The nature of expectations of bariatric surgery in patients during the pre‐ and post‐operative period: A unicentric, qualitative study of patient perspectives
Bibliographic record
Abstract
Many patients (20%-30%) experience suboptimal weight loss (WL) after bariatric surgery (BS), and unrealistic preoperative WL expectations may be a contributing factor. This study aimed to describe the nature of patients' general expectations of BS during the pre-surgical period, and how patients determined whether their expectations and WL goals (WLGs) were realistic. The extent to which patients' expectations and WLGs were met and/or changed during the post-surgical period was also assessed. Semi-structured interviews were conducted with 15 preoperative patients recruited approximately 6-months before surgery. Focus groups were also conducted with 14 post-operative patients recruited approximately 6-months after surgery. Interviews and focus groups were audio-recorded, transcribed verbatim and analysed using qualitative content analysis. Preoperative patients reported expectations that BS would positively impact physical and psychological health, social relationships, as well as quality of care. Preoperative patients perceived that they and their health care professionals had unrealistically high expectations of WL. Post-operative patients reported being generally satisfied with the outcomes of surgery, even though many did not reach their expected WL. Finally, most post-operative patients reported changing their expectations from pre- to post-surgery. This study provides data that may help inform the development of preoperative interventions focusing on helping patients set realistic expectations for WL and related outcomes, which could better prepare patients for the challenges they will face after surgery.
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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 | 0.012 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| 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".