The wide‐ranging life outcome correlates of a general psychopathology factor in adolescent psychopathology
Bibliographic record
Abstract
BACKGROUND: The structure of psychopathology has been much debated within the research literature. This study extends previous work by providing comparisons of the links between psychopathology and several life outcomes (temperamental, economic, social, psychological and health) using a three-correlated-factors model, a bifactor model, a revised-bifactor model and a higher-order model. METHODS: Data from a sample of Dutch adolescents were used (n = 2 230), and psychopathology factors were modelled using self-reported and parent-reported longitudinal data from youth across four assessments during adolescence, from ages 11 to 19. Outcome variables were assessed at age 22 using adolescent-reports and parent-reports and more objective measures (e.g. body mass index). RESULTS: While no measurement model was clearly superior, we found modest associations between the psychopathology factors and life outcomes. Importantly, after taking into account a general factor, the associations with life outcomes decreased for the residual parts of thought problems (across all domains) and internalizing problems (for temperamental and psychological outcomes), but not for externalizing problems, compared with the traditional three-correlated-factors model. Patterns were similar for adolescent-reported and parent-reported data. CONCLUSIONS: Findings suggest that a general factor is related to psychopathology and life outcomes in a meaningful way. Results are discussed in terms of individual differences in propensity to psychopathology and more broadly in light of recent developments concerning the structure of psychopathology. © 2019 The Authors Personality and Mental Health Published by John Wiley & Sons Ltd.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".