions for body image among women diagnosed with breast cancer: A systematic review and narrative synthesis
Bibliographic record
Abstract
OBJECTIVE: This systematic review aimed to summarize evidence for the feasibility and acceptability of psychosocial interventions for body image among women diagnosed with breast cancer and the study methods used to evaluate the interventions in question. METHODS: Articles were identified via MEDLINE, CINAHL, CENTRAL, PsychINFO, and EMBASE. Inclusion criteria were: (1) peer-reviewed publication in English from 2000 onward with accessible full-text, (2) reported data on the feasibility and/or acceptability of psychosocial interventions and/or study methods, (3) included at least one measure of body image or reported a body-related theme, and (4) sample comprised women diagnosed with breast cancer. All study designs were eligible. Two reviewers independently performed study selection, data extraction, and quality assessment. RESULTS: Sixty-two articles were included. Participants and comparator groups varied as did interventions. Feasibility and acceptability of the interventions and study methods were inconsistently operationalized and reported across studies. Evidence of feasibility and acceptability was heterogeneous within and across studies, though mostly positive. CONCLUSION: Published psychosocial interventions for body image and study methods are generally feasible and acceptable. Findings should be used to advance the development, implementation, and evaluation of interventions designed to improve outcomes (body image or otherwise) for women diagnosed with breast cancer. SYSTEMATIC REVIEW REGISTRATION: This review was registered with the International Prospective Register of Systematic Reviews (PROSPERO; ID: CRD42021269062, 11 September 2021).
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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 | 0.144 | 0.397 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.012 | 0.013 |
| Bibliometrics | 0.012 | 0.013 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".