Trajectory research in children on the autism spectrum: a scoping review protocol
Bibliographic record
Abstract
INTRODUCTION: Longitudinal trajectory methods, featuring outcome assessments at three or more time points, are increasingly being used as appropriate approaches to understand developmental pathways of people on the autism spectrum across the lifespan. Understanding the scope of this rapidly expanding body of research can help inform future trajectory studies and identify areas for potential meta-analysis as well as key evidence gaps. We present the protocol for a scoping review whose objective is to identify and summarise the scope of research that uses a longitudinal trajectory study design to examine development in children diagnosed with autism. Specifically, we will identify outcome domains and age intervals that have been well characterised, areas where further research is needed and the historical use of various longitudinal trajectory analytical approaches. METHODS AND ANALYSIS: We outline the methods for the proposed scoping review according to the framework outlined by Arksey and O'Malley, with subsequent clarifications and enhancements by other authors. Using a search strategy developed by a medical librarian, we will search six databases for relevant publications. Titles and abstracts will be screened in duplicate, followed by full-text screening. Data extraction fields developed predominantly a priori from a set of guiding subquestions will be used to chart relevant data. The findings will include quantitative aggregate summaries, narrative summaries, and appraisal of trajectory studies according to our methodological subquestions. We will consult autistic self-advocate and parent-caregiver stakeholders to facilitate interpretation of the findings. ETHICS AND DISSEMINATION: Research ethics approval is not required for this scoping review. The results will be presented to researcher, care professional, policy-maker and stakeholder audiences at local and international conferences, other dissemination activities and published in a peer-reviewed journal.
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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 | 0.196 | 0.182 |
| Meta-epidemiology (narrow) | 0.005 | 0.006 |
| Meta-epidemiology (broad) | 0.011 | 0.012 |
| Bibliometrics | 0.024 | 0.022 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.009 | 0.010 |
| Research integrity | 0.013 | 0.009 |
| Insufficient payload (model declined to judge) | 0.057 | 0.017 |
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".