0485 Patterns of Nighttime Caregiving and Parent-Infant Sleep Outcomes: A Latent Class Analysis
Bibliographic record
Abstract
Abstract Introduction Parental-infant sleep and sleep problems are a significant source of stress for parents. Although greater paternal involvement in childcare is broadly associated with improved maternal and infant sleep outcomes, there is limited understanding of how different patterns of nighttime caregiving are distributed across families and their unique implications for parent-infant sleep. Identifying distinct caregiving arrangements and their relationships with sleep outcomes could provide critical insights into optimizing nighttime care practices for families. Methods We recruited 138 parent dyads who had an infant between 6 to 18 months of age to complete an online questionnaire about parental division of nighttime care, parental sleep, infant sleep, parental mental health, and relationship satisfaction. Results These nighttime caregiving patterns were identified as: Mother Exclusive, Mother Dominant, Mother More than Partner, Equal Contribution, and Partner More than Mother. Significant differences in parental sleep duration and quality and number of infant night wakes were observed across groups (p < 0.001). Patterns involving greater paternal involvement, such as Equal Contribution and Father Major, were associated with reduced parental fatigue and improved parental sleep quality. Conclusion A greater proportion of nighttime infant care is provided by mothers compared with partners. The findings suggest that greater paternal involvement is associated with better parental sleep quality. Longitudinal and experimental studies are needed to further investigate causal relationships between nighttime caregiving patterns and family sleep outcomes. Additionally, exploring barriers to greater paternal involvement and strategies to encourage equitable caregiving could inform interventions aimed at optimizing family functioning and well-being. Support (if any) University of Victoria Internal Research Grant
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".