”To get my life back” - interview study on restorative surgery decisions after colectomy in ulcerative colitis
Bibliographic record
Abstract
Abstract Introduction The purpose of restorative surgery after colectomy is to improve quality of life. Still little is known about patient perspectives. We explored factors influencing UC patients’ choice between restorative procedures and stoma, and their experiences of associated healthcare. Method Semi-structured interviews were conducted with 21 ulcerative colitis patients subjected to subtotal colectomy and either had chosen restorative surgery or a permanent stoma. Participants were recruited from two hospitals within the CRUISE trial. Interviews were conducted in person or via Zoom and analysed using conventional content analysis as described by Elo and Kyngäs. Data collection continued until saturation was reached. Result Twenty-one participants (14 men, 7 women; median age 34) were interviewed 43 months post-colectomy. Analysis revealed three main categories and seven subcategories: (1) Decisive factors in surgical choice, (2) Shared decision-making, and (3) Factors healthcare can influence. Participants emphasized striving for normality and high quality of life, regardless of surgical choice. Informed decision-making and active involvement were central themes. Additionally, the attitude of healthcare professionals, continuity of care, and support structures significantly shaped patients’ perceptions and choices. The findings highlight the complex interplay of physical, psychosocial, and systemic factors influencing surgical decisions. Discussion This study provides valuable insights into the experiences of patients with ulcerative colitis undergoing colectomy. Adequate information, shared decision-making, and striving for normality were central to treatment satisfaction and QoL. A more patient-centred approach may enhance both physical and emotional outcomes by supporting informed, individualized choices in surgical decision-making.
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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 | 0.008 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| 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".