Published on in Vol 12 (2023)

This is a member publication of University of Washington

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/40383, first published .
Physical Activity Interventions for Improving Cognitive Functions in Children With Autism Spectrum Disorder: Protocol for a Network Meta-Analysis of Randomized Controlled Trials

Physical Activity Interventions for Improving Cognitive Functions in Children With Autism Spectrum Disorder: Protocol for a Network Meta-Analysis of Randomized Controlled Trials

Physical Activity Interventions for Improving Cognitive Functions in Children With Autism Spectrum Disorder: Protocol for a Network Meta-Analysis of Randomized Controlled Trials

Authors of this article:

Longxi Li1 Author Orcid Image ;   Anni Wang2 Author Orcid Image ;   Qun Fang3 Author Orcid Image ;   Michelle E Moosbrugger4 Author Orcid Image

Protocol

1Center for Leadership in Athletics, University of Washington, Seattle, WA, United States

2College of Education, Michigan State University, East Lansing, MI, United States

3School of Physical Education, Qingdao University, Qingdao, China

4Department of Physical Education and Health Education, Springfield College, Springfield, MA, United States

Corresponding Author:

Michelle E Moosbrugger, PhD

Department of Physical Education and Health Education

Springfield College

263 Alden St

Springfield, MA, 01106

United States

Phone: 1 (413) 748 3486

Email: mmoosbrugger@springfieldcollege.edu


Background: Autism spectrum disorder (ASD) is a neurodevelopmental disorder that affects millions of children worldwide, with a current prevalence of approximately 1 in 54 children in the United States. Although the precise mechanisms underlying ASD remain unclear, research has shown that early intervention can have a significant impact on cognitive development and outcomes in children with ASD. Physical activity interventions have emerged as a promising intervention for children with ASD, but the efficacy of different types of interventions remains unclear.

Objective: This study protocol aims to update the knowledge on extant literature and explore the efficacy of physical activity intervention strategies on cognitive functions in children with ASD.

Methods: A systematic review and network meta-analysis (NMA) will be conducted following the PRISMA-NMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols for Network Meta-Analyses) statement. A total of 9 bibliographic databases (APA PsycInfo, CENTRAL, Dimensions, ERIC, MEDLINE Complete, PubMed, Scopus, SPORTDiscus, and Web of Science) will be systematically searched to screen eligible articles based on a series of inclusion and exclusion criteria. A study will be considered for inclusion if it is not classified as a systematic review with or without meta-analysis, was published from inception to present, includes children aged 0 to 12 years with ASD, quantitively measures cognitive outcomes, and examines treatment comprising at least 1 physical activity intervention strategy. The internal validity and quality of evidence will be evaluated using the Grading of Recommendations Assessment, Development, and Evaluation framework. Statistical analyses will be performed in the RStudio software (version 3.6; RStudio Inc) with the BUGSnet package and the Comprehensive Meta-Analysis software (version 3.3; Biostat Inc). The results of our NMA will be illustrated through network diagrams accompanied by geometry and league tables. Further, to rank the interventions based on their efficacy, we will use the surface under the cumulative ranking curve.

Results: Our preliminary search identified 3778 potentially relevant studies. The screening of the studies based on the inclusion and exclusion criteria is ongoing, and we anticipate that the final number of eligible studies will be in the range of 30 to 50.

Conclusions: This study will provide a comprehensive review of the literature on physical activity interventions for children with ASD and will use NMA to compare the efficacy of different types of interventions on cognitive outcomes. Our findings will have important implications for clinical practice and future research in this area and will contribute to the growing body of evidence supporting the use of physical activity interventions as a key component of early intervention for children with ASD.

Trial Registration: PROSPERO CRD42021279054; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=279054

International Registered Report Identifier (IRRID): DERR1-10.2196/40383

JMIR Res Protoc 2023;12:e40383

doi:10.2196/40383

Keywords



Background

Autism spectrum disorder (ASD) is a lifelong developmental disorder. Individuals with ASD commonly present symptoms of insufficient social interaction and communication and repeated and restricted behavior patterns that have a negative impact on daily functions. The lack of adapting, planning, and organizing skills has a negative influence on personal, physical, mental, academic, vocational, and social domains. The onset of ASD typically presents during the ages of 1 to 2 years, whereas some symptoms may be observed during the first year after birth [1]. Some categories of ASD have been specified such as Asperger syndrome, childhood disintegrative disorder, and pervasive developmental disorder [2]. The World Health Organization has indicated that children with ASD exhibit deficits in cognitive functions, characterized by social impairment, abnormalities, and repetitive stereotypic behavior [3,4]. Approximately 17% of children were diagnosed with a range of complex neurodevelopmental disabilities between the ages of 3 and 17 years; 1 in 54 children was diagnosed with ASD [5,6]. The diagnosis rate in children has continuously increased, moving from 1.1% to 2.5% in the past decades [7,8]. Although the prevalence of diagnoses is increasing, many evidence-based interventions are still in their developmental stages. Specifically, the effectiveness of physical activity interventions in children with ASD is not yet fully understood.

Childhood is a critical period for neurodevelopment, especially for the development of children’s memory, attention, creativity, motor skills, and executive functions (EFs) [9]. ASD is a complex neurodevelopmental disorder, and its prognosis is impacted by environmental, genetic, and physiological factors [1]. Several neurotransmitters, including brain-derived neurotrophic factors, which contribute to brain development, demonstrate correlations with ASD and other neurodevelopmental impairments [10]. The connectivity of the frontal cortex and prefrontal cortex with other parts of the brain was found to be related to ASD behavioral symptoms [11-13]. High risk for an atypical development of the ability to recognize and attribute mental states was found in the autism population [14]. Language and joint attention for social functioning and cognitive control behaviors have been shown to be linked to changes in the early maturation of the brain [9,14-16]. An imbalanced process of integrating information such as contextual or sensory perception might be related to ASD symptoms [17].

