MétaCan
Menu
← Back to cohort
Record W7082160976 · doi:10.11575/prism/49886

The Impact of Diagnostic Timing on Healthcare Use: Statistical Trends Among Early- and Late-diagnosed Autistic Youth

2025· other· en· W7082160976 on OpenAlexaboutno aff

Bibliographic record

VenueOpen MIND · 2025
Typeother
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsnot available
Fundersnot available
KeywordsAutismHealth careReferralMental healthcareMental healthHealth professionalsDevelopmental disorderCognition

Abstract

fetched live from OpenAlex

Background: Autism is a neurodevelopmental condition that now affects 1 in 50 Canadian children, with prevalence rising over the past 20 years. A disparity continues to exist in the ratio of males to females who have an autism diagnosis, with rates as high as four autistic males for every one autistic female. There is also an increasing trend of children and adolescents receiving their autism diagnosis much later in childhood and into adolescence, most often in youth without cognitive or developmental delays and mild autistic traits. A late autism diagnosis (i.e., after 6 years of age) is often associated with multiple co-occurring mental health challenges such as depression, anxiety, non-suicidal self-injury, and suicidal thoughts leading to a higher likelihood of accessing healthcare resources than non-autistic peers. Healthcare administration databases allow for researchers to determine trends in healthcare service usage, and while there is some literature on how much autistic children and adolescents are accessing healthcare services, there has been almost no exploration into the healthcare utilization of late diagnosed autistic people. This is the first study to determine and compare the number of encounters with the healthcare system between early and late diagnosed autistic children and adolescents (herein, youth), and characterize the referral reasons for these encounters. Objectives: The present study extended previous literature on healthcare service access in autistic children and adolescents and: (1) examined if late diagnosed autistic youth access more healthcare services than early diagnosed autistic youth; and (2) investigated if late diagnosed autistic youth have more distinct referral reasons compared to early diagnosed autistic youth. Methods: Participants were identified from a larger file review study; 147 children and adolescents diagnosed with autism spectrum disorder (herein autism) at the Alberta Health Services (AHS) Autism Diagnostic Clinic were included in the study (median age at assessment = 5.0 years, 24.49% female). Records from two administrative databases for participants were obtained: Practitioner Claims and the National Ambulatory Care Reporting System (NACRS), which include information on physician visits, emergency department visits, same-day surgery, visits to outpatient clinics, mental health services, urgent care, and public health clinics. A series of logistic regression analyses were conducted to determine if early versus late diagnosis predicted frequency of healthcare encounters, as well as the number of unique reasons for accessing services, while controlling for age. Sex was also added in the logistic regressions to determine if sex moderated either of these associations. Results: Sample sizes for diagnostic timing groups (early vs. late diagnosed) were comparable (53.74% early diagnosed), as well as a comparable sex distribution (25.0% female in late diagnosed group, 21.5% female in early diagnosed group). When controlling for age of first encounter, a late diagnosis predicted 59% more psychiatric visits than the early diagnosed group (β = 0.47, p = .0243). However, when sex was added as a moderator, this effect only approached significance (p = .066). Diagnostic timing and sex were not significant predictors in the number of visits to the emergency department, outpatient clinics, or overall physician claims. In looking at reasons for health care encounters, diagnostic timing and sex were not significant predictors of the number of distinct reasons for accessing healthcare services. Conclusions: This study is the first of its kind to examine the impact of timing of receiving an autism diagnosis and sex on the frequency of healthcare visits, as well as the unique reasons for accessing healthcare services. Findings highlight that late diagnosed autistic youth accessed a significantly higher number of psychiatric services; however, this effect diminished after adding sex as a moderator into the analysis. Findings from this study can inform post-diagnosis supports as well as training for medical professionals to better support late diagnosed autistic youth.

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)0.002
metaresearch head score (Gemma)0.007
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 score0.097
Threshold uncertainty score0.192

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.002
Bibliometrics0.0030.004
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.044
GPT teacher head0.322
Teacher spread0.279 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueOpen MIND→Same topicGeochemistry and Geologic Mapping→French-language works237,207→