MétaCan
Menu
Back to cohort
Record W4415534214 · doi:10.1016/j.cjprs.2025.08.003

Construction of a patient-centered decision support tool for cosmetic breast surgery

2025· article· en· W4415534214 on OpenAlexaboutno aff
Weiwei Bian, Danning Zheng, Nur Akmar Taha, Lin Yang, Xinyi Liu, Jiafei Yang

Bibliographic record

VenueChinese Journal of Plastic and Reconstructive Surgery · 2025
Typearticle
Languageen
FieldMedicine
TopicDigital Imaging in Medicine
Canadian institutionsnot available
Fundersnot available
KeywordsDecision support systemDecision aidsFocus groupBreast surgeryClinical decision support systemQualitative researchMEDLINEDecision analysisProcess (computing)

Abstract

fetched live from OpenAlex

This study aimed to develop and evaluate a patient-centered decision aid (PDA) to support shared decision-making among individuals undergoing aesthetic breast surgery in China. The Ottawa Decision Support Framework served as the theoretical foundation for the development of the tool, which was created through a multistage process that included a literature review, expert focus group interviews, and a pilot clinical application involving 20 patients. The PDA was implemented using a WeChat mini-program and structured into six core modules: assessment of decision-making, evaluation of support resources, information acquisition, provider selection, surgical plan selection, and decision evaluation. Expert panels, comprised of experienced clinicians and patients, assessed the importance of each component, with all primary indicators receiving scores above 4.75 on a five-point scale. Pilot testing revealed that PDA enhanced patient understanding of risks and benefits, elucidated values and preferences, reduced decisional regret, and improved communication efficiency between patients and clinicians. The qualitative interviews confirmed their practical utility and cultural adaptability. This tool offers a structured, evidence-informed, and interactive platform to empower patients to make well-aligned decisions regarding aesthetic breast procedures. Future research should focus on scaling its application and exploring artificial intelligence integration to personalize decision support.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.243
Threshold uncertainty score0.717

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.009
GPT teacher head0.262
Teacher spread0.252 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueChinese Journal of Plastic and Reconstructive SurgerySame topicDigital Imaging in MedicineFrench-language works237,207