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Journal of Pediatric Psychology logoLink to Journal of Pediatric Psychology
. 2024 Mar 29;49(5):365–371. doi: 10.1093/jpepsy/jsae015

Child routines moderate a brief behavioral intervention to enhance sleep in school-aged children

Azeb Gebre 1,✉, Nicola Hawley 2, Mary A Carskadon 3, Hollie Raynor 4, Elissa Jelalian 5, Judith Owens 6, Rena R Wing 7, Chantelle N Hart 8,9
PMCID: PMC11098045  PMID: 38553029

Abstract

Objective

To examine whether child routines (the consistency or variation in children’s daily routines, household responsibilities, discipline routines, and homework routines) moderated the effectiveness of a brief behavioral intervention to enhance sleep in school-aged children.

Methods

Secondary analysis was conducted with a subset of 66 families with short sleeping (≤9.5 hr/day) children, 8–11 years old (female = 68%; mean age = 9.76, SD = 1.02) who completed the Child Routines Inventory at baseline and were then randomized to receive a behavioral sleep intervention (n = 32) or to control (n = 34). Sleep period was objectively measured using wrist actigraphy at baseline and 2 months post-randomization. Moderation analysis was performed using ordinary least squares regression using the PROCESS macro for SPSS.

Results

Controlling for sleep period at baseline, treatment condition was significantly related to the sleep period at 2 months post-randomization, with the intervention group achieving a longer sleep period compared to the usual sleep period group (control) (b = 46.30, p < .01). Intervention response was moderated by child routines (b = 1.43, p < .05). Specifically, the intervention produced the greatest change in sleep period for children who engaged in greater routine behaviors at baseline than those who engaged in fewer routine behaviors.

Conclusions

Families that engage in routine behaviors may be better equipped to adopt the behavioral modifications required to get a good night’s sleep. The findings highlight the importance of working with families to establish routine behaviors to improve responses to behavioral sleep interventions.

Keywords: behavioral sleep intervention, school-aged children, child routines, sleep

 

Research suggests a consistent decline in children’s sleep duration over the last century, with many children not getting the recommended amount of sleep (Córdova et al., 2018; Matricciani et al., 2012). Inadequate sleep duration has been associated with an array of negative outcomes in children including impaired learning and memory (Kopasz et al., 2010; Vriend et al., 2013), behavior problems (Gruber et al., 2010; Sadeh et al., 2002), poor school performance (Dewald et al., 2010), and emotion dysregulation (Vriend et al., 2013). It has also been identified as a significant risk factor for childhood obesity (Fatima et al., 2015; Felső et al., 2017; Martinez et al., 2014; Wu et al., 2017) and unhealthy eating habits, specifically increased consumption of energy-dense foods and sugar-sweetened beverages, and decreased consumption of fruits and vegetables (Córdova et al., 2018; Hart et al., 2013). Moreover, a recent meta-analysis provides compelling evidence for the association of insufficient sleep with elevated blood pressure and insulin resistance (Sun et al., 2020). Given the adverse effects of poor sleep on children’s health, developing interventions to promote healthy sleep is imperative.

Brief behavioral sleep interventions have been effective at treating sleep disorders (Mindell et al., 2006) and improving sleep in those with neurodevelopmental disorders (Hiscock et al., 2015; Papadopoulos et al., 2019; Sciberras et al., 2011). Emerging evidence suggests that behavioral sleep interventions may also be effective in improving sleep in typically developing school-aged children (Hart et al., 2016; Hiscock et al., 2019; Quach et al., 2011). For example, in a randomized controlled trial, Hart and colleagues (2022) found that relative to children randomized to control (sleep as usual), children receiving a brief behavioral intervention objectively improved their sleep duration by an average of 40 min/night by the 2-month follow-up. Although sleep duration increased for the intervention group overall, there was considerable variability in treatment response, with 48% of children not achieving a clinically meaningful change in sleep (i.e., increased sleep period of 30 min or more) over the 2-month study period (Hart et al., 2022). Identification of individual child and family characteristics or factors associated with a better treatment response could provide important information to enhance behavioral interventions.

