Cognitive Dysfunction in Major Depressive Disorder: Assessment, Impact, and Management
Bibliographic record
Abstract
Cognitive dysfunction is increasingly being recognized as an important clinical dimension in major depressive disorder. This review summarizes the existing data on the epidemiology, assessment, and treatment of cognitive dysfunction among nonelderly adults with the disorder. Overall, cognitive dysfunction is prevalent, persists through periods of symptom remission, and may be independently associated with functional outcomes. However, although the evidence increasingly suggests that clinicians should be heedful of their patients' cognitive functioning, there is as yet no consensus on how best to monitor cognition clinically. In addition, although most studies have reported improved cognition with antidepressant medications, psychotherapy, and neuromodulation, the clinical significance of these improvements is unclear, and high-level evidence to guide decision making is limited. Nonetheless, given the important functional implications, clinicians should assess and monitor cognition and optimize both medication and psychological treatments to mitigate cognitive dysfunction among patients with major depressive disorder.
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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 | 0.001 | 0.000 |
| 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 | 0.001 |
| 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".