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Feasibility of Actigraphy for Evaluating Sleep and Daytime Physical Activity in Children with Autism Spectrum Disorder

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Title: Feasibility of Actigraphy for Evaluating Sleep and Daytime Physical Activity in Children with Autism Spectrum Disorder
Language: English
Authors: Alder, M. L. (ORCID 0000-0002-7817-3476), Johnson, C. R., Zauszniewski, J. A., Malow, B. A., Burant, C. J., Scahill, L.
Source: Journal of Autism and Developmental Disorders. Sep 2023 53(9):3670-3682.
Availability: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
Peer Reviewed: Y
Page Count: 13
Publication Date: 2023
Sponsoring Agency: Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) (DHHS/NIH)
Contract Number: R01HD099480
Document Type: Journal Articles
Reports - Research
Descriptors: Sleep, Physical Activity Level, Young Children, Autism Spectrum Disorders, Measurement Equipment, Behavior Problems, Child Behavior, Measurement Techniques
DOI: 10.1007/s10803-022-05661-5
ISSN: 0162-3257
1573-3432
Abstract: This research evaluated the feasibility of actigraphy to measure sleep and physical activity in children (ages 2-8 years) with autism spectrum disorder (ASD). We also explored associations between sleep and physical activity. Validated screening measures established eligibility. Questionnaires, diaries, and 5 days and 5 nights of actigraphy monitoring were used to collect data. Of the 32 children enrolled, 27 (84.4%) completed actigraphy monitoring. Based on the median steps per day, children with high physical activity had lower total sleep time and more disruptive behaviors than children with low physical activity. Findings support the feasibility of using actigraphy to measure sleep and physical activity in children with ASD. Larger studies are needed to evaluate interactions of physical activity on sleep in this population.
Abstractor: As Provided
Entry Date: 2023
Accession Number: EJ1390506
Database: ERIC
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  Value: <anid>AN0170899339;aut01sep.23;2023Aug31.03:50;v2.2.500</anid> <title id="AN0170899339-1">Feasibility of Actigraphy for Evaluating Sleep and Daytime Physical Activity in Children with Autism Spectrum Disorder </title> <p>This research evaluated the feasibility of actigraphy to measure sleep and physical activity in children (ages 2–8 years) with autism spectrum disorder (ASD). We also explored associations between sleep and physical activity. Validated screening measures established eligibility. Questionnaires, diaries, and 5 days and 5 nights of actigraphy monitoring were used to collect data. Of the 32 children enrolled, 27 (84.4%) completed actigraphy monitoring. Based on the median steps per day, children with high physical activity had lower total sleep time and more disruptive behaviors than children with low physical activity. Findings support the feasibility of using actigraphy to measure sleep and physical activity in children with ASD. Larger studies are needed to evaluate interactions of physical activity on sleep in this population.</p> <p>Keywords: Actigraphy; Autism spectrum disorder; Disruptive behavior; Physical activity; Sleep</p> <p>Autism spectrum disorder (ASD) is a neurodevelopmental disorder affecting an estimated 1 in 44 children in the United States (Maenner et al., [<reflink idref="bib39" id="ref1">39</reflink>]). In addition to defining features of impaired social communication and repetitive behavior, children with ASD may show disruptive behaviors (such as aggression, tantrums, self-injury, hyperactivity), anxiety, feeding disorders and sleep problems (Christensen et al., [<reflink idref="bib13" id="ref2">13</reflink>]). Across a range of severity, as many as 80% of children on the autism spectrum have significant sleep problems and 63% do not meet the recommended daily physical activity levels (Goldman et al., [<reflink idref="bib22" id="ref3">22</reflink>]; Levin & Scher, [<reflink idref="bib36" id="ref4">36</reflink>]; Mazzone et al., [<reflink idref="bib44" id="ref5">44</reflink>]; Pan, [<reflink idref="bib55" id="ref6">55</reflink>]). These challenges contribute to parental stress and hinder family quality of life (Khanna et al., [<reflink idref="bib35" id="ref7">35</reflink>]; Postorino et al., [<reflink idref="bib57" id="ref8">57</reflink>]).</p> <hd id="AN0170899339-2">Sleep Problems and Disruptive Behavior in Children with ASD</hd> <p>Sleep problems in children with ASD include: bedtime resistance, trouble falling asleep, maintaining sleep, parasomnias (e.g., bruxism, night terrors), early morning awakening (Johnson et al., [<reflink idref="bib30" id="ref9">30</reflink>]; Katz et al., [<reflink idref="bib34" id="ref10">34</reflink>]). Parents may also report resulting daytime sleepiness (Devnani & Hegde, [<reflink idref="bib17" id="ref11">17</reflink>]). Sleep disturbances in children with ASD are multifactorial and may persist into adulthood (Goldman et al., [<reflink idref="bib23" id="ref12">23</reflink>]). Factors that may contribute to sleep disturbance in children with ASD include: heightened arousal, anxiety, adverse effects of medication, genetic (i.e., altered sleep–wake rhythms; Charrier et al., [<reflink idref="bib12" id="ref13">12</reflink>]), environmental (i.e., light exposure), physical inactivity, iron deficiency, and poor sleep hygiene (i.e., lack of an established bedtime routine; Devnani & Hegde, [<reflink idref="bib17" id="ref14">17</reflink>]; Dosman et al., [<reflink idref="bib18" id="ref15">18</reflink>]; Esteves et al., [<reflink idref="bib19" id="ref16">19</reflink>]; Johnson et al., [<reflink idref="bib29" id="ref17">29</reflink>]; Malow & McGrew, [<reflink idref="bib42" id="ref18">42</reflink>]; Mazzone et al., [<reflink idref="bib44" id="ref19">44</reflink>]; Souders et al., [<reflink idref="bib68" id="ref20">68</reflink>]). Insufficient sleep in children with ASD is associated with increased irritability, stereotypic behavior, and decreased participation in learning opportunities (Cohen et al., [<reflink idref="bib14" id="ref21">14</reflink>]; Mazurek & Sohl, [<reflink idref="bib43" id="ref22">43</reflink>]; Schreck et al., [<reflink idref="bib63" id="ref23">63</reflink>]). Abel and colleagues ([<reflink idref="bib1" id="ref24">1</reflink>]) reported that poor sleep as measured by actigraphy was associated with disruptive behavior. The importance of sleep quality on overall development and disruptive behavior underscores the need for a deeper study on sleep disturbances in children on the autism spectrum.</p> <hd id="AN0170899339-3">Sleep and Physical Activity Level in Children with ASD</hd> <p>Daytime physical activity improves sleep in some pediatric populations but not others (Orsey et al., [<reflink idref="bib52" id="ref25">52</reflink>]). In a sample of obese adolescents, Mendelson et al. ([<reflink idref="bib49" id="ref26">49</reflink>]) reported that a regimented exercise program increased sleep duration. By contrast, in a sample of young children in the general pediatric population, Williams et al. ([<reflink idref="bib77" id="ref27">77</reflink>]) reported that children with high levels of physical activity had lower sleep duration than those with lower levels of physical activity. For some children with ASD, high physical activity levels may improve sleep duration (Brand et al., [<reflink idref="bib11" id="ref28">11</reflink>]; Wachob & Lorenzi, [<reflink idref="bib74" id="ref29">74</reflink>]). Studies in youth on the autism spectrum also show variable association with high or low physical activity and sleep problems (Memari et al., [<reflink idref="bib48" id="ref30">48</reflink>]; Wachob & Lorenzi, [<reflink idref="bib74" id="ref31">74</reflink>]). Youth with ASD have behavioral characteristics that may influence physical activity and sleep compared to other pediatric populations. Behavioral phenotypes such as overarousal, hyperactivity may affect physical activity and sleep (McGimsey & Favell, [<reflink idref="bib46" id="ref32">46</reflink>]). Motor delays and sensorimotor impairments may also influence physical activity and, indirectly, sleep problems in children with ASD (Srinivasan et al., [<reflink idref="bib69" id="ref33">69</reflink>]). As with children in the general pediatric population, low physical activity levels in children with ASD may also affect the likelihood of health problems such as obesity and cardiovascular disease (Curtin et al., [<reflink idref="bib16" id="ref34">16</reflink>]; McCoy, [<reflink idref="bib45" id="ref35">45</reflink>]).