Associations of common mental disorders with personality traits over a 17-year period
Bibliographic record
Abstract
Changes in personality traits are not unusual, and common mental disorders (CMDs) may play a role. In a large population sample of 55,056 individuals, we examined associations of CMDs recorded in a national registry over 17 years (2004–2021) with self- and informant-rated Big Five personality traits (assessed once in 2021–2022). Besides comparing diagnosed and undiagnosed individuals, we considered the number and timing of CMD records. Those diagnosed with CMDs during the 17-year period differed from undiagnosed individuals by about 0.50 SD s higher neuroticism and slightly higher openness. For neuroticism, the difference was greater for those with more recent and numerous diagnoses, whereas for openness, the association did not depend on the number or timing of diagnoses. These findings suggest increased neuroticism in response to mental health issues, which may take over a decade to gradually return to baseline, and that less open people may be less likely to seek mental health help. We also found evidence of temporary decreases in extraversion and conscientiousness in response to depressive disorders. Findings were similar in self- and informant-ratings, suggesting they were not assessment artefacts. Our findings are consistent with small personality trait changes in response to mental disorders that gradually fade over several years.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".