An organized and stable family environment is acknowledged as an important factor in child functioning (Brody & Flor, 1997; Evans, 2006; Fiese et al., 2002) and may also be important for supporting success in behavioral interventions (Bradley et al., 2001). Children in households with more structure and routines, including consistent schedules for meals, school work, leisure activities, and leaving and returning home, tend to have better self-control (Brody & Flor, 1997; Ferretti & Bub, 2014), fewer behavioral problems, and more positive parent–child relationships (Brody & Flor, 1997; Fiese et al., 2002). Research also suggests that routines may serve a protective function against the emergence of internalizing and externalizing behavior problems by providing children with consistent and predictable lifestyles (Bridley & Jordan, 2012) and fostering the development of self-regulatory skills (Bater & Jordan, 2017) and a positive sense of self (Harris et al., 2014).

Specific to sleep, bedtime routines are an important component of clinical interventions aimed at improving sleep and mitigating bedtime behavioral issues (Mindell et al., 2009). Studies of school-aged children show positive associations between bedtime routines (e.g., consistent sleep schedules) and sleep quality (Buxton et al., 2015; Galland & Mitchell, 2010). Consistent sleep routines have also been linked to cognitive flexibility and improved inhibition (Kitsaras et al., 2018). Likewise, a recent study of preschool-aged children found that consistent bedtime routines predicted less bedtime anxiety, which in turn predicted better sleep quality through an increase in adherence to bedtime (Larsen & Jordan, 2022). Sytsma and colleagues (2001) asserted that establishing routines for children can promote adherence to instructions by providing predictable environmental cues and fostering rule-governed behavior. Moreover, evidence points to the importance of routines for adherence to treatment recommendations (Fiese & Wamboldt, 2000; Fiese, 2007; Greening et al., 2007). For example, children with routines were found to be more adherent to their asthma treatment regimen than those without routines (Fiese & Wamboldt, 2000; Fiese, 2007). Further, by establishing predictability within the home, routines may promote child well-being by providing a sense of belonging, increasing family cohesion (Fiese et al., 2002; Fiese, 2007; Sytsma et al., 2001), and aiding in the development of rule-governed behaviors (Budescu & Taylor, 2013; Sytsma et al., 2001). Thus, family environments that encourage routines, supportive parent–child relations, and clear communication of expectations may promote success in behavioral interventions by increasing adherence to behavior change recommendations and reducing family stress.

Current study

The current study represents secondary data analyses of a randomized controlled trial designed to evaluate the efficacy of a behavioral intervention to enhance children’s sleep, and thereby affect their caloric intake and weight. Specifically, the current analysis examined whether differences in parent-reported child routines at baseline moderated the effects of the intervention on children’s sleep. We hypothesized that greater reported routine behavior at baseline would be associated with greater improvements in sleep secondary to behavioral intervention. Although the importance of examining moderators of treatment outcomes in randomized clinical trials has been emphasized in the literature (Kraemer et al., 2002, 2006), few studies have examined moderators of behavioral interventions generally and sleep interventions specifically.

Methods

Sample

Participants were children ages 8–11 years whose reported time in bed (TIB) was ≤9.5 hr/night and who were above the 10th body mass index (BMI) percentile for their age and gender, but no more than 100% overweight (i.e., double the median BMI for a child’s age and gender). Children with parent-reported medical or psychiatric conditions, medication use that could impact sleep or weight status, and/or were diagnosed with a sleep disorder were excluded from the study. Of the 103 enrolled participants, 78 (76%) had complete baseline data and were randomized. Eleven cases were excluded from the current study for having incomplete sleep data at the 2-month follow-up (five lost to follow-up, six with unusable data due to watch malfunction/nonadherence to the ActiGraph protocol), and one case was identified as a multivariate outlier and dropped from analyses.

