Abstract
Objective/Background:
Behavioral sleep interventions (BSIs) are 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 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 healthcare 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.
Keywords: infant, behavioral sleep intervention, sleep, disparities
An estimated 20–30% of older infants and toddlers have problematic night wakings, requiring parental assistance throughout the night (Bayer, Hiscock, Hampton, & Wake, 2007; Martin, Hiscock, Hardy, Davey, & Wake, 2007). While night wakings in young infants are more likely to be driven by nutritional need, many older infants wake frequently because of sleep associations. That is, children who fall asleep with parental assistance or associations (e.g., while being rocked, held, or fed) are more likely to require this same association to return to sleep throughout the night following naturally occurring awakenings (Mindell, Meltzer, Carskadon, & Chervin, 2009). These prolonged night wakings are often disruptive to both infant and parent sleep, and have been associated with parental stress (Byars, Yeomans-Maldonado, & Noll, 2011), maternal depression (Hiscock & Wake, 2001), and overall poorer caregiver physical and mental health (Bayer et al., 2007).
Behavioral sleep intervention (BSI) is an umbrella term that describes a variety of strategies to reduce negative infant sleep associations and promote independent sleep onset and maintenance. Examples of BSIs include modified extinction, in which a parent places an infant awake in bed and checks on her periodically until she is asleep, and parental fading, in which a parent places a child awake in bed and gradual fades the degree of parental presence over time. BSIs often also include implementing age-appropriate bedtime and wake times, as well as a consistent bedtime routine. These behavioral strategies are highly efficacious in infants and in toddlers (Mindell, Kuhn, Lewin, Meltzer, & Sadeh, 2006). More than twenty randomized control trials of BSIs have found reductions in infant night wakings and improvements in multiple aspects of child and family functioning (Meltzer & Mindell, 2014).
While BSI efficacy is well-studied in clinical and research settings, how BSIs are implemented in the real world, and by whom, is relatively understudied. Two previous studies have examined rates of BSI implementation in parents in Canada (Loutzenhiser, Hoffman, & Beatch, 2014) and in Germany and Switzerland (Maute & Perren, 2018). Almost half (49.6%) of Canadian respondents reported implementing BSI, compared with 32.6% of parents from Switzerland and Germany. Given the documented cultural and regional differences in beliefs and practices around infant sleep (e.g., Mindell, Sadeh, Kwon, & Goh, 2010), more studies are needed to examine BSI implementation in other areas of the world.
Also poorly understood is whether BSI implementation and success vary by race and ethnicity. Knowledge about the relative likelihood of BSI implementation is further limited by the fact that efficacy studies have predominantly included samples with limited racial and ethnic diversity (Schwichtenberg, Abel, Keys, & Honaker, 2019). This is in contrast to the increasing evidence of a “sleep disparity” in young children, with higher rates of problematic sleep for children from some racial-ethnic minority groups. While numerous studies have documented racial-ethnic disparities in the sleep of preschool- and school-aged children (e.g.,El-Sheikh et al., 2013; Hale, Berger, LeBourgeois, & Brooks-Gunn, 2009; McLaughlin Crabtree et al., 2005; Williamson & Mindell, 2020), fewer have examined these differences in infant and toddler sleep. Examining sleep duration in infants and toddlers, Nevarez et al. (2010) found that Black non-Hispanic infants and toddlers slept 30–60 minutes less per day than White non-Hispanic infants and toddlers. In addition, racial-ethnic differences in the practice of infant bedsharing have been frequently documented (Moon, Darnall, Feldman-Winter, Goodstein, & Hauck, 2016), with higher rates of bedsharing in US racial-ethnic minority groups.
One potential driver of disparities in sleep could be racial-ethnic differences in rates of BSI implementation. BSIs have been consistently and robustly associated with improvements in both infant sleep (including sleep duration; Mindell et al. 2006) and in secondary outcomes such as parental sleep, stress, and mood (Moore & Mindell, 2013). Relatedly, independent sleep onset (i.e., a child falling asleep without adult intervention) is a primary feature of BSIs, and is predictive of better overall sleep across infancy and childhood (Mindell et al., 2009). Further, there may be racial/ethnic differences in other factors that impact BSI implementation, such as barriers to implementation and parental cognitions about infant sleep. For example, the belief that promoting self-soothing in infants is beneficial to their development would be hypothesized to increase the likelihood of BSI implementation, whereas the belief that child sleep tendencies are fixed and difficult to alter would likely decrease the likelihood that a parent would engage in sleep intervention. A better understanding of possible racial/ethnic differences in BSI implementation, as well as predictive factors, could help identify intervention targets to reduce sleep disparities.
The aims of the current study were to: a) examine the prevalence of BSI implementation and related factors (e.g., familiarity; cognitions) in a diverse US community sample of mothers; b) assess differences by race and ethnicity in BSI implementation, related factors, and sleep patterns; and c) measure predictors of BSI implementation. We hypothesized rates of BSI implementation similar to estimated prevalence rates for problematic night wakings (20–30%), and high rates of familiarity, given the proliferation of books and internet articles promoting these strategies (Ramos et al., 2006). In light of documented disparities in sleep patterns and habits (Nevarez, Rifas-Shiman, Kleinman, Gillman, & Taveras, 2010), we further hypothesized that Black non-Hispanic and White Hispanic mothers would be less likely to implement BSIs. Finally, we hypothesized that BSI implementation would be predicted by BSI familiarity, fewer endorsed barriers, and cognitions consistent with BSI approaches.
