Relationship Between Sensory Processing and Sleep in Typically Developing Children

Abstract

OBJECTIVE. The relationship between sensory processing factors and the sleep habits and patterns of typically developing children ages 8–12 yr was investigated.

METHOD. Forty-five typically developing children and their parents or caregivers took part. Parents completed the Sensory Processing Measure–Home Form, Children’s Sleep Hygiene Scale, and Children’s Sleep Habits Questionnaire, and the children completed the Children’s Report of Sleep Patterns. Spearman ρ correlation and linear regression analyses were completed with the children’s sleep habits and patterns as the dependent variables and the sensory processing factors as the independent variables.

RESULTS. Sensory processing factors were significantly associated with the children’s sleep habits and patterns, as reported by parents and children. Predictive relationships were established between the children’s sensory processing factors and sleep habits and patterns.

CONCLUSION. Occupational therapy practitioners should consider sensory processing factors when working with children who present with suspected sleep problems.

All people, including children, engage in the occupation of sleep (American Occupational Therapy Association [AOTA], 2014). Reduced sleep quality in children has been associated with reduced scores in school-related cognitive tasks, emotional regulation, short-term memory, and some aspects of attention (Paavonen et al., 2010; Reale, Guarnera, & Mazzone, 2014; Vriend et al., 2013). The link between children’s sleep and sensory processing factors requires further examination. In this study we investigated whether typically developing children’s sensory processing factors were associated with their sleep patterns, habits, and routines.

The U.S. National Sleep Foundation recommends that the appropriate amount of sleep for children ages 6–13 yr is 9–11 hr per night (Hirshkowitz et al., 2015). Shorter sleep duration is linked with lower scores on cognitive tasks (Paavonen et al., 2010). According to Vriend et al. (2013), sleep that was shortened by 1 hr affected children’s emotional regulation, short-term memory, and some aspects of attention. Sleep disturbances, particularly waking up at night, had a negative impact on academic performance, according to the final exam results of 154 Italian school children ages 5–11 yr (Reale et al., 2014).

Findings from most studies are derived from parent-report data about children’s sleep. Surani et al. (2015) conducted a cross-sectional study involving 1,507 elementary and middle-school students in Texas who completed the Child Sleep Habits Questionnaire (CSHQ; Owens, Spirito, & McGuinn, 2000) after a sleep education program. The children reported difficulty sleeping and stayed awake long after their parents thought they had fallen asleep, highlighting the difference between parent- and child-reported data.

Sensory processing is a neurological process of sensory input to the central nervous system and subsequent behavioral responses to assist with regulation of arousal levels throughout the day. Patterns of sensory processing occur across the lifespan in everyone (Dunn, 2007). Sensory processing problems in children with autism spectrum disorder (ASD) have been related to problem behaviors, motor behaviors, routines, and social behaviors (O’Donnell, Deitz, Kartin, Nalty, & Dawson, 2012; Tomcheck, Little, & Dunn, 2015). Children with attention deficit disorder have also been found to have difficulties with sensory processing that relate to behavioral problems, hyperactivity, and impulsivity (Pfeiffer, Daly, Nicholls, & Gullo, 2015; Shimizu, Bueno, & Miranda, 2014).

Sensory processing challenges influence children’s performance in social participation, play, and self-care. Emerging evidence suggests that sensory processing factors influence sleep performance in all children, whether typically or nontypically developing (Koenig & Rudney, 2010). Shani-Adir, Rozenman, Kessel, and Engel-Yeger (2009) reported associations between sensory hypersensitivity and sleep quality in 57 Israeli children diagnosed with atopic dermatitis compared with 37 healthy children ages 4–10 yr.

Another case control study, conducted by Wengel, Hanlon-Dearman, and Fjeldsted (2011), reported that irregular sensory processing patterns in children with fetal alcohol syndrome were correlated with sleep disturbances, including increased bedtime resistance, sleep latency, shorter sleep duration, and increased anxiety and night awakening events. A cohort study reported that children with ASD were likely to have increased sensory sensitivity, which is associated with difficulty filtering out stimuli when trying to fall asleep and stay asleep (Reynolds, Lane, & Thacker, 2012).