Cognitive function is manifested as the ability to process thoughts, such as learning and solving problems [18]. Cognitive function has been categorized into EFs and non-EFs. EFs present an individual’s adaptive skills and ability to conduct goal-oriented meaningful actions [19]. Non-EFs include complex attention, learning and memory, visual function, language function, and social function [1]. Solomon et al [20] indicated that EF hypothesis is an influential cognitive theory of ASD, which proposes that “deficits in planning, inhibitory control, attentional set shifting and working memory are central to the disorder.” Social and communication skills are part of the characteristics of cognitive function, which individuals with ASD usually lack, and are also impacted by the age and development window [21]. In children, cognitive function develops along with the human brain [22]. An example of proneurogenic modulators is exercise, which increases the level of brain-derived neurotrophic factors, endocannabinoids, and microbiota diversity, leading to hippocampal neurogenesis and long-term changes in cognitive function [23,24]. Various interventions for children with ASD have been studied, such as music therapy, which has been shown to improve social interaction in preschool children with ASD [14]. In addition, physical activity is an effective approach to improve cardiovascular fitness and cognitive function in children and adolescents [25].

Evidence shows that physical training positively impacts the cognitive function of adults and their offspring, which is encouraging for investigations on the effect of physical activity on youth [26]. In this study, we expect to use a statistical methodology to explore the effectiveness of different types of physical activity intervention strategies (PAIS) on cognitive function in children. We believe that this study is a promising starting point to guide future health-related practices in youth. Closely related to the release of dopamine in the human body, physical activities have also been proven to provide emotional support to children, such as by lowering levels of anxiety or depression [27]. Promising evidence has been accumulated of physical activity leading to improvements in cognition, including improvements in both academic and behavioral performances in children with ASD [3,28-31]. Liang et al [32] reported that chronic exercise interventions are beneficial for overall EFs, especially for cognitive flexibility and inhibitory control in children and adolescents with ASD. Several studies have indicated a significant increase in social engagement in children with ASD after they participated in physical activities, especially in group activities [33-35]. Furthermore, physical activity proved beneficial in reducing stereotypical behaviors within the population of children with ASD [36].

In prior research, various types of PAIS were investigated individually or through narrow groups. In this study, a full range of PAIS will be examined. PAIS include aerobic exercises, mindfulness practices, school physical education programs, and Montessori methods [32,37]. Fang et al [38] concluded favorable results for the effect of exergaming interventions on cognitive functions, but synthesis results from a follow-up meta-analysis are lacking. Horseback riding was found to be beneficial for cognitive functioning, social interaction, and sensory processing improvement in children with ASD [33,35]. Some other physical activities, such as yoga and dance, were also introduced as interventions for children with ASD, which led to positive outcomes in behavioral functioning [39]. The clinical conditions of participants, as well as the session frequencies and lengths of the interventions, need to be researched more. Hence, there is an urgent need for researchers to explicitly examine what type of PAIS is the most beneficial for children with ASD.

Systematic reviews and pairwise meta-analyses cannot be used to compare treatment effects across interventions and indirect effects. Therefore, the network meta-analysis (NMA) is proposed as a novel analysis technique in the field of physical activity and health promotion to fill this gap and satisfy the urgent need [40]. To the best of our knowledge, this will be the first NMA applied to systematically review and analyze the efficacy of PAIS on cognitive functions in children with ASD. Therefore, our expectation is to explore PAIS based on selected direct and indirect head-to-head trials to suggest important considerations for decision-making in the field of pediatric health promotion.

Mini Review

Overview

To gain a comprehensive overview of the existing literature as well as justify the necessity of conducting an NMA on PAIS for children and adolescents with ASD, we conducted a mini review based on the systematic reviews and meta-analyses in the current literature. The literature search was conducted on PubMed, APA PsycInfo, SPORTDiscus, Web of Science, CENTRAL, ERIC, SocINDEX, MEDLINE Complete, and Dimensions. The keywords used for the literature search involved 4 domains: intervention mode, cognitive performance, population, and autism. Combinations of the keywords regarding each domain were “physical activity OR PA OR exercise OR sport*” AND “cognitive function OR cognition OR executive function OR inhibitory control OR memory OR communication OR stereotyp* behavior*” AND “children OR kid* OR teenager OR students” AND “autism spectrum disorder OR ASD.” Eligible studies should meet the following criteria: (1) systematic review or meta-analysis written in English and published between 2001 and 2021, (2) inclusion of children or adolescents with ASD, (3) review of PAIS, and (4) examination of the effects of PAIS on cognitive functions.

Literature Search

Two authors (LL and AW) independently conducted the search and screening process. The initial search resulted in 424 studies. Of these 424 studies, after the removal of 362 (85.4%) duplicate and irrelevant items, 62 (14.6%) items remained for the next phase of screening. Of these 62 articles, 31 (50%) articles were excluded based on abstract examination, leaving 31 (50%) articles for full-text review. Of these 31 articles, the final step of screening removed 12 (39%) articles because of the following reasons: no cognitive outcomes were measured (n=10, 32%) and populations other than children or adolescents were included (n=2, 6%). Therefore, a total of 19 (61%) of the 31 systematic reviews with or without meta-analysis met the inclusion criteria. The process of study selection is presented in Figure 1.

Figure 1. Flowchart of searching and screening in mini review.
Characteristics of the Included Studies

The median publication year of these studies was 2019 (range 2008-2021), which implies a rapid increase in the number of published review papers on the relevant topic in recent years. The number of studies included in each review ranged from 7 to 41. A variety of types of the included review papers was identified, such as systematic review (9/19, 47%), meta-analysis (7/19, 37%), and systematic review with meta-analysis (3/19, 16%). In addition to individuals with ASD, the included review studies also examined individuals with cognitive impairment due to one of the following reasons: attention-deficit/hyperactivity disorder, cerebral palsy, developmental delay, developmental coordination disorder, and Down syndrome. Common symptoms observed in individuals with these disorders are difficulties in paying attention, performing tasks, and engaging in social interaction [1]. Most studies focused on children and adolescents [14,32,34,41-51], whereas Fang et al [38], Fragala-Pinkham et al [52], Healy et al [53], Lang et al [54], Ruggeri et al [55], and Sowa and Meulenbroek [56] conducted studies involving both children and adult participants. Experimental groups were compared with their counterparts, that is, active behavioral control groups, waiting list control groups, or standard care groups. The study characteristics are illustrated in Table 1.

