Early parent–child relationships and risk of mood disorder in a <scp>C</scp>anadian sample of offspring of a parent with bipolar disorder: findings from a 16‐year prospective cohort study
Bibliographic record
Abstract
AIM: Exposure to parental bipolar disorder (BD) early in life may increase the risk of developing a mood disorder. However, the impact of early parent-child relationships when a parent is affected and how this impacts an offspring's risk remains unclear. The primary objective of this study was to determine the association between parent-child relationships and risk of mood disorder in offspring of parents with BD and, secondly, to determine the interaction of temperament and life stress on this association. METHODS: Two hundred and thirty-three offspring completed annual clinical assessments following Kiddie Schedule for Affective Disorders (KSADS) format interviews as part of an ongoing Canadian prospective cohort study conducted from 1996 to 2013. Offspring completed measures of early adversity, life stress and temperament. Clinical data from the affected parents were prospectively collected over the first decade of their offspring's life using SADS format interviews. RESULTS: Higher perceived neglect from mother and offspring emotionality were significantly associated with the hazard of mood disorder (hazard ratio (HR): 1.1, 95% confidence interval (CI): 1.0-1.2 and HR: 1.7, 95% CI: 1.0-3.1, respectively). Duration of exposure to parental BD significantly interacted with offspring emotionality to predict mood disorder (P = 0.01). Further, perceived neglect from mother was associated with offspring high emotionality (P = 0.02). CONCLUSIONS: Neglect from mother is a significant early predictor of mood disorder in offspring at familial risk for BD and may increase emotional sensitivity. Psychosocial support and interventions for high-risk families could be beneficial in reducing early adversity, maternal neglect and the risk of subsequent mood disorders in offspring.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".