To date, two cross-sectional studies have explored relationships between sensory processing and sleep in typically developing children. One, involving healthy children from Israel, indicated that tactile sensitivity predicted difficulties with sleep and behavior (Shochat, Tzischinsky, & Engle-Yeger, 2009). The second investigation, by Vasak, Williamson, Garden, and Zwicker (2015), focused on typically developing toddlers referred to a community occupational therapy practice for sleep difficulties. Vasak et al. found small but not statistically significant correlations between sensory sensitivity and sleep. They noted that children with increased sensory sensitivity patterns slept less during the day and took longer to fall asleep at night.

The current literature supports the view that sleep quality is also strongly related to children’s daily occupational performance and that sensory processing patterns influence occupational performance, including sleep (Shochat et al., 2009; Vasak et al., 2015). Because of the lack of evidence describing links between sensory processing factors and sleep habits and patterns in typically developing children, however, we designed this study to investigate that relationship.

Method

Participants

We used convenience sampling methods to recruit 45 typically developing children age 8–12 yr and their parents or caregivers from community youth sporting organizations in the Geelong, Victoria, Australia, region. The children were included in the study if they had no known diagnosis of intellectual disabilities, learning difficulties, mental health problems, or physical impairments, as reported by parents, and no prior contact with other professional services to address sensory processing or sleep problems. To participate, both children and their parents or caregivers were required to have functional English skills and be able to comprehend verbal and written instructions given in English appropriate for their age level.

Instruments

Sensory Processing Measure–Home Form.

The Sensory Processing Measure–Home Form (SPM–HF; Parham & Ecker, 2007) is a 75-item scale that assesses sensory processing ability, praxis, and social participation in children ages 5–12 yr. The 75 items are divided across several sensory domains: Vision, Hearing, Touch, Taste and Smell, Social Participation, Body Awareness, Balance and Motion, and Planning and Ideas. The SPM–HF is completed by the child’s parent or caregiver and takes approximately 15–20 min to complete. Reliability and validity of the scale were examined in a sample of 1,051 typically developing children ages 5–12 yr from the United States. The eight SPM–HF subscales had Cronbach’s αs ranging from .70 to .80. Evidence of the SPM–HF’s test–retest reliability has been reported, with all subscale coefficients being greater than .94 (Parham, Ecker, Miller Kuhaneck, Henry, & Glennon, 2007). Evidence of the SPM–HF’s construct validity and convergent validity were also reported in its test manual (Parham & Ecker, 2007).

Children’s Sleep Hygiene Scale.

The Children’s Sleep Hygiene Scale (CSHS; Harsh, Easley, & LeBourgeois, 2002) is a 22-item parent-report measure that assesses sleep hygiene practices of children ages 2–12 yr. Parents indicate their child’s sleep behavior during the past month using a 6-point Likert scale. Internal consistency as measured by Cronbach’s α was reported as .76, and evidence of the CSHS’s validity has also been reported (Harsh et al., 2002).

Children’s Sleep Habits Questionnaire.

The CSHQ is a 45-item parent-report questionnaire that examines the sleep behaviors of their children. The CSHQ items cover a range of categories considered to be common clinical symptoms of sleep complaints: Bedtime Behavior, Sleep Onset, Sleep Duration, Anxiety Around Sleep, Behavior During Sleep and Night Awakenings, Sleep Disordered Breathing, Parasomnias, Morning Awakenings, and Daytime Sleepiness (Owens et al., 2000). Reliability and validity of the CSHQ were determined in two groups: (1) a community sample of 1,099 children ages 4–10 yr and (2) a clinical sample of 154 children with diagnosed sleep disorders, both from the United States. Internal consistency αs were .68 in the community sample and .78 in the clinical sample. Test–retest reliability was assessed in a community sample of 60 parents after a 2-wk interval, with subscale correlations ranging from .62 to .79 (Owens et al., 2000). The specificity and sensitivity of the CSHQ were reported as .72 and .80, respectively (Owens et al., 2000). Evidence for the validity of the CSHQ has also been reported (Markovich, Gendron, & Corkum, 2015)

Children’s Report of Sleep Patterns.