Method
Participants
Participants included 353 mothers with a child between the ages of 6 and 18 months. This age group was selected as it is a common age group for which BSIs are recommended (Honaker & Meltzer, 2014). There were no other inclusion or exclusion criteria. To analyze differences in race and ethnicity, we engaged in purposeful sampling with the goal of recruiting at least one-hundred mothers in each of the following racial-ethnic groups: 1) Black non-Hispanic; 2 White non-Hispanic; and 3) White Hispanic. In addition, we sampled with the goal of obtaining approximately equal representation of mothers with more (post-secondary education or more) and less (high school diploma or less) education within each racial-ethnic group. Participants were all members of an online panel managed by the marketing research firm Survey Sampling Interventional (SSI; Shelton, CT). SSI’s panel of users are recruited through banners, invitations, and other types of messaging, and go through a quality control process prior to panel inclusion. For this study, only participants in the US were invited.
Procedure
The survey was hosted on REDCap and distributed by SSI. Participants meeting the eligibility criteria were randomly selected from SSI’s panel and 98,971 were invited electronically to participate in a survey. The survey was closed to respondents once the target sample had been obtained. To reduce self-selection bias, no specific project details were included in the survey invitation. Incentives varied based on the participants’ preferences and included money, points towards prizes, or charitable donations. Participants responded to the survey in September - October of 2016. The study was considered as exempt from Human Subjects Review by the Office of Research Compliance at the Indiana University School of Medicine. No identifying data were collected.
Survey
The survey (Supplemental Figure 1) was created by the authors and piloted with two mothers of young children using a cognitive interviewing strategy. The information collected included family demographics, BSI familiarity, implementation, and barriers, sleep knowledge and cognitions, and infant/toddler sleep behaviors and problems.
Family Demographics.
Demographic questions included the age, race, and ethnicity of the mother and child, child gender, the number of children in the home, maternal education, employment and marital status, and current annual household income (Table 1).
Table 1.
Family Demographic Information
| Full Sample (n=353) | By Racial/Ethnic Group | ||||
|---|---|---|---|---|---|
|
|
|||||
| Black non-Hispanic (n=118) | White non-Hispanic (n=122) | White Hispanic (n=113) | |||
| Variable | n (%) | n (%) | n (%) | n (%) | p-value |
|
| |||||
| Child Gender (% female) | 194 (55.0) | 65 (55.1) | 72 (59.0) | 57 (50.4) | .42 |
| Children in Home (% with one child) | 142 (40.2) | 49 (41.5) | 50 (41.0) | 43 (38.1) | .84 |
| Respondent Age | .02 | ||||
| <25 years | 112 (31.7) | 40 (33.9) | 28 (23.0) | 44 (38.9) | |
| 25–34 years | 190 (53.8) | 56 (47.5) | 79 (64.8) | 55 (48.7) | |
| >35 years | 51 (14.5) | 22 (18.6) | 15 (12.3) | 14 (12.4) | |
| Marital Status (% married/living with partner) | 269 (76.6) | 78 (66.7) | 108 (88.5) | 83 (74.1) | <.01 |
| Highest Level of Education | .25 | ||||
| Some high school | 22 (6.2) | 9 (7.6) | 6 (4.9) | 7 (6.2) | |
| High School diploma or GED | 144 (40.8) | 46 (39.0) | 45 (36.9) | 53 (46.9) | |
| Some college | 93 (26.4) | 33 (28.0) | 29 (23.8) | 31 (27.4) | |
| College or post graduate degree | 94 (26.6) | 30 (25.4) | 42 (34.4) | 22 (19.5) | |
| Employment Status (% of mothers employed) | 186 (52.7) | 54 (45.8) | 65 (53.3) | 52 (46.4) | .44 |
| Annual Household Income | <.01 | ||||
| <$40,000 / year | 200 (56.8) | 80 (68.4) | 57 (46.7) | 63 (55.8) | |
| ≥$40,000 / year | 152 (43.2) | 37 (31.6) | 65 (53.3) | 50 (44.2) | |
| Child Age (months)a | 11(3.9) | 10.9 (3.8) | 11(3.9) | 11 (4.0) | .93 |
Note.
Means and standard deviations (in parantheses) are reported
Gray shading indicates a statistically significant main effect (p<.05).
BSI Familiarity, Implementation, and Related Factors.
Respondents were provided with a definition of a “sleep intervention” (see Supplemental Figure 1). Mothers were asked about their familiarity with BSI, the sources of their familiarity, and if they had ever tried BSI. Mothers who responded “yes” were further asked details regarding BSI implementation, and their perception as to the helpfulness of the BSI. All respondents were also asked to rate their agreement with nine items assessing potential barriers to successful BSI implementation (Table 3). Response options were on a six-point Likert scale ranging from 1 (strongly disagree) to 6 (strongly agree). Agreement with each of the nine barriers was dichotomized into disagree (1–3) and agree (4–6).
Table 3.
