M63. TRANSDIAGNOSTIC NEUROCOGNITIVE DEFICITS IN PSYCHIATRY: A REVIEW OF META-ANALYSES
Bibliographic record
Abstract
Abstract Background In recent decades, several meta-analyses have documented the severity of neurocognitive impairments in various domains and psychiatric disorders. There is also a growing body of literature on the common factors among psychiatric disorders (e.g., common psychological factors, neurobiological alterations or genetic variants). The first objective of this review was to investigate transdiagnostic neurocognitive impairments across several psychiatric disorders. The second objective was to document transdiagnostic neurocognitive impairments across the life span, to establish whether they are consistent across age. Methods A literature search was conducted in Pubmed, PsycINFO and Embase to identify all meta-analyses of neurocognitive deficits in psychiatry published prior to August, 2017. The following psychiatric disorders were considered: mood disorders, psychotic disorders, autism spectrum disorders, attention-deficit/hyperactivity disorder (ADHD), and anxiety disorders. The R-AMSTAR (Revised Assessment of Multiple Systematic Reviews) was used to assess methodological quality of all retrieved meta-analyses. The final selection included only the most rigorous meta-analyses. Results A total of 36 meta-analyses were included. They documented neurocognitive impairments in schizophrenia, autism spectrum disorder, ADHD, bipolar disorder, depression, obsessive-compulsive disorder, and posttraumatic stress disorder. Neurocognitive impairments were observed in the majority of psychiatric disorders, regardless of age group (childhood/adolescence, first episode, adulthood, elderly). Across all disorders, deficits in executive functions and in episodic memory were the most severe and the most frequently reported. Moreover, severe deficits in executive functions were frequently reported across age groups. Neurocognitive deficits were consistently more severe in schizophrenia compared to other psychiatric disorders, across all age groups. Discussion Neurocognitive impairments were observed in almost all disorders, in all age groups. Some neurocognitive impairments were more frequently reported across all disorders. Indeed, executive functions and episodic memory were severely impaired in almost every age group and psychiatric disorder considered in this review. Deficits in these two domains appear to be transdiagnostic and they remain relatively stable across the life span. Transdiagnostic factors could be key targets for transdiagnostic cognitive interventions in psychiatric populations. Neurobiological, neuropsychological, and genetic hypotheses of transdiagnostic neurocognitive impairments are discussed.
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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 | 0.021 | 0.057 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.039 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".