Sleep patterns among preschool offspring of parents with and without psychopathology: Association with the development of psychopathology in childhood
Bibliographic record
Abstract
BACKGROUND: Disturbed sleep during early childhood predicts social-emotional problems. However, it is not known how various early childhood sleep phenotypes are associated with the development of childhood psychopathology, nor whether these relationships vary as a function of parental psychopathology. We identified sleep phenotypes among preschool youth; examined whether these phenotypes were associated with child and parent factors; and determined if early sleep phenotypes predicted later childhood psychopathology. METHODS: Using data from the Pittsburgh Bipolar Offspring study, parents with bipolar disorder (BD), non-BD psychopathology, and healthy controls reported about themselves and their offspring (n = 218) when their children were ages 2-5. Offspring and parents were interviewed directly approximately every 2 years from ages 6-18. Latent class analysis (LCA) identified latent sleep classes; we compared these classes on offspring demographics, parental sleep variables, and parental diagnoses. Kaplan-Meier survival models estimated hazard of developing any new-onset Axis-I disorders, as well as BD specifically, for each class. RESULTS: The optimal LCA solution featured four sleep classes, which we characterized as (1) good sleep, (2) wake after sleep onset problems, (3) bedtime problems (e.g., trouble falling asleep, resists going to bed), and (4) poor sleep generally. Good sleepers tended to have significantly less parental psychopathology than the other three classes. Risk of developing new-onset Axis-I disorders was highest among the poor sleep class and lowest among the good sleep class. CONCLUSIONS: Preschool sleep phenotypes are an important predictor of the development of psychopathology. Future work is needed to understand the biopsychosocial processes underlying these trajectories.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".