A thorough investigation of the bifactor model of psychopathology in a representative birth cohort: Testing internal and predictive validity to inform models of comorbidity.
Why this work is in the frame
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Bibliographic record
Abstract
This study used symptom dimensions reflecting DSM-V internalizing, externalizing, eating disorders, and substance use (SU) and related problems to thoroughly investigate the structure of psychopathology in mid-adolescence (15 and 17 years, N = 1,515, 52% female). Compared to other hierarchical configurations (unidimensional, correlated factors, or higher-order model), a bifactor model of psychopathology wherein all first-order symptom dimensions loaded onto a second-order general psychopathology factor (P factor) and one of three, second-order specific internalizing, externalizing, or SU factors, best captured the structure of the psychopathology in mid-adolescence. This bifactor model was then used to predict several distinct mental health disorders and alcohol use disorder (AUD) at 20 years, via a structural equation model (SEM). The P factor (bifactor model) was associated with all but one outcome (suicidal ideation without an attempt), at 20 years. Controlling for the P factor, there were no additional, positive, temporal cross-associations (i.e., between mental health (mid-adolescence) and AUD at 20 years, or between SU (mid-adolescence) and mental health problems at 20 years). These results are bolstered by findings from a well-fitting correlated factors model. Namely, when mid-adolescent psychopathology was modeled using an adjusted correlated factors model, associations with outcomes at 20 years were largely masked, with no significant partial, temporal cross-associations. Thus, collectively, findings indicate that comorbidity between SU and mental health in youth may be largely attributable to an underlying liability to experience both problems (i.e., P factor). Ultimately, results support targeting the common liability to psychopathology in the prevention of later mental health problems and AUD. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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