Identification of clinician challenges in order to drive the development of competency-based education: results from an international needs assessment in multiple sclerosis
Bibliographic record
Abstract
Objective. To highlight clinical gaps of neurologists and nurses regarding their skills and confidence in engaging and communicating with multiple sclerosis (MS) patients to inform the design of continuing medical education (CME) initiatives. Methods. This international IRB-approved study deployed in six countries (France, Germany, Italy, Spain, UK and USA), utilised a mixed-methods approach (qualitative interviews and an online survey) to explore the self-reported challenges of neurologists and nurses across the spectrum of MS care. Results. The sample included actively practising neurologists (n=148) and nurses (n=146), 42% of whom had an annual caseload of 150+ MS patients. The participants reported challenges in assessing patients’ adherence to treatment, engaging patients in shared decision-making and communicating confidently with patients and caregivers. Participants reported their own skill and confidence deficits as potential causalities for these challenges. Conclusion. Results suggest that neurologists and nurses would be receptive to education to develop their skills with regard to communication with patients and caregivers. CME and performance improvement initiatives should address the clinical challenges identified in this study to optimise clinicians’ effectiveness and patient outcomes. Patient–provider communication skills represent a priority area for the development of CME and performance improvement initiatives.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".