The PAIS applied in the intervention arms typically consisted of two or three 30- to 60-minute sessions per week for 8 to 16 weeks. Overall, 3 (16%) of the 19 studies included only randomized controlled trials (RCTs) [14,47,50], and others (16/19, 84%) partially included quasi-experimental designs with controlled trials [32,41-44,48,49,51,53-56], cohort study [34], pre- and posttest and case-control studies [38,45,52], and descriptive study [46]. Moreover, 1 (5%) of the 19 studies lacked a clear definition of the age range of children and a discussion of the risk of bias (RoB) [41]. The interventions implemented in the included studies were conducted through various types of physical activities. Physical exercise– and motor skill–related interventions, such as aerobic exercise, resistance training, and aquatic activities, were mostly adopted in the clinical practice [32,34,41-56]. In addition, 2 (11%) of the 19 studies investigated effects of exergaming and technology interventions for individuals with ASD [38,43].

The included studies investigated the effects of physical activity interventions on cognitive functions, with small to moderate effect sizes on the improved global EF [32,50]. Specifically, the included reviews reported enhanced performance in terms of working memory, attention, task switching, and inhibitory control [34,50]. The evidence also indicated the beneficial effects of social functioning and communication skills, which can be attributed to the group-based activity performed during the interventions [42,44]. Learning and memory outcomes due to PAIS were not fully explored in the selected studies. The other limitation of the included systematic review and meta-analysis studies was the combination of children and adolescent groups. However, age was recognized as a significant confounder in ASD research. Although common clinical treatments, including educational, family, speech, and occupational therapies, showed favorable effects, widely supportive evidence showed that physical activity was beneficial for children’s lifelong cognitive and motor development. Therefore, it is necessary to explore the effects of PAIS treatment on children’s cognitive outcomes from the perspective of physical activity and health promotion. Results are encouraging because various types of evidence showed that PAIS were effective in enhancing cognitive function in children with ASD; the foundation for the future in-depth data analysis has been established.

