The Pediatric Autism Research Cohort (PARC) Study: protocol for a patient-oriented prospective study examining trajectories of functioning in children with autism
Bibliographic record
Abstract
Introduction The developmentally variable nature of autism poses challenges in providing timely services tailored to a child’s needs. Despite a recent focus on longitudinal research, priority-setting initiatives with stakeholders highlighted the importance of studying a child’s day-to-day functioning and social determinants of health to inform clinical care. To address this, we are conducting a pragmatic multi-site, patient-oriented longitudinal investigation: the Pediatric Autism Research Cohort (PARC) Study. In young children (<7 years of age) newly diagnosed with autism, we will: (1) examine variability in trajectories of adaptive functioning from the point of diagnosis into transition to school; and (2) identify factors associated with trajectories of adaptive functioning. Methods and analysis We aim to recruit 1300 children under 7 years of age with a recent (within 12 months) diagnosis of autism from seven sites: six in Canada; one in Israel. Participants will be followed prospectively from diagnosis to age 8 years, with assessments at 6-month intervals. Parents/caregivers will complete questionnaires administered via a customized online research portal. Following each assessment timepoint, families will receive a research summary report describing their child’s progress on adaptive functioning and related domains. Analysis of the longitudinal data will map trajectories and examine child, family and service characteristics associated with chronogeneity (interindividual and intraindividual heterogeneity over time) and possible trajectory turning points around sensitive periods like the transition to school. Ethics and dissemination Ethics approvals have been received by all sites. All parents/respondents will provide informed consent when enrolling in the study. Using an integrated knowledge translation approach, where stakeholders are directly engaged in the research process, the PARC Study will identify factors associated with trajectories of functioning in children with autism. Resulting evidence will be shared with government policy makers to inform provincial and national programs. Findings will be disseminated at conferences and published in peer-reviewed journals.
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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 | 0.053 | 0.045 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.042 | 0.010 |
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".