</p> <hd id="AN0170899339-4">Actigraphy in Children with ASD</hd> <p>Actigraphy is an objective, non-invasive way to measure sleep duration, sleep efficiency, and daytime physical activity in the home setting (Memari et al., [<reflink idref="bib48" id="ref36">48</reflink>]). Actigraphy has been used to measure sleep and physical activity in various pediatric populations (Meltzer et al., [<reflink idref="bib47" id="ref37">47</reflink>]; Sitnick et al., [<reflink idref="bib66" id="ref38">66</reflink>]). To date, few studies have used actigraphy to evaluate physical activity in children with ASD (Moore et al., [<reflink idref="bib51" id="ref39">51</reflink>]; Richdale & Schreck, [<reflink idref="bib58" id="ref40">58</reflink>]; Souders et al., [<reflink idref="bib68" id="ref41">68</reflink>]; Wiggs & Stores, [<reflink idref="bib76" id="ref42">76</reflink>]). Actigraphy measures movement with a watch-like device (i.e., actigraph) that may be worn on the wrist or ankle as a proxy measure of a child's sleep–wake cycle and daytime physical activity (Hodge et al., [<reflink idref="bib27" id="ref43">27</reflink>]; Moore et al., [<reflink idref="bib51" id="ref44">51</reflink>]). Sleep indices include total sleep time (TST), sleep onset latency (SOL), wake after sleep onset (WASO), and sleep efficiency (SE%; Malow et al., [<reflink idref="bib41" id="ref45">41</reflink>]; Moore et al., [<reflink idref="bib51" id="ref46">51</reflink>]), which provide inferences about sleep quality. In children with ASD, studies have reported that poor sleepers had increased SOL, decreased TST, and decreased SE% compared to good sleepers (Goldman et al., [<reflink idref="bib21" id="ref47">21</reflink>]; Malow et al., [<reflink idref="bib40" id="ref48">40</reflink>]). Actigraphy measures of physical activity can be divided into four categories: type (e.g., structured swimming), timing (e.g., morning), intensity (e.g., moderate), and duration (e.g., minutes). Common physical activity indices include steps per day and intensity: light and moderate-to-vigorous physical activity (MVPA; Johansson et al., [<reflink idref="bib28" id="ref49">28</reflink>]). A barrier to the use of actigraphy in children with ASD is the well-documented sensory sensitivities that may reduce compliance with wearing the actigraphy device (Adkins et al., [<reflink idref="bib2" id="ref50">2</reflink>]). Compliance with actigraphy may encounter additional challenges in studies designed to monitor sleep and physical activity over several days (Malow et al., [<reflink idref="bib40" id="ref51">40</reflink>]; Moore et al., [<reflink idref="bib51" id="ref52">51</reflink>]). To date, little is known about physical activity measured by wrist actigraphy in young children on the autism spectrum.</p> <p>To our knowledge, no prior studies have used wrist actigraphy to measure sleep and daytime physical activity in combination with parent-report measures in young children with ASD. The purpose of this study was to evaluate the feasibility of using actigraphy to measure sleep and physical activity in children with ASD and to gather preliminary data on the association of sleep and physical activity in this population.</p> <hd id="AN0170899339-5">Methods</hd> <p></p> <hd id="AN0170899339-6">Participants</hd> <p>The study conformed to the Declaration of Helsinki standards and was approved by the Case Western Reserve University Institutional Review Board (IRB). Legal guardian signature was obtained prior to data collection. A sample of 32 children with a community, medical practitioner diagnosis of ASD ages 2 to 8 years were recruited through Facebook support groups, autism schools, and outpatient services. Parents were told that the purpose of this study was to evaluate the effect of physical activity on sleep and that the study did not require the child to have a sleep problem. Parents completed a screening phone call with the principal investigator (MLA) to review the study procedures and eligibility criteria. Eligible children age ≥ 4 years scored 15 or higher on the Social Communication Questionnaire (SCQ; Rutter et al., [<reflink idref="bib60" id="ref53">60</reflink>]); children < 4 years scored 8 or higher on the Modified Checklist for Autism in Toddlers, Revised (M-CHAT-R; Robins et al., [<reflink idref="bib59" id="ref54">59</reflink>]). Children with known or suspected sleep disordered breathing (e.g., snoring) or parasomnias were excluded based on the parent-reported medical history and the Modified Simonds and Parraga Sleep Questionnaire (MSPSQ; Simonds & Parraga, [<reflink idref="bib65" id="ref55">65</reflink>]). These children were referred to a pediatric sleep clinic.</p> <p>Of the 38 children screened by telephone, six were excluded. Four children did not meet the age criterion, another child with suspected sleep disordered breathing was referred to a sleep clinic, and one did not meet ASD screening threshold on the SCQ.</p> <hd id="AN0170899339-7">Screening Measures</hd> <p></p> <hd id="AN0170899339-8">Social Communication Questionnaire, lifetime version (SCQ)</hd> <p>The SCQ (Rutter et al., [<reflink idref="bib60" id="ref56">60</reflink>]) is a 40-item (Yes/No) parent-reported screening measure for ASD in children ≥ 4 years. The SCQ is based on algorithm items from the Autism Diagnostic Interview, Revised (ADI-R; Rutter et al., [<reflink idref="bib60" id="ref57">60</reflink>]). The cutoff score of 15 is recommended in the SCQ manual with a sensitivity of 0.96 and specificity of 0.80 (Berument et al., [<reflink idref="bib9" id="ref58">9</reflink>]). For children with phrase speech, the ability to talk using short phrases or sentences, the internal consistency is high (Kuder-Richardson 20 = 0.87; Rutter et al., [<reflink idref="bib60" id="ref59">60</reflink>]). In this study, the internal consistency estimate (Kuder-Richardson 20) was 0.59 on the SCQ.</p> <hd id="AN0170899339-9">Modified Checklist for Autism in Toddlers, revised (M-CHAT-R)</hd> <p>The M-CHAT-R is a 20-item (Yes/No) parent-reported screening measure used to detect toddlers 16 to 30 months with an increased likelihood for ASD (Robins et al., [<reflink idref="bib59" id="ref60">59</reflink>]). Higher scores indicate an increased likelihood of ASD: scores 0–2 indicate low likelihood; scores 3–7 indicate a moderate likelihood; scores 8–20 indicate a high likelihood (Robins et al., [<reflink idref="bib59" id="ref61">59</reflink>]). The M-CHAT-R was collected on children < 4 years of age. The total M-CHAT-R score falls below the adequate internal consistency threshold (Kuder-Richardson 20 = 0.63; Robins et al., [<reflink idref="bib59" id="ref62">59</reflink>]). Despite this recognized limitation, the measure is widely used and was selected for this study. In this study, the internal consistency estimate (Kuder-Richardson 20) was 0.82 on the M-CHAT-R.</p> <hd id="AN0170899339-10">Modified Simonds and Parraga Sleep Questionnaire (MSPSQ)</hd> <p>The MSPSQ is a 36-item tool designed to screen for sleep problems in youth with developmental disabilities ages 5 to 18 years (Simonds & Parraga, [<reflink idref="bib65" id="ref63">65</reflink>]; Wiggs & Stores, [<reflink idref="bib75" id="ref64">75</reflink>]). In this study, we used 16 items comprised of sleep disordered breathing (5 items) and parasomnias (11 items). Items are scored from 1 to 5: 1 = never, 2 = about once a month, 3 = a few times a month, 4 = once or twice a week, and 5 = many times a week or daily for a possible range of 16 to 80. Maas and colleagues ([<reflink idref="bib38" id="ref65">38</reflink>]) reported good internal consistency (Cronbach's alpha = 0.80) and solid convergent validity with the Sleep Disturbance Scale for Children (<emph>r</emph> = 0.79, <emph>p</emph> < 0.001). In this study, the internal consistency estimate (Cronbach's alpha) was 0.78 and 0.52 for the sleep disordered breathing and parasomnia subscales, respectively.</p> <hd id="AN0170899339-11">Outcome Measures</hd> <p></p> <hd id="AN0170899339-12">Actigraphy</hd> <p>Per protocol, we planned to collect sleep and physical activity movement data for 5 consecutive days and nights (Monday–Friday) with an actigraph device placed on the child's non-dominant wrist using the ActiGraph wGT3X-BT (Pensacola, FL). Compared to gold standard polysomnography, actigraphy has a high sensitivity (0.94 ± 0.06) to detect sleep and a moderate specificity (0.5 ± 0.2) to detect wake after sleep onset in children with ASD (Yavuz-Kodat et al., [<reflink idref="bib78" id="ref66">78</reflink>]). Five consecutive nights is recommended for optimal use of the sleep scoring algorithm (Acebo et al., 1999). However, not all children in this study were able to wear the device for five nights. Based on previous studies, we prespecified that each participant had to have ≥ 4 nights of sleep to be included in data analysis and have ≥ 3 days of 6 h per day for physical activity (Allik et al., [<reflink idref="bib3" id="ref67">3</reflink>]; Bisson et al., [<reflink idref="bib10" id="ref68">10</reflink>]; Thomas & Burr, [<reflink idref="bib71" id="ref69">71</reflink>]). Data were initialized with Firmware version 1.9.2 and sampled at 30-Hertz with a normal activity filter. Actigraphy data were computed with ActiLife version 6.13.4 (2019).