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Record W2065022050 · doi:10.1186/1472-6874-9-11

Satisfaction and quality of life in women who undergo breast surgery: A qualitative study

2009· article· en· W2065022050 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBMC Women s Health · 2009
Typearticle
Languageen
FieldMedicine
TopicBreast Implant and Reconstruction
Canadian institutionsUniversity of British ColumbiaMcMaster University
Fundersnot available
KeywordsPatient satisfactionQuality of life (healthcare)PsychosocialBreast surgeryBreast reconstructionBreast reductionMedicineQualitative researchReconstructive surgeryMammaplastyNursingSurgeryBreast cancerInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: In cosmetic and reconstructive breast surgery, measurement of patient-reported outcomes has become increasingly important to research efforts and clinical care. We aimed to describe how breast conditions and breast surgery impact on patient satisfaction and quality of life. METHODS: We conducted qualitative, in-depth interviews with 48 women who had undergone either breast reduction (n = 15), breast augmentation (n = 12), or breast reconstruction (n = 21) surgery in order to begin to build a theoretical understanding of patient satisfaction and quality of life in breast surgery patients. Interviews were audio-taped, transcribed verbatim and analyzed thematically. RESULTS: The patient interviews revealed that breast conditions and breast surgery impact women in the following six main areas: satisfaction with breasts; satisfaction with overall outcome; psychosocial well-being; sexual well-being; physical well-being; and satisfaction with the process of care. We used these six themes to form the basis of a conceptual framework of patient satisfaction and quality of life in women who undergo breast surgery. CONCLUSION: Our conceptual framework establishes the main issues of concern for breast surgery patients. This new framework can be used to help develop local guidelines for future clinical assessment, management and measurement, establish the validity of the current management strategies, and develop evidence-based guidance for the development of new patient reported outcome measures for future outcomes research.

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.

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)0.003
metaresearch head score (Gemma)0.000
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 score0.118
Threshold uncertainty score0.433

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.068
GPT teacher head0.376
Teacher spread0.308 · 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