Impact of inflammatory bowel disease on student experience in postsecondary education
Bibliographic record
Abstract
Objectives: This literature review seeks to identify based on the current literature how the burden of disease for IBD patients manifests itself as this cohort transitions simultaneously from pediatric to adult care and from secondary to post-secondary education. Methods: This paper reviews the current literature regarding postsecondary students with IBD and provides a summary of research regarding key factors in their quality of experience. The research was conducted through databases including Taylor & Francis, PubMed, as well as searches via Google Scholar. Results: Over the course of this search, thirty-three relevant studies were identified. These studies addressed the themes outlined in this paper, including academic performance, social adaptation, transition of care, as well as overall transition to a postsecondary institution. Each of these is further broken down to identify specific determinants of IBD student experience. Conclusions: Although students with IBD can demonstrate resilience and adaptive behavior, the evidence suggests there are significant limitations impacting their perceived experience. The barriers IBD students face impact their ability to experience postsecondary education as they intend to, forcing them to adjust in adaptive or maladaptive manners. This review also attempts to generate possible solutions to specific barriers identified from current research, generating directions of action for students, physicians, and academic supports.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".