</p> <p>Actigraphy sleep measures, nighttime movement events, were averaged over ≥ 4 nights and included sleep efficiency % (SE% = percentage of time spent asleep divided by time in bed X 100), total sleep time (TST = minutes from sleep onset to wake), sleep onset latency (SOL = minutes from bedtime to sleep onset), and wake after sleep onset (WASO = minutes spent awake after sleep onset). The Sadeh ([<reflink idref="bib61" id="ref70">61</reflink>]) algorithm with a 60-s epoch interval was used to analyze actigraphy sleep data. The Sadeh algorithm is a well-validated measure of the sleep–wake cycle with comparison data in pediatric populations (Meltzer et al., [<reflink idref="bib47" id="ref71">47</reflink>]; Sadeh, [<reflink idref="bib61" id="ref72">61</reflink>]).</p> <p>The Johansson et al. ([<reflink idref="bib28" id="ref73">28</reflink>]) vector magnitude (VM) algorithm with a 5-s epoch interval for preschoolers was used to analyze actigraphy physical activity data. A 5-s epoch interval is recommended to capture short bursts of moderate-to-vigorous physical activity (MVPA) for young children; longer epoch lengths (e.g., 60-s) are used to examine sedentary behavior (Altenburg et al., [<reflink idref="bib4" id="ref74">4</reflink>]; Johansson et al., [<reflink idref="bib28" id="ref75">28</reflink>]). VM counts ≥ 1393 per 5-s epoch were classified as MVPA. Actigraphy physical activity measures included the mean steps, MVPA, and MVPA% (percentage of time per day spent in MVPA intensity levels divided by time in sedentary, light, and MVPA X 100).</p> <hd id="AN0170899339-13">Sleep and Physical Activity Diaries</hd> <p>Parents completed sleep and physical activity diaries to record bedtime, waketime, total sleep days, and total activity days scored. Sleep diaries were used to aid scoring of the actigraphy data. The physical activity diary was used to classify: sedentary-light-physical activity (e.g., watching tv, walking), moderate-physical activity (e.g., playing outside, riding a bike), and vigorous-physical activity (e.g., running, jogging).</p> <hd id="AN0170899339-14">Modified Children's Sleep Habits Questionnaire (M-CSHQ)</hd> <p>The M-CSHQ is commonly used parent-reported sleep assessment in young children with ASD (Moore et al., [<reflink idref="bib51" id="ref76">51</reflink>]). The M-CSHQ is specifically designed to screen for the most common sleep disturbances in children aged 4–10 years as described in the International Classification of Sleep Disorders (Katz et al., [<reflink idref="bib34" id="ref77">34</reflink>]; Shui et al., [<reflink idref="bib64" id="ref78">64</reflink>]; Thorpy, [<reflink idref="bib72" id="ref79">72</reflink>]). In this study we used the modified 23-item parent-report M-CSHQ (Katz et al., [<reflink idref="bib34" id="ref80">34</reflink>]). This version includes four subscales: Sleep Initiation and Duration, Sleep Anxiety/Co-Sleeping, Night Waking/Parasomnias, and Daytime Sleepiness (Katz et al., [<reflink idref="bib34" id="ref81">34</reflink>]). On the M-CSHQ, items are scored on a 3-point scale: 1 = up to one night per week; 2 = 2–4 times per week; 3 = 5–7 nights per week (Owens et al., [<reflink idref="bib53" id="ref82">53</reflink>]). The M-CSHQ subscales show a range of internal consistency (Cronbach's alpha = 0.67 to 0.81; Katz et al., [<reflink idref="bib34" id="ref83">34</reflink>]). A total score of ≥ 35 was used as a threshold to indicate sleep problems (Shui et al., [<reflink idref="bib64" id="ref84">64</reflink>]). In this study, the internal consistency estimate (Cronbach's alpha) was 0.86 on the M-CSHQ.</p> <hd id="AN0170899339-15">Aberrant Behavior Checklist (ABC)</hd> <p>The ABC is a 58-item parent-report measure consisting of five subscales. In this study, we used the 15-item Aberrant Behavior Checklist-Irritability subscale (ABC-I; Aman & Singh, [<reflink idref="bib5" id="ref85">5</reflink>]). The ABC-I subscale includes items on tantrums, mood instability, aggression, and self-injury and has been used as an outcome measure in many intervention studies (Bearss et al., [<reflink idref="bib7" id="ref86">7</reflink>]; Scahill et al., [<reflink idref="bib62" id="ref87">62</reflink>]). The ABC-I is scored on a 3-point scale from 0 (not a problem) to 3 (the problem is severe in degree) and a total score of 0 to 45. The ABC has excellent internal consistency (Cronbach's alpha = 0.92; Kaat et al., [<reflink idref="bib33" id="ref88">33</reflink>]). A score of ≥ 15 was used a threshold for moderate behavior problems (Bearss et al., [<reflink idref="bib7" id="ref89">7</reflink>]). In this study, the internal consistency estimate (Cronbach's alpha) was 0.93 on the ABC-I.</p> <hd id="AN0170899339-16">Study Design and Procedures</hd> <p>This cross-sectional study was conducted during the COVID-19 pandemic. Thus, modifications were made to accommodate the pandemic health precautions. Screening for eligibility began with a phone call followed by written informed consent. The research electronic data capture (REDCap) system was used to collect online survey data (Harris et al., [<reflink idref="bib25" id="ref90">25</reflink>], [<reflink idref="bib26" id="ref91">26</reflink>]). Consented participants first completed online screening questionnaires, and if eligible, were then asked to complete online questionnaires. The online questionnaires were completed in the order listed above. The total time to complete the online questionnaires was approximately 1 h and 30 min. After completing the online questionnaires, participants scheduled a video conferencing (Zoom; Barbu, [<reflink idref="bib6" id="ref92">6</reflink>]) session and received an actigraph by mail. The lead investigator (MLA) then conducted the Zoom session with the parent, and child in some cases, on the use of the actigraphy device. To protect privacy of participants, IRB-approved conventions such as creating a waiting room and assigning individualized meeting passcodes were used. The 15–30-min Zoom sessions were not recorded. To increase actigraphy watch compliance, parents were given the following strategies: extra time to practice, different wrist bands to reduce discomfort from sensory sensitivities, positive reinforcement, and desensitization by increasing amount of time wearing the device. Similar strategies have been successful in previous studies (Fawkes et al., [<reflink idref="bib20" id="ref93">20</reflink>]; Johnson et al., [<reflink idref="bib31" id="ref94">31</reflink>]). Parents were asked to report the child's medical history, bedtime information, and medications. Participants received $25 for completing the online surveys and $25 for completing the actigraphy protocol.</p> <hd id="AN0170899339-17">Analysis</hd> <p>Descriptive statistics including mean, standard deviation, median and range were calculated on demographics and parent ratings for the full sample. Internal consistency (Cronbach's alpha or Kuder-Richardson 20) was calculated when appropriate. The descriptive results for actigraphy included children with complete actigraphy data.</p> <p>To evaluate feasibility, we calculated the percentage of children who met or exceeded prespecified thresholds of ≥ 3 days of 6 h per day for physical activity and ≥ 4 nights of sleep, percentages of completed diaries, and completed online surveys. Acceptability was supported by parental attendance and participation in Zoom sessions. Of interest were the percentages of study participants who met the age-specific guidelines on the actigraphy sleep indices of SE%, TST, and SOL. Mean values on each child were compared to published guidelines by Merbler et al. ([<reflink idref="bib50" id="ref95">50</reflink>]). Actigraphy SE < 85%, SOL ≥ 30 min, or WASO ≥ 30 min indicate poor sleep quality (Lichstein et al., [<reflink idref="bib37" id="ref96">37</reflink>]; Souders et al., [<reflink idref="bib67" id="ref97">67</reflink>], [<reflink idref="bib68" id="ref98">68</reflink>]). To determine whether children had adequate daily sleep time, actigraphy TST and parent-reported daytime naps in minutes on sleep diaries were compared to age-specific developmental recommendations from the American Academy of Sleep Medicine (1–2 years of age = 11–14 h including naps; 3–5 years of age = 10–13 h including naps; 6–12 years of age = 9–12 h; Paruthi et al., [<reflink idref="bib56" id="ref99">56</reflink>]).