The Children’s Report of Sleep Patterns (CRSP; Meltzer et al., 2013) is a 60-item questionnaire developed specifically to be completed by children ages 8–12 yr. The 60 items are distributed across three scales: (1) Sleep Patterns, (2) Sleep Hygiene including Caffeine, Activities Before Bed, Sleep Location and Electronics subscales; and (3) Sleep Disturbance including Bedtime fears and worries, Restless Legs, Parasomnias, and Insomnia subscales (Meltzer et al., 2013). Internal consistency based on Cronbach’s α coefficients was reported to be >.70. Test–retest reliability correlations were all >.80 for all scales, and evidence of the CRSP’s construct validity has also been reported (Meltzer et al., 2013).

Procedure

Approval to conduct this study was granted by the Deakin University Human Ethics Advisory Group. Consent was obtained from organizations for the researchers to approach children and their parents/caregivers, inviting them to participate in the study by distributing information packs that included a plain language statement for both adults and children, consent forms, and a demographics questionnaire. After receiving the information about the study, participants indicated their interest by returning the consent forms by mail or email. After determining which participants met the inclusion criteria, we asked the parents/caregivers to complete the SPM–HF, CSHS, and CSHQ and the children to complete the CRSP.

Data Analysis

Data were analyzed using IBM SPSS Statistics (Version 23; IBM Corp., Armonk, NY). Spearman ρ correlation analyses were conducted to determine the associations between sensory processing and sleep using the subscale scores from the SPM–HF and the subscale scores from each of the other sleep scales. Multilinear regression analysis was conducted on the variables with significant correlations to determine whether the SPM–HF subscale scores were predictive of the CSHS, CSHQ, and CRSP subscale scores.

Results

Participant Demographics

Of the total sample (n = 45), 26 participants (57.8%) were male and 19 (42.2%) were female. The average age of the child participants was 9.9 yr (standard deviation = 1.46). The children recruited for the study were in Grades 2–6 and attended state (91.1%) and independent (8.9%) primary schools. The majority of the parents or caregivers who completed the SPM–HF, CSHS, and CSHQ were mothers (n = 43; 95.6%).

Correlations Between SPM–HF and CSHS Subscales

We found positive correlations between a number of the SPM–HF and CSHS subscale scores, including (1) CSHS Physiological scores with SPM–HF Social Participation (ρ = .36, p < .05) and Taste and Smell (ρ = .35, p < .05) scores, (2) CSHS Bedtime Routine scores with SPM–HF Taste and Smell (ρ = .34, p < .05), and (3) CSHS Sleepiness and SPM–HF Social Participation (ρ = .34, p < .05; Table 1).

Table 1.

Correlation Analysis (Spearman’s ρ) Results for SPM–HF Subscales and CSHS Subscales (N = 45)

	CSHS Subscales
SPM–HF Subscales	Physiological	Cognitive	Emotion	Environment	Bedtime Routine	Sleepiness
Social Participation	.36*	.19	.19	.26	.15	.34*
Vision	−.02	−.15	.09	.11	.04	−.23
Hearing	−.01	−.08	.03	.14	.27	−.07
Touch	.03	.13	.20	−.02	.20	.27
Taste and Smell	.35*	.11	.03	.06	.34*	.17
Body Awareness	.25	−.06	.18	−.01	.10	.18
Balance and Motion	.06	.13	.19	.21	.04	.16
Planning and Ideas	.15	.14	.16	.05	.29	.28

Note. CSHS = Children’s Sleep Hygiene Scale; SPM–HF= Sensory Processing Measure–Home Form.

p < .05.

