Neurophysiological Markers Related to Negative Self-referential Processing Differentiate Adolescent Suicide Ideators and Attempters
Bibliographic record
Abstract
Background: Adolescent suicide is a major public health concern, and presently, there is a limited understanding of the neurophysiological correlates of suicidal behaviors. Cognitive models of suicide indicate that negative views of the self are related to suicidal thoughts and behaviors, and this study investigated whether behavioral and neural correlates of self-referential processing differentiate suicide ideators from recent attempters. Methods: = 26) completed a self-referential encoding task while high-density electroencephalogram data were recorded. Behavioral analyses focused on negative processing bias (i.e., tendency to attribute negative information as being self-relevant) and drift rate (i.e., slope of reaction time and response type that corresponds to how quickly information is accumulated to make a decision about whether words are self-referent). Neurophysiological markers probing components reflecting early semantic monitoring (P2), engagement (early late positive potential), and effortful encoding (late late positive potential) also were tested. Results: Adolescent suicide ideators and recent suicide attempters reported comparable symptom severity, suicide ideation, and mental disorders. Although there were no behavioral differences, compared with suicide ideators, suicide attempters exhibited greater P2 amplitudes for negative versus positive words, which may reflect enhanced attention and arousal in response to negative self-referential stimuli. There were no group differences for the early or late late positive potential. Conclusions: Enhanced sensory arousal in response to negative stimuli-that is, attentional orienting to semantic, emotional, and self-relevant features-differentiates adolescent suicide attempters from ideators and thus may signal risk for suicidal behavior.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".