</p> <p>Exploratory analyses compared findings on parent-reported sleep problems and parent-reported disruptive behavior to primary actigraphy sleep and physical activity indices. To explore the effect of physical activity, two-tailed independent samples <emph>t</emph>-tests were used to compare children with high physical activity to those with low physical activity on the four most common actigraphy sleep indices (SE%, SOL, TST, WASO), parent-reported sleep disturbances (M-CSHQ), and parent-reported disruptive behavior (ABC-I). High physical activity was defined as ≥ to the median of 12,129.40 steps per day; low physical activity < 12,129.40 steps per day. Data analyses were conducted with IBM SPSS statistics, version 28 (Armonk, NY, 2021). A <emph>p</emph> value < 0.05 was considered significant.</p> <hd id="AN0170899339-18">Results</hd> <p>Participants included 32 children (24 boys, 8 girls) with a mean age of 5 years and 6 months ± 1 year and 8 months (Median = 5 years and 10 months; See Table 1). Other parent-reported medical history in Table 1 included amblyopia, low muscle tone/motor delays, weed pollen allergy, constipation, tonsillectomy and adenoidectomy, apraxia, global developmental delay and expressive-receptive disorder, albinism, and KDM5C (Lysine Demethylase 5C). Twenty-five children (78.1%) were taking medications; 18 children (72%) were taking more than one medication. Based on parent report, one participant had a caffeinated beverage after 6 pm; 31 did not. Eleven children had access to screen-based media devices (e.g., iPad, television) 30 min before bedtime; 21 did not.</p> <p>Table 1 Demographic, clinical, and medical characteristics (<emph>N</emph> = 32)</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left"><p>Child clinical characteristics</p></th><th align="left"><p>Mean ± SD</p></th><th align="left"><p>Median</p></th><th align="left"><p><italic>N</italic> (%)</p></th></tr></thead><tbody><tr><td align="left" colspan="4"><p>Screening measures</p></td></tr><tr><td align="left"><p> M-CHAT-R (<italic>n</italic> = 6)</p></td><td char="." align="char"><p>12.17 ± 2.71</p></td><td align="left"><p>13</p></td><td char="." align="char" /></tr><tr><td align="left"><p> SCQ (<italic>n</italic> = 26)</p></td><td char="." align="char"><p>22.65 ± 4.66</p></td><td align="left"><p>23</p></td><td char="." align="char" /></tr><tr><td align="left"><p> MSPSQ sleep disordered breathing</p></td><td char="." align="char"><p>8.84 ± 4.48</p></td><td align="left"><p>7</p></td><td char="." align="char" /></tr><tr><td align="left"><p> MSPSQ parasomnias</p></td><td char="." align="char"><p>22.78 ± 6.42</p></td><td align="left"><p>21.50</p></td><td char="." align="char" /></tr><tr><td align="left" colspan="4"><p>Outcome variables</p></td></tr><tr><td align="left"><p> M-CSHQ</p></td><td char="." align="char"><p>39.03 ± 8.58</p></td><td align="left"><p>39.50</p></td><td char="." align="char" /></tr><tr><td align="left"><p> ABC-I</p></td><td char="." align="char"><p>16.69 ± 9.80</p></td><td align="left"><p>16.50</p></td><td char="." align="char" /></tr><tr><td align="left" colspan="4"><p>Medical conditions</p></td></tr><tr><td align="left"><p> Gastrointestinal reflux disorder</p></td><td char="." align="char" /><td align="left" /><td char="(" align="char"><p>2 (6.3%)</p></td></tr><tr><td align="left"><p> Asthma</p></td><td char="." align="char" /><td align="left" /><td char="(" align="char"><p>2 (6.3%)</p></td></tr><tr><td align="left"><p> Eczema/itching</p></td><td char="." align="char" /><td align="left" /><td char="(" align="char"><p>7 (21.9%)</p></td></tr><tr><td align="left"><p> Iron deficiency</p></td><td char="." align="char" /><td align="left" /><td char="(" align="char"><p>3 (9.4%)</p></td></tr><tr><td align="left" colspan="4"><p>Co-existing psychiatric disorders</p></td></tr><tr><td align="left"><p> ADHD</p></td><td char="." align="char" /><td align="left" /><td char="(" align="char"><p>11 (34.4%)</p></td></tr><tr><td align="left"><p> Oppositional defiant disorder</p></td><td char="." align="char" /><td align="left" /><td char="(" align="char"><p>1 (3.1%)</p></td></tr><tr><td align="left"><p> Anxiety</p></td><td char="." align="char" /><td align="left" /><td char="(" align="char"><p>7 (21.9%)</p></td></tr><tr><td align="left"><p>Other medical diagnoses</p></td><td char="." align="char" /><td align="left" /><td char="(" align="char"><p>9 (28.1%)</p></td></tr><tr><td align="left" colspan="4"><p>Medications for sleep</p></td></tr><tr><td align="left"><p> Clonidine</p></td><td char="." align="char" /><td align="left" /><td char="(" align="char"><p>2 (6.3%)</p></td></tr><tr><td align="left"><p> Melatonin</p></td><td char="." align="char" /><td align="left" /><td char="(" align="char"><p>14 (43.8%)</p></td></tr><tr><td align="left"><p> Trazodone</p></td><td char="." align="char" /><td align="left" /><td char="(" align="char"><p>1 (3.1%)</p></td></tr><tr><td align="left" colspan="4"><p>Medications for impulsivity and distractibility</p></td></tr><tr><td align="left"><p> Guanfacine</p></td><td char="." align="char" /><td align="left" /><td char="(" align="char"><p>2 (6.3%)</p></td></tr><tr><td align="left"><p> Atomoxetine</p></td><td char="." align="char" /><td align="left" /><td char="(" align="char"><p>1 (3.1%)</p></td></tr><tr><td align="left" colspan="4"><p>Medications for anxiety</p></td></tr><tr><td align="left"><p> Fluoxetine</p></td><td char="." align="char" /><td align="left" /><td char="(" align="char"><p>1 (3.1%)</p></td></tr><tr><td align="left" colspan="4"><p>Medications for ADHD</p></td></tr><tr><td align="left"><p> Stimulants<sup>a</sup></p></td><td char="." align="char" /><td align="left" /><td char="(" align="char"><p>3 (9.4%)</p></td></tr><tr><td align="left"><p>Daily multivitamin or dietary supplements</p></td><td char="." align="char" /><td align="left" /><td char="(" align="char"><p>24 (75%)</p></td></tr><tr><td align="left"><p>Other medications<sup>b</sup></p></td><td char="." align="char" /><td align="left" /><td char="(" align="char"><p>2 (6.3%)</p></td></tr><tr><td align="left"><p>Weekly occupational therapy</p></td><td char="." align="char" /><td align="left" /><td char="(" align="char"><p>22 (68.8%)</p></td></tr><tr><td align="left"><p>Weekly physical therapy</p></td><td char="." align="char" /><td align="left" /><td char="(" align="char"><p>7 (21.9%)</p></td></tr><tr><td align="left"><p>Speech and language therapy</p></td><td char="." align="char" /><td align="left" /><td char="(" align="char"><p>24 (75%)</p></td></tr></tbody></table> </ephtml> </p> <p>Table 1 Demographic, clinical, and medical characteristics (<emph>N</emph> = 32)</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left"><p>Child and parent demographics</p></th><th align="left"><p>Mean ± SD</p></th><th align="left"><p>Median</p></th><th align="left"><p><italic>N</italic> (%)</p></th></tr></thead><tbody><tr><td align="left" colspan="4"><p>Child race</p></td></tr><tr><td align="left"><p> American Indian, Alaska Native</p></td><td char="." align="char" /><td align="left" /><td char="(" align="char"><p>1 (3.1%)</p></td></tr><tr><td align="left"><p> Black, African American</p></td><td char="." align="char" /><td align="left" /><td char="(" align="char"><p>6 (18.8%)</p></td></tr><tr><td align="left"><p> White</p></td><td char="." align="char" /><td align="left" /><td char="(" align="char"><p>25 (78.1%)</p></td></tr><tr><td align="left"><p> Unknown</p></td><td char="." align="char" /><td align="left" /><td char="(" align="char"><p>1 (3.1%)</p></td></tr><tr><td align="left"><p>Parent age (years)</p></td><td char="." align="char"><p>37.44 ± 6.30</p></td><td align="left"><p>37</p></td><td char="." align="char" /></tr><tr><td align="left" colspan="4"><p>Parent race</p></td></tr><tr><td align="left"><p> Black, African American</p></td><td char="." align="char" /><td align="left" /><td char="(" align="char"><p>3 (9.4%)</p></td></tr><tr><td align="left"><p> White</p></td><td char="." align="char" /><td align="left" /><td char="(" align="char"><p>29 (90.6%)</p></td></tr><tr><td align="left" colspan="4"><p>Parent Employment</p></td></tr><tr><td align="left"><p> Full time</p></td><td char="." align="char" /><td align="left" /><td char="(" align="char"><p>9 (28.1%)</p></td></tr><tr><td align="left"><p> Part time</p></td><td