Early exposure to parental bipolar disorder and risk of mood disorder: the <scp><i>F</i></scp><i>lourish</i> <scp>C</scp>anadian prospective offspring cohort study
Bibliographic record
Abstract
AIM: Exposure to postnatal parental depression is associated with offspring mood disorder later in life; however, little is known about exposure to parental bipolar disorder (BD) and subsequent risk of psychopathology. The aim of this study was to determine the association between the duration, severity and timing of exposure to parental BD in early childhood and subsequent risk of mood disorder. METHODS: 189 offspring of a parent with BD completed annual assessments following Kiddie Schedule for Affective Disorders (KSADS) format semistructured interviews as part of an ongoing 16-year prospective cohort study. Clinical data from the affected parents were collected over the first decade of their offspring's life using SADS-L format semistructured interviews and coded using the Affective Morbidity Index (AMI). RESULTS: A longer duration of exposure to parental BD was associated with a 1.5-fold risk of any psychopathology (95% confidence interval (CI): 1.0-2.3) and a 2.5-fold increased risk of substance use disorders (95% CI: 1.2-5.3). Exposure during the first 2 years of life was significantly associated with the risk of mood disorder (hazard ratio (HR): 1.1, 95% CI: 1.0-1.2), whereas exposure later in childhood was not. CONCLUSIONS: The duration of exposure to active parental BD in childhood is an important risk factor for the subsequent development of mood and non-mood psychopathology risk in offspring. These findings emphasize the importance of effective treatment of parents with BD to help both themselves and their children, especially early in development.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".