Maternal Agreement with Barriers to Behavioral Sleep Intervention
| Full Sample (n=340) | By Racial-Ethnic Group | |||
|---|---|---|---|---|
|
|
||||
| Black non-Hispanic (n=115) | White non-Hispanic (n=117) | White Hispanic (n=113) | ||
|
| ||||
| Mean Barrier Ratinga (standard deviation) | 2.9 (1.2) | 2.8 (1.2) | 3.0 (1.2) | 2.8 (1.2) |
| Mean Number of Barriers Endorsedb (standard deviation) | 3.4 (2.9) | 3.2 (2.9) | 3.8 (3.0) | 3.2 (2.9) |
| Endorsement of Specific Barriers (% agreeb) | ||||
| Sleep intervention would be difficult because . . . | ||||
| my baby crying in the middle of the night might wake my neighbors or other people I live with | 47.1 | 42.6 | 48.7 | 50.0 |
| I do not have enough energy to try something new | 43.8 | 40.0 | 51.3 | 39.8 |
| it would disturb my sleep | 42.1 | 42.6 | 46.2 | 37.0 |
| if my baby cried, other people at home would pick up the baby or tell me to pick up the baby | 41.5 | 45.2 | 42.7 | 36.1 |
| my baby crying in the evening might disturb neighbors or other people I live with | 40.6 | 37.4 | 41.0 | 43.5 |
| I have other young children at night to care for | 39.1 | 33.0 | 47.0 | 37.0 |
| I have to wake up early in the morning for work. | 34.1 | 34.8 | 35.0 | 32.4 |
| at least two nights per week, I am not the person who puts my child to bed | 26.8 | 26.1 | 32.5 | 21.3 |
| there is not another adult in my home who would help me with this | 26.3 | 20.9 | 34.2 | 26.9 |
Note. There were no significant differences in mean barrier rating or sum of barriers endorsed by racial-ethnic group. Further, neither variable was predictive of BSI implementation in our model. As a result, and to minimize the number of statistical comparisons, we did not conduct comparative analyses for individual barriers.
Response options were on a six-point Likert scale ranging from 1 (strongly disagree) to 6 (strongly agree).
Agreement with each of the nine barriers was dichotomized into disagree (1–3) and agree (4–6). The mean number of barriers endorsed signifies the mean number of barriers with which the respondents agreed (4–6).
To assess sleep knowledge, the survey included five true/false sleep knowledge items (see Table 5). A summary score indicating percentage of correct responses was generated for respondents who answered at least three knowledge items. To assess cognitions, nine items from the Infant Sleep Vignettes Interpretation Scale (ISVIS; Sadeh, Flint-Ofir, Tirosh, & Tikotzky, 2007) were included. The ISVIS consists of 14 hypothetical cases of infants or toddlers presenting with a sleep difficulty. For each case, respondents rate agreement with different cognitions or interpretations about the child’s sleep difficulty on a 6-point Likert scale ranging from strongly disagree (1) to strongly agree (6). Cognitive statements represent three categories. High agreement for the Distress category endorses a belief that a child fussing in bed is distressed and should be helped or soothed by the parent. In contrast, high agreement for the Limits category suggests that the child should learn to self-soothe with minimal parental assistance. Finally, the Temperament category emphasizes the child’s temperament or character as contributory to the sleep problem, deemphasizing the role of parental behavior. These three scales were found to have good internal validity, with alphas higher than .90 (Sadeh et al., 2007). Three vignettes (nine items, three from each category) were included. These vignettes were selected for their diversity in terms of child gender and age, and for their relevance to BSI implementation, with two describing cases with frequent infant night wakings (Vignettes 10 and 14) and one with difficulty falling asleep (Vignette 7). Mean scores were derived for each of the three categories.
Table 5.
Racial/Ethnic Disparities in Sleep Patterns and Problems
| Variable | Full Sample (n=353) | By Racial/Ethnic Group | ||
|---|---|---|---|---|
|
|
||||
| Black non-Hispanic (n=118) | White non-Hispanic (n=122) | White Hispanic (n=113) | ||
| Parent-endorsed sleep problema | 76 (21.5) | 29 (24.6) | 27 (22.1) | 20 (17.7) |
| Severe Sleep Problem (ISQ Score >12) | 182 (46.9) | 65 (56.0) | 53 (43.8) | 50 (44.6) |
| Lack of consistent bedtime routine (≤4 nights/week) | 163 (46.2) | 60 (50.8) | 56 (45.9) | 47 (41.6) |
| Bedsharing (% yes) | 90 (25.5) | 46 (39.0)* | 15 (12.3)*^ | 29 (25.7)^ |
| Infant Bedsharing (% yes)b | 53 (24.8) | 25 (39.1)* | 7 (10.3)* | 17 (27.4) |
| Independent sleep onset (% no)c | 231 (79.4) | 89 (89.0)*+ | 71 (71.0)* | 71 (78.0)+ |
| Sleep Difficulty (% yes)d | 199 (57.0) | 66 (56.9) | 68 (56.2) | 65 (58.0) |
| ISQ Scoree | 11.5 (6.4) | 12.5 (6.3)* | 10.5 (6.8)* | 11.5 (6.1) |
Note. ISQ = Infant Sleep Questionnaire
Significant difference between Black non-Hispanic and White non-Hispanic mothers. Black non-Hispanic mothers reported a significantly higher mean ISQ score (d=.3, p<.05), were more likely to report bedsharing overall (OR-3.99, p<.0001), significantly more likely to report bedsharing in infants <12 months (OR=2.12, p<.01), and were less likely to report independent sleep onset (OR=.29, p<.01).
