The Early Natural History of Bipolar Disorder: What We Have Learned from Longitudinal High-Risk Research
Bibliographic record
Abstract
Longitudinal high-risk research has provided convergent evidence that major mood and psychotic disorders often develop from nonspecific antecedents in predisposed people over time and development. For example, bipolar disorder (BD) appears to evolve from nonspecific childhood antecedents, including anxiety and sleep problems, followed by adjustment and minor mood disturbances through early adolescence, culminating in major mood episodes in later adolescence and early adulthood. Therefore, the current cross-sectional symptom-based diagnostic approach requires rethinking: it considers neither the familial risk nor the longitudinal clinical course, with the consequence that the early stages of illness are not recognized as belonging to the end-stage disorder. Emerging evidence of identifiable clinical stages in the development of BD has tremendous potential for early identification, development of stage-specific treatments, and advancing our understanding of the pathophysiology associated with illness onset and progression. The clinical staging model also has direct implications for the optimal organization of clinical services for high-risk youth. Specifically, specialty psychiatric programs are needed that break down traditional institutional barriers to provide surveillance and timely comprehensive psychiatric assessment during the entire risk period, from childhood through to early adulthood. In this regard, the development of specialty psychiatric programs aiming to identify youth in the early stages of evolving psychosis are substantially ahead of services for youth in the early stages of evolving major mood disorders.
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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 | 0.058 | 0.114 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.006 | 0.015 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".