Patient Expectations of Bariatric and Body Contouring Surgery
Bibliographic record
Abstract
BACKGROUND: Patient expectations are important in bariatric and body contouring surgery because the goals include improvements in health-related quality of life, appearance, and body image. The aim of this study was to identify patient expectations along the weight loss journey and/or body contouring surgery. METHODS: This qualitative study took an interpretive description approach. Between September 2009 and February 2012, 49 patients were interviewed postbody contouring surgery. Data were analyzed using a line-by-line approach whereby expectations were identified and labeled as expected, unexpected, or neutral. Constant comparison was used to ensure coding was done consistently. Interviews continued until no new themes emerged. RESULTS: Participants described expectations according to appearance, health-related quality of life, and patient experience of care. Two areas stood out in terms of unmet expectations and included appearance and physical health, ie, recovery from body contouring surgery. Most participants, who underwent bariatric surgery, expected neither the extent of excess skin after weight loss nor how the excess skin would make them look and feel. For recovery, participants did not expect that it would be as long or as hard as it was in reality. CONCLUSIONS: A full understanding of outcomes and expectations for this patient population is needed to enhance patient education and improve shared medical decision making. Education materials should be informed by the collection of evidence-based patient-reported outcome information using measures such as the BODY-Q. A patient-reported outcome scale measuring patient expectations is needed for obese and bariatric 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 | 0.009 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".