Procedure

Procedures for this study have been previously described (Hart et al., 2016, 2022). Families from southeastern New England and the Mid-Atlantic region of the United States were recruited through newspaper advertisements, mailings, and flyers posted throughout the community. Recruitment primarily occurred during the academic year, with enrollment extending to the summer for families whose children participated in structured activities like day camps or summer school, which mirrored their school-year schedules. This approach was adopted to reduce the potential impact of unstructured time on sleep outcomes (Brazendale et al., 2017). After completing a brief phone screen, eligible families were invited to an orientation, where the study’s purpose and procedures were explained. After parental consent and child assent were obtained, enrolled families completed a baseline assessment week. During this period, parents provided information on their child’s routines, while the child wore an actigraph to assess sleep. Dyads also maintained a 7-day sleep diary and made two daily calls to the research facility to report on their wake times and bedtimes. Participants’ final eligibility was established at the end of the baseline week based on their average TIB. Participants were then randomized to either increase their TIB by 1–1.5 hr/night (intervention group; typically going to bed 1 hr, but up to 1.5 hr, earlier) or continue their current sleep schedules (control group).

The intervention group received two face-to-face intervention sessions (approximately 45–60 min and 30 min in length, respectively) in the first 2 weeks post-randomization and two follow-up phone calls (approximately 15 min each) at 4 and 6 weeks post-randomization. The sessions/phone follow-ups were delivered by bachelors, masters, and PhD-trained intervention staff and focused on effective behavioral strategies to increase TIB, including goal setting (e.g., developing bedtime schedules to enhance sleep duration), self-monitoring, use of positive routines, stimulus control (e.g., sleep hygiene recommendations), problem-solving regarding challenges with the sleep plan, and effective use of positive reinforcement. The control group received the same amount of face-to-face and over-the-phone contact; however, the interactions were limited to discussions about the study’s procedures.

Measures

Demographics

Demographic information, including parent and child age, gender race/ethnicity, education level, and family income, was collected at baseline by the parent report.

Child routines

The Child Routines Inventory (Sytsma et al., 2001) is a 39-item parent-reported measure of common routine behaviors in children. Each item is rated on a 5-point Likert-type scale ranging from 0 (never) to 4 (nearly always), with higher scores indicating more frequent routines. In addition to a total routine score (maximum score, 156), the CRI produces four subscale scores: daily living routines (e.g., does the same things each night before bed or eats dinner at about the same time each day), household responsibilities (e.g., has regular chores), discipline routines (e.g., has household rules such as “No cursing” or “No running inside”), and homework routines (e.g., begins homework at about the same time and in the same place). Psychometric evaluations of the measure have revealed high internal consistency and good test–retest reliability (Sytsma et al., 2001). In this study, the measure also demonstrated high reliability for the total routine score (Cronbach’s alpha of .85), which was the primary variable of interest.

Sleep

Sleep was assessed using the Actiwatch 2 actigraph (AW2; Phillips Respironics, Bend, OR), which has established reliability and validity in children (Meltzer et al., 2012). Children wore the AW2s on their non-dominant wrist continuously for each 1-week assessment at baseline and for 2 months. Devices were configured to collect data in 1-min epochs. Actigraph sleep data were scored with the assistance of self-reported bedtimes and wake times from call-ins and sleep diaries (Acebo & LeBourgeois, 2006). The variable of interest, sleep period (time between actigraph estimated sleep onset and wake), was averaged across each week.

Analytic strategy

Data were analyzed using SPSS version 25. Independent sample t-tests were first performed to determine if there were significant baseline group differences between the control and intervention on demographic variables, routines, and sleep period. An ordinary least squares regression analysis was conducted using the PROCESS macro for SPSS, Model 1 (Hayes, 2017) to examine whether the effect of the treatment condition (X: 0 = control, 1 = intervention) on sleep period at 2 months post-randomization (Y) was dependent on baseline routine scores (M or moderator). The baseline sleep period was entered into the regression model as a covariate to control for individual differences. The model also contained an independent variable (treatment condition) moderator (routines), and a multiplicative interaction term (treatment condition × routines). Consistent with recommendations (Holmbeck, 2002), the significant two-way interaction was probed by examining the simple effects, which entailed investigating how the relationship between the independent variable and the dependent variable varied at different levels of the moderator (specifically, high: 1 SD above the mean and low: 1 SD below the mean).

