Assessing the socioeconomic burden in pediatric inflammatory bowel disease—a survey of families and national providers
Bibliographic record
Abstract
Objectives: Despite rapidly rising rates of pediatric inflammatory bowel disease (IBD), literature exploring the financial burden on families of children with IBD remains limited. This study sought to better understand the socioeconomic burden of pediatric IBD on families at our institution and compare IBD provider practices and perceptions across the country. Methods: Two separate electronic surveys exploring demographics, financial impacts of an IBD diagnosis, and perceptions around IBD care were developed for patient families and IBD providers respectively. Descriptive statistics and regression analysis took place to assess survey responses. Thematic analysis was also undertaken to qualitatively assess family survey comments. Results: = 18) suggests some variability in clinical practice, allied health support, and financial support for families. However, providers almost universally recognize the financial, mental health, and employment impacts on families as significant socioeconomic burdens on families. Conclusions: This is the first study in Canada to directly explore national provider practices and the socioeconomic burden on families of children with IBD. Results indicate a good correlation between provider awareness and the increased financial burden on families but suggest ongoing care gaps to address impacts on employment, mental health, and out-of-pocket costs. This data suggests that various quality improvement opportunities for research and advocacy exist to better support families, both locally and beyond.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".