Interactions between neuroticism and stressful life events predict response to pharmacotherapy for major depression: A CAN‐BIND 1 report
Bibliographic record
Abstract
Exposure to stressful life events and individual differences in the personality trait neuroticism are important risk factors that interact to predict major depressive disorder (MDD). Less is known about their effect on treatment response in depression. Here, we examine whether stressful life events experienced prior to and during treatment interact with neuroticism to predict response to 16-week pharmacotherapy for MDD. Participants included 159 outpatients with MDD who were initially treated with 8 weeks of escitalopram. Those who responded to the initial treatment continued on escitalopram monotherapy, whereas non-responders received 8 weeks of adjunctive aripiprazole. Personality was assessed using the NEO-Five Factor Inventory, and stressful life events were assessed using the Life Events and Difficulties Schedule, a rigorous contextual interview that includes independent ratings of threatening life events. High baseline neuroticism was associated with a lower likelihood of response when patients experienced one or more negative life events before treatment. Secondary analyses indicated that this effect was specific to neuroticism, and not better accounted for by its self-criticism or negative affect facets. Our results suggest that assessing personality and stressful life events at baseline can help clinicians assess which patients will respond to antidepressant therapy and which may need treatment augmentation.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 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".