Results

Demographic and descriptive statistics

The baseline descriptive statistics of the sample are presented in Table 1. The present sample consisted of 66 participants (female = 68%; mean age = 9.76, SD = 1.02), with 34 randomized to the control condition and 32 to the intervention condition. Independent sample t-tests showed that there were no significant differences between conditions on child age, gender, race/ethnicity, routines, or sleep period at baseline (p’s > .05; see Table 1).

Table 1.

Baseline sample characteristics.

Characteristics Total (N = 66) Intervention (N = 32) Control (N = 34) t (64)
Age, M (SD)a 9.76 (1.02) 9.66 (1.04) 9.85 (1.02) .778
Gender, n (%) −.953
 Male 21 (31.8) 12 (37.5) 9 (26.5)
 Female 45 (68.2) 20 (62.5) 25 (73.5)
Race/ethnicity, n (%)b .775
 White 22 (33.8) 9 (28.1) 13 (38.2)
 Black, Asian, mixed race, and othersc 43 (66.2) 22 (68.8) 21 (61.8)
Sleep period, M (SD)a 513.75 (38.88) 516.03 (35.76) 511.62 (42.03) −.458
CRI total, M (SD) 109.83 (13.55) 109.73 (14.42) 109.92 (12.89) .059
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Note. CRI = Child Routines Inventory.

a

Age was measured in years and sleep period was measured in min.

b

The degree of freedom for race/ethnicity was 63 with data missing for a child.

c

Black includes those who describe themselves as African American. Mixed race includes those participants who self-identify as more than one race. Others include Native Hawaiian and other Pacific Islander and any other race not listed.

Regression results

Results from the regression analysis are summarized in Table 2. Consistent with what was reported previously (Hart et al., 2022), controlling for sleep period at baseline, treatment condition was significantly related to sleep period at 2 months post-randomization, with the intervention group having a longer sleep period compared to the control group (b = 46.30 min, p < .01). Baseline routine score was not significantly associated with sleep period at 2 months post-randomization (b = .14, p = .67). However, the two-way interaction exploring whether baseline routines moderated the link between treatment condition and sleep period at 2 months post-randomization revealed a significant effect (b = 1.30, p < .05). Specifically, the results from the simple slopes analysis (Table 3) indicated that while the effect of treatment condition (relative to control) on the 2-month sleep period was significant at low (1 SD below mean), moderate (mean), and high (1 SD above mean) levels of routine, it was strongest for children whose families reported higher routine behaviors at baseline (b = 65.34 min, p < .01) compared to those reporting low levels of routines (b = 26.52 min, p = .04). Figure 1 graphs the regression slopes representing the associations between treatment condition and 2-month sleep period post-randomization at low, medium, and high levels of baseline routines.

Table 2.

Ordinary Least Squares Regression model predicting 2-month sleep period.

b SE p
Sleep period at baseline 0.817 0.110 <.001
Treatment condition (0 = control, 1 = intervention) 46.303 8.43 <.001
Routines 0.137 0.317 .666
Treatment condition × routines 1.301 .628 .042
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Note. R2 =.62; R2 increase due to interaction (ΔR2) = .03; F (1, 61) = 4.30, p = .04.

Table 3.

Conditional effects of treatment condition on sleep period at 2 months post-randomization at low, moderate, and high values of routines.

Effect SE t p 95% confidence interval
LB UB
Routines
 1 SD below mean 28.677 11.98 2.39 .020 4.734 52.650
 At the mean 46.303 8.43 5.49 <.001 29.453 63.153
 1 SD above mean 63.929 11.96 5.35 <.001 40.014 87.845
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Note. LB = lower bound; UB = upper bound.

Figure 1.

Figure 1.

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The interactive effect of treatment condition and baseline routines on sleep period at 2 months post-randomization controlling for baseline sleep period.

Post hoc analyses were performed to determine whether specific types of routines may be more beneficial for enhancing sleep. Results revealed that the association between group membership (intervention vs. control) and sleep period at 2 months post-randomization was not moderated by daily routines, discipline routines, or homework routines, p’s > .05; household routines had a marginal, but non-significant, moderating effect on treatment response (b = 2.80, p = .07). Additionally, post hoc analyses were conducted on the moderating effect of overall child routines on the relation between treatment condition and residualized change score for TIB to account for within-child changes in TIB. The results were consistent with the primary findings (b = 1.31, p < .05).

