Associating Internalizing and Externalizing Symptom Features With the Personality Inventory for DSM-5 Brief Form (PID-5-BF) in a Large Community Sample
Bibliographic record
Abstract
= 661 Canadian adults in the community. Depression, anxiety, and perceived stress measures were obtained, as were indices of alcohol and cannabis use. Symptoms of depression and perceived stress were associated with all PID-5-BF dimensions, except for antagonism. Anxiety symptoms were associated with negative affectivity (NA) and, to a lesser extent, psychoticism. A younger age and female sex were related to higher depression and stress scores. In contrast to the models assessing depressive, anxiety and stress symptoms, in which NA was the strongest contributor, no significant contribution of internalizing traits (i.e., PID-5-BF NA) on substance use outcomes was found when externalizing traits were included in the models. Specifically, binge drinking and cannabis use were associated with higher disinhibition scores and lower psychoticism scores. Regression models were substantially weaker for substance use than for the mood and stress symptoms. Younger individuals used more cannabis and males engaged in more binge drinking. These findings largely confirm PID-5-BF's construct validity, and indicate that various indices of wellbeing (not necessarily personality-associated measures) are associated with personality traits, as measured with the brief from of PID-5-BF.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".