Prevalence and Correlates of Childhood-onset Bipolar Disorder among Adolescents
Bibliographic record
Abstract
Abstract Background Early-onset Bipolar Disorder (BD) is associated with a more severe illness as well as a number of clinical factors amongst adults. Early-onset can be categorised as childhood- (age < 13) or adolescent- (age ≥ 13) onset, with the two displaying different clinical profiles. However, among adolescents, there is a paucity of research comparing the both prevalence and clinical profiles of childhood-onset to adolescent-onset BD. We set out to examine potential differences in demographic, clinical, and familial characteristics amongst adolescents with childhood- vs. adolescent-onset BD. Methods The study included 195 adolescents with BD, ages 14–18 years Age of onset was determined retrospectively by self-report. Participants completed the semi-structured K-SADS-PL diagnostic interviews along with self-reported dimensional scales. Analyses examined between-group differences in demographic, clinical, and familial variables, as well as individual manic and depressive symptom severity for most severe past episodes. Variables that were associated with age of onset at p < 0.1 in univariate analyses were evaluated in a logistic regression model. Results Approximately one-fifth of participants had childhood-onset BD (n = 35; 17.9%). A number of clinical and demographic factors were significantly associated with childhood-onset BD. However, there were no significant differences in individual depression and mania symptom severity. In multivariate analyses, the variables most strongly associated with childhood-onset were police contact, stimulant treatment, and family history of suicidal ideation (positively associated), as well as smoking and psychiatric hospitalization (negatively associated). Conclusions In this large clinical sample of adolescents with BD, one-fifth reported childhood-onset BD. Correlates of childhood-onset generally aligned with those observed in the literature, the majority of which were age-related. The lack of differences in individual manic and depressive symptom severity were particularly noteworthy. Future research is warranted to better understand the genetic and environmental implications of high familial loading of psychopathology associated with childhood-onset, and to integrate age-related treatment and prevention strategies.
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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 | 0.001 | 0.001 |
| 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".