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Record W4412846800 · doi:10.1177/00332941251363887

Do Autistic Traits Predict Obsessive-Compulsive Symptoms? A Community-Based Study

2025· article· en· W4412846800 on OpenAlexaboutno aff
Selim Tümkaya, Bengü Yücens, Aslıhan Özdemir Yaşaran, Volkan Akmehmetoglu, Filiz Karadağ

Bibliographic record

VenuePsychological Reports · 2025
Typearticle
Languageen
FieldPsychology
TopicObsessive-Compulsive Spectrum Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsAutistic traitsPsychologyAnxietyAutismBeck Depression InventoryClinical psychologyPopulationBeck Anxiety InventoryPsychiatryDepression (economics)Autism spectrum disorderMedicine

Abstract

fetched live from OpenAlex

Obsessive Compulsive Disorder (OCD) and Autism Spectrum Disorder (ASD) have similar characteristics. People with one of these disorders are more likely to meet the diagnosis of the other disorder than the general population. This study mainly investigated whether autistic traits predicted obsessive-compulsive symptom subtypes after controlling for some demographic features and clinical variables. This study included 460 university students from two universities and their family members. The subjects were asked to complete a sociodemographic and clinical data form, the Vancouver Obsessional Compulsive Inventory (VOCI), the Autism-Spectrum Quotient (AQ), the Beck Depression Inventory (BDI) and the Beck Anxiety Inventory (BAI). The relationship between autistic symptoms and obsessive-compulsive symptoms was assessed using linear regression analysis, controlling for age, sex, depression, anxiety scores, and a history of frequent childhood upper respiratory tract infections (URTIs). The AQ attention-switching score was associated with hoarding ( β = 0.135, p = .002), just-right ( β = 0.087, p = .026), indecisiveness ( β = 0.101, p = .006), and total VOCI ( β = 0.080, p = .038) score. AQ subscale scores other than attention-switching were not associated with VOCI scores. Age was negatively associated with obsessions ( β = −0.133, p = .001), just-right ( β = −0.129, p = .002), indecisiveness ( β = −0.214, p < .001), and total VOCI score ( β = −0.109, p = .006). BDI and BAI total scores were positively associated with all VOCI scores (all β in between 0.114 and 0.318, all p in between 0.033 and <0.001). Checking ( p = .025), just-right ( p = .038), and total VOCI scores ( p = .046) were significantly higher in the group with a history of frequent childhood URTIs compared to the group without. Individuals with OCD symptoms may exhibit attention-switching deficits similar to those of individuals with ASD symptoms, suggesting a subgroup of OCD that shares features with ASD. Attention-switching deficits should be further investigated in terms of the relationship between ASD and OCD.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.129
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.029
GPT teacher head0.364
Teacher spread0.335 · 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.

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

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