Significant differencebetween Black non-Hispanic and White Hispanic mothers. Black non-Hispanic mothers were less likely to report independent sleep onset (OR=0.36, p<.05).
Significant difference between White Hispanic mothers and White non-Hispanic mothers. White Hispanic mothers were more likely to endorse bedsharing (OR=1.75, p<.05).
Parent-endorsed sleep problem was derived from a Brief Infant Sleep Questionnaire (BISQ) item. Endorsing “small,” “moderate” or “serious” problems were coded as yes, whereas a “very small problem” or “not a problem at all” were coded as no.
n=194 for the full sample; sample sizes are much lower as toddlers (≥12 months) are excluded from the sample.
Independent sleep onset variable was derived from parental response to a BISQ item, with parental endorsement that the child fell asleep “in his/her own crib/bed alone in the room” or “in parents’ bed alone in the room” suggesting independent sleep onset, and parental endorsement that the infant fell asleep being nursed, rocked or held suggesting lack of independent sleep onset
The sleep difficulty variable indicates that the parent reported one or more of the following infant sleep characteristics: 1) sleep onset latency (SOL) >30 minutes; 2) wake after sleep onset (WASO) >30 minutes; and 3) night wakings 3 nights a week or more.
Mean (standard deviation)
Sleep Patterns.
All mothers completed the Infant Sleep Questionnaire (ISQ; Morrell, 1999), which consists of ten items, six of which are used to derive an overall score ranging from 0–38. Items assess difficulties with settling to sleep, waking at night, and sleeping in the parental bed as a consequence of difficulty settling (e.g., reactive bedsharing). A higher score suggests more problematic sleep, with a score of 12 or higher indicating a sleep problem. In addition, four items from the Brief Infant Sleep Questionnaire (BISQ; Sadeh, 2004) were included, specifically: 1) the place in which the child slept (e.g., crib, bassinet); 2) how the child typically fell asleep; 3) the number of days per week with a consistent bedtime routine; and 4) whether the parent considered the child’s sleep to be a problem, with response options ranging from “not a problem” to “a serious problem.” Parent-perceived problem was dichotomized with a “small”, “moderate”, or “serious” problem denoting a parent-perceived problem, and “not a problem” and “a very small problem” indicating the absence of a problem. Finally, we created a variable reflecting non-problematic sleep based on three criteria: 1) sleep onset latency (SOL) <30 minutes; 2) wake after sleep onset (WASO) <30 minutes; and 3) night wakings less than 3 nights a week. These estimates were selected using common clinical cut-offs for insomnia symptoms (Honaker & Meltzer, 2014) and derived from parent-responses to corresponding items from the ISQ.
Data Analysis
BSI implementation and related factors for the overall sample were examined using descriptive measures (e.g., means and proportions). To assess differences in outcomes between racial-ethnic groups, we first compared demographic information by race and ethnicity using Chi-Square tests for categorical variables and ANOVAs for continuous variables (Table 1). Significant factors (p<.05) were identified as covariates, specifically maternal age (<25 years; 25–34 years; 35 years or older), marital status (married or living with a partner; other), and income (<40K and ≥40K). With these covariates, racial-ethnic differences in sleep patterns, BSI implementation, and related factors were then examined using binary logistic regression (for dichotomous variables) and ANOVAS (for continuous variables), with race-ethnicity group as the main effect. There were no significant interaction terms. For significant outcomes, pairwise comparisons between the three race-ethnicity groups were assessed by examining estimate statements.
To examine predictors of BSI implementation, we conducted stepwise binary logistic regression modeling with the following predictors, selected for their theoretical relationship with the outcome of BSI implementation (yes/no): familiarity with BSIs (familiar or not familiar), sleep knowledge score, number of barriers endorsed, child age in months, maternal education (high school or less vs. post-secondary education or more) and mean scores on the ISVIS for temperament, limits, and distress. In the first step, bivariate models were performed and any variable with p<.20 was retained for the final multivariate model. We employed this more inclusive cut-off (p<.20) with the assumption that the influence of these variables is moderate. In the final model, only ISVIS limit-setting, BSI familiarity, and maternal education were included based on this criteria.
Following these a-priori analyses, additional exploratory analyses were conducted to aid our interpretation. To examine potential differences between mothers who were not familiar with BSIs and those who were familiar (but did not implement BSIs), we conducted a series of binary logistic regression analyses for demographic variables, sleep patterns, and factors related to implementation. In addition, two separate ANOVAs were conducted to assess differences between these two groups in infant sleep (ISQ score) with the independent variables of parent-perceived helpfulness and BSI implementation (yes/no). All analytic assumptions were verified and all analyses were performed using SAS v9.4 (SAS Institute, Cary, NC).
Results
Survey Response
The study flow is depicted in Figure 1. The survey link was followed by 586 individuals, of whom 71.4% (n = 418) were eligible. Of those eligible, almost all (95.7%; n = 400) consented to participate. We excluded participants who responded to fewer than five items (n = 38), did not provide race, ethnicity, or education data (n = 1), and did not pass a data quality check (n = 8), leaving a final sample of n = 353.
