ABSTRACT
Objective/Background
Behavioral Sleep Interventions (BSI) is an efficacious class of treatment approaches for infant sleep disturbance. Little is known about BSI implementation in the real world. Objectives were to a) examine the prevalence of BSI implementation and related factors in a diverse sample of US mothers; b) assess racial-ethnic group differences; and c) examine predictors of BSI implementation.
Participants
Participants included mothers (n= 353) with an infant (6–18 months) from one of the three racial-ethnic groups: White Hispanic (n= 113), White non-Hispanic (n= 122), Black non-Hispanic (n= 118).
Methods
Respondents completed an online survey assessing BSI implementation, familiarity, barriers, sleep knowledge, cognitions, and sleep patterns.
Results
Approximately one-third (36%) of the sample endorsed BSI implementation and 59% reported BSI familiarity. Black non-Hispanic mothers were more likely to report stopping a BSI prior to completion (OR = 4.92, p <.05) and more likely to hear about BSI from a health-care professional (OR = 1.32, p <.05) compared to White non-Hispanic mothers. Racial-ethnic group differences were identified for a variety of sleep practices, including bedsharing, independent sleep onset, and score on a validated measure of problematic sleep. No racial-ethnic group differences were found in BSI implementation, cognitions, or barriers. BSI implementation was predicted by BSI familiarity, more maternal education, and cognitions around infant self-soothing.
Conclusions
Differential BSI implementation does not appear to be a major driver of sleep disparities, although Black non-Hispanic mothers who decide to implement BSI do report notably lower completion rates. Future studies should examine alternative mechanisms of sleep disparities as well as strategies to promote sleep health in diverse families.
Conflict of interest
Dr. Mindell receives grant support and is a consultant for Johnson & Johnson Consumer Inc. Dr. Honaker is a consultant for Google LLC. Dr. Schwichtenberg receives grant support from the National Institute of Mental Health, National Institute of Child Health and Human Development, Purdue Institute for Integrative Neuroscience, and the Purdue Research Foundation.Study data were collected and managed using REDCap electronic data capture tools hosted at Indiana University. REDCap (Research Electronic Data Capture) is a secure, web-based application designed to support data capture for research studies, providing: 1) an intuitive interface for validated data entry; 2) audit trails for tracking data manipulation and export procedures; 3) automated export procedures for seamless data downloads to common statistical packages; and 4) procedures for importing data from external sources.
Disclosure statement
No potential conflict of interest was reported by the authors.
Supplementary material
Supplemental data for this article can be accessed on the publisher’s website.