The Information Needs and Preferences of Persons with Longstanding Inflammatory Bowel Disease
Bibliographic record
Abstract
BACKGROUND: Understanding the information needs and preferred vehicles of information delivery to patients with inflammatory bowel disease (IBD) will enhance their care. OBJECTIVE: To survey persons with longstanding IBD as to their information needs and preferred vehicles of information delivery. METHODS: The population-based Manitoba IBD Cohort (n=271, mean disease duration 11 years) was surveyed to assess its information needs across 23 issues, both retrospectively at the time of diagnosis and currently. RESULTS: Most participants (64%) were initially diagnosed by a gastroenterologist, or otherwise by a family physician (19%) or surgeon (12%). Recalling time of diagnosis, at least 80% rated as very important information about common symptoms of IBD, possible complications, long-term prognosis, medication side effects, self management of symptoms and when to involve the doctor, yet only 10% to 36% believed they received the right amount of information about these issues. Dietary guidance was also regarded as important by 80% to 89%, yet only 8% to 16% received the correct amount of information. Regarding current needs, a large proportion believed it would be very helpful to have more information about long-term prognosis (66%) and diet considerations (60% to 68%). The following information sources were regarded as very acceptable: medical specialist (81%); brochure (79%); family doctor (64%); and website (64%), with 51% ranking the medical specialist as the first choice. In a comparison of the responses of this cohort to those of a recently diagnosed sample, there was remarkable consistency in the information needs and most desired sources of information. DISCUSSION: In the present population-based cohort with longstanding disease, dietary information was regarded as the least adequately addressed. There was clear openness to receiving information through other routes than just the medical specialist, suggesting that optimizing brochures and websites would be an important adjunct source of information. CONCLUSION: Approximately 10 years after diagnosis, only a small percentage of persons with IBD believed they received the correct amount of information about the issues they regarded as most important to have discussed at diagnosis.
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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 | 0.001 | 0.006 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".