Understanding the role of the healthcare professional in patient self-management of allergic rhinitis
Bibliographic record
Abstract
OBJECTIVE: Allergic rhinitis is a common, usually long-standing, condition that may be self-diagnosed or have a formal diagnosis. Our aim was to identify how allergic rhinitis sufferers self-manage their condition. METHODS: A sample of 276 self-identified adult allergy sufferers pooled from social media completed an online survey comprising 13 questions. The survey was fielded by a professional research organization (Lab42). The main outcome measures included the use of prescription and/or non-prescription allergy medication, and interactions with physician and/or pharmacist with respect to medication use. RESULTS: Of the respondents, 53% (146/276) indicated that they used both prescription and over-the-counter medication to manage their allergy symptoms. Of those who used prescription medication, 53% reported that they discussed their prescription medication in great detail with their physician when it was prescribed, while 42% spoke about it briefly. Following the initial prescription, few discussions about the prescription occur with the physician (45% indicate several discussions, 40% indicate one or two discussions, and 10% indicate no discussions). In most cases (~75% of the time), allergy prescription refills did not require a doctor visit with patients obtaining refills through phone calls to the doctor's office or through the pharmacy. Two-thirds of patients (69%) report that they have discussed their prescription allergy medication with a pharmacist, with greater than half of respondents having discussed the use of the non-prescription medication with their doctor. CONCLUSION: Patients with diagnosed allergic rhinitis appear to be self-managing their condition with few interactions with their doctor about their allergy prescription. Interactions with a pharmacist about allergy medication (prescription and non-prescription) appear to be more common than interactions with a physician.
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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 | 0.019 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".