char="." align="char" /><td align="left" /><td char="(" align="char"><p>12 (37.5%)</p></td></tr><tr><td align="left"><p> Homemaker</p></td><td char="." align="char" /><td align="left" /><td char="(" align="char"><p>15 (46.9%)</p></td></tr><tr><td align="left"><p> Unemployed/disabled</p></td><td char="." align="char" /><td align="left" /><td char="(" align="char"><p>3 (9.4%)</p></td></tr><tr><td align="left"><p> Part time student</p></td><td char="." align="char" /><td align="left" /><td char="(" align="char"><p>1 (3.1%)</p></td></tr><tr><td align="left" colspan="4"><p>Parent race</p></td></tr><tr><td align="left"><p> Black, African American</p></td><td char="." align="char" /><td align="left" /><td char="(" align="char"><p>3 (9.4%)</p></td></tr><tr><td align="left"><p> White</p></td><td char="." align="char" /><td align="left" /><td char="(" align="char"><p>29 (90.6%)</p></td></tr><tr><td align="left" colspan="4"><p>Parent education</p></td></tr><tr><td align="left"><p> High school graduate or general education degree</p></td><td char="." align="char" /><td align="left" /><td char="(" align="char"><p>5 (15.6%)</p></td></tr><tr><td align="left"><p> Some college or 2-year degree</p></td><td char="." align="char" /><td align="left" /><td char="(" align="char"><p>5 (15.6%)</p></td></tr><tr><td align="left"><p> College graduate</p></td><td char="." align="char" /><td align="left" /><td char="(" align="char"><p>12 (37.5%)</p></td></tr><tr><td align="left"><p> Advanced graduate or professional degree</p></td><td char="." align="char" /><td align="left" /><td char="(" align="char"><p>10 (31.3%)</p></td></tr><tr><td align="left" colspan="4"><p>Household Income</p></td></tr><tr><td align="left"><p> < $20,000</p></td><td char="." align="char" /><td align="left" /><td char="(" align="char"><p>2 (6.3%)</p></td></tr><tr><td align="left"><p> $20,000-$40,000</p></td><td char="." align="char" /><td align="left" /><td char="(" align="char"><p>6 (18.8%)</p></td></tr><tr><td align="left"><p> $40,001-$60,000</p></td><td char="." align="char" /><td align="left" /><td char="(" align="char"><p>5 (15.6%)</p></td></tr><tr><td align="left"><p> $60,001-$90,000</p></td><td char="." align="char" /><td align="left" /><td char="(" align="char"><p>6 (18.8%)</p></td></tr><tr><td align="left"><p> > $90,000</p></td><td char="." align="char" /><td align="left" /><td char="(" align="char"><p>8 (25.0%)</p></td></tr><tr><td align="left"><p> Do not wish to answer</p></td><td char="." align="char" /><td align="left" /><td char="(" align="char"><p>5 (15.6%)</p></td></tr></tbody></table> </ephtml> </p> <p> <emph>ABC-I</emph> Aberrant Behavior Checklist—irritability subscale, <emph>ADHD</emph> attention-deficit/hyperactivity disorder, <emph>M-CSHQ</emph>Mmodified Children's Sleep Habits Questionnaire, <emph>M-CHAT-R</emph> Modified Checklist for Autism in Toddlers, revised, <emph>MSPSQ</emph> Modified Simonds and Parraga Questionnaire <emph>SCQ</emph> Social CommunicationQquestionnaire, lifetime version <sups>a</sups>Stimulants included amphetamine and methylphenidate <sups>b</sups>Other medications included polyethylene glycol 3350 and fluticasone propionate nasal spray</p> <p>Table 1 provides mean scores for SCQ, M-CHAT-R, MSPSQ, M-CSHQ, and ABC-I. The skewness and kurtosis values for all outcome variables indicated a normal distribution. Scores on the M-CSHQ ranged from 25 to 56; 21 of 32 (65.6%) had elevated scores on the M-CSHQ (i.e., ≥ 35; Shui et al., [<reflink idref="bib64" id="ref100">64</reflink>]). Scores on the ABC-I ranged from 0 to 35; 17 of 32 (53.1%) had moderate scores on the ABC-I (i.e., ≥ 15; Bearss et al., [<reflink idref="bib7" id="ref101">7</reflink>]).</p> <hd id="AN0170899339-19">Feasibility Outcomes</hd> <p>Parents of the 32 participants received the actigraphs by mail prior to the Zoom session, which was conducted by the principal investigator (MLA). Parents who attended the Zoom session reported that it was informative. One mother declined to attend the Zoom training session based on her conviction that the child would not tolerate wearing the actigraphy device. Four children of the 31 parents who attended the Zoom session subsequently refused to wear the actigraph. Thus, 27 (84.4%) children, who met prespecified criteria for actigraphy monitoring (i.e., ≥ 3 days of 6 h per day for physical activity and ≥ 4 nights of sleep), were included in the actigraphy analysis. Of the 32 parents, 27 provided sleep diaries and 29 provided physical activity diaries. There were no differences in mean age, mean scores on the M-CSHQ or ABC-I in children with complete actigraphy data and those without complete actigraphy data. There were no technical problems with actigraph data collection, and all collected data were analyzed. Online questionnaires were completed for all participants.</p> <hd id="AN0170899339-20">Sleep and Physical Activity Diaries</hd> <p>Of the 27 children with complete actigraphy data, parent-reported child bedtimes and waketimes ranged from 19:10 to 22:18 h (<emph>M</emph> = 20:43 ± 0:49, <emph>Median</emph> = 20:44) and 5:39 to 9:33 h (<emph>M</emph> = 7:17 ± 1:04, <emph>Median</emph> = 7:07). Actigraphy sleep indices were averaged over 4–5 nights (<emph>M</emph> = 4.89 ± 0.32 days, <emph>Median</emph> = 5); daytime physical activity measures over 3–5 days (<emph>M</emph> = 4.85 ± 0.46 days, <emph>Median</emph> = 5). Total daytime physical activity days averaged between 11 h and 35 min to 15 h per day (<emph>M</emph> = 13 h and 7 min ± 54 min, <emph>Median</emph> = 13 h and 6 min). The average number of minutes of daytime naps ranged between 0 and 138 min (<emph>M</emph> = 50.13 ± 48.12, <emph>Median</emph> = 48.50). Parents completed physical activity diaries for 29 of 32 participants and recorded 238 recorded activities. Of these, 29.4% were sedentary-light-physical activity; 45.8% were moderate-physical activity, and 24.8% were vigorous-physical activity (see Table 2).</p> <p>Table 2 Parent diary entries on physical activity by level of intensity (<emph>N</emph> = 29)</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left"><p>Activities (<italic>N</italic> = 238)</p></th><th align="left"><p><italic>N</italic> (%)<sup>a</sup></p></th></tr></thead><tbody><tr><td align="left" colspan="2"><p>Sedentary-light-intensity level</p></td></tr><tr><td align="left"><p> Walking</p></td><td char="(" align="char"><p>20 (8.4%)</p></td></tr><tr><td align="left"><p> Playing with Legos or building blocks</p></td><td char="(" align="char"><p>12 (5.0%)</p></td></tr><tr><td align="left"><p> Watching a movie or playing video games</p></td><td char="(" align="char"><p>12 (5.0%)</p></td></tr><tr><td align="left"><p> Completing puzzles or reading books</p></td><td char="(" align="char"><p>9 (3.8%)</p></td></tr><tr><td align="left"><p> Playing with water</p></td><td char="(" align="char"><p>9 (3.8%)</p></td></tr><tr><td align="left"><p> Crafting (i.e., chalk)</p></td><td char="(" align="char"><p>6 (2.5%)</p></td></tr><tr><td align="left"><p> Playing musical instruments (i.e., drums)</p></td><td char="(" align="char"><p>2 (0.8%)</p></td></tr><tr><td align="left" colspan="2"><p>Moderate-Intensity Level</p></td></tr><tr><td align="left"><p> Playing outside at a playground</p></td><td char="(" align="char"><p>59 (24.8%)</p></td></tr><tr><td align="left"><p> Swinging or rocking on gym equipment</p></td><td char="(" align="char"><p>16 (6.7%)</p></td></tr><tr><td align="left"><p> Riding a bike</p></td><td char="(" align="char"><p>12 (5.0%)</p></td></tr><tr><td align="left"><p> Playing catch (i.e., baseball, soccer, or t-ball)</p></td><td char="(" align="char"><p>10 (4.2%)</p></td></tr><tr><td align="left"><p> Playing tag or Hide-and-go-seek</p></td><td char="(" align="char"><p>5 (2.1%)</p></td></tr><tr><td align="left"><p> Playing on the balance beam or in a ball pit</p></td><td char="(" align="char"><p>4 (1.7%)</p></td></tr><tr><td align="left"><p> Playing on a slide</p></td><td char="(" align="char"><p>3 (1.3%)</p></td></tr><tr><td align="left" colspan="2"><p>Vigorous-Intensity Level</p></td></tr><tr><td align="left"><p> Running, jogging, hiking</p></td><td char="(" align="char"><p>23 (9.7%)</p></td></tr><tr><td align="left"><p> Jumping (i.e., ground, trampoline)</p></td><td char="(" align="char"><p>21 (8.8%)</p></td></tr><tr><td align="left"><p> Swimming</p></td><td char="(" align="char"><p>8 (3.4%)</p></td></tr><tr><td align="left"><p> Climbing a treehouse</p></td><td char="(" align="char"><p>6 (2.5%)</p></td></tr><tr><td align="left"><p> Wrestling</p></td><td char="(" align="char"><p>1 (0.4%)</p></td></tr></tbody></table> </ephtml> </p> <p>Parents maintained diaries for two children who did not wear the actigraph device <sups>a</sups>The number is the total activities recorded. The percentage is the number divided by 238</p> <hd id="AN0170899339-21">Actigraphy Sleep and Physical Activity Indices</hd> <p>Table 3 displays the means, standard deviations, and range of actigraphy sleep and physical activity indices. Based on published guidelines, 25 of 27 children had poor SE% (92.6%); 13 of 27 children had poor SOL (48.1%); 27 of 27 had poor WASO; 24 participants had inadequate TST (< 11 h for children 2 years of age; < 10 h for children 3 to 5 years of age; < 9 h for children 6 to 8 years of age; Lichstein et al., [<reflink idref="bib37" id="ref102">37</reflink>]; Paruthi et al., [<reflink idref="bib56" id="ref103">56</reflink>]; Souders et al., [<reflink idref="bib67" id="ref104">67</reflink>], [<reflink idref="bib68" id="ref105">68</reflink>]). For children ≤ 5 years of age (<emph>N</emph> = 10), parent-reported day time naps from the sleep diaries were included in the TST; 8 of 10 still fell below threshold. The physical activity analysis showed that MVPA counts per 5-s epochs per day ranged from 46.80 to 669.20. The MVPA % of time per day ranged from 0.57% and 7.08%.