Long-term Mother and Child Mental Health Effects of a Population-Based Infant Sleep Intervention: Cluster-Randomized, Controlled Trial
Bibliographic record
Abstract
OBJECTIVES: Maternal depression is an established risk for adverse child development. Two thirds of clinically significant depressive symptoms occur in mothers reporting an infant sleep problem. We aimed to determine the long-term effects of a behavioral intervention for infant sleep problems on maternal depression and parenting style, as well as on child mental health and sleep, when the children reached 2 years of age. METHODS: We conducted a cluster-randomized trial in well-child centers across 6 government areas of Melbourne, Australia. Participants included 328 mothers reporting an infant sleep problem at 7 months, drawn from a population sample (N = 739) recruited at 4 months. We compared the usual well-child care (n = 154) versus a brief behavior-modification program designed to improve infant sleep (n = 174) delivered by well-child nurses at ages 8 to 10 months and measured maternal depression symptoms (Edinburgh Postnatal Depression Scale); parenting practices (Parent Behavior Checklist); child mental health (Child Behavior Checklist); and maternal report of a sleep problem (yes or no). RESULTS: At 2 years, mothers in the intervention group were less likely than control mothers to report clinical depression symptoms: 15.4% vs 26.4% (Edinburgh Postnatal Depression Scale community cut point) and 4.2% vs 13.2% (Edinburgh Postnatal Depression Scale clinical cut point). Neither parenting style nor child mental health differed markedly between the intervention and control groups. A total of 27.3% of children in the intervention group versus 32.6% of control children had a sleep problem. CONCLUSIONS: The sleep intervention in infancy resulted in sustained positive effects on maternal depression symptoms and found no evidence of longer-term adverse effects on either mothers' parenting practices or children's mental health. This intervention demonstrated the capacity of a functioning primary care system to deliver effective, universally offered secondary prevention.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".