Bibliographic record
Abstract
OBJECTIVES: To do a needs assessment directed to neurologists attending a workshop on communication skills emphasizing relationships between physician and patient, assessment of disability and quality of life of migraine patients, and communication of therapies for migraine. METHODS: A structured questionnaire was sent to all participants related to the issues indicated in the objective. This was prepared by the faculty and the results were collated by the author and presented at the beginning of the workshop. This paper overviews the use and results of a needs assessment to highlight learning needs of the participants and to focus the issues, interest and interactions of neurologists in a workshop. The workshop focused primarily on communication skills and on the understanding of disability and quality of life issues in migraine patients. RESULTS: In general the responses revealed that the attendees were neurologists in practice for more than 15 years, that over 50% had prior knowledge of communication skills and used them in various ways, and 74% were involved in teaching family physicians. Some knew and used disability and quality of life tools but up to one third of participants did not assess disability in their patients. Most wanted to learn more about communication skills and other objectives noted and 19% of respondents wanted to learn more about prophylactic antimigraine treatments and how to differentiate/contrast the triptans. CONCLUSION: Using a needs assessment tool allowed organizers of an educational workshop to determine the current knowledge and perceived and unperceived needs of the participants with respect to communication skills, assessing disability and quality of life issues, and communication of treatments to migraine 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 | 0.006 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.004 |
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".