</p> <p>Table 3 Actigraphy sleep and physical activity indices (<emph>N</emph> = 27)</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left" colspan="2"><p>Indices</p></th><th align="left"><p>Mean ± SD</p></th><th align="left"><p>Median</p></th><th align="left"><p>Range</p></th></tr></thead><tbody><tr><td align="left" colspan="5"><p>Sleep</p></td></tr><tr><td align="left"><p> SE %</p></td><td char="±" align="char" colspan="2"><p>75.20 ± 6.88</p></td><td char="." align="char"><p>74.79</p></td><td char="." align="char"><p>59.39–89.74</p></td></tr><tr><td align="left"><p> SOL min</p></td><td char="±" align="char" colspan="2"><p>33.85 ± 28.07</p></td><td char="." align="char"><p>23.80</p></td><td char="–" align="char"><p>1.00–115.20</p></td></tr><tr><td align="left"><p> TST min</p></td><td char="±" align="char" colspan="2"><p>475.31 ± 41.69</p></td><td char="." align="char"><p>474.40</p></td><td char="–" align="char"><p>395.00–578.40</p></td></tr><tr><td align="left"><p> WASO min</p></td><td char="±" align="char" colspan="2"><p>125.99 ± 42.32</p></td><td char="." align="char"><p>122.60</p></td><td char="–" align="char"><p>56.20–228.80</p></td></tr><tr><td align="left" colspan="5"><p>Physical activity</p></td></tr><tr><td align="left"><p> MVPA counts per day</p></td><td char="±" align="char" colspan="2"><p>260.11 ± 155.58</p></td><td char="." align="char"><p>236.80</p></td><td char="–" align="char"><p>46.80–669.20</p></td></tr><tr><td align="left"><p> MVPA % per day</p></td><td char="±" align="char" colspan="2"><p>2.80 ± 1.60</p></td><td char="." align="char"><p>2.41</p></td><td char="–" align="char"><p>0.57–7.08</p></td></tr><tr><td align="left"><p> Steps per day</p></td><td char="±" align="char" colspan="2"><p>12,335.24 ± 2971.98</p></td><td char="." align="char"><p>12,129.40</p></td><td char="–" align="char"><p>5031.40–18,281.20</p></td></tr></tbody></table> </ephtml> </p> <p>MVPA is counts per 5-s epochs per day (Johansson et al., [<reflink idref="bib28" id="ref106">28</reflink>]). MVPA % is percentage of time per day spent in MVPA intensity levels divided by time in sedentary, light, and MVPA X 100 <emph>MVPA</emph> moderate-to-vigorous physical activity, <emph>SE</emph> sleep efficiency, <emph>SOL</emph> sleep onset latency, <emph>TST</emph> total sleep time, <emph>WASO</emph> wake after sleep onset</p> <hd id="AN0170899339-22">High Physical Activity and Low Physical Activity Differences in Sleep and Disruptive Behavior</hd> <p>Table 4 displays the results of independent sample <emph>t</emph>-tests for children with high physical activity vs those with low physical activity. High physical activity was defined as ≥ to the median of 12,129.40 steps per day; low physical activity < 12,129.40 steps per day. There were no physical activity group differences on SE%, SOL, WASO or M-CSHQ. Children with high physical activity had significantly lower TST minutes (<emph>M</emph> = 458.44 ± 25.31), compared to those with low physical activity (<emph>M</emph> = 493.48 ± 48.81; <emph>p</emph> = 0.026). Children with high physical activity had significantly higher parent-reported disruptive behavior (ABC-I; <emph>M</emph> = 20.21 ± 10.91), compared to those with low physical activity (<emph>M</emph> = 12.23 ± 8.11; <emph>p</emph> = 0.042). There were no physical activity group differences on the M-CSHQ subscales (data not shown).</p> <p>Table 4 Differences between high physical activity and low physical activity in children on the autism spectrum (<emph>N</emph> = 27)</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left" rowspan="2"><p>Variables</p></th><th align="left"><p>High Physical Activity (<italic>N</italic> = 14)</p></th><th align="left"><p>Low Physical Activity (<italic>N</italic> = 13)</p></th><th align="left" rowspan="2"><p><italic>t</italic> (25)</p></th><th align="left" rowspan="2"><p><italic>p</italic>-value</p></th><th align="left" rowspan="2"><p><italic>Cohen's d</italic></p></th></tr><tr><th align="left"><p>Mean ± SD</p></th><th align="left"><p>Mean ± SD</p></th></tr></thead><tbody><tr><td align="left" colspan="6"><p>Actigraphy</p></td></tr><tr><td align="left"><p> SE %</p></td><td char="." align="char"><p>73.42 ± 5.54</p></td><td char="." align="char"><p>77.11 ± 7.85</p></td><td char="." align="char"><p>1.42</p></td><td char="." align="char"><p>0.169</p></td><td char="." align="char"><p>0.54</p></td></tr><tr><td align="left"><p> SOL min</p></td><td char="." align="char"><p>39.45 ± 30.34</p></td><td char="." align="char"><p>27.83 ± 25.19</p></td><td char="." align="char"><p>− 1.08</p></td><td char="." align="char"><p>0.291</p></td><td char="." align="char"><p>0.42</p></td></tr><tr><td align="left"><p> TST min</p></td><td char="." align="char"><p>458.44 ± 25.31</p></td><td char="." align="char"><p>493.48 ± 48.81</p></td><td char="." align="char"><p>2.37</p></td><td char="." align="char"><p><bold>0.026</bold></p></td><td char="." align="char"><p>0.90</p></td></tr><tr><td align="left"><p> WASO min</p></td><td char="." align="char"><p>129.30 ± 40.80</p></td><td char="." align="char"><p>122.43 ± 45.28</p></td><td char="." align="char"><p>− 0.41</p></td><td char="." align="char"><p>0.682</p></td><td char="." align="char"><p>0.16</p></td></tr><tr><td align="left" colspan="6"><p>Parent-report</p></td></tr><tr><td align="left"><p> M-CSHQ</p></td><td char="." align="char"><p>40.57 ± 8.22</p></td><td char="." align="char"><p>35.15 ± 7.41</p></td><td char="." align="char"><p>− 1.79</p></td><td char="." align="char"><p>0.085</p></td><td char="." align="char"><p>0.69</p></td></tr><tr><td align="left"><p> ABC-I</p></td><td char="." align="char"><p>20.21 ± 10.91</p></td><td char="." align="char"><p>12.23 ± 8.11</p></td><td char="." align="char"><p>− 2.25</p></td><td char="." align="char"><p><bold>0.042</bold></p></td><td char="." align="char"><p>0.88</p></td></tr></tbody></table> </ephtml> </p> <p>Results from the two-tailed independent samples <emph>t</emph>-tests are displayed. The median-split method was used to classify steps as high physical activity (≥ 12,129.40 steps per day) or low physical activity (< 12,129.40 steps per day) Bolded values are significant at the 0.05 level <emph>SE</emph> sleep efficiency, <emph>SOL</emph> sleep onset latency, <emph>TST</emph> total sleep time, <emph>WASO</emph> wake after sleep onset, <emph>M-CSHQ</emph> Modified Children's Sleep Habits Questionnaire, <emph>ABC-I</emph> Aberrant Behavior Checklist-irritability subscale</p> <hd id="AN0170899339-23">Parent-Reported Sleep Problems on the M-CSHQ and SE% and TST as Primary Actigraphy Sleep Indi...</hd> <p>For the children with complete actigraphy data, 17 of 27 (63%) children scored above the cut off (≥ 35) on the M-CSHQ. Of these children above the cut off on the M-CSHQ, 16 of 17 (94.1%) scored below the TST actigraphy threshold and 17 of 17 scored below the SE% threshold. Of the children below the M-CSHQ cutoff, 8 of 10 (80%) children scored below TST actigraphy threshold and 8 of 10 (80%) scored below the SE% threshold suggesting that actigraphy picked up on sleep problems that were under identified by the parent-reported M-CSHQ.</p> <hd id="AN0170899339-24">Parent-Reported Disruptive Behavior on the ABC-I and SE% and TST as Primary Actigraphy Sleep...