Figure 1.
Study Flow Diagram
*We identified four data checks as follows: 1) responding “true” to all knowledge items; 2) providing the same response for all 9 items from the ISVIS measure; 3) providing the same response for all nine items on barriers to infant BSI; and 4) providing no response or a non-meaningful response (e.g., typing random letters on the keyboard) for all open-ended items. Data were excluded for participants whose responses met three or more of the criteria above, suggesting poor data quality.
Family Demographics
Reflecting the sampling strategy, there was a roughly even distribution for race and ethnicity, with34.6% White non-Hispanic, 32.0% White Hispanic, and 33.4% Black non-Hispanic. Also consistent with our purposeful sampling, there were no significant differences between the three racial-ethnic groups in educational attainment. A significant main effect across race-ethnicity groups was found, however, for maternal age, marital status, and household income (Table 1).
BSI Implementation and Related Factors
Implementation.
Overall, 36.0% of the sample reported having implemented infant BSIs, and implementation rates did not vary significantly by racial-ethnic group (Table 2). Of those who reported implementing BSIs, 20.2% stopped BSIs prior to completion. Black non-Hispanic mothers were significantly more likely (OR=4.92, p<.05) to report stopping early, compared to White non-Hispanic mothers. There were no differences in ISQ score between those who reported implementing BSIs (M=11.69, SD=6.45) and those who did not (M=11.17, SD=6.45; F(1,342)=.52, p=.47). Of parents who reported implementing BSI (n=99), 54.5% perceived BSI as helpful in improving their child’s sleep, 21.2% felt BSI helped but only for a short time, 5.7% felt it helped somewhat, and 1.1% felt BSI was not at all helpful. Those who felt BSI was helpful reported better infant sleep on the ISQ (M=9.19, SD=6.44) compared to those who felt BSI helped only temporarily, somewhat, or not at all (M=13.25, SD=5.06; F(1,96)=11.63, p<.001). Of mothers who did not implement BSIs, 45.9% had an infant who slept well (i.e., SOL and WASO <30 minutes; night waking fewer than 3 nights a week), 54.5% were not familiar with BSI, 18.6% perceived their infant’s sleep as problematic, and 44.1% had an elevated ISQ score (>12). There were no racial-ethnic group differences for perceived helpfulness of BSIs, although the small sample size for this analysis (n=98) should be noted.
Table 2.
Behavioral Sleep Intervention Implementation
| Full Sample (n=353) | By Racial/Ethnic Group | |||
|---|---|---|---|---|
|
|
||||
| Black non-Hispanic (n=118) | White non-Hispanic (n=122) | White Hispanic (n=113) | ||
| Variable | n (%) | n (%) | n (%) | n (%) |
|
| ||||
| BSI Implementation (% yes) | 124 (36.0) | 41 (35.7) | 40 (33.6) | 43 (39.1) |
| BSI Completion (% completed)a | 99 (79.8) | 27 (65.9)* | 36 (90.0)* | 36 (83.7) |
| BSI Helpfulness (% perceived as helpful)b | 54 (55.1) | 17 (63.0) | 21 (58.3) | 16 (45.7) |
| BSI Familiarity (% familiar) | 210 (59.5) | 67 (56.8) | 75 (61.5) | 68 (60.2) |
| BSI Familiarity Source (% endorsed) | ||||
| Reading | 95 (26.9) | 26 (22.0) | 35 (28.7) | 34 (30.1) |
| Healthcare Professional | 60 (17.0) | 27 (22.9)* | 15 (12.3)* | 18 (15.9) |
| Trusted Individual | 55 (15.6) | 15 (12.7) | 21 (17.2) | 19 (16.8) |
Note. BSI = Behavioral Sleep Intervention
Black non-Hispanic mothers were significantly more likely (OR=1.32; p<.05) to endorse having heard about BSIs from a healthcare professional and more likely (OR=4.92; p<.05) to report stopping BSIs prior to completing, compared to White non-Hispanic mothers.
n=124 for the full sample, as only those who reported having implemented BSI received this item.
Parents who responded “Yes definitely” to an item about the helpfulness of BSIs n=98 for the full sample, as only those who reported having completed BSI (n=99) received this item and one response was missing.
Familiarity.
59.5% of respondents reported that they were familiar with BSIs prior to completing the survey, with no significant differences by racial/ethnic group. Of those who were familiar, the most frequent source was reading about BSIs (26.9%), followed by learning about BSIs from a healthcare professional (17.0%), or another trusted individual (15.6%). Black non-Hispanic mothers were significantly more likely (OR=1.32, p<.05) to endorse having heard about BSIs from a healthcare professional, compared to White non-Hispanic mothers.
Barriers to BSI Implementation.
The mean barrier rating was 2.9 (SD=1.2) on a 6-point scale with higher ratings indicating more agreement (Table 3). Respondents endorsed an average of 3.4 (SD=2.9) barriers out of nine. Barrier endorsement ranged from a high of 47.1% of respondents (infant crying might wake others) to a low of 26.3% (lack of another adult to help implement BSIs). No racial-ethnic group differences were significant for either mean barrier rating or for the number of barriers endorsed.