Correlations Between SPM–HF and CSHQ Subscales

Low but statistically significant negative correlations were obtained between SPM–HF and CSHQ subscales scores, including (1) CSHQ Sleep Duration with SPM–HF Touch (ρ = .33, p < .05), Taste and Smell (ρ = .33, p < .05), and Planning and Ideas (ρ = −.33, p < .05); (2) CSHQ Sleep Disordered Breathing with SPM–HF Social Participation (ρ = −.38, p < .01), Body Awareness (ρ = −.40, p < .01), Balance and Motion (ρ = −.39, p < .01), and Planning and Ideas (ρ = −.37, p < .05); and (3) CSHQ Daytime Sleepiness with SPM–HF Touch (ρ = .36, p < .05) and Taste and Smell (ρ = −.31, p < .05; Table 2).

Table 2.

Correlation Analysis (Spearman’s ρ) Results for SPM–HF Subscales and CSHQ Subscales (N = 45)

	CSHQ Subscales
SPM–HF Subscales	Bedtime Routines	Sleep Onset Delay	Sleep Duration	Sleep Anxiety	Night Wakings	Parasomnias	Sleep Disordered Breathing	Daytime Sleepiness
Social Participation	−.04	−.24	−.08	.13	−.22	−.21	−.38**	−.06
Vision	−.04	.16	.07	.03	−.08	−.27	−.04	−.02
Hearing	−.02	.20	−.01	−.03	−.05	−.25	−.12	−.07
Touch	.04	−.09	−.33*	.00	−.16	−.13	−.17	−.36*
Taste and Smell	−.17	−.02	−.33*	.11	−.22	−.21	−.22	−.31*
Body Awareness	−.09	−.04	−.21	.16	−.14	−.15	−.40**	−.02
Balance and Motion	.01	−.11	.05	−.03	−.21	−.26	−.39**	−.03
Planning and Ideas	−.04	−.03	−.33*	.15	−.18	−.12	−.37*	−.22

Note. CSHQ = Children’s Sleep Habits Questionnaire; SPM–HF= Sensory Processing Measure–Home Form.

p < .05. **p < .01.

Correlations Between SPM–HF and CRSP Subscales

Negative correlations were also obtained between the parent-reported SPM–HF and the children’s reported CRSP sleep factors, including (1) CRSP Caffeine with SPM–HF Taste and Smell (ρ = −.34, p < .05), (2) CRSP indicator items with SPM–HF Social Participation (ρ = −.34, p < .05) and Balance and Motion (ρ = −.29, p < .05), (3) CRSP Restless Legs and SPM–HF Balance and Movement (ρ = −.30, p < .05), and (4) CRSP Activities and SPM–HF Planning and Ideas (ρ = −.30, p < .05; Table 3).

Table 3.

Correlation Analysis (Spearman’s ρ) Results for SPM–HF Subscales and CRSP Subscales (N = 45)

	CRSP Subscales
SPM–HF Subscales	Caffeine	Activities	Sleep Location	Electronics	Bedtime Fears/Worries	Restless Legs	Parasomnia	Indicator Items	Sleepiness
Social Participation	.19	−.19	−.11	−.23	.09	−.23	−.17	−.34*	−.27
Vision	.15	.03	−.02	.28	−.08	−.18	.21	−.10	.06
Hearing	.17	−.28	−.09	.08	.01	−.16	.04	−.05	.18
Touch	−.30*	−.28	−.22	−.08	.14	−.05	−.07	.06	−.03
Taste and Smell	−.34*	−.29	−.17	−.12	−.04	−.19	−.18	.05	−.23
Body Awareness	−.02	−.05	.02	.15	.20	.01	.26	−.05	.12
Balance and Motion	.14	−.24	−.08	−.22	.10	−.30*	−.12	−.29*	−.32*
Planning and Ideas	.09	−.30*	−.10	.08	.10	−.12	.09	−.13	.08

Note. CRSP= Children’s Report of Sleep Patterns; SPM–HF= Sensory Processing Measure–Home Form.

p < .05.

