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), such as anxiety, depression, and alcohol use disorder, may play a role. In a large population sample of 55,056 individuals, we examined the associations of CMDs recorded in a national registry over 17 years with self- and informant-rated Big Five personality traits. Besides comparing diagnosed and undiagnosed individuals, we considered the number and timing of the CMD records. Those diagnosed with a CMD during the 17-year period differed from undiagnosed individuals by about 0.50 SDs higher neuroticism and slightly higher openness. For neuroticism, the difference from undiagnosed individuals was greater for those with more recent and more numerous diagnoses, whereas for openness, the association did not depend on the number or timing of diagnoses. These findings are consistent with increased neuroticism in response to mental health issues, which may take more than a decade to gradually return to the baseline, and with less open people being less likely to seek help for mental health issues. We also found evidence consistent with temporary decreases in extraversion and conscientiousness in response to depressive disorder. The findings were consistent across self- and informant-ratings, suggesting they were not assessment artefacts. This study, the largest to date, suggests that some personality trait changes in response to mental disorders may persist for at least a decade, much longer than previously thought.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".