Decoupling Personality and Acute Psychiatric Symptoms in a Depressed Sample and a Community Sample
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The association between depression and neuroticism is complex; however, because of the difficulty in assessing neuroticism during mood episodes, the mechanisms underlying this relationship remain poorly understood. In this study, we sought to decompose neuroticism into finer grained elements that were uncorrelated with psychiatric symptoms and examine the incremental validity of those elements in explaining deficits in interpersonal functioning. A bifactor model with one general factor and six specific factors fit the data well in both a depressed ( N = 807) and a community ( N = 1,284) sample, and the specific factors were relatively independent of acute symptoms. Moreover, two specific factors (Angry Hostility and Self-Consciousness) accounted for incremental variance in interpersonal functioning problems in the community sample and a subgroup of depressed participants. The results demonstrate that neuroticism can be decomposed into components that are distinct from symptoms and incrementally associated with deficits in interpersonal functioning.
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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 | 0.009 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it