Regression Analysis Findings

Predictive relationships were determined between the SPM–HF subscales and parent-report CSHS. The SPM–HF Social Participation and Taste and Smell subscales uniquely explained 25% of the total variance on the CSHS Physiology subscale, F (2, 42) = 7.01, adjusted R ² = .21, p < .05. Both SPM–HF subscales made unique significant contributions to the predictive model: Social Participation, p = .15, 95% confidence interval (CI) [0.04, 0.37], β (β) = 0.348, and Taste and Smell, p = .04, 95% CI [0.39, 1.26], β (β) = 0.293.

The CSHS Bedtime Routine subscale and the SPM–HF Taste and Smell subscale indicated that Taste and Smell explained 9.2% of the total variance on the CSHS Bedtime Routine subscale, F(1, 43) = 4.34, adjusted R ² = .07, p < .05, β (β) = 0.303, p = .043, 95% CI [0.02, 1.03]. The SPM–HF Social Participation subscale was predictive of high scores on the CSHS Sleep Stability subscale, with the R ² value indicating that the regression model accounted for 13.5% of the CSHS Sleep Stability subscale’s total variance, F(1, 43) = 6.70, adjusted R ² = 0.12, p < .05, β (β) = 0.367, p = .013, 95% CI [0.05, 0.37].

Predictive relationships were determined between parent-reported sensory processing factors and child-reported sleep habits and patterns (via the CRSP). The SPM–HF Taste and Smell subscale uniquely explained 13.6% of the total variance on the CRSP Caffeine subscale score, p = .014, 95% CI [−1.08, −0.13], β (β) = −0.380. The SPM–HF Balance and Motion subscale explained 14.6% of the total variance on the CRSP Restless Legs subscale, F (1, 43) = 7.37, adjusted R ² = .13, p < .05, β (β) = 0.383, p = .009, 95% CI [1.10, −0.16]. Finally, the SPM–HF Planning and Ideas subscale explained 12.1% of the total variance on the CRSP Activities Before Bed subscale, F(1, 43) = 5.89, adjusted R ² = .10, p < .05, β (β) = 0.347, p = .019, 95% CI [−0.64, −0.06].

Discussion

Emerging evidence from the current literature suggests a relationship between sensory processing factors and children’s sleep habits and patterns (Shochat et al., 2009; Vasak et al., 2015). This study was the first to examine the relationships between sensory processing factors and sleep in a sample of typically developing children who did not present with any known sleep problems.

We observed several significant correlations, as measured by the CSHS, CSHQ, and CRSP, between the SPM–HF subscales and the sleep habits and patterns of the children in our sample. Several predictive relationships between children’s sensory processing factors and their sleep habits and patterns (as reported by both parents and children) also were found. Note that the SPM–HF Hearing and Vision subscales did not significantly correlate with any of the CSHS, CSHQ, or CRSP subscales, whereas the SPM–HF subscales were significantly correlated with at least one or more of the children’s sleep-related subscales.

Spira (2014) investigated the effectiveness of a sensory intervention program for school-age children from Israel (N = 50) with sensory modulation disorder on the outcomes of sleep behaviors and social participation. Parents of the children completed the Short Sensory Profile (Dunn, 1999), the CSHQ, the Child Behavior Checklist (Achenbach & Ruffle, 2000), and the SPM–HF Social Participation subscale. Spira made the following observations: Greater daytime sleepiness was associated with heightened tactile sensitivity and taste/smell sensitivity, r = .28, p < .05. Night wakings were associated with lower movement sensitivity, r = .28, p < .05. Parasomnias were modestly related to lower energy, r = .27, p < .05, as was sleep onset delay, r = .28, p < .05. Finally, greater sleep anxiety was modestly linked with higher visual/auditory sensitivity, r = .28, p < .05 (Spira, 2014, p. 81). These findings are consistent with the results of the current study.

Influence of Sensory Processing on Sleep Hygiene

To date, no other study has used the CSHS or CRSP when investigating relationships between sensory processing and sleep in children. The CSHS provided information about environmental factors that may influence children’s sleep onset and maintenance (Harsh et al., 2002). The CSHS and SPM–HF together allowed us to investigate whether children’s sensory processing function influenced their participation in bedtime preparation activities. Significant, positive predictive relationships were obtained between the SPM–HF Social Participation subscale, accounting for 9.8% of the variance on the CSHS Physiological subscale and 13.5% of the variance for the CSHS Sleepiness subscale. This suggests that children, who are more likely to have higher levels of social participation, are more likely to have better sleep physiological hygiene and sleep stability factors.

