Perceptual decision making and metacognition in relation to obsessive-compulsive traits
Bibliographic record
Abstract
• Metacognitive performance is shown to be altered in OCD. • The higher score in OCD symptoms was related to better metacognitive performance. • It was also related to less behavioral adaptation to post-error conditions. • This disassociation may reflect the disassociation between OCD insight and compulsions. Metacognition is one of the cognitive functions that is shown to be altered in obsessive–compulsive disorder (OCD). Studies focusing on metacognitive efficiency have demonstrated disrupted precision of confidence estimates in OCD. However, the data of those studies may have been contaminated by the overestimation of metacognitive efficiency resulting from the use of the staircase method. We used a two-alternative forced-choice task in which difficulty was held constant within each block but varied across blocks throughout the task. No feedback was given to the participants. We collected data from 161 healthy university students with varying degrees of tendencies of OCD symptoms. Contrary to the previous literature, participants with a higher obsessive–compulsive tendency had higher metacognitive efficiency. Applying the drift–diffusion modeling approach to the first-order decisions of participants revealed that participants with a higher obsessive–compulsive tendency had lower efficiency in integrating perceptual information and less cautious thresholds. Finally, we investigated post-error slowing and found that participants with a higher obsessive–compulsive tendency exhibited limited adaptation of responses to errors and low confidence levels. Overall, our results suggest that having a higher obsessive–compulsive tendency is associated with sufficient metacognitive capacity but also with limited utilization of the metacognitive information for behavioral adaptation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".