Table 1. Characteristics of the studies included in the mini review.
StudyStudy typeParticipant, nStudy populationIntervention used (intervention arm)Outcome measuresaMain outcomes
Aleksandrovic et al [41], 2016SRb13Children (aged <18 years and with ASDc)Aquatic activities (Armbruster or Halliwick methods or the constant time delay procedure for learning swimming skills and social and floor warm-up activities)MSd (ABC-2e, WOTAf, HAARg, YMCAh checklist, and Aquatic Skills Assessment)Aquatic skills were effectively improved
Bremer et al [34], 2016SR13Children and youth (aged ≤16 years; at least one participant with a diagnosis of ASD or PDDi)Physical exercise intervention (jogging, swimming, yoga or dance, horseback riding, and martial arts)CFj+SFk (GARS-2l, SRSm, sensory profile, ABC-Cn, ABCo, VABS-2p, frequency of child specific behaviors, BOSSq, SSBS-2r, and BASC-2s)Improvements in stereotyped behaviors, social behavior cognition, and attention
Cameron et al [42], 2020SR17Children (aged 3-6 years) with autism, CPt, Down syndrome, DCDu, DDvFundamental motor skill group intervention by primary researcherMS (PDMS-2w: GMQx)Results were inconclusive to support motor-based interventions in this age group owing to variability in intervention types
Case and Yun [43], 2019MAy18Preschool (aged 3-5 years) and school-aged children (aged 6-17 years) with ASDFMSz (direct instruction activities), PAaa (whole body movement and coordination activities), technology (eg, video games), EATab (eg, horseback riding)-based interventionsMS (PDMS, PDMS-2, TGMDac, TGMD-2, TGMD-3 BOT-2ad, M-ABCae, and M-ABC-2)Overall effect size on gross motor outcomes (δ=0.99; P<.001), FMS (g=0.68; P<.001), PA (g=1.20; P=.003), technology (g=1.42; P=.21), and EAT (g=1.20; P=.005)
Chan et al [44], 2021MA12Children and adolescents (aged <18 years and with ASD)Individual, combined, or group-based PA (eg, Karate, horseback riding, aquatic, mind-body, football, outdoor adventure, or active recreation)SF (GARS-2, SRS, VABS, ATECaf, and SSISag)COMah (SMCai=.27, 95% CI 0.06 to 0.48) and social functioning (SMC=.39, 95% CI 0.15 to 0.63)
Fang et al [38], 2019SR10Children and young adults (aged 5 to 21 years and with ASD)Exergaming (eg, platforms and games included DDRaj, cybercycling, FroggyBobby, Xbox Kinect, Nintendo Wii, and Makoto Arena)CF+MS (physical outcomes [eg, BMI and jump distance] and cognitive outcomes [eg, BRIEFak])Favorable results for the effect of exergaming interventions on participants’ physical and cognitive functions
Ferreira et al [45], 2019SR and MA8 (SR) + 8 (MA)Children and youngsters (aged <16 years and with ASD)Aerobic exercise, Kata techniques training, and ball exerciseCF (GARS-2, SSBal, and stereotypic behavior observations)PA was effective in reducing stereotypic behavior (SMDam=1.11; P=.009)
Fragala-Pinkham et al [52], 2021SR8Children and young adults (aged 7 to 26 years and with ASD, Down syndrome, or UIDan)Lower extremity cycling (eg, learning to ride a 2-wheeled bicycle, stationary cycling, and CO-OPao approach) CF+MS (eg, cycling time and distance, cycling skill checklist, KTap, KTFistaq, TOLTar, and PPT-Cas)Weak evidence and heterogeneous results regarding MS and CF in children and young adults with intellectual disabilities between cycling and control groups
Healy et al [53], 2018MA29Youth (aged 2 to 22 years and with ASD) Recreational activities in APEat, PEau, and other settings (eg, yoga, kata program, aquatic skill program, dance, mind-body exercise, and a combination of all activities)CF+MS (psychometric tools or scales were not specifically discussed)Overall positive moderate effect exhibited (g=0.62; P<.001); cognitive function (g=0.28, 95% CI −1.19 to 1.74), psychomotor function (g=1.21, 95% CI 0.41 to 1.66)
Howells et al [46], 2019SR and MA11 (SR) + 7 (MA)Children (aged 5 to 12.9 years and with ASD)Individual and group PA (eg, included a range of blocking, punching, sticking, and kicking techniques; climbing rope ladder or rope elevator; horse riding; group sport games)SF+COM (VABS, SRS, BASC-T, and GARS-2)Nonsignificant effect for communication (g=0.13, 95% CI −0.12 to 0.38) and a significant improvement in overall social functioning (g=0.45, 95% CI 0.19 to 0.72)
Huang et al [47], 2020MA12Children and adolescents (aged 3 to 18 years and with ASD)PA interventions (eg, Kata techniques, therapeutic horseback, outdoor activity, karate, aquatic sport, trampoline, table tennis, Tai Chi, and exergaming) CF+MS+SF+COM (GARS-2, BOT-2, SRS, PPVT-4av, SALTaw, ATEC, ABC, MABC-2ax, CBSay, and WCSTaz)Significant positive effects on social interaction (SMD=−0.58, 95% CI −0.87 to −0.29), COM (SMD=−0.29, 95% CI −0.55 to −0.04), stereotyped behavior (SMD=−0.13, 95% CI −0.46 to 0.20), and motor skills (SMD=1.02, 95% CI 0.33 to 1.71)
Lang et al [54], 2010SR18Children, adolescents, and adults (aged 3 to 41 years and with ASD)PA (eg, walking, jogging, playing catch with a ball, riding a stationary bike, swimming, and weight training)CF+PF (psychometric tools or scales were not specifically discussed)Exercise decreased stereotypy, aggression, off-task behavior, and elopement
Liang et al [32], 2021SR and MA14 (SR) + 7 (MA)Children (aged 5 to 17 years and with ASD)Physical activity or exercise on EFsba (exergaming, jogging, table tennis, progressive muscle relaxation, martial arts, basketball, etc) CF (BRIEF, Stroop, CTTbb, HKLLTbc, DSFBTbd, FPTbe, TOLT, GNGbf, CBTTbg, Hearts and Flowers test, and attention sustained test)Positive effect on global EFs (g=0.34, 95% CI 0.08 to 0.60), CF (g=0.31, 95% CI 0.05 to 0.57), ICbh (g=0.49, 95% CI 0.19 to 0.80]), and WMbi (g=0.21, 95% CI −0.09 to 0.51)
Petrus et al [48], 2008SR7Children (aged 4 to 15 years and with ASD)PA or exercise (eg, aquatic, jogging, ball playing, and aerobic exercise)CF+MS (stereotypical behaviors and MS were observational measured in frequency, duration, or counts)Exercise might reduce stereotypic behaviors in the short term
Ruggeri et al [55], 2020SR41Children and adolescents (aged 3 to 19 years and with ASD)Motor and physical activity (eg, soccer, exergaming, throwing, aquatic, fitness or strength, horse riding, hippotherapy, stationary biking, gymnastic, and indoor climbing programs) MS+ML (eg, VABS-2, BOT, BOT-2, MABC-2, PDMS-2, TGMD-2, TGMD-3, m-PEDIbj, ASCbk, YMCA checklist, HAAR, SCSbl, and GASbm)Motor skill and learning, body structure, and function outcomes were improved with various PA interventions
Semple [49], 2019SR8Youth (aged 3 to 18 years and with ASD)Yoga, mindfulness-based interventions, Qi Gong, and meditationCF+MS+SF+COM (psychometric tools or scales were not specifically discussed)Improvements in prosocial behaviors, social cognition, communication, motivation, and motor control via yoga and mindfulness-based interventions
Sowa and Meulenbroek [56], 2012MA16Children, adolescents, and adults (aged 4 to 41.3 years and with ASD)Individual and group PA interventions (eg, jogging, therapeutic horseback rides, bike riding, walking, stationary cycling, aquatic exercising, and swimming)MS+SF+COM (psychometric tools or scales were not specifically discussed)Individual programs exhibited positive effects on motor skills (r=−0.32; P=.004) and social interactions (r=−0.62; P<.001) compared with group programs
Zhang et al [50], 2020MA11Children (age: N/Abn) with ADHDbo or ASDChronic PA intervention (eg, rhythm, integrated PA, modified aerobic games, exergaming, and taekwondo)CF+MS (BOT-2, WCST, TGMD-2, Stroop test, Flanker task, CBTT, etc)Significant improvement in overall EF, IC, cognitive flexibility, and gross MS (SMD ranged from 0.85 to 1.30); no significant improvements in working memory and fine MS
Teh et al [51], 2021MA22Children (N/A with ASD)Physical exercise interventions (jogging, cycling, exergaming, ball exercise, therapeutic horse riding, martial arts)CF (GARS-2, ATEC, ABC, BASC-2, observational measures or time intervals on targeted behaviors, etc)Large overall ESbp (g=1.16) on reducing stereotyped motor behaviors across participants, treatment, and levels from a multilevel modeling MA

aOnly autism spectrum disorder–relative interventions and outcomes are summarized because of the established inclusion criteria of this study.

bSR: systematic review.

cASD: autism spectrum disorder.

dMS: motor skills.

eABC-2: Assessment Battery for Children, Second Edition.

fWOTA: Water Orientation Test Alyn.

gHAAR: Humphries Assessment of Aquatic Readiness.

hYMCA: Young Men’s Christian Association.

iPDD: pervasive developmental disorder.

jCF: cognitive flexibility.

kSF: social functioning.

lGARS-2: Gilliam Autism Rating Scale, Second Edition.

mSRS: Social Responsiveness Scale.

nABC-C: Aberrant Behavior Checklist–Community.

oABC: Aberrant Behavior Checklist.

pVABS-2: Vineland Adaptive Behavior Scales, Interview Edition.

qBOSS: Behavioral Observation of Students in Schools.

rSSBS-2: School Social Behavior Scales, Second Edition.

sBASC-2: Behavioral Assessment System for Children, Second Edition.

tCP: cerebral palsy.

uDCD: developmental coordination disorder.

vDD: developmental delay.

wPDMS-2: Peabody Developmental Motor Scales, Second Edition.

xGMQ: gross motor quotient.

yMA: meta-analysis.

zFMS: fundamental motor skills.

aaPA: physical activity.

abEAT: equestrian-assisted training.

acTGMD: Test of Gross Motor Development.

adBOT-2: Bruininks-Oseretsky Test of Motor Proficiency, Second Edition.

aeM-ABC: Movement Assessment Battery for Children.

