Impaired test performance yet spared neurocognitive functioning in individuals with obsessive-compulsive disorder: the role of performance mediators
Bibliographic record
Abstract
INTRODUCTION: Although most studies report neurocognitive deficits in patients with obsessive-compulsive disorder (OCD), important exceptions exist, highlighting the possible role of mediators (e.g., poor motivation). This study investigated neurocognitive functioning and potential influences affecting performance in OCD. METHODS: Forty-three participants (13 OCD patients, 30 healthy controls) were assessed using a battery of neurocognitive tests. During the assessment, the examiner completed the Impact on Performance Scale (IPS) which measures variables that may impact neurocognitive performance. RESULTS: subscale. Performance differences across the two groups were attenuated to a non-significant small-to-medium effect when the IPS was entered as a covariate. A total of 34% of patients showed scores greater than one standard deviation below the mean compared to 9.63% in healthy individuals. Yet, when a conservative impairment criterion (≥2 standard deviations below the mean) was applied, less than 10% of patients displayed deficits. CONCLUSIONS: Neurocognitive impairment in OCD is likely exaggerated. In addition to considering important mediators researchers should report the percentage of participants displaying performance deficits rather than mean group differences alone; the latter obscures the high percentage of patients without impairment and thus may unduly foster stigma in this population.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".