Irritable Bowel Syndrome in Primary Care: The Patients’ and Doctors’ Views on Symptoms, Etiology and Management
Bibliographic record
Abstract
BACKGROUND: To facilitate the development of clinical guidelines and to direct future irritable bowel syndrome (IBS) research, insight into the perceptions of patients and general practitioners (GPs) regarding IBS is required. OBJECTIVES: To compare patients' and GPs' views on the symptomatology, etiology and treatment of IBS. METHODS: One hundred forty-two IBS patients and 100 GPs were requested to complete a structured questionnaire. RESULTS: The response rates of the patients and GPs were 80% and 47%, respectively. Abdominal pain and bloating were considered to be the most bothersome symptoms in IBS, by both patients and GPs. Although all patients were diagnosed by their GP as having IBS, and 62% met the Manning criteria, only 18% fulfilled the Rome II criteria for IBS. Patients consider food intolerance and GPs regard lack of fibre as the main etiologic dietary factor. Many IBS patients expect a diagnostic work-up, but GPs generally restrict this to elderly patients. GPs start IBS management with dietary advice (94%), counselling (77%) and drug therapy (55%). Patients expect reassurance (47%) and drug treatment (37%), but dietary interventions are less appreciated (9%). CONCLUSIONS: Patients and GPs have different perceptions of the efficacy of diagnostic and dietary interventions in IBS. GPs should explore the patients expectations and incorporate these in their approach to IBS patients.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".