</hd> <p>For the children with complete actigraphy data, 14 of 27 (51.9%) children scored above the cut off ≥ 15 on the ABC-I. Of these children above the cut off on the ABC-I, 13 of 14 (92.9%) scored below the TST actigraphy threshold and 14 of 14 scored below the SE% threshold. Most children below the ABC-I cutoff (11 of 13, 84.6%) also scored below TST actigraphy threshold and 11 of 13 (84.6%) scored below the SE% threshold. Regardless of the ABC-I score, sleep problems were still likely.</p> <hd id="AN0170899339-25">Discussion</hd> <p>This study examined the feasibility of actigraphy as a measure of sleep and physical activity in young children on the autism spectrum. The acceptability of actigraphy was supported by the high rate of completion of study procedures. Thirty-two young children with a community diagnosis of ASD enrolled in the study. Parents of 27 children (84.4%) had complete data. The Zoom session was successful for all but 4 children. This is consistent with studies that used face-to-face training (Johnson et al., [<reflink idref="bib31" id="ref107">31</reflink>]). The use of videos to train research staff on actigraphy procedures has been previously reported (Fawkes et al., [<reflink idref="bib20" id="ref108">20</reflink>]). The findings in this study support the feasibility of using Zoom video technology to train parents on collecting sleep and physical activity actigraphy data in young children on the autism spectrum.</p> <p>This study also gathered preliminary data on the impact of physical activity on sleep in children on the autism spectrum. Children with higher physical activity had lower actigraphy TST than children with lower physical activity. Although preliminary, these findings have not been reported previously. To our knowledge, this was the second study to evaluate sleep and physical activity in combination with parent-reported sleep disturbances in a larger sample and younger age group of children with ASD using wrist placement (Wachob & Lorenzi, [<reflink idref="bib74" id="ref109">74</reflink>]). Total sleep time and physical activity levels vary in young children with ASD (Katz et al., [<reflink idref="bib34" id="ref110">34</reflink>]; Pan & Frey, [<reflink idref="bib54" id="ref111">54</reflink>]). This study provides preliminary information on the interaction of sleep and physical activity in children with ASD, which remains poorly understood.</p> <p>In the sample of 27 children with complete actigraphy data, 25 had poor SE%, 13 had poor SOL, 27 had poor WASO, 24 children had inadequate TST compared to age-matched norms. On the M-CSHQ total score, 17 participants met or exceeded the cut-off for sleep disturbance. All children with parent reported sleep problems on the M-CSHQ had poor SE% and inadequate TST. However, of the 10 children below cut-off for a sleep problem on the M-CSHQ, 8 had poor SE% and inadequate TST on actigraph. This suggests that actigraphy detected sleep problems missed by the parent reported sleep problems M-CSHQ measure. Our findings on M-CSHQ and TST as measured by actigraphy are consistent with Veatch et al. ([<reflink idref="bib73" id="ref112">73</reflink>]).</p> <p>On average children in this sample had 260.11 MVPA counts per 5-s epochs per day and MVPA per day average of 2.80%. In children with ASD, Wachob and Lorenzi ([<reflink idref="bib74" id="ref113">74</reflink>]) showed an average MVPA of 8.2%. The children in this study did not spend as much time per day in MVPA compared to the children in the study by Wachob and Lorenzi ([<reflink idref="bib74" id="ref114">74</reflink>]). Using a median split of the number of steps per day, we examined the effect of high physical activity and low physical activity on actigraphy sleep indices. Children with high physical activity had lower TST minutes compared to children with low physical activity. No group differences were observed on other actigraphy sleep indices. In a study of 10 children with ASD, Wachob and Lorenzi ([<reflink idref="bib74" id="ref115">74</reflink>]) reported that higher level of physical activity was associated with better sleep quality. Although physical activity and sleep were measured objectively with actigraphy in the study by Wachob and Lorenzi ([<reflink idref="bib74" id="ref116">74</reflink>]), high physical activity and low physical activity differences were not examined and the children in the study had acceptable SE% compared to the children in our pilot study.</p> <p>We also explored differences in parent-reported disruptive behavior on the ABC-I on actigraphy sleep and physical activity measures. In this pilot study, children with higher physical activity (i.e., steps per day) had greater disruptive behavior on the ABC-I than children with lower physical activity. Just over half the sample exceeded a score of 15 (cut off for moderate disruptive behavior) on the parent-rated ABC-Irritability subscale. Of the children above this ABC-I cut off, 92.9% had inadequate TST and 100% had poor SE% on actigraphy. Our preliminary findings suggest that disruptive behavior may be associated with greater physical activity but does not predict better sleep. In this small sample, perhaps higher physical activity and disruptive behavior suggest more dysregulated children who likely have dysregulated sleep.</p> <p>In a sample of 36 youth with cancer (age 8–18), Orsey et al. ([<reflink idref="bib52" id="ref117">52</reflink>]) reported that higher daytime physical activity as measured by actigraphy was associated with better sleep quality and efficiency. Our preliminary findings did not suggest an association between greater physical activity and improved sleep. In addition, children with greater physical activity had greater disruptive behavior, greater sleep disturbance on the parent-reported sleep measure (M-CSHQ) and impaired sleep on actigraphy indices compared to children with lower physical activity. This trend needs further exploration to identify underlying mechanisms and potential interventions for sleep problems in young children on the autism spectrum.</p> <p>This study was designed to evaluate the feasibility of using actigraphy to measure physical activity and sleep in young children with ASD. There are several limitations that warrant mention. First, the small sample size did not allow evaluation of subgroups by age, gender, medication, or co-occurring conditions (e.g., ADHD) which may affect physical activity in children on the autism spectrum. We also did not look at the ABC-Hyperactivity subscale which would have provided a parent report on daytime activity. Children with low muscle tone or motor delays (i.e., sensorimotor impairments) may have reduced physical activity levels compared to children with sensation seeking behavior and could be examined in future studies. The small sample size and lack of a control group limits the generalizability of the findings. The cross-sectional design in this sample of convenience did not permit examination of change over time. We included children with a community, medical practitioner ASD diagnosis, which may have included children who would not have met diagnostic criteria for ASD using state of the art assessments. The study was conducted during the COVID-19 pandemic. This eliminated face-to-face interaction and training on the use of actigraphy. In addition, the COVID-19 pandemic may have affected sleep and physical activity in children in this sample (Theis et al., [<reflink idref="bib70" id="ref118">70</reflink>]). Due to the pandemic restrictions and safety protocols, the children in this sample attended school in-person, hybrid, or virtually, which could have influenced sleep and physical activity patterns. In the absence of accepted MVPA algorithms for use in young children with ASD, we applied the algorithm from Johansson and colleagues (2016).</p> <hd id="AN0170899339-26">Conclusions</hd> <p>The feasibility of actigraphy to measure sleep and physical activity in pediatric populations is well established (Meltzer et al., [<reflink idref="bib47" id="ref119">47</reflink>]) in Rett syndrome (Merbler et al., [<reflink idref="bib50" id="ref120">50</reflink>]), cerebral palsy (Coker-Bolt et al., [<reflink idref="bib15" id="ref121">15</reflink>]; Gorter et al., [<reflink idref="bib24" id="ref122">24</reflink>]), and cancer (Orsey et al., [<reflink idref="bib52" id="ref123">52</reflink>]). A few studies have examined the use of actigraphy to measure sleep and physical activity in youth, adolescents, and adults on the autism spectrum (Benson et al., [<reflink idref="bib8" id="ref124">8</reflink>]; Memari et al., [<reflink idref="bib48" id="ref125">48</reflink>]; Wachob & Lorenzi, [<reflink idref="bib74" id="ref126">74</reflink>]). This study used a wrist-worn actigraphy device for physical activity and sleep in young children with ASD. Due to the COVID-19 pandemic, this study used Zoom technology and online data collection methods. Our results support the feasibility of using actigraphy to measure physical activity and sleep in young children with ASD using Zoom technology. In this small sample, we observed a wide range of physical activity levels (Jones et al., [<reflink idref="bib32" id="ref127">32</reflink>]; Srinivasan et al., [<reflink idref="bib69" id="ref128">69</reflink>]). Preliminary results suggest an interaction of sleep, physical activity, and disruptive behavior. The extent and mechanism of this interaction warrants further study in a well-characterized and larger sample of young children with ASD compared to age-matched community peers.