DIAGNOSTIC AND COLLABORATION NEEDS REGARDING ASD BY COMMUNITY PAEDIATRICIANS IN SOUTHERN ALBERTA
Bibliographic record
Abstract
Abstract BACKGROUND Paediatricians play a central role in the screening and diagnosis for autism spectrum disorder (ASD). Current diagnostic procedures rely on a history, screening and diagnostic tools, and collaboration with developmental specialists. The assessment process may vary among paediatricians due to the variety of available screening and diagnostic tools and opportunities to collaborate. As part of a quality improvement initiative through Child Development Services at the Alberta Children’s Hospital, paediatricians were surveyed about their present ASD screening and diagnostic practice. OBJECTIVES To examine ASD screening and diagnostic practices among paediatricians for 4 to 6 year-old children in southern Alberta. DESIGN/METHODS Paediatricians were recruited from southern Alberta to complete an anonymous online survey. Data were analyzed using descriptive statistics. RESULTS The response rate was 40% (36/90). The majority of participants (86%) reported using an ASD screening tool, and (56%) reported experiencing one or more barriers related to screening tool use. All participants reported experiencing one or more barriers to ASD diagnosis. Despite these barriers, 69% of participants reported making an ASD diagnosis within the last 12 months, and 61% of paediatricians indicated feeling confident in their ability to diagnose ASD. Most participants (57%) indicated that they would prefer to make an ASD diagnosis themselves, rather than have this be undertaken by another clinician. CONCLUSION Paediatricians in southern Alberta report important barriers in screening and diagnostic practices related to ASD. Further discussion with community paediatricians is required related to addressing these barriers to develop care pathways for this population.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".