Information needs and preferences of recently diagnosed patients with inflammatory bowel disease
Bibliographic record
Abstract
BACKGROUND: The aim of this study was to assess the information needs and experiences of patients who were recently diagnosed with inflammatory bowel disease (IBD). METHODS: Seventy-four patients, diagnosed with Crohn's disease or ulcerative colitis, 3-24 months previously were recruited from gastroenterology practices and completed the information needs survey. RESULTS: The most frequent sources of information in the first 2 months after diagnosis were the gastroenterologist and the Internet. In all, 24% of patients reported feeling dissatisfied with the information they were given at the time of their diagnosis, 31% were moderately satisfied, and 45% were very satisfied. There were many areas of information about the disease, its treatment, and self management that patients considered to be important and received little or no information about. When patients described how they would prefer to receive information if they were considering a new treatment in the future, 68% indicated that they preferred information from a medical specialist. CONCLUSIONS: Given the large number of topics judged by patients to be important and the complexity of the information required, it would be very difficult to communicate this information in oral discussion during typical consultation visits. Supplementing physician-patient consultations with well-designed written information or a Website recommendation may produce more effective communication and education. Patients rated these sources of information as having a high level of acceptability.
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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 | 0.000 |
| 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) | 0.003 | 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".