Candidate Risks Indicators for Bipolar Disorder: Early Intervention Opportunities in High-Risk Youth
Bibliographic record
Abstract
BACKGROUND: Psychiatric illnesses like bipolar disorder are increasingly understood to be neurodevelopmental disorders with clinical, psychological, and biological indicators recognizable long before the emergence of the full-blown syndromes. METHODS: This paper is a selective review of findings from studies of high-risk children of affected parents that inform the knowledge of illness risk and development markers of bipolar disorder. We specifically focus on candidate clinical, biological, and psychological risk indicators that could serve as targets for future early intervention and prevention studies. RESULTS: There is convergent evidence from prospective studies that bipolar disorder typically debuts as depressive episodes after puberty. In some high-risk children, sleep and anxiety disorders precede mood disorders by several years and reflect an increased vulnerability. An association between early exposure to adversity (eg, exposure to parental illness, neglect from mother) and increased risk of psychopathology may be mediated through increased stress reactivity evident at both behavioral and biological levels. Inter-related psychological processes including reward sensitivity, unstable self-esteem, rumination, and positive self-appraisal are risk factors for mood disorders. Disturbances in circadian rhythm and immune dysfunction are associated with mood disorders and may be vulnerability markers influenced by these other risk factors. CONCLUSIONS: There is accruing evidence of a number of measurable and potentially modifiable markers of vulnerability and developing illness in youth at familial risk for bipolar disorder. Longitudinal studies of multiple biological and psychological risk processes in high-risk offspring, both individually and together, will improve our understanding of illness onset and lead to the development of specific early interventions.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".