Sleep Knowledge and Cognitions
Across the sample, the mean percentage of correct responses for the five sleep knowledge items was 72.4 (Table 4). While there were no racial-ethnic group differences in overall sleep knowledge, Black non-Hispanic mothers were less likely (OR=0.44, p<.05) to correctly respond to item 1 (compared to White non-Hispanic mothers), suggesting a greater likelihood of believing that most 6-month-old babies are not able to sleep for 5–6 hours without needing to feed. Mean scores for cognitions about infant sleep based on the three items on the ISVIS were 3.97 (SD=1.12) for Limits, 3.75 (SD=1.07) for Distress, and 3.43 (SD=1.00) for Temperament. No racial-ethnic group differences were significant.
Table 4.
Maternal Sleep Knowledge
| Item | Full Sample (n=339) | By Racial/Ethnic Group | ||
|---|---|---|---|---|
|
|
||||
| Black non-Hispanic (n=118) | White non-Hispanic (n=122) | White Hispanic (n=113) | ||
| % Correct | ||||
|
| ||||
| By the time they are 6 months old, most babies can sleep 5 to 6 hours without needing to eat. (TRUE) | 78.2 | 71.1* | 84.6* | 78.7 |
| Studies have shown that letting a baby (ages 6–18 months) cry when falling asleep can cause emotional and attachment problems. (FALSE) | 60.8 | 62.3 | 59.8 | 60.2 |
| Babies who fall asleep while feeding are more likely to need a feeding to fall back to sleep in the middle of the night. (TRUE) | 69.3 | 69.3 | 74.4 | 63.9 |
| A consistent bedtime routine will help a baby sleep through the night. (TRUE) | 88.5 | 92.1 | 82.9 | 90.7 |
| A 12-month old baby needs more than 10 hours of sleep per day. (TRUE) | 65.4 | 60.2 | 68.4 | 67.6 |
Note. Correct answers are presented in parantheses.
Black non-Hispanic mothers were less likely (OR=0.44; p<.05) to correctly respond to this item.
Sleep Patterns
Overall, 21.5% of respondents endorsed their child’s sleep as problematic, with no differences by racial-ethnic group (Table 5). However, 46.9% of the sample met criteria for a sleep problem (ISQ score >12). Black non-Hispanic mothers reported a significantly higher mean ISQ (M=12.5, SD=6.3) score compared to White non-Hispanic mothers (M=10.5, SD=6.8; p<.05; d=.3). More than half of mothers (53.8%) endorsed using a consistent bedtime, with no significant differences by racial-ethnic group. Bedsharing was reported by 25.5% of respondents, and was reported significantly more often by both Black non-Hispanic mothers (OR=3.99, p<.0001) and by White Hispanic mothers (OR=1.75, p<.05), compared to White non-Hispanic mothers. Patterns were similar when bedsharing was examined only in infants younger than 12 months (for whom the AAP recommends avoiding bedsharing due to safety concerns), though with this smaller sub-sample there were fewer significant differences. Black non-Hispanic mothers were more likely to report bedsharing with an infant (OR=2.12, p<.01) compared to White non-Hispanic mothers. Most respondents (79.4%) reported their child did not fall asleep independently, with Black non-Hispanic mothers less likely to endorse independent sleep onset compared to White non-Hispanic (OR=0.29, p<.01) and White Hispanic (OR=.36, p<.05) mothers.
Factors Predictive of BSI Implementation
Of the eight predictive variables (Table 6) only child age and Temperament score were not associated with BSI implementation in bivariate correlations (p>.20). Thus, predictors included in the multivariate model were mean scores for Limits and Distress, sleep knowledge score, number of barriers, familiarity, and maternal education. These remaining six predictors were entered into the final multivariate model. Three of these variables were associated with BSI implementation. Mothers who were not familiar with BSIs prior to the survey, were less likely (OR=0.17; p<.0001) to report having implemented BSIs. In fact, more than half of those who did not implement BSIs (54.5%) were unfamiliar with this class of interventions. Respondents with less education (high school diploma or less) were half as likely to have implemented BSIs (OR=0.51, p<.01) compared to those with more education. Of mothers with more education, 62.9% reported BSI implementation, compared with 37.1% of those with less education. Finally, respondents who endorsed the cognition that it is important for children to learn to self-soothe (Limits score on the ISVIS) were more likely (OR=1.67, p<.001) to have implemented BSIs.
Table 6.
Predictors of BSI Implementation
| Variable | BSI Implementation | Bivariate a | Multivariate b | |||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Yes | No | Estimate | 95% CI | p | Estimate | 95% CI | p | |||
|
|
|
|||||||||
| M (SD) or n (%) | M (SD) or n (%) | LL | UL | LL | UL | |||||
|
| ||||||||||
| Temperament Score | 3.44 (1.10) | 3.42 (.946) | 1.02 | .08 | 1.28 | .84 | ||||
| Limits Score | 4.25 (1.06) | 3.80 (1.15) | 1.45 | 1.17 | 1.79 | <.01 | 1.67 | 1.31 | 2.12 | <.01 |
| Distress Score | 3.55(1.11) | 3.86 (1.03) | 0.75 | .61 | .93 | .01 | .82 | .63 | 1.06 | .13 |
| Knowledge Score | 3.80 (1.00) | 3.52 (1.07) | 1.30 | 1.04 | 1.61 | .02 | 1.05 | .82 | 1.35 | .68 |
| Barriers Score | 2.94 (1.14) | 2.73 (1.27) | 0.86 | .71 | 1.04 | .12 | .84 | .67 | 1.05 | .13 |
| Familiarity with BSI (% Not familiar) | 23 (16.1) | 120 (83.9) | 0.19 | .11 | .32 | <.01 | .17 | .10 | .30 | <.01 |
| Child age (months) | 11.15 (3.89) | 10.87 (3.88) | 1.02 | .96 | 1.08 | .52 | ||||
| Maternal education (% HS or less) | 46 (37.1) | 115 (52.3) | 0.54 | .34 | .85 | <.01 | .51 | .31 | .86 | .01 |
Note. BSI = behavioral sleep intervention; CI = confidence interval; LL = lower limit; UL = upper limit; HS = high school.