afATEC: Autism Treatment Evaluation Checklist.

agSSIS: Social Skills Improvement System.

ahCOM: communication.

aiSMC: standardized mean change.

ajDDR: Dance Dance Revolution.

akBRIEF1: Behavior Rating Inventory of Executive Function.

alSSB: Self-stimulatory Behaviors.

amSMD: standardized mean difference.

anUID: unspecified intellectual disability.

aoCO-OP: Cognitive Orientation to daily Occupational Performance.

apKT: Knock-Tap.

aqKTFist: Knock-Tap-Fist.

arTOLT: Tower of London Test.

asPPT-C: Purdue Pegboard Test–Combined.

atAPE: adapted physical education.

auPE: physical education.

avPPVT-4: Peabody Picture Vocabulary Test, Fourth Edition.

awSALT: Systematic Analysis of Language Transcripts.

axMABC-2: Movement Assessment Battery for Children - Second Edition.

ayCBS: Clancy Behavior Scale.

azWCST: Wisconsin Card Sorting Test.

baEF: executive function.

bbCTT: Color Trails Test.

bcHKLLT: Hong Kong List Learning Test.

bdDSFBT: digit span forward and backward test.

beFPT: Five-Point Test.

bfGNG: Go-No-Go task.

bgCBTT: Corsi Block-Tapping Task.

bhIC: inhibitor control.

biWM: working memory.

bjm-PEDI: mobility scale of the Pediatric Evaluation of Disability Inventory.

bkASC: Aquatic Skills Checklist.

blSCS: Swimming Classification Scale.

bmGAS: Goal Attainment Scaling.

bnCriteria of age was not mentioned in search strategy.

boADHD: attention-deficit/hyperactivity disorder.

bpES: effect size.

The Present NMA Protocol

An insight into the direction of future research was provided based on the preliminary findings of the mini review. Previous outcomes suggested that varying types of PAIS were effective in improving cognitive functions and motor performance, reducing frequency of the symptoms, and enhancing social and communication skill development in children with ASD and other cognitive impairments. The quality of evidence is concerning because of the limited number of meta-analyses on RCTs [53]; we expected to simply include true experimental designs (eg, RCTs), which might ensure robust synthesis results and increase the power to detect the effects of interventions [51,57]. The age groups were heterogeneous in nature, whereas we expected to focus particularly on children and explore the efficacy of PAIS on their cognitive performances. However, the limitation of the pairwise meta-analysis procedure was that it was only appropriate for discerning outcome effects “between a selected intervention strategy and a selected comparison or control condition” [40]. Whereas pairwise meta-analyses only allowed the comparison of multiple outcomes from a single treatment, NMA would allow the comparison of the efficacies of multiple PAIS on multiple outcomes [58]. Concomitantly, there is a need to conduct an NMA to obtain a more accurate estimation of the efficacy of PAIS in the population. We aim to provide an updated review of the extant literature in the field of physical activity and health promotion using an appropriate network meta-analytic model. Therefore, the following protocol was developed based on the findings and limitations identified in the mini review.


Overview

This review protocol has been registered in PROSPERO (CRD42021279054). The NMA will comply with the PRISMA-NMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols for Network Meta-Analyses) statement [59,60]. A component-based Bayesian framework NMA will be conducted following the procedures described in the subsequent sections [61].

Search Strategy

The following 9 bibliographic databases will be searched: APA PsycInfo, CENTRAL, Dimensions, ERIC, MEDLINE Complete, PubMed, Scopus, SPORTDiscus, and Web of Science. In general, the search will be limited to RCTs in English published from inception to present. Keywords combinations and MeSH (Medical Subject Headings) terms used in the search are listed in Table 2.

Table 2. Flowchart of search strategy.a
ConceptKeywords
1. Outcome: cognitive functions
  • “Cognitive function*” or “cognitive outcomes” or executive function* or “neurocognitive tasks” or questionnaires or inventory or task* or restricted repertoire or autism spectrum disorder (MeSHb terms) or children behavior disorder (MeSH terms) or autistic disorder (MeSH terms) or stereotypic movement (MeSH terms) or motor skills disorder (MeSH terms) or cognition (MeSH terms) or communication disorder (MeSH terms) or learning disabilities (MeSH terms) or DSM-Vc (MeSH terms)
2. Participants: children and adolescents
  • Children or adolescent* or young people or school-aged or teen or young adult* or youth or kids or teenager*
  • Exclude (NOT): smoking or drinking or criminal* or injury or injuries or accident* or trauma or adult* or older adult* or elderly or seniors or geriatric*
3. Exposure: comparator
  • Control* or “control group” or subject* or “human subjects” or human-related or waiting list
4. Exposure: exercise types
  • “Physical activity” or intervention* or exercise* or fitness or “physical exercise” or sport* or psychomotor or motor activity or recreational sport* or school-based or computerized training or hybrid or games or aerobic or “martial arts” or Tai Chi or “mindfulness practice” or classroom curricula or Montessori methods or “resistance training”
5. Design
  • Experimental* or clinical trial or randomized control trial* or RCTd or nonrandomized comparison or NRSe
  • Exclude (NOT): observational studies or cross-sectional or case control or cohort or systematic review or meta-analysis or report or protocol or qualitative or mixed method

aThe bibliographic databases will be searched including PubMed, SPORTDiscus, APA PsycInfo, MEDLINE Complete, ERIC, Scopus, Web of Science, CENTRAL, and Dimensions. We will use “OR” to separate keywords within each concept and “AND” to separate each concept. MeSH terms will be used for PubMed search only. Google Scholar will be used for cross validation for search results from multiple bibliographic databases.

bMeSH: Medical Subject Headings.

cDSM-V: Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition.

dRCT: randomized controlled trial.

eNRS: nonrandomized studies.

Inclusion and Exclusion Criteria

The following subsections on population, intervention, comparator, outcomes, and study design explicate the various elements of Population, Intervention, Comparison, Outcome Measures, and Design (PICOS), which is the framework used in this study to facilitate the literature search [58].

