Findings from bipolar offspring studies: methodology matters
Bibliographic record
Abstract
AIM: High-risk studies provide the opportunity to describe the early natural history of bipolar disorder (BD); however, findings have varied substantially. In this review, we compare different methods of ascertainment and assessment, and their impact on study findings. METHODS: Through a literature search, we identified 11 high-risk studies meeting inclusion criteria for this review. Studies included were those that focused on lifetime psychopathology in the offspring as the main outcome and provided adequate information on the methods of family ascertainment, as well as on parent and offspring assessment. We compared and contrasted psychopathological outcomes in the offspring among the studies using different methods. RESULTS: High-risk studies that identified affected parents through their involvement in neurobiological research and confirmed diagnosis in the parent and offspring through best estimate procedures tended to report lower rates of co-morbidity in the proband parent, lower rates of psychopathology in the non-proband parent, lower rates of attention deficit hyperactivity disorder and externalizing disorders, and older ages of onset of major mood disorders in the offspring compared with studies that identified affected parents through self-referral and confirmed diagnosis in the parent and offspring through structured research interviews. Studies that identified severely ill parents and used semi-structured assessments tended to have an intermediate position in terms of outcomes. CONCLUSIONS: This review indicates that different methods of family ascertainment and of assessment of parent and offspring impact the findings pertaining to lifetime psychopathology and clinical course of BD in high-risk studies. The implications of this finding for mapping the natural history of BD are discussed.
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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 | 0.151 | 0.382 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.009 | 0.014 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".