Influence of Experiences From Birth to 5 Years of Age on Emotional and Psychological Health

Christakis, Dimitri A.; Rivara, Frederick P.

doi:10.1001/archpediatrics.2010.67

Cited by 2 publications

(1 citation statement)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Early life experiences play a critical role in children's development, influencing health outcomes, educational achievements and well-being (Christakis & Rivara, 2010;Merrick et al, 2019). The developmental and epigenetic effects of these early childhood experiences appear to influence brain functions, thereby generating long-term effects on the individual's welfare (Panksepp, 2013).…”

Section: Introductionmentioning

confidence: 99%

Economic evaluation methods used in home‐visiting interventions: A systematic search and review

Bailey

Skouteris

Morris

et al. 2021

Health Soc Care Community

View full text Add to dashboard Cite

Home-visiting interventions are used to improve outcomes for families experiencing disadvantage. As scarce resources must be allocated carefully, appropriate methods are required to provide accurate information on the effect of these programmes. We aimed to investigate: economic evaluation/analysis methods used in home-visiting programmes for children, young people and families, study designs and methods suitable in situations where randomised-controlled-trials are not feasible, and type of costs included in analyses, including any implementation costs stated. A systematic search and review was conducted of existing full economic evaluation/analysis methods in home-visiting programmes for children, young people and/or families. We included studies published in English between January 2000 and mid-November 2020.Of the 4,742 papers sourced, 60 were retained for full-text review, and 21 included.Economic-analysis methods found in the included studies were: within trial economic evaluation, economic evaluation using decision analytic modelling (i.e. cost-utility, cost-benefit analysis), cost comparison and cost-consequence. Studies incorporating return on investment and budget impact analysis were also found. Study designs suitable when randomisation was not feasible included parallel cluster randomised trials and using pre-post intervention data. Costs depended mainly on study context and only one study reported implementation costs. We hope this information will help guide future economic evaluations of home-visiting interventions.

show abstract

Section: Introductionmentioning

confidence: 99%

Economic evaluation methods used in home‐visiting interventions: A systematic search and review

Bailey

Skouteris

Morris

et al. 2021

Health Soc Care Community

View full text Add to dashboard Cite

show abstract

The relationship between machine-learning-derived sleep parameters and behavior problems in 3- and 5-year-old children: results from the CHILD Cohort study

Hammam

Sadeghi

Carson

et al. 2020

Sleep

View full text Add to dashboard Cite

Study Objectives Machine learning (ML) may provide insights into the underlying sleep stages of accelerometer-assessed sleep duration. We examined associations between ML-sleep patterns and behavior problems among preschool children. Methods Children from the CHILD Cohort Edmonton site with actigraphy and behavior data at 3-years (n = 330) and 5-years (n = 304) were included. Parent-reported behavior problems were assessed by the Child Behavior Checklist. The Hidden Markov Model (HMM) classification method was used for ML analysis of the accelerometer sleep period. The average time each participant spent in each HMM-derived sleep state was expressed in hours per day. We analyzed associations between sleep and behavior problems stratified by children with and without sleep-disordered breathing (SDB). Results Four hidden sleep states were identified at 3 years and six hidden sleep states at 5 years using HMM. The first sleep state identified for both ages (HMM-0) had zero counts (no movement). The remaining hidden states were merged together (HMM-mov). Children spent an average of 8.2 ± 1.2 h/day in HMM-0 and 2.6 ± 0.8 h/day in HMM-mov at 3 years. At age 5, children spent an average of 8.2 ± 0.9 h/day in HMM-0 and 1.9 ± 0.7 h/day in HMM-mov. Among SDB children, each hour in HMM-0 was associated with 0.79-point reduced externalizing behavior problems (95% CI −1.4, −0.12; p < 0.05), and a 1.27-point lower internalizing behavior problems (95% CI −2.02, −0.53; p < 0.01). Conclusions ML-sleep states were not associated with behavior problems in the general population of children. Children with SDB who had greater sleep duration without movement had lower behavioral problems. The ML-sleep states require validation with polysomnography.

show abstract

Influence of Experiences From Birth to 5 Years of Age on Emotional and Psychological Health

Cited by 2 publications

References 15 publications

Economic evaluation methods used in home‐visiting interventions: A systematic search and review

Economic evaluation methods used in home‐visiting interventions: A systematic search and review

The relationship between machine-learning-derived sleep parameters and behavior problems in 3- and 5-year-old children: results from the CHILD Cohort study

Contact Info

Product

Resources

About