Population

Studies including children aged between 0 and 12 years with a diagnosis of ASD (Asperger syndrome, autism, or unspecified developmental disorder) with varying severity (mild, moderate, or severe) will be accepted. The study should include at least 1 diagnostic criterion regarding the Diagnostic and Statistical Manual of Mental Disorder [1], International Statistical Classification of Diseases and Related Health Problems, or Autism Diagnostic Observation Schedule. In addition, demographic information, including age, gender, and sample size, should be reported.

Intervention

Studies intended to increase cognitive functions in participants with ASD using physical activity or exercise interventions will be included. Studies evaluating physical activity exhibited in school-based physical education, exergaming, mindfulness practice (eg, yoga, martial arts, and Tai Chi), aerobic exercise and sports, and any types of therapeutic physical activity interventions will be included.

Comparison

Studies with comparators such as active behavioral control group, waiting list control group, and standard care group will be eligible for inclusion in the network of evidence.

Outcome Measures

Studies should report mean differences in cognitive function measurements between the beginning of the intervention and follow-up test. Studies should have obtained at least 1 validated outcome measurement of cognitive functions. Study features must include the measurement tool with either objective or self-reported patterns.

Design

RCTs should have assessed the outcome measures before (baseline) and after the intervention; the study should have included >1 session of intervention.

Exclusion Criteria

The following studies were excluded: studies including participants who were aged >12 years or were unable to conduct psychomotor movements, studies not involving an RCT, studies where the intervention lasted <8 weeks, and studies not written in English.

Study Selection and Data Extraction

Recording and managing related literature will be accomplished using the Mendeley software (Mendeley Ltd). Two authors will independently screen the titles and abstracts of the searched peer-reviewed studies based on the preestablished criteria for inclusion. A third reviewer will be involved to initiate a full-text evaluation if any conflicted selections occur. The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flowchart illustrates the search and screening processes (Figure 2).

Study characteristics, including author information, publication year, mean age in sample, diagnostic criteria for ASD, study period, intervention arms, and study design, will be summarized using Microsoft Excel (version 2010; Microsoft Corp). Specifically, we will adopt a thematic organization approach to categorize intervention arms within all relevant RCTs into six predefined categories: (1) school physical education programs, (2) exergaming, (3) aerobic exercise and sports, (4) mindfulness practice, (5) computerized and noncomputer games combination, and (6) therapeutic physical activity interventions [32,37]. The project administrator will serve as the coordinator, dealing with potential disagreements or unclearly defined PAIS categories. Internal discussions and consultation with an experienced researcher in physical activity and health promotion are considered 2 solutions for disagreements and uncertainties. The interrater agreement rate, Cohen k, between reviewers regarding the eligibility criteria of the study will be reported [62]. Note that grouped and ungrouped or supervised and unsupervised intervention arms will be separated as 1 effect size per treatment [51]. Quantified outcomes (mean of the intervention arms and comparators, SDs, and 95% CIs) will be extracted from the aforementioned categories, including measurement results regarding cognitive functions (eg, global EFs, working memory, thinking flexibility, inhibitory control, attention, or memory outcomes). In the NMA, we will compare the effects of the predefined intervention categories on participants’ cognitive performance. Raw data (eg, sample sizes and t, F, or P values) will be extracted to help estimate the effect size if the means and SDs were not reported [51]. When necessary, the corresponding authors of selected studies will be contacted to obtain unpublished and missing data to allow for effect size estimates.

Figure 2. PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flowchart of searching and screening.

Assessment of RoB

The Grading of Recommendations Assessment, Development, and Evaluation will be used to assess the quality of the selected studies in the NMA and pairwise meta-analysis [63-65]. Two authors will independently assess bias due to randomization, deviations from intervention, missing data, outcome measurement, and the selection of reported results in the selected RCTs. Each item is classified as high, some concerns, or less or unclear or no information upon RoB, and the results of the grading of evidence quality will then be generated as a table (Cochrane RoB tool; version 2.0 [66]). Homogeneity will be assessed by summarizing the selected study characteristics in a general table and observing whether the treatments and participant characteristics are suitable and comparable across all studies [40,58]. Consistency should be ensured such that direct evidence and indirect evidence essentially agree with each other without any discrepancies [40]. The R package (R Foundation for Statistical Computing) developed by van Valkenhoef et al [67] will be used to evaluate the inconsistency between indirect and direct comparisons via the node-splitting method. We evaluated consistency using a node-splitting technique that compares the direct and indirect estimates for each comparison. Transitivity will be qualitatively examined to ensure that direct trials do not differ with respect to the distribution of effect modifiers in which all treatments are jointly randomizable [68].

Statistical Analysis

The primary outcome for this study will be changes in cognitive functions. However, unlike physiological and biochemical indexes, cognitive performances were measured through preestablished validated psychometric instruments (illustrated in Table 1). Guiding through the approach applied by Désaméricq et al [69], the effect size will be calculated for each extracted result, and these effect sizes will then be combined into 3 cognitive scores, as listed in Multimedia Appendix 1. An omnibus composite unit free score of cognitive outcomes will be created by averaging all subordinate domain effect sizes within a study per intervention arm. Studies including multiple treatments or outcomes will provide the effect size of each treatment or outcome. Extracted data, such as sample size, treatment and control means and SDs for between-group designs, and preintervention and postintervention mean and SDs for within-group designs, will be converted to correlated summary results, standardized mean differences (SMDs), for NMA to explore the efficacy of PAIS on cognitive performance [70]. The effect sizes will be computed using SMD with 95% CIs between groups [32,71]. Hedges g in a random model will be used in consideration of potential variances across the selected studies if the number of studies is <20 [32,51,72]. Effect sizes will be classified as small, moderate, or high, respectively, with regard to the cutoff values of 0.2, 0.5, and 0.8 [32,73]. The calculations will be computed through a between-case SMD estimator, the web application scdhlm [74]. Heterogeneity will be evaluated through the means of Q test and I2 values, considering statistical heterogeneity of 25% as low, 50% as medium, and 75% as high [32,75,76]. Sensitivity analyses will be conducted to determine whether any study separately influenced the overall results [77]. To minimize the impact of heterogeneous outcomes or extreme values, we will apply the threshold of z score 3.29 to screen out outliers in the mean effect scores [46,53,78]. The level of significance will be set at.05 in this study. The NMA will be performed in RStudio (version 3.6; RStudio Inc [79]) using the BUGSnet package (version 1.1.0 [80]).

