Treatment Comfort of Adult Neurologists in Childhood Onset Conditions
Bibliographic record
Abstract
BACKGROUND: The majority of children with chronic neurodevelopmental disabilities are surviving to adulthood. Our goal was to assess how prepared and comfortable adult neurologists are in treating young adults with childhood onset chronic neurological conditions and evaluate the difficulty pediatric neurologists experience when transferring these patients to adult care. METHODS: We conducted a cross-sectional study using two postal surveys of all pediatric and adult neurologists in the province of Quebec, Canada. RESULTS: The response rate was 51.5%, with 119 neurologists completing the survey. Half of neurologists agreed that adult neurologists may not have adequate training in childhood onset disorders to prepare them to manage the disorders in adulthood, and 60% of pediatric neurologists reported having difficulty finding an adult provider for their patients. Adult neurologists were least comfortable treating patients with autism, chromosomal or metabolic disorders, and cognitive or behavioral disorders. CONCLUSION: Almost half of those surveyed believed that adult neurologists are not adequately trained to care for this growing patient population. Improving treatment comfort and knowledge among adult neurologists in childhood onset chronic neurological conditions may smooth the transition of these young adults from pediatric to adult care.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".