Executive functions and psychopathology: A transdiagnostic network analysis
Bibliographic record
Abstract
Mental health research is shifting toward dimensional, transdiagnostic frameworks, yet the role of executive functions (EFs) across psychopathological domains remains unclear. In this study, we examined transdiagnostic associations and potential directional pathways linking EFs with psychopathology in a large sample of preadolescents (N = 9,119) from the Adolescent Brain Cognitive Development (ABCD) study. We employed a Gaussian graphical model (GGM) to estimate partial correlations and a directed acyclic graph (DAG) to infer potential directional influences between EFs and psychopathology. Modest associations were observed among the EFs and psychopathology. Working memory emerged as a central node, showing positive associations with attention problems, social problems, and rule-breaking behavior, and negative associations with anxious/depressed and somatic complaints. These results were mirrored in the DAG, which identified working memory and attention problems as key converging hubs. Sex-stratified analyses revealed notable differences in network structure. Our findings reveal a core transdiagnostic role for working memory in preadolescent psychopathology.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".