Communicating Gastrointestinal Symptoms: The Patient’s Challenge
Bibliographic record
Abstract
Gastrointestinal (GI) disorders present with signs that are objective and symptoms that are subjective, evaluable only if an individual can recognize, characterize, describe, and communicate them to a healthcare professional (HCP). The aim of this study was to quantify the extent to which healthcare seekers perceive difficulties in communicating their GI symptoms to HCPs. Interviews were conducted in two settings where individuals were expected to acknowledge experiencing GI symptoms: a tertiary-care, ambulatory GI clinic and the digestive health medication area of a large retail pharmacy. A 13-item questionnaire was designed to identify subjects' perceptions of the component stages of a symptom communication process. Surveys were completed by 100 participants, 50 from the clinic and 50 from the pharmacy. Most participants reported that it was difficult to know if their symptom descriptions had been understood (clinic: 68%; pharmacy: 86%), that difficulty in describing symptoms hampered access to healthcare (clinic: 82%; pharmacy: 76%), and that use of different descriptors (e.g., icons) would facilitate symptom reporting (clinic: 90%; pharmacy: 98%). Apart from difficulties in selecting a standard term and in providing a specific description for their symptoms, perceived barriers to communicating symptoms did not differ between the clinic and pharmacy settings. Most individuals with GI symptoms perceive difficulty in communicating their symptoms to healthcare professionals. Improved access and improved GI healthcare require new, patient-centered tools for symptom communication. These may be pictogram- or icon-based tools rather than traditional verbal descriptors.
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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 | 0.005 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".