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Record W53394325

Navigating the autism diagnostic system: Implications for earlier identification.

2005· article· en· W53394325 on OpenAlexaboutno aff
Alison Ann. Spadafora

Bibliographic record

VenueScholarship at UWindsor (University of Windsor) · 2005
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsnot available
Fundersnot available
KeywordsAutismIdentification (biology)PsychologyDevelopmental psychology
DOInot available

Abstract

fetched live from OpenAlex

Autism Spectrum Disorders are characterized by repetitive, stereotyped behaviours and impairments in communication and socialization. The present research examined parents' experiences during the course of obtaining an autism diagnosis for their children. Participants, who resided throughout Ontario, were recruited through the Autism Society of Ontario and the Summit Centre Preschool for Children with Autism. The questionnaire was designed for the present research and focused on parents' initial concerns about their children's development and attempts at seeking professional help. By parent report, the children were diagnosed with Autistic Disorder (N = 52), Asperger's Disorder (N = 7) and PDD-NOS (N = 21). Results indicate that in 75% of cases, symptoms of autism were first identified by children's mothers at 19.71 months of age on average. The average amount of time that had passed between the age at which parents initially became concerned about their children's development and the age at the first appointment with a professional to address their concerns was 10.38 months. For the entire sample, the average age at diagnosis was 4.29 years of age and results of the research suggest that children are being diagnosed at younger ages over time. Child demographic variables (i.e., gender, ethnicity, birth order and socioeconomic status) did not significantly impact age at initial concern, the help-seeking delay and age at diagnosis. Parents believed that increasing medical doctors' knowledge about autism, decreasing the amount of time on waiting lists and having more professionals available to assess and diagnose autism would make the autism diagnostic system more efficient. Implications of the results for facilitating earlier diagnosis are discussed.Dept. of Psychology. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2005 .S665. Source: Masters Abstracts International, Volume: 44-03, page: 1517. Thesis (M.A.)--University of Windsor (Canada), 2005.

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)0.009
metaresearch head score (Gemma)0.065
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.314
Threshold uncertainty score0.624

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.065
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0030.002
Scholarly communication0.0030.007
Open science0.0030.003
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0100.001

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 head0.039
GPT teacher head0.297
Teacher spread0.258 · 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 designQualitative
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

Citations1
Published2005
Admission routes1
Has abstractyes

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