0842 Parent Engagement with Digital Sleep Health Interventions for Young Children: A Global Scoping Review
Bibliographic record
Abstract
Abstract Introduction It is widely recognized that young children may experience sleep problems early in life that affect child development outcomes. Digital technology offers an accessible platform to reach and engage families of young children with sleep health solutions early in life.Our global scoping review aimed to investigate the use of digital technology as a resource to facilitate parental interventions aimed at enhancing sleep health among children in early childhood (3 –8 years old). Methods We performed a scoping review of peer-reviewed articles published from inception to 2023 for the following databases: PubMed, Embase, Web of Science including FSTA and Scielo, MEDLINE, Cochrane Library, Engineering Village, CINAHL, APA PsycInfo, Global Health and citation searching. In conjunction with the authors, two librarians conducted an extensive literature search, and the strategies can be found at [osf.io/74hba]. Our methodological approach encompassed a systematic review of key terms related to sleep, communication, parental involvement, and internet-based intervention. Inclusion criteria included intervention studies with parents of children 3-8 years old via digital communications (e.g. social media, telehealth, websites, mobile apps, wearable devices) to address sleep health in their child. Exclusion criteria included platforms unrelated to sleep, studies that digitally recruited participants but did not use a digital platform, studies with children outside the target age, or protocol studies. Review Registration: https://doi.org/10.17605/OSF.IO/TNFY2 Results Four articles met the final inclusion criteria. A final sample size of 194 parent-child dyads across Australia, Canada, the Netherlands, and the United States were enrolled. Mean child age was 5 years old and mean parent age was 37. Sleep health behavior outcomes in children addressed by digital mobile health solutions included bedtime resistance, night wakings, sleep onset, sleep duration, obstructive sleep apnea, sleep latency and independent sleep in child’s own bed. Sleep health outcomes also included positive improvements in parent sleep health education. Conclusion Parent engagement with child sleep health interventions yielded favorable outcomes, enhancing the overall sleep health of children. More research is needed to understand tailored interventions for sustained sleep health improvements in child sleep. Support (if any) K01HL169419-01
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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 | 0.016 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.015 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| 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".