Social participation is influenced by sensory processing, with a direct link made in a study by Hilton, Graver, and LaVesser (2007), who found statistically significant correlations between sensory overresponsivity and challenges with social performance. Cosbey, Johnston, and Dunn (2010) reported that children with SPD had more social interaction with family members than with peers. It also appears that children’s social participation may be influenced by their motor abilities. In a study involving 88 kindergarten-age children, Yair and Bart (2006) reported that children who presented with motor skill challenges were more likely to engage in solitary play than social play.

Internal child temperament may also be a determinant of social behavior, with significant associations reported between the two variables. For example, Baer et al. (2015) determined that children who were more impulsive tended to be less socially competent than children who had better behavioral regulation skills. Spira (2014) also found a predictive link between sensory processing and social participation in a sample of school-age children from Israel (N = 50) with sensory modulation disorder. Spira’s hierarchical regression determined that “the sensory related measures accounted for 13.8% of the change in social participation, p < .001” (p. iii).

Environmental factors, such as parenting values about bedtime habits in the home, may potentially influence children’s sleep hygiene during bedtime preparation activities. A study of 766 Italian schoolchildren reported that increased parent-imposed structure at bedtime was related to better sleep quality and knowledge about the importance of sleep (Esposito, Gnisci, Fabbri, & Cicogna, 2014). This finding is supported by a study of 84 English children completed by Jones and Ball (2014), who also reported that sleep hygiene was better when parents carried out a consistent bedtime structure and routine for their children.

Positive predictive relationships between the SPM–HF Taste and Smell subscale and the CSHS Physiological subscale accounted for 9.8% of its variance. The SPM–HF Taste and Smell subscale was also predictive of the CSHS Bedtime Routine subscales, accounting for 9.1% of its variance. This indicates that children who tend to be overly responsive to taste and smell have better CSHS physiology sleep hygiene and better bedtime routines. CSHS physiology sleep hygiene factors include items such as consuming caffeinated drinks, excessive drinking of liquid, or complaints about hunger before bed. Although recent evidence supports that increased sensitivity to smell influences consumption of new foods (Monnery-Patris et al., 2015), reduced instances of caffeine intake among school-age children may be due to other environmental influences, such as parental values and beliefs.

Beckford, Grimes, and Riddell (2015) investigated caffeine consumption in children and found that children were more likely to consume caffeinated beverages in the home between 5:00 p.m. and 8:30 p.m., and consumption was more likely if they were of a low socioeconomic background. The socioeconomic background of the families in our study was not recorded; however, parental reports of good physiological hygiene were supported by the children’s report of significant predictive relationship between the SPM–HF Taste and Smell subscale and child-reported caffeine consumption from the CRSP, accounting for 13.6% of the variance.

Influence of Sensory Processing on Children’s Sleep Habits

Shochat et al. (2009) reported a predictive relationship between tactile hypersensitivity as measured by the Short Sensory Profile and sleep habits as measured by CSHQ in a sample of 51 healthy schoolchildren. Contrary to these findings, in the current study we found low but significant negative correlations between the SPM–HF Touch subscale and the Sleep Duration and Daytime Sleepiness subscales of the CSHQ. This means that children whose SPM–HF scores indicated some problems in the sensory processing area of touch were more likely to sleep longer without disruption and were less likely to experience daytime sleepiness. This finding is similar to one found in a study involving healthy adults, where a greater tendency for sensory seeking was significantly correlated with fewer sleep disturbances (Engel-Yeger & Shochat, 2012). Similarities between typically developing children and healthy adults suggest that both of these groups are less likely to experience sensory processing problems and are, therefore, less likely to experience difficulties with their sleep activities.

