A Stitch in Time Saves Nine: Early Trajectories of Psychotic-Like Experiences (PLEs) and Cognitive Bias in Children from the Adolescent Brain Cognitive Development (ABCD) Study.
Bibliographic record
Abstract
Psychiatric disorders often emerge in late adolescence, but identifying childhood risk factors can promote earlier detection and prevent severe mental illness. Psychotic-like experiences (PLEs), a mild form of subclinical psychotic symptoms, are more common in childhood than adulthood. Their persistence may be crucial to understanding their clinical significance. Few studies have explored the link between persistent PLEs and mental health outcomes in adolescence. Cognitive biases, including attentional biases toward emotional stimuli, are linked to various mental health symptoms such as psychosis. This study investigates whether persistent, distressing PLEs co-occur with attentional bias and predict later psychopathology. We hypothesize that distressing PLEs at two or more timepoints correlate with attentional bias (measured at the one year and three year follow-ups) and predict higher symptoms of emotional dysfunction, psychosis, and externalizing psychopathology. Our sample, from the Adolescent Brain Cognitive Development study (Data Release 5.0), included 5740 participants (mean age = 9.5, SD = 0.5). Preliminary results showed no significant relationship between Emotional Stroop performance and distressing PLEs at year one and year three, as indicated by mean endorsed distress scores. Correlations did not differ for participants with a mean distress score above zero across a minimum of two assessments. These findings could suggest that persistent-distressing PLEs in childhood may predict a different domain of future symptoms than attentional biases toward emotional stimuli. Ongoing analyses will help determine the relevance of attentional biases and persistent distressing PLEs in predicting future symptoms of emotional dysfunction, externalizing, and psychosis.
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How this classification was reachedexpand
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 | 0.008 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".