Moderation Analysis

Moderation analysis will be conducted to examine the variability among potential sources owing to heterogeneous PAIS settings. Moderators such as participant age, exercise intensity, and intervention setting (eg, group vs individual) will be examined using robust variance estimation [51]. Our expectation is to provide another perspective of synthesis results to elicit the higher order outcomes from NMA. Moderation analysis will be performed in the Comprehensive Meta-Analysis software (version 3.3; Biostat Inc).

Ethical Considerations and Dissemination

The ethics approval process is exempted because this study will be based on findings of previous studies. This review protocol has been registered in PROSPERO with the aims of promoting transparency and minimizing the RoB [81]. Future results will be submitted to a peer-reviewed journal of the relevant field for consideration for publication.

Expected Findings

We expect to compare the effects of different PAIS on cognitive outcomes (overall and by domain) over a period of treatment (at least 8 weeks). We will perform an NMA; we will select all RCTs that consider PAIS as a treatment for cognitive outcomes in children with ASD. This study will bridge the gap and provide a novel perspective and robust evidence to clinicians and practitioners for future decision-making in children with ASD. Forecasted results will include study characteristics, qualitative appraisal of cognitive tasks and intervention technologies, and quality of the selected studies; visual demonstration of synthesis results such as network diagrams and associated geometry will be generated and evaluated, respectively. Expected results will be able to rank the efficacy of multiple PAIS (eg, aerobic exercise, mindlessness practices, school-based physical education programs, and exergaming) with effect size differences demonstrated between multiple treatments. In addition to network plots, results will be illustrated in tables of network characteristics, data plots, league tables and league heat plots, surface under the cumulative ranking curve plots, and rankograms. An in-depth discussion will be held. In general, results may reveal the rank efficacy of PAIS, in combination or as single treatment, on promoting cognitive functions and further social and communication skills in children with ASD. In addition, owing to the COVID-19 pandemic, social restrictions and isolation were enforced, which led to an increase in sedentary behavior and physical inactivity, which, in turn, increased the risks of cardiovascular disease and mental wellness crisis in children [82-84]. There are more concerns especially regarding children with ASD [85,86]. We will include an in-depth discussion of feasible interventions along with safety suggestions for programming during the global pandemic.


Our preliminary search identified 3778 potentially relevant studies. The screening of the studies based on the inclusion and exclusion criteria is ongoing, and we anticipate that the final number of eligible studies will be in the range of 30 to 50.


Principal Findings

With the described protocol, we aim to address the urgent need for effective PAIS to reduce the negative impact on cognitive outcomes in children with disabilities, including those with ASD. As noted in our mini review, research suggests that PAIS may have a positive impact on cognitive function in children with ASD, but there is limited information on the comparative effectiveness of different types of PAIS. Therefore, our study represents an important contribution to the field, as it is the first systematic review and NMA protocol to propose to examine the efficacy of PAIS on cognitive performance in children with ASD.

Preliminary results from the mini review suggested that several types of PAIS, including yoga, martial arts, and aerobic exercise, may have positive effects on cognitive performance in children with ASD. Specifically, we found that these interventions were associated with improvements in cognitive flexibility, attention, and memory. Notably, our NMA will allow us to indirectly compare the effectiveness of different types of PAIS, providing valuable insights into which interventions may be most effective for improving cognitive function in this population.

Our study represents an important contribution to the literature on the efficacy of PAIS in improving cognitive performance in children with ASD. Although we have taken steps to minimize bias and ensure the quality of the study, as listed in Multimedia Appendix 2, there are some limitations that should be considered when interpreting our results. First, our study is limited by the quality and heterogeneity of the included studies. Although we have conducted a comprehensive search of multiple databases and used rigorous inclusion criteria, some relevant studies may have been missed. Second, as with any systematic review and NMA protocol, our study is limited by the quality and consistency of the data extracted from the included studies. We took steps to mitigate these issues by using a rigorous assessment of the RoB and data extraction processes. In addition, the statistical and moderation analyses we have planned will allow us to explore the sources of heterogeneity and potential moderators of treatment effects. Finally, we have adhered to ethical guidelines and plan to disseminate our findings to relevant stakeholders to facilitate the translation of research into practice.

Conclusions

Despite these limitations, we believe that our study provides valuable insights into the efficacy of PAIS for improving cognitive performance in children with ASD. Our findings suggest that clinicians and policy makers should consider incorporating PAIS into interventions aimed at improving cognitive function in this population. Furthermore, our study highlights the need for additional research in this area, including larger, well-controlled studies to further examine the comparative effectiveness of different types of PAIS. Overall, we hope that our study will contribute to the development of evidence-based interventions that can help improve outcomes for children with ASD.

Data Availability

This is not applicable at present, as this is a protocol paper. However, future and final data sets will be available from the corresponding author upon reasonable request.

Authors' Contributions

LL conceptualized this study. LL and AW contributed to the study conception and design and drafting the protocol. MEM and QF revised the draft critically for important intellectual content and gave final approval of the version for publication. MEM monitored the project administration. All authors contributed to the manuscript and approved the submitted version.

Conflicts of Interest

None declared.

Multimedia Appendix 1

Cognitive measures in effect calculation.

DOCX File , 19 KB

Multimedia Appendix 2

PRISMA-NMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols for Network Meta-Analyses) checklist.

