Opinions and clinical practices related to diagnosing and managing patients with psychogenic movement disorders: An international survey of movement disorder society members
Bibliographic record
Abstract
Five hundred and nineteen members of the Movement Disorder Society completed a 22-item questionnaire probing diagnostic and management issues in psychogenic movement disorders (PMD). When patients showed definite evidence of PMD with no other unexplained clinical features, approximately 20% said they informed patients of the diagnosis and requested no further neurological testing. The 51% who reported conducting standard neurological investigations to rule out organic causes before presenting the diagnosis to such patients had fewer years of fellowship training and fewer PMD patients seen per month. A non-PMD diagnosis was correlated with patients' normal social or personal functioning, little or no employment disruption, lack of non-physiologic findings, and lack of psychiatric history. Ongoing litigation was more predictive of the PMD diagnosis for US compared to non-US respondents. Two thirds of respondents, more commonly younger and academic clinician researchers, refer PMD patients to a psychiatrist or mental health specialist while also providing personal follow up. Physician reimbursement, insurability of PMD patients, and ongoing litigation interfered with managing PMD patients to a greater extent in the US compared to non-US countries. Acceptance of the diagnosis by the patient and identification and management of psychological stressors and concurrent psychiatric disorders were considered most important for predicting a favorable prognosis. These findings suggest that expert opinions and practices related to diagnosing and managing PMD patients differ among movement disorders neurologists. Some of the discrepancies may be accounted for by factors such as training, type of practice, volume of patients, and country of practice, but may also reflect absence of practice guidelines.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".