Fecal Microbiota Transplantation for the Treatment of Ulcerative Colitis: A Qualitative Assessment of Patient Perceptions and Experiences
Bibliographic record
Abstract
BACKGROUND: Fecal microbiota transplantation (FMT) is a promising experimental therapy for ulcerative colitis (UC), yet patient acceptance remains poorly understood. AIMS: The aim of this study was to explore perceptions and experiences of adult patients who received FMT for UC. METHODS: This study used a qualitative descriptive design with thematic content analysis. Patients who were approached for enrollment in a clinical trial (NCT02606032) were invited to participate in face-to-face semistructured interviews. Two groups were interviewed: those who chose to pursue FMT and those who declined FMT. Non-FMT patients were interviewed once; FMT patients were interviewed twice at pre- and post-treatment. RESULTS: Nine FMT patients (78% female, average age 46.7 years old) and eight non-FMT patients (50% female, average age 39.5 years old) were enrolled. Pretreatment themes included FMT as a natural therapy, external barriers to pursuing FMT, concerns with FMT and factors influencing the decision to pursue FMT. While both groups generally perceived FMT as a natural therapy, pre-FMT patients showed greater acceptance of alternative medicine. Both groups demonstrated poor understanding and similar initial concerns with product cleanliness. Pre-FMT patients were motivated to pursue FMT by feelings of last resort. Post-FMT themes included therapeutic impact of FMT and psychosocial impact of FMT. Post-FMT patients reported overall satisfaction and a unanimous preference for FMT over conventional medications. CONCLUSION: This is the first study to assess adult patient perceptions and real-life experiences with FMT for the treatment of UC. By improving patient education, we may achieve greater acceptance of FMT.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".