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Record W4323851547 · doi:10.3390/diagnostics13061045

The Use of the Alberta Infant Motor Scale (AIMS) as a Diagnostic Scale for Infants with Autism

2023· article· en· W4323851547 on OpenAlexaboutno aff
Mooly Kochav-Lev, Odeya Bennett-Back, Meir Lotan, Chen Stein‐Zamir

Bibliographic record

VenueDiagnostics · 2023
Typearticle
Languageen
FieldMedicine
TopicInfant Development and Preterm Care
Canadian institutionsnot available
Fundersnot available
KeywordsScale (ratio)AutismPsychologyDevelopmental psychologyGeographyCartography

Abstract

fetched live from OpenAlex

Autism spectrum disorder (ASD) is a group of developmental disabilities presenting difficulties in social interaction and language and an increased occurrence of cognitive, sensory, and motor gaps. Early intervention has been reported to improve the function of children with ASD. However, motor screening for children with ASD is difficult, as there are no specific tools for identifying this specific population. This study reports the results of using the Alberta Infant Motor Scale (AIMS), which assesses gross infant motor skills from ages 0 to 18 months, as a screening tool for detecting motor developmental delay (MDD) in small children with ASD. METHODS: This retrospective cohort study included all children registered at one health care organization in Israel born between 2011 and 2017 (N = 240,299). Early childhood MDD was defined as having at least one recorded developmental physiotherapy (DPT) visit before the age of 2 years. Reasons for referral to DPT and the results of using AIMS as an appropriate tool for revealing developmental delays in infants with ASD are presented. RESULTS: ASD diagnosis was reported in 1821 children (prevalence rate 0.75%). Of those, 388 (odds ratio 4.1, 95% CI 3.6-4.6) children were referred to DPT. Children with ASD mostly received DPT for motor delays (46.19%), torticollis (19.52%), developmental delay (15.48%), and preterm birth (7.38%). The use of AIMS as an early detection tool suggests that more than 87% of children with ASD and MDD present with a developmental delay or risk for one when using this scale. CONCLUSIONS: The prevalence of ASD among children referred to DPT for MDD is higher than its prevalence within the general population. The most common reasons for a child with ASD to be referred for DPT services are MMDs. AIMS was found to be a sensitive tool to pinpoint relevant candidates for ASD screening among children treated in DPT. Possible effects of the study: The use of AIMS as a relevant assessment scale for this group of clients is recommended. Training DPTs in identifying initial ASD signs and developing their clinical reasoning abilities will increase the chance of implementing early intervention with this group of clients.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation 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 score0.214
Threshold uncertainty score0.814

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.019
GPT teacher head0.254
Teacher spread0.235 · 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 teacher head, 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

Citations3
Published2023
Admission routes1
Has abstractyes

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