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Record W4415803890 · doi:10.1017/s1092852925100679

Moving beyond symptom subtypes: testing a common dimension of lifetime OCD symptoms

2025· article· en· W4415803890 on OpenAlexaff
Abel S. Mathew, Sarah L. Garnaat, David R. Strong, Nicole McLaughlin, Kathleen D. Askland, O. Joseph Bienvenu, Janice Krasnow, Marco A. Grados, Bernadette Cullen, Fernando S. Goes, Steven A. Rasmussen, James A. Knowles, James T. McCracken, John Piacentini, Daniel Geller, S. Evelyn Stewart, Mark A. Riddle, Paul S. Nestadt, Gerald Nestadt, Jack Samuels, Benjamin D. Greenberg

Bibliographic record

VenueCNS Spectrums · 2025
Typearticle
Languageen
FieldPsychology
TopicObsessive-Compulsive Spectrum Disorders
Canadian institutionsMcMaster UniversityBC Mental Health & Substance Use ServicesUniversity of British ColumbiaPricewaterhouseCoopers (Canada)
Fundersnot available
KeywordsDimension (graph theory)Multilevel modelMEDLINEBayesian probabilityComorbidityPsychometrics

Abstract

fetched live from OpenAlex

INTRODUCTION: Obsessive-compulsive disorder (OCD) is a neuropsychiatric disorder characterized by recurrent intrusive thoughts and ritualized behaviors, often aimed at reducing distress. OCD is heterogeneous in its presentation and many patients with OCD experience a variety of different symptoms throughout their course of illness. Efforts to understand symptom domains in OCD have typically identified three to five symptom domains, such as the domains of doubt/checking, contamination, superstitions/rituals, symmetry/hoarding, and taboo thoughts. Recent studies in the genetics of OCD have suggested a common OCD dimension may provide additional information above and beyond the previously identified symptom domains. Thus, we sought to test a hierarchical model of lifetime OCD symptoms and evaluate the utility of the inclusion of a common OCD dimension. METHODS: Participants included 999 individuals participating in the OCD Collaborative Genetics Study (OCGS) and an additional 2363 individuals participating in the OCD Genetic Association Study (OCGAS). We evaluated unidimensional, 5-factor, and hierarchical models of lifetime OCD symptom presentation using confirmatory factor analysis. RESULTS: Results suggested that the hierarchical model best fit the data. Further evaluation of these models using a Bayesian testlet response model showed that lifetime presence of specific OCD symptoms was differentially associated with lifetime OCD severity. Moreover, symptoms associated with greater lifetime severity were generally reported less frequently than symptoms present at lower levels of lifetime severity. Implications of these findings and future directions are discussed.

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)0.008
metaresearch head score (Gemma)0.023
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 score0.012
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.023
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
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 head0.008
GPT teacher head0.277
Teacher spread0.269 · 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

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