Families’, practitioners’, and researchers’ experience in the trajectory for the diagnostic evaluation of developmental disorders in young children
Bibliographic record
Abstract
BACKGROUND: A collaborative initiative was undertaken to restructure diagnostic and support services for developmental disabilities (DD) in young children in the province of Québec. Representatives from multiple stakeholder groups, including researchers, parents, and clinicians, shared insights based on their experiences with diagnostic evaluation services. AIMS: The present study documented stakeholders' experiences with existing DD services, with a focus on identifying barriers, facilitators, and gathering actionable recommendations for the creation of a new model for diagnostic evaluation. METHOD: Twenty-nine stakeholders shared their experiences in focus group and individual interviews. Their discourse was analyzed according to the quality determinants of the ETAP framework (Rivard et al., 2020) and categorized as barriers, facilitators, or recommendations. RESULTS: Stakeholders described several barriers related to continuity and accessibility within the current system but also discussed some facilitators that promoted, e.g., the accessibility and validity of services. They made several recommendations to improve upon or clarify existing elements and identified what could be added. CONCLUSIONS: These testimonials from stakeholders emphasize the need to conceptualize the DD service trajectory as a whole. This will require improving upon information-sharing and collaboration practices, formalizing procedures, and adding case navigation and parent support modalities.
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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 | 0.030 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.009 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".