Discussion

The negative impact of inadequate sleep on children’s health has been well documented. Recent studies support the efficacy of brief behavioral interventions for enhancing sleep in typically developing children (Hart et al., 2016, 2022). The current study examined whether the effect of a brief behavioral intervention to enhance sleep in school-aged children was moderated by parent-reported child routines at baseline. Our results indicate that while the intervention significantly improved sleep periods for all children who received it, those with higher overall routine behaviors at baseline demonstrated greater improvement than those with lower routine behaviors. Moreover, post hoc analysis of the moderating effect of overall routines on the link between treatment condition and the residual change score for TIB revealed a significant result, indicating that the routines had a meaningful effect on within-child changes in sleep duration. Notably, children who experienced larger increases in sleep duration post-intervention benefited more from the routines compared to those with smaller increases. The findings are consistent with previous literature that suggests children thrive in a structured and routinized home environment (Brody & Flor, 1997; Fiese et al., 2002; Evans, 2006) and evidence indicating that routines are effective in the management of bedtime problems (Larsen & Jordan, 2022; Mindell et al., 2009).

There are a number of reasons why engagement in routine behaviors may have assisted families who enroll in behavioral interventions. For example, families who already have regular routines in place may have been better prepared to respond to the changes required by the intervention. Evidence shows that children with more regular routines are better able to self-regulate and manage their behavior (Brody & Flor, 1997; Ferretti & Bub, 2014). Thus, children with higher levels of routine may be better able to control the impulse to stay up past the bedtimes prescribed by the intervention. Additionally, children with regular routines may experience a greater sense of control and predictability in their lives (Sytsma et al., 2001). This sense of stability may contribute to a positive mindset and motivation to follow through with the behavioral changes required by the intervention, leading to a better response to treatment. Moreover, families who report higher levels of child routines may have well-established habits and therefore may be better equipped to incorporate the prescribed plan for increasing sleep into their everyday routines without interrupting family life.

Research also suggests that routines facilitate positive parent-child interactions (Brody & Flor, 1997; Sytsma et al., 2001) and that parents who maintain highly routinized homes are more likely to monitor their children’s behaviors and provide the necessary support (Budescu & Taylor, 2013; Spagnola & Fiese, 2007)—all of which may provide a strong foundation for sleep behavior change. It is also likely that parents who maintain routinized households may be more efficient at ensuring their child’s adherence to the prescribed behavior changes. Indeed, our findings align with existing evidence suggesting that family routines positively impact medical regimen adherence in children (Fiese & Wamboldt, 2000). In light of our current findings, it may be important for clinicians and interventions aiming to foster positive sleep behavior change in families to prioritize guiding families in establishing routines.

Interestingly, among the control group, those who reported high levels of baseline routines had a shorter sleep period at two months than those with low levels of routine. This observed difference was modest—approximately a 10-minute/night difference in the sleep period between these two groups—particularly in relation to observed differences in sleep period among those randomized to intervention. It is possible that those with highly routine behaviors had more consistent bedtimes and wake times that did not change as much over the course of the intervention. In contrast, those randomized to control with fewer routines may have experienced more variable sleep schedules over the study, and the modest elevation in sleep period may simply reflect that.

It is interesting that, in post hoc analyses, no effect was observed for specific types of routines moderating treatment outcomes. This suggests that more general familiarity with and engagement in routines in everyday life rather than specific types of routine behaviors (e.g., daily living) may have a positive impact on response to behavioral interventions. When considered with evidence suggesting that greater routine behaviors are associated with greater parental monitoring and support (Budescu & Taylor, 2013; Spagnola & Fiese, 2007; Sytsma et al., 2001) and child self-regulation (Bater & Jordan, 2017; Brody & Flor, 1997; Ferretti & Bub, 2014), it is not surprising that engagement in any variety of routine behaviors could assist families with implementing behavior change. However, this may also be due to the fact that the CRI does not have a specific subscale assessing bedtime or sleep routines.

