Bibliographic record
Abstract
OBJECTIVES: To examine the importance of good communication when informing the patient of the diagnosis of migraine; to review the essentials of successful communication between physician and patient on the aspect of diagnosis; to survey learning resources for physicians on communicating information to patients. METHODS: This paper is based on observations made by the author of the successful interactions of numerous international "headache experts" with their patients, on a review of the medical education literature pertaining to the teaching of communication skills, and on 30 years of not always successful communication with patients. RESULTS: Communicating the diagnosis of migraine is an opportunity to educate and reassure the patient, to lay the foundation for rational treatment and to help establish the successful doctor-patient relationship which is essential for effective management. No matter how accurate the diagnosis, failure to communicate it effectively to the patient (and often to significant others) may impair interactions with the patient and compromise therapy. Effective communication of a diagnosis requires clarity, relevance to the patient, a positive attitude, and reinforcement through repetition, questioning and dialogue. In terms of using the diagnosis to lay a foundation for therapy, it is useful to explain the symptoms as transient physical dysfunction of normal tissues, to indicate that there are multiple mechanisms underlying the dysfunction of which only some may presently be susceptible to treatment and to stress the relevance of emotions as factors which may powerfully affect, for better or worse, the underlying disturbed physiology of migraine. Into this model can be "plugged" all the relevant therapies for migraine. This is the ideal, but every day experience in the headache consultant's office suggest that in both primary care and specialist practice, it is infrequently attained. There are scant resources other than example for physicians to learn communication of headache diagnosis specifically but there are numerous print and web resources available to physicians wh wish to learn and/or teach the generic principles of effective communication, and these principles require little or no modification to be applied to the headache patient and the headache doctor.
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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 | 0.006 | 0.055 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".