Perseveration is not Related with Functionality in Bipolar I Disorder with a Psychotic Mood Episode
Bibliographic record
Abstract
Aim: The aim of this study was to assess perseverative errors and responses as measured by the Wisconsin Card Sorting Test (WCST) in remitted bipolar I disorder patients having at least one previous psychotic mood episode and investigated the relationship between perseveration, areas of functionality, and clinical features. Methods: In the current study 48 remitted patients with bipolar I disorder diagnosed with DSM-IV criteria, and 45 socio-demographically matched healthy controls were consecutively enrolled. Socio-demographic and clinical characteristics form, Young Mania Rating Scale, Hamilton Depression Rating Scale, Bipolar Disorder Functioning Questionnaire (BDFQ), the Wisconsin Card Sorting Test (WCST), the DSM-IV Structured Clinical Interview for axis I Disorders, Montreal Cognitive Assessment Scale were used. Results: The distribution of age, gender and years of education between the patient and the control group was similar. In the patient group scores of perseverative errors in WCST was found to be higher than controls but there were no significant association between the total BDFQ scores of patients and the number of perseverative errors or responses. Conclusion: Perseverative errors and responses on the WCST was significantly higher in the remitted patients with bipolar I disorder who had at least one psychotic mood episode, when compared with the healthy controls, but this impairment did not have any impact on functioning.
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 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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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".