Inhibitory control and psychopathology: A meta-analysis of studies using the stop signal task
Bibliographic record
Abstract
The Stop Signal Task (SST) is a measure that has been used widely to assess response inhibition. We conducted a meta-analysis of studies that examined SST performance in patients with various psychiatric disorders to determine the magnitude and generality of deficient inhibition. A five-item instrument was used to assess the methodological quality of studies. We found medium deficits in stop signal reaction time (SSRT), reflecting the speed of the inhibitory process, for attention-deficit hyperactivity disorder (ADHD) (g = 0.62), obsessive compulsive disorder (OCD) (g = 0.77) and schizophrenia (SCZ) (g = 0.69). SSRT was less impaired or normal for anxiety disorder (ANX), autism, major depressive disorder (MDD), oppositional defiant disorder/conduct disorder (ODD/CD), pathological gambling, reading disability (RD), substance dependence, and Tourette syndrome. We observed a large SSRT deficit for comorbid ADHD + RD (g = 0.82). SSRT was less than moderately impaired for ADHD + ANX and ADHD + ODD/CD. Study quality did not significantly affect SSRT across ADHD studies. This confirms an inhibition deficit in ADHD, and suggests that comorbid ADHD has different effects on inhibition in patients with ANX, ODD/CD, and RD. Further studies are needed to firmly establish an inhibition deficit in OCD and SCZ.
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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 | 0.014 | 0.026 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.036 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".