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Record W4312103349 · doi:10.1111/jcpp.13744

Continuity of trajectories of autism symptom severity from infancy to childhood

2022· article· en· W4312103349 on OpenAlexafffund
Martina Franchini, Isabel M. Smith, Lori Sacrey, Eric Duku, Jessica Brian, Susan E. Bryson, Tracy Vaillancourt, Vickie Armstrong, Péter Szatmári, Wendy Roberts, Caroline Roncadin, Lonnie Zwaigenbaum

Bibliographic record

VenueJournal of Child Psychology and Psychiatry · 2022
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsMcMaster Children's HospitalAutism CanadaHospital for Sick ChildrenCentre for Addiction and Mental HealthUniversity of OttawaHolland Bloorview Kids Rehabilitation HospitalSickKids FoundationHamilton Health SciencesDalhousie UniversityUniversity of TorontoMcMaster UniversityUniversity of AlbertaIzaak Walton Killam Health Centre
FundersKids Brain Health NetworkCanadian Institutes of Health ResearchAlberta Innovates - Health Solutions
KeywordsAutism Diagnostic Observation ScheduleAutismAutism spectrum disorderPsychologyPediatricsCohortDevelopmental psychologyTrajectoryAudiologyMedicine

Abstract

fetched live from OpenAlex

BACKGROUND: Behavioral symptom trajectories are informative of the development of young children at increased likelihood for autism spectrum disorder (ASD). METHODS: Developmental trajectories of early signs were examined in a cohort of siblings of children diagnosed with ASD (n = 502) from 6 to 18 months using the Autism Observation Scale for Infants (AOSI), and from 18 months to 5-7 years using the Autism Diagnostic Observation Schedule (ADOS). Diagnostic outcomes for ASD at age 3 confirmed diagnosis for 137 children. We further analyzed the conditional probability of a switch from a trajectory measured with the AOSI to a trajectory measured with the ADOS as well as predictors from age 6 months. RESULTS: We derived three early trajectories of behavioral signs ("Low," "Intermediate," and "Increasing") from 6 to 18 months using the AOSI. We then derived three similar, distinct trajectories for the evolution of symptom severity between 18 and 60-84 months of age (Low, Intermediate, Increasing) using the ADOS. Globally, the Low trajectory included children showing fewer ASD signs or symptoms and the Increasing trajectory included children showing more severe symptoms. We also found that most children in the Low AOSI trajectory stayed in the corresponding ADOS trajectory, whereas children in an Increasing AOSI trajectory tended to transition to an Intermediate or Increasing ADOS trajectory. Developmental measures taken at 6 months (early signs of ASD, Fine Motor, and Visual Reception skills) were predictive of trajectory membership. CONCLUSIONS: Results confirm substantial heterogeneity in the early emergence of ASD signs in children at increased likelihood for ASD. Moreover, we showed that the way those early behavioral signs emerge in infants is predictive of later symptomatology. Results yield clear clinical implications, supporting the need to repeatedly assess infants at increased likelihood for ASD as this can be highly indicative of their later development and behavior.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.011
GPT teacher head0.301
Teacher spread0.289 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2022
Admission routes2
Has abstractyes

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