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Record W4402327277 · doi:10.1101/2024.09.06.24313128

A Psychometric Examination of the Dimensional Obsessive Compulsive Scale in a Treatment-Seeking Youth Sample

2024· preprint· en· W4402327277 on OpenAlexaff
Nicholas R. Farrell, Catherine W. MacDonald, Mia Nuñez, Andreas Rhode, Nicholas Lume, Patrick B. McGrath, Marina Baskova, E.L. Wilson, Jonathan S. Abramowitz, Jamie D. Feusner

Bibliographic record

VenuemedRxiv · 2024
Typepreprint
Languageen
FieldPsychology
TopicObsessive-Compulsive Spectrum Disorders
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsSample (material)PsychologyScale (ratio)Obsessive compulsiveClinical psychologyGeography

Abstract

fetched live from OpenAlex

Abstract The Dimensional Obsessive Compulsive Scale (DOCS) was developed to address several limitations of existing self-report measures of obsessive compulsive disorder (OCD) symptoms, and has been found to be a psychometrically sound method of assessing OCD symptoms in adults. However, to date, the psychometric performance of the DOCS has not been studied in a youth sample. The present study addressed this gap in the literature by examining the psychometric properties of the DOCS in a large sample (n=182) of treatment-seeking youth diagnosed with OCD. Results indicated that the DOCS showed good convergent validity with a youth OCD assessment scale, as well as similar sensitivity to the effects of treatment-related change in symptom severity. The DOCS also maintained its original four-factor structure in the youth sample, similar to findings in adults, supporting the consistency of the four subscales included. Overall, the DOCS appears to represent a promising method for assessing OCD symptom severity and response to treatment of OCD in 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 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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.077
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.032
GPT teacher head0.307
Teacher spread0.274 · 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

Citations4
Published2024
Admission routes1
Has abstractyes

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