Following a step-wise approach, variables with p < .20 in the bivariate analyses were included in the final multivariate model.
[AIC=378.49; −2 Log Likelihood = 366.49]. Grey shading indicates significant predictors (p < .05) of behavioral sleep intervention implementation.
Comparisons by BSI Familiarity
Of those who did not implement BSIs, mothers who reported they were familiar with BSIs (and thus may have had other reasons for choosing not to implement them) were more likely to report higher family incomes (50% vs. 34.2%, p=.01), and were more likely to be married or living with a partner (87.8% vs. 70.8% p<.01). There were no racial-ethnic group differences in reported barriers, overall sleep knowledge, child sleep patterns, cognitions about sleep, or other demographic variables.
Discussion
Overall BSI Implementation and Predictive Factors
Approximately one-third (36%) of mothers in this US sample reported BSI implementation. This is comparable to that found in a European sample (~33%; Maute & Perren, 2018) and lower than in a Canadian sample (~50%; Loutzenhiser, Hoffman, & Beatch, 2014).
Our findings highlight several factors that might explain why some US mothers do not implement BSIs, specifically lack of familiarity with BSIs, negative cognitions and beliefs about BSIs, and the perception that a child’s sleep is not problematic. Contrary to our hypothesis, mothers generally did not endorse high rates of potential structural barriers to BSI implementation, such as concerns about waking siblings or disrupting parental sleep, nor were such barriers predictive of which mothers implemented BSIs. The barriers assessed were primarily structural in nature, however, pertaining to domains such as parental availability in the evening and the sleep environment. Barriers related to maternal beliefs and emotions around implementing BSI with their child may have been more predictive, and should be considered in future studies.
Lack of familiarity with BSIs was reported by 40.5% of the overall sample, and by 54.5% of those who did not implement BSIs. Not surprisingly, familiarity was a significant predictor of implementation, with mothers unfamiliar with BSIs notably less likely to implement BSIs. Exploratory analysis indicated that mothers who were familiar with BSIs, yet chose not to implement them, differed in some ways from mothers who did not implement BSIs because of lack of familiarity. Mothers who elected not to implement BSIs despite familiarity were more likely to have a higher income and live with a partner in the home. One possible explanation is that mothers who had a partner in the home had assistance with infant bedtime and night wakings, mitigating the perceived need for intervention. Interestingly, a small percentage of parents who were unfamiliar with BSIs (18.5%) did report having implemented BSI. Thus, some parents do appear to be implementing elements of BSIs without awareness of BSI as an intervention. Overall, familiarity appears to be an important driver of BSI implementation, though is neither necessary nor sufficient.
Maternal cognitions around infant sleep and BSIs may further explain why some mothers do not implement BSIs. Approximately 40% of mothers believed that BSIs were associated with infant emotional and attachment problems, contrary to the scientific literature (Gradisar et al., 2016; Price, Wake, Ukoumunne, & Hiscock, 2012). Relatedly, the belief that infants should learn to self-soothe was predictive of BSI implementation in our model.
Another reason mothers may not implement BSIs might be their perception that their child’s sleep is not problematic. Of those who had not tried BSIs, only 18.6% reported their perception that their child’s sleep was problematic. As previously documented, the perception of sleep as problematic is subjective, and is highly dependent on parental culture, beliefs, knowledge, and attitudes (Sadeh, Mindell, & Rivera, 2011; Sadeh et al., 2007; Sadeh, Mindell, Luedtke, & Wiegand, 2009). In our sample, 45.9% of children whose mothers did not implement BSIs likely did not require intervention as they did not have settling difficulties or frequent night wakings. In other cases, however, mothers who do not perceive their child’s sleep as a problem may still benefit from intervention, as infant night wakings requiring parental intervention can be highly disruptive to parental sleep and daytime functioning (Byars et al., 2011; Hiscock & Wake, 2001). In contrast to the low proportion of mothers who perceived their infant’s sleep as problematic, almost half of mothers who did not try BSIs (44.1%) reported sleep behaviors consistent with a sleep problem on a validated measure. Problem perception was not a significant predictor in our model; however, this may reflect insufficient power in light of the small proportion of the sample who perceived their child’s sleep as problematic.
While most (79.8%) mothers who tried BSIs reported completing the intervention, only half (54.5%) felt that BSIs led to sustained improvements in their infant’s sleep. Not surprisingly, those that perceived BSIs as helpful over an extended period reported better infant sleep compared to those who felt it was not helpful or helpful only for a short time. Overall, findings support the need for additional parental education about BSIs to increase familiarity and awareness of BSI as a treatment option. Relatedly, mothers may benefit from additional information about strategies for successful implementation and maintenance of gains over time.
