Cognitive Dysfunction in Major Depressive Disorder: A State-of-the-Art Clinical Review
Bibliographic record
Abstract
Major depressive disorder (MDD) is a prevalent and recurring mental disorder often associated with high rates of non-recovery and substantial consequences on psychosocial outcome. Cognitive impairment is one of the most frequent residual symptoms of MDD. The persistence of cognitive impairment even in remitted phases of the disorder, notably in the domains of executive function and attention, suggests that it may serve as a mediational nexus between MDD and poor functional outcome, accounting for occupational and relational difficulties regardless of clinical improvement on depressive symptoms. The critical impact of cognitive deficits on psychosocial dysfunction invites clinicians to regularly screen and assess cognition across multiple domains, taking into account also clinical correlates of cognitive dysfunction in MDD. Despite the availability of several instruments for the screening and assessment of cognitive dysfunction, the lack of consensus guiding the choice of appropriate instruments increases the likelihood to underestimate cognitive dysfunction in MDD in clinical settings. On the other hand, the unsatisfactory effect of most antidepressant treatments on cognitive deficits for many individuals with MDD calls for the development of genuinely novel therapeutic agents with potential to target cognitive dysfunction. Notwithstanding the necessity of further investigations, this review indicates that neuropsychological deficits (e.g., impaired executive functions) are stable markers of MDD and underscores the need for the development of integrative and multi-modal strategies for the prevention and treatment of neuropsychological impairments in MDD.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".