DOCX File , 24 KB

  1. Diagnostic And Statistical Manual Of Mental Disorders, Fifth Edition. Arlington, VA. American Psychiatric Association; 2013.
  2. Steiner H, Kertesz Z. Effects of therapeutic horse riding on gait cycle parameters and some aspects of behavior of children with autism. Acta Physiol Hung. Sep 2015;102(3):324-335. [FREE Full text] [CrossRef] [Medline]
  3. Tse C, Lee H, Chan K, Edgar V, Wilkinson-Smith A, Lai W. Examining the impact of physical activity on sleep quality and executive functions in children with autism spectrum disorder: a randomized controlled trial. Autism. Oct 2019;23(7):1699-1710. [FREE Full text] [CrossRef] [Medline]
  4. Autism. World Health Organization. URL: http://www.who.int/features/qa/85/en/ [accessed 2021-09-09]
  5. Data and statistics on autism spectrum disorder. Centers for Disease Control and Prevention. URL: https://www.cdc.gov/ncbddd/autism/data.html [accessed 2021-09-06]
  6. Maenner MJ, Shaw KA, Baio J, EdS1; Washington A, Patrick M, PhD-7; et al. Prevalence of autism spectrum disorder among children aged 8 years - autism and developmental disabilities monitoring network, 11 sites, United States, 2016. MMWR Surveill Summ. Mar 27, 2020;69(4):1-12. [FREE Full text] [CrossRef] [Medline]
  7. Baio J, Wiggins L, Christensen DL, Maenner MJ, Daniels J, Warren Z, et al. Prevalence of autism spectrum disorder among children aged 8 years - autism and developmental disabilities monitoring network, 11 sites, United States, 2014. MMWR Surveill Summ. Apr 27, 2018;67(6):1-23. [FREE Full text] [CrossRef] [Medline]
  8. Zablotsky B, Black L, Maenner M, Schieve L, Danielson M, Bitsko R, et al. Prevalence and trends of developmental disabilities among children in the United States: 2009-2017. Pediatrics. Oct 2019;144(4):2009. [FREE Full text] [CrossRef] [Medline]
  9. Gabbard CP. Lifelong Motor Development. 7th edition. Philadelphia. Wolters Kluwer Health; 2018.
  10. AlOlaby RR, Sweha SR, Silva M, Durbin-Johnson B, Yrigollen CM, Pretto D, et al. Molecular biomarkers predictive of sertraline treatment response in young children with fragile X syndrome. Brain Dev. Jun 2017;39(6):483-492. [FREE Full text] [CrossRef] [Medline]
  11. Bremer E, Graham JD, Heisz JJ, Cairney J. Effect of acute exercise on prefrontal oxygenation and inhibitory control among male children with autism spectrum disorder: an exploratory study. Front Behav Neurosci. 2020;14:84. [FREE Full text] [CrossRef] [Medline]
  12. Just MA, Cherkassky VL, Keller TA, Kana RK, Minshew NJ. Functional and anatomical cortical underconnectivity in autism: evidence from an FMRI study of an executive function task and corpus callosum morphometry. Cereb Cortex. Apr 2007;17(4):951-961. [FREE Full text] [CrossRef] [Medline]
  13. Wass S. Distortions and disconnections: disrupted brain connectivity in autism. Brain Cogn. Feb 2011;75(1):18-28. [CrossRef] [Medline]
  14. Maw SS, Haga C. Effectiveness of cognitive, developmental, and behavioural interventions for Autism Spectrum Disorder in preschool-aged children: a systematic review and meta-analysis. Heliyon. Sep 2018;4(9):e00763. [FREE Full text] [CrossRef] [Medline]
  15. Margari L, Craig F, Margari F, Legrottaglie A, Palumbi R, De Giambattista C. A review of executive function deficits in autism spectrum disorder and attention-deficit/hyperactivity disorder. Neuropsychiatr Dis Treat. May 2016;12:1191. [CrossRef]
  16. Kuhl PK. Brain mechanisms in early language acquisition. Neuron. Sep 09, 2010;67(5):713-727. [FREE Full text] [CrossRef] [Medline]
  17. Pellicano E, Burr D. When the world becomes 'too real': a Bayesian explanation of autistic perception. Trends Cogn Sci. Oct 2012;16(10):504-510. [FREE Full text] [CrossRef] [Medline]
  18. Halpern DF. Teaching critical thinking for transfer across domains: disposition, skills, structure training, and metacognitive monitoring. Am Psychologist. 1998;53(4):449-455. [CrossRef]
  19. Demetriou EA, Pepper KL, Park SH, Pellicano L, Song YJ, Naismith SL, et al. Autism spectrum disorder: an examination of sex differences in neuropsychological and self-report measures of executive and non-executive cognitive function. Autism. Nov 2021;25(8):2223-2237. [CrossRef] [Medline]
  20. Solomon M, Ozonoff SJ, Cummings N, Carter CS. Cognitive control in autism spectrum disorders. Int J Dev Neurosci. Apr 13, 2008;26(2):239-247. [FREE Full text] [CrossRef] [Medline]
  21. Barneveld PS, Swaab H, van Engeland H, de Sonneville L. Cross-sectional evidence for a decrease in cognitive function with age in children with autism spectrum disorders? Autism Res. Oct 2014;7(5):527-534. [FREE Full text] [CrossRef] [Medline]
  22. Heidari S, Mostafaei S, Razazian N, Rajati M, Saeedi A, Rajati F. Correlation between lead exposure and cognitive function in 12-year-old children: a systematic review and meta-analysis. Environ Sci Pollut Res Int. Aug 2021;28(32):43064-43073. [FREE Full text] [CrossRef] [Medline]
  23. Kim TW, Park HS. Physical exercise improves cognitive function by enhancing hippocampal neurogenesis and inhibiting apoptosis in male offspring born to obese mother. Behav Brain Res. Jul 16, 2018;347:360-367. [CrossRef] [Medline]
  24. Yeager A. How exercise reprograms the brain. The Scientist. Nov 1, 2018. URL: https://www.the-scientist.com/features/this-is-your-brain-on-exercise-64934#reference9 [accessed 2021-08-08]
  25. Donnelly JE, Lambourne K. Classroom-based physical activity, cognition, and academic achievement. Prev Med. Jun 2011;52 Suppl 1:S36-S42. [FREE Full text] [CrossRef] [Medline]
  26. Benito E, Kerimoglu C, Ramachandran B, Pena-Centeno T, Jain G, Stilling RM, et al. RNA-dependent intergenerational inheritance of enhanced synaptic plasticity after environmental enrichment. Cell Rep. Apr 10, 2018;23(2):546-554. [FREE Full text] [CrossRef] [Medline]
  27. Fedewa AL, Ahn S. The effects of physical activity and physical fitness on children's achievement and cognitive outcomes: a meta-analysis. Res Q Exerc Sport. Sep 2011;82(3):521-535. [CrossRef] [Medline]
  28. Yu CC, Wong SW, Lo FS, So RC, Chan DF. Study protocol: a randomized controlled trial study on the effect of a game-based exercise training program on promoting physical fitness and mental health in children with autism spectrum disorder. BMC Psychiatry. Feb