Anhedonia and cognitive function in adults with MDD: results from the International Mood Disorders Collaborative Project
Bibliographic record
Abstract
BACKGROUND: Cognitive dysfunction is common in major depressive disorder (MDD) and a critical determinant of health outcome. Anhedonia is a criterion item toward the diagnosis of a major depressive episode (MDE) and a well-characterized domain in MDD. We sought to determine the extent to which variability in self-reported cognitive function correlates with anhedonia. METHOD: A post hoc analysis was conducted using data from (N=369) participants with a Diagnostic and Statistical Manual of Mental Disorders, 4th Edition, Text Revision (DSM-IV-TR)-defined diagnosis of MDD who were enrolled in the International Mood Disorders Collaborative Project (IMDCP) between January 2008 and July 2013. The IMDCP is a collaborative research platform at the Mood Disorders Psychopharmacology Unit, University of Toronto, Toronto, Canada, and the Cleveland Clinic, Cleveland, Ohio. Measures of cognitive function, anhedonia, and depression severity were analyzed using linear regression equations. RESULTS: A total of 369 adults with DSM-IV-TR-defined MDD were included in this analysis. Self-rated cognitive impairment [ie, as measured by the Adult ADHD Self-Report Scale (ASRS)] was significantly correlated with a proxy measure of anhedonia (r=0.131, p=0.012). Moreover, total depression symptom severity, as measured by the total Montgomery-Åsberg Depression Rating Scale (MADRS) score, was also significantly correlated with self-rated measures of cognitive dysfunction (r=0.147, p=0.005). The association between anhedonia and self-rated cognitive dysfunction remained significant after adjusting for illness severity (r=0.162, p=0.007). CONCLUSIONS: These preliminary results provide empirical data for the testable hypothesis that anhedonia and self-reported cognitive function in MDD are correlated yet dissociable domains. The foregoing observation supports the hypothesis of overlapping yet discrete neurobiological substrates for these domains.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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 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".