Assessing the Transition Intervention Needs of Young Adults With Inflammatory Bowel Diseases
Bibliographic record
Abstract
OBJECTIVES: The transition of inflammatory bowel disease (IBD) patients from pediatric to adult care can be challenging. Developing an effective transition intervention requires assessing the current transition experience for potential improvements, determining preferred content and format, and assessing patients' transition skills. METHODS: This mixed-methods study of 20 transitioned IBD patients (ages 17-20 years) used semistructured interviews and validated assessments of self-management/self-advocacy and IBD knowledge. Interviews were analyzed thematically. Assessment scores were compared with published reference data by estimating proportion or mean differences and 95% confidence intervals (CIs). RESULTS: The concept of a transition intervention was well-received by participants. Preferred content centered on medications, disease and what to expect. Preferred ways to acquire knowledge were one-on-one instruction, handouts, and websites. Identified themes were "individualized and multifaceted," "teach about transition," and "support the shift in responsibility." Among participants, 95% did not achieve 90% mastery of transition skills (0.6% higher [95% CI -10.7% to 9.5%] than the reference estimate) and the mean knowledge score was 15.15 (3.86 [95% CI 2.27 to 5.45] points higher than the reference estimate). CONCLUSIONS: We have identified preferred intervention formats and content as well as skill areas to target for improvement. As a result of this work, we will design a website intervention pertaining to identified themes.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".