P534 Qualitative perspectives of parent and child participants from a trial of faecal microbiota transplant for paediatric ulcerative colitis
Bibliographic record
Abstract
Abstract Background Faecal microbiota transplant (FMT) is being studied across a range of therapeutic indications including ulcerative colitis (UC). Pediatric patients may have unique perspectives on microbiome-based therapeutics given their younger age, fewer comorbidities, and greater susceptibility to microbial influences. We recently conducted the first randomised-controlled trial (RCT) of FMT for pediatric UC (PediFETCh Trial) and conducted qualitative interviews of child participants and their parents. This study aims to describe the experiences and perceptions of these children who received FMT, and their parents. Methods Participants in the PediFETCh Trial (ClinicalTrials.gov: NCT02487238) were invited to participate in face-to-face, semi-structured interviews. Interviews were audiotaped, transcribed, and analyzed using open coding (NVivo 12 Pro). Results 8 pediatric participants and 8 parents were interviewed. Data were summarised across 4 domains and 11 composite themes (Table 1). Most children and parents saw FMT as a ‘safe, natural’ treatment. Prior to enrollment, children were concerned about receiving ‘someone else’s poo’ and potential physical discomfort, while parents were concerned about transmission of enteric infections and psychiatric diseases. Both groups felt their decision to pursue FMT was influenced by frustration with lack of response to medications, and fear of medication-related side effects. Following completion of the study, most children and parents had no concerns about potential side effects of FMT, and children reported feeling ‘completely normal’. Children were split between preferring FMT or medication therapies. The convenience of medications was valued, while others favoured FMT for its symptomatic improvement and perceived naturality. It was noted that some alternative healthcare practitioners did not support patients’ desire to pursue FMT. Conclusion Our study offers valuable insight into the experiences of receiving FMT in pediatric participants and their parents. This data suggest a high rate of acceptance and interest in FMT-based therapeutics in this population and offers strategies to improve the delivery of FMT in future pediatric-focused RCTs.
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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 | 0.016 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".