Family dysfunction, stressful life events, and mental health problems across development in the offspring of parents with an affective disorder
Bibliographic record
Abstract
BACKGROUND: Offspring of parents with affective disorders (OAD) are at risk of developing a wide range of mental disorders. Deficits in the rearing environment and high levels of stress are well-known risk factors for negative outcomes in OAD. Building on prior research, we aim to examine the longitudinal relationships between family dysfunction, stressful life events, and mental health in OAD and control offspring of parents with no affective disorder. In the present study, we hypothesized that high levels of family dysfunction would be associated with more internalizing and externalizing problems across time in OAD than in controls, and that family dysfunction would mediate the relationship between stressful life events in adolescence and poor mental health in adulthood, particularly in OAD. METHODS: = 11.1 years, SD = 0.6, at baseline) and their parents completed measures across six time points, spanning 15 years. Mental health, family dysfunction, and stressful life events were assessed with the Youth and Adult Self-Report, Family Assessment Device, and an in-house measure, respectively. RESULTS: Multi-group structured equation modeling revealed that family dysfunction was linked to internalizing and externalizing problems in OAD, but not controls, across time. Risk status did not moderate family dysfunction's mediation of the relationship between stressful life events and negative outcomes in adulthood. CONCLUSIONS: OAD show high sensitivity to dysfunction in the rearing environment across childhood and adolescence, which supports the use of family based interventions to prevent the development of mental disorders in high-risk youth.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".