Limitations and future directions

There are several limitations to note when interpreting the results. Despite strengths in the inclusion of children from diverse racial and ethnic backgrounds, the study consisted of a small, English-speaking, predominately female sample, which may limit the generalizability of our findings. Future studies should investigate the role of routines in behavioral sleep interventions in a larger, more diverse sample. Further, given that research suggests that the quality and quantity of routines in the home vary across cultures (Fiese et al., 2002), it is also important that future work consider factors that shape variations in the routines of families from diverse cultural backgrounds. In addition, child routines were based on parent reports; future studies may benefit from accounts from both parent and child. Lastly, the study examined a single treatment moderator. Other individual, structural, or environmental variables (e.g., parenting style, number of parent jobs) may also moderate the response to a brief behavioral intervention.

Despite these limitations, findings from the present study offer insights into the characteristics of the home environment that might facilitate optimal response to behavioral programs designed to increase sleep in children. Our results suggest that children from more highly routinized homes may benefit the most from brief behavioral interventions. Future behavioral programs should consider not only targeting sleep but also instilling routine behaviors in children’s daily activities.

Acknowledgments

The authors would like to thank the families who participated in the original study and all the staff at Miriam Hospital and Temple University who worked on the study.

Contributor Information

Azeb Gebre, Center for Obesity Research and Education, College of Public Health, Temple University, Philadelphia, PA, United States.

Nicola Hawley, Department of Chronic Disease Epidemiology, Yale University, New Haven, CT, United States.

Mary A Carskadon, Department of Psychiatry and Human Behavior, Alpert Medical School, Brown University, Providence, RI, United States.

Hollie Raynor, Department of Nutrition, University of Tennessee at Knoxville, Knoxville, TN, United States.

Elissa Jelalian, Department of Psychiatry and Human Behavior, Alpert Medical School, Brown University, Providence, RI, United States.

Judith Owens, Department of Neurology and Center for Pediatric Sleep Disorders, Boston Children’s Hospital, Boston, MA, United States.

Rena R Wing, Department of Psychiatry and Human Behavior, Alpert Medical School, Brown University, Providence, RI, United States.

Chantelle N Hart, Center for Obesity Research and Education, College of Public Health, Temple University, Philadelphia, PA, United States; Department of Social and Behavioral Science, College of Public Health, Temple University, Philadelphia, PA, United States.

Funding

This work was supported by funding from the National Heart Lung and Blood Institute (R01HL092910 to C.N.H.). The NHLBI had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or decision to submit the manuscript for publication.

Conflicts of interest: C.N.H. has previously conducted consultation work for Weight Watchers International and currently provides consultation on a grant funded by the NovoNordisk Foundation. E.J. previously served as a Consultant for Weight Watchers International. Additionally, R.R.W. is a member of the Scientific Advisory Board at NOOM. Neither Weight Watchers nor NOOM provided financial support for this study, and they did not have any influence on the methods employed. The remaining authors declare no relevant financial relationships or additional conflicts of interest pertaining to this article.

Author contributions

Azeb Gebre (Conceptualization [lead], Formal analysis [lead], Methodology [lead], Writing—original draft [lead], Writing—review & editing [equal]), Nicola Hawley(Conceptualization [supporting], Methodology [supporting], Writing—review & editing [equal]), Mary Carskadon (Conceptualization [supporting], Methodology [supporting], Writing—review & editing [equal]), Holly Raynor (Conceptualization [supporting], Methodology [supporting], Writing—review & editing [equal]), Elissa Jelalian (Conceptualization [supporting], Methodology [supporting], Writing—review & editing [equal]), Judith Owens (Conceptualization [supporting], Methodology [supporting], Writing—review & editing [equal]), Rena R. Wing (Conceptualization [supporting], Methodology [supporting], Writing—review & editing [equal]), and Chantelle N. Hart (Conceptualization [supporting], Data curation [lead], Formal analysis [supporting], Funding acquisition [lead], Methodology [supporting], Writing—original draft [supporting], Writing—review & editing [equal])

Data availability

The data underlying this article are available from the corresponding author on request.

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Data Availability Statement

The data underlying this article are available from the corresponding author on request.

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