Addressing knowledge gaps in Parkinson’s disease: a report on the Movement Disorder Society’s Centre-to-Centre initiative to improve Parkinson’s disease services in Lao People’s Democratic Republic
Bibliographic record
Abstract
BACKGROUND: Lao People's Democratic Republic (Lao PDR) has only nine neurologists for seven million people; none have formal training in Parkinson's disease (PD). Medical specialists require sufficient PD knowledge to provide high-quality care. METHODS: This study outlines a Centre-to-Centre programme for developing PD expertise in underserved regions through a tailored two-year educational enterprise between an established movement disorder mentor centre at Chulalongkorn University in Thailand and mentee centres in Lao PDR. Background knowledge of 80 Laotian physicians was assessed using a validated PD knowledge questionnaire containing 26 questions divided into 3 sections (diagnosis, therapeutic options, disease course) before and immediately after one-day kick-start training. Responses were compared across physicians' demographic groups. RESULTS: Of 80 respondents, 50 (62.5%) were board-certified physicians, of which 27 (54%) specialised in internal medicine. Apparent knowledge gaps were shown by a 51.2% correct response rate for total score, 52.8% for diagnosis, 50.6% for therapeutic options, and 48.2% for disease course. No significant differences in total score or any domain sub-scores between neurologists and other specialties were found. Many did not know which non-motor symptoms could occur as prodromal symptoms or late in course of PD. Incorrect responses mainly reflected a lack of knowledge of the impact of medication on disease. Total and domain sub-scores significantly improved after the course (p < 0.05, each). The size of difference of the means was significant for the total score (d = 0.82), therapeutic option (d = 0.56), and disease course (d = 0.68) sub-scores. CONCLUSIONS: Significant improvement of PD knowledge amongst Laotian physicians is demonstrated after a training course, focusing on practical management of PD. Our findings highlight the importance of continued medical education, especially PD-specific training.
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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 | 0.001 | 0.003 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".