Dissociating self-reported cognitive complaint from clinical insight in schizophrenia
Bibliographic record
Abstract
Whereas new pharmacological treatments are developed for cognitive impairments in schizophrenia, self-assessment of cognitive dysfunctioning besides their objective validity could be of interest in evaluating patients' motivation to engage in rehabilitation program. Nevertheless insight into symptoms is severely impaired in schizophrenia and is negatively linked with poor compliance. But it is yet unknown if patients with poor insight into their symptoms could have some insight into their cognitive impairments. The aim of this study was to explore the relationships existing between the cognitive complaint and the level of awareness of the disease in patients with schizophrenia. A total of 101 patients with DSM-IV schizophrenia or schizoaffective disorder and 60 control participants were recruited. Insight was assessed using the Scale to assess Unawareness of Mental Disorder (SUMD) and cognitive complaint intensity was assessed with the Scale to Investigate Cognition in Schizophrenia (SSTICS). Participants with schizophrenia displayed the same level of cognitive complaint when compared to healthy controls. Strong correlations were observed between SSTICS total score and duration of illness, levels of depression and state anxiety. Patients with a good insight into the therapeutic effects achieved with medication expressed a more important cognitive complaint. No correlations were found between the four others SUMD insight dimensions and total SSTICS score. The partial overlap of insight into illness and cognitive complaint suggests that insight is modular in schizophrenia. Assessment of cognitive complaint and awareness of illness need to be assessed before engagement in rehabilitation program.
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".