Parent-proxy report of children’s sleep habits in other studies that have investigated the relationships between children’s sensory processing and sleep have predominantly used the CSHQ to gather data. Shani-Adir et al. (2009) reported that children with atopic dermatitis experienced sensory hypersensitivity and that these children experienced more difficulties on the CSHQ subscales compared with their typically developing peers. These difficulties were indicated on the Sleep Duration, Parasomnias, Sleep Disordered Breathing, and Daytime Sleepiness subscales. All of these subscales except for Parasomnia had significant low-level negative correlations with the SPM–HF subscales in the current study. The CSHQ Sleep Duration subscale shared a weak but significant correlation with the SPM–HF Planning and Ideas, Touch, and Taste and Smell subscales. This suggests that the more problems indicated in the SPM–HF subscales, the less likely the child was to experience problems as identified by the CSHQ sleep subscales. This finding adds support to Shochat et al.’s (2009) study, in which typically developing children were less likely to experience sleep problems indicated by the CSHQ.

Influence of Sensory Processing on Sleep Habits and Patterns

Our literature review identified a gap in child-reported data on sleep patterns and habits. To obtain a client-centered perspective from children that describes a subjective experience (e.g., sleep), it was necessary to collect information directly from the children, and this was achieved with the CRSP. This study found a significant negative predictive relationship between the SPM–HF Balance and Motion subscale and the CRSP Restless Legs subscale (variance = 14.6%), indicating that although children may have some problems with balance and motion, they are less likely to experience symptoms associated with restless legs. The cause of restless legs syndrome is unknown, and the syndrome is commonly associated with other conditions experienced by the individual (Klingelhoefer, Bhattacharya, & Reichmann, 2016).

Higher scores on the SPM–HF Planning and Ideas subscale had a negative predictive relationship with the CRSP Activities Before Bed subscale (variance = 12.1%), indicating that the children were more likely to report a desirably calm bedtime routine. Pfeiffer et al. (2015) used the SPM–HF and reported that children with attention deficit hyperactivity disorder often presented with problems in the area of planning and ideas. Together, these results suggest that children with sensory processing dysfunction may have difficulties with the daily occupation of sleep, in particular as it relates to sleep preparation activities (similar to the CRSP Activities Before Bed subscale).

Limitations and Future Research

In this study we collected data from a small sample of 45 typically developing children from a specific geographical region; therefore, generalizing these findings to a wider population should be done with caution. The participants volunteered to take part in the study, however, and this may have biased the data collected because of the convenience sampling approach we used.

The current study revealed significant correlations and predictive relationships between children’s sensory processing issues and their sleep habits and patterns. This relationship should be further examined in additional studies with a larger sample of children and parents and a wider range of age groups. A study comparing children with known sensory processing dysfunction with a group of typically developing children would provide further evidence about the relationship between children’s sensory processing abilities and their sleep habits and patterns. Future studies that include the perspective of the child are also strongly recommended.

Implications for Occupational Therapy Practice

Our findings indicate that significant associations exist between children’s sensory processing abilities and their functional participation in sleep occupations and therefore provide a preliminary reference point from which to assess children referred to occupational therapy for sleep problems. Key points for occupational therapy practice are as follows:

Sleep is an important and essential occupation for children.

Several predictive relationships exist between children’s sensory processing and their sleep habits and patterns.

Clinicians should evaluate children’s sleep as part of their assessments.

Conclusion

This study provides preliminary insights into the relationship between the sensory processing patterns of typically developing children and their sleep habits and patterns. It also established that several predictive relationships exist between children’s sensory processing components and their sleep habits and patterns. This study provides a reference point for clinicians when evaluating whether sensory processing may influence key components of children’s occupational performance (i.e., sleep). We also suggest using a combination of parent-proxy and child self-report sleep scales.

Footnotes

Acknowledgments

The authors sincerely acknowledge all participants and their families who volunteered to take part in this study. We also thank the organizations that supported our recruitment. This project was completed without any formal funding, and the authors report no conflicts of interest.

The two authors were involved in the development, design, and execution of this study. The first author drafted the initial version of the manuscript, and the other author provided critical feedback during its revision and further refinement.

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