</p> <hd id="AN0170899339-27">Acknowledgments</hd> <p>This project was prepared as part of a doctoral dissertation. The authors would like to thank the autism organizations for helping with recruitment, and the families who participated in the study.</p> <hd id="AN0170899339-28">Author Contributions</hd> <p>MLA, CRJ, JAZ, BAM, CJB, and LS contributed to the study conception, design, methodology, and reporting. Project administration, material preparation, data collection, and analysis were performed by MLA. The first draft of the manuscript was written by MLA and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.</p> <hd id="AN0170899339-29">Funding</hd> <p>This work was funded in part by the Eunice Kennedy Shriver National Institute of Child Health and Human Development Measuring Sleep Problems in Children with ASD Grant (No. R01HD099480; LS, CRJ, MLA) and by the Legacy Fellowship (MLA) and Alumni Association Awards (all authors) at Case Western Reserve University Frances Payne Bolton School of Nursing located at 10900 Euclid Avenue, Cleveland, OH 44106.</p> <hd id="AN0170899339-30">Declarations</hd> <p></p> <hd id="AN0170899339-31">Conflict of interest</hd> <p>Dr. Scahill has served as a consultant to Roche, Janssen, Impel, and Finch. Dr. Scahill receives book royalties from Oxford, Guilford and American Psychological Association and license fees from Roche and Yamo. Dr. Johnson receives book royalties from Oxford and American Psychological Association. We have no other conflicts of interest to disclose.</p> <hd id="AN0170899339-32">Ethical Approval</hd> <p>All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.</p> <hd id="AN0170899339-33">Consent to Participate</hd> <p>Written informed consent was obtained from all legal guardians of the child participants included in this study.</p> <hd id="AN0170899339-34">Publisher's Note</hd> <p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p> <ref id="AN0170899339-35"> <title> References </title> <blist> <bibl id="bib1" idref="ref24" type="bt">1</bibl> <bibtext> Abel EA, Schwichtenberg AJ, Brodhead MT, Christ SL. 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Items – Name: Title
  Label: Title
  Group: Ti
  Data: Feasibility of Actigraphy for Evaluating Sleep and Daytime Physical Activity in Children with Autism Spectrum Disorder
– Name: Language
  Label: Language
  Group: Lang
  Data: English
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Alder%2C+M%2E+L%2E%22">Alder, M. L.</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0002-7817-3476">0000-0002-7817-3476</externalLink>)<br /><searchLink fieldCode="AR" term="%22Johnson%2C+C%2E+R%2E%22">Johnson, C. R.</searchLink><br /><searchLink fieldCode="AR" term="%22Zauszniewski%2C+J%2E+A%2E%22">Zauszniewski, J. A.</searchLink><br /><searchLink fieldCode="AR" term="%22Malow%2C+B%2E+A%2E%22">Malow, B. A.</searchLink><br /><searchLink fieldCode="AR" term="%22Burant%2C+C%2E+J%2E%22">Burant, C. J.</searchLink><br /><searchLink fieldCode="AR" term="%22Scahill%2C+L%2E%22">Scahill, L.</searchLink>
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  Data: <searchLink fieldCode="SO" term="%22Journal+of+Autism+and+Developmental+Disorders%22"><i>Journal of Autism and Developmental Disorders</i></searchLink>. Sep 2023 53(9):3670-3682.
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  Label: Availability
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  Data: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
– Name: PeerReviewed
  Label: Peer Reviewed
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  Data: Y
– Name: Pages
  Label: Page Count
  Group: Src
  Data: 13
– Name: DatePubCY
  Label: Publication Date
  Group: Date
  Data: 2023
– Name: SourceSuprt
  Label: Sponsoring Agency
  Group: SrcSuprt
  Data: Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) (DHHS/NIH)
– Name: NumberContract
  Label: Contract Number
  Group: NumCntrct
  Data: R01HD099480
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: Journal Articles<br />Reports - Research
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Sleep%22">Sleep</searchLink><br /><searchLink fieldCode="DE" term="%22Physical+Activity+Level%22">Physical Activity Level</searchLink><br /><searchLink fieldCode="DE" term="%22Young+Children%22">Young Children</searchLink><br /><searchLink fieldCode="DE" term="%22Autism+Spectrum+Disorders%22">Autism Spectrum Disorders</searchLink><br /><searchLink fieldCode="DE" term="%22Measurement+Equipment%22">Measurement Equipment</searchLink><br /><searchLink fieldCode="DE" term="%22Behavior+Problems%22">Behavior Problems</searchLink><br /><searchLink fieldCode="DE" term="%22Child+Behavior%22">Child Behavior</searchLink><br /><searchLink fieldCode="DE" term="%22Measurement+Techniques%22">Measurement Techniques</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1007/s10803-022-05661-5
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 0162-3257<br />1573-3432
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: This research evaluated the feasibility of actigraphy to measure sleep and physical activity in children (ages 2-8 years) with autism spectrum disorder (ASD). We also explored associations between sleep and physical activity. Validated screening measures established eligibility. Questionnaires, diaries, and 5 days and 5 nights of actigraphy monitoring were used to collect data. Of the 32 children enrolled, 27 (84.4%) completed actigraphy monitoring. Based on the median steps per day, children with high physical activity had lower total sleep time and more disruptive behaviors than children with low physical activity. Findings support the feasibility of using actigraphy to measure sleep and physical activity in children with ASD. Larger studies are needed to evaluate interactions of physical activity on sleep in this population.
– Name: AbstractInfo
  Label: Abstractor
  Group: Ab
  Data: As Provided
– Name: DateEntry
  Label: Entry Date
  Group: Date
  Data: 2023
– Name: AN
  Label: Accession Number
  Group: ID
  Data: EJ1390506
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1390506
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1007/s10803-022-05661-5
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 13
        StartPage: 3670
    Subjects:
      – SubjectFull: Sleep
        Type: general
      – SubjectFull: Physical Activity Level
        Type: general
      – SubjectFull: Young Children
        Type: general
      – SubjectFull: Autism Spectrum Disorders
        Type: general
      – SubjectFull: Measurement Equipment
        Type: general
      – SubjectFull: Behavior Problems
        Type: general
      – SubjectFull: Child Behavior
        Type: general
      – SubjectFull: Measurement Techniques
        Type: general
    Titles:
      – TitleFull: Feasibility of Actigraphy for Evaluating Sleep and Daytime Physical Activity in Children with Autism Spectrum Disorder
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Alder, M. L.
      – PersonEntity:
          Name:
            NameFull: Johnson, C. R.
      – PersonEntity:
          Name:
            NameFull: Zauszniewski, J. A.
      – PersonEntity:
          Name:
            NameFull: Malow, B. A.
      – PersonEntity:
          Name:
            NameFull: Burant, C. J.
      – PersonEntity:
          Name:
            NameFull: Scahill, L.
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 09
              Type: published
              Y: 2023
          Identifiers:
            – Type: issn-print
              Value: 0162-3257
            – Type: issn-electronic
              Value: 1573-3432
          Numbering:
            – Type: volume
              Value: 53
            – Type: issue
              Value: 9
          Titles:
            – TitleFull: Journal of Autism and Developmental Disorders
              Type: main
ResultId 1