Race / Ethnicity
Contrary to our hypothesis, rates of BSI implementation did not differ across racial-ethnic groups. Relatedly, there were no differences in BSI familiarity, perceived barriers, or overall sleep knowledge. We did find that Black non-Hispanic mothers were almost five times more likely to report stopping BSIs prior to completing the intervention compared to White non-Hispanic mothers. As Black non-Hispanic mothers did not report more functional barriers to BSIs, greater likelihood of discontinuing BSIs may be related to other factors such as acceptability of the intervention or differences in how BSIs were implemented. We also found that Black non-Hispanic mothers had higher ratings for distress on the ISVIS (Sadeh, Flint-Ofir, Tirosh, & Tikotzky, 2007), though this difference only trended towards significance (OR=.32, p=.06). Thus, Black non-Hispanic mothers may be more likely to endorse the belief that a crying infant is in distress and should be soothed by a parent.
Overall, findings highlight racial-ethnic group differences in sleep practices (including bedsharing, independent sleep onset, and score on a validated sleep measure), but fewer differences in BSI implementation, knowledge, or barriers. This suggests that differential BSI implementation rates may not be a major driver of sleep disparities. However, we did find that Black non-Hispanic mother were almost five times more likely to stop BSI implementation prior to completion, which could be an indicator of lower acceptability of currently available BSIs in this population. To address this disparity, an important first step will be to better understand the experiences and perceptions of Black non-Hispanic mothers regarding BSI implementation. In addition, it will be important to explore other factors that might contribute to identified sleep disparities, such as parental work and sleep schedules or feeding methods.
Limitations
This study is the first to examine rates of BSI implementation in a community sample of US mothers, and also the first to examine differences in BSI implementation based on race/ethnicity. Several limitations deserve note. As survey respondents were members of a research marketing panel, they may not be representative of the larger US population. While we recruited a diverse sample in terms of race, ethnicity, and education, we included only three racial-ethnic groups. Relatedly, in order to explore racial-ethnic group differences we oversampled Black non-Hispanic and White Hispanic mothers compared to the US population more broadly. However, given few differences found between the three groups, findings from our overall sample likely do provide a strong estimate of US practices. Given that we surveyed mothers of infants starting at 6 months, some of the mothers in our sample may have eventually become familiar with and/or implemented infant BSIs as their child became older. In this case, our estimate of BSI prevalence would be an underestimate. However, rates of implementation for infants (6–11.9 months) and toddlers (12–18 months) were comparable in our sample. Further, we included only three of fourteen items from the ISVIS, which likely limited the reliability and validity of the instrument in assessing parental cognitions, though we chose to focus on the vignettes most applicable to this study. While maternal education level was equally balanced within the three racial-ethnic groups, the groups did differ significantly in annual household income. Though we controlled for maternal education in our analyses, the effects of socioeconomic status and race/ethnicity may still have been confounded in our sample. Additionally, our sample consisted of mothers and did not include fathers or other types of caregivers. Previous research suggests that women may have lower tolerance for infant crying compared to men (Sadeh et al., 2016). As such, our findings, particularly those regarding parental cognitions related to BSIs, may not generalize to parents more broadly.
Summary and Future Directions
Approximately one-third of mothers are implementing behavioral sleep interventions. For many families (~40%), BSIs are likely not necessary as mothers report their infant settles to sleep easily and does not regularly wake during the night. Barriers to implementation include lack of familiarity with BSIs, and, in some cases, parental beliefs that are not consistent with BSI implementation. Further, some mothers whose infants wake frequently do not perceive these awakenings as problematic, but might still benefit from intervention. Taken together, these findings support the need for strategies to increase parental knowledge of this evidence-based approach and its potential benefits for young children and their families. The goal is not for all families to implement BSIs, as these strategies may not be a good fit for all families and in many cases are not needed. However, providing parents with accurate information about BSIs would allow them to make an informed decision about their infant’s sleep.
This study also replicates previous findings regarding racial-ethnic disparities in infant and toddler sleep habits and practices, with more problematic sleep in Black non-Hispanic infants and toddlers. Differential BSI implementation does not appear to be a major driver of these disparities, although Black non-Hispanic mothers who decide to implement BSIs do report notably lower completion rates. Future studies should explore mechanisms for sleep disparities in young children, and develop and evaluate strategies to improve infant and toddler sleep health in diverse families.
Supplementary Material
Acknowledgments
This study was funded, in part, with support by Indiana University Health, with the assistance from the Indiana Clinical and Translational Sciences Institute funded by a grant from the National Institutes of Health, National Center for Advancing Translational Sciences, Clinical and Translational Sciences Award. Dr. Honaker’s time was supported by Grant Number UL1TR002529 (A Shekhar, PI) from the National Institutes of Health, National Center for Advancing Translational Sciences, Clinical and Translational Sciences Award and the Indiana University School of Medicine.
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.
Contributor Information
Sarah Morsbach Honaker, Indiana University School of Medicine.
Jodi A. Mindell, Saint Joseph’s University Children’s Hospital of Philadelphia.
James E. Slaven, Indiana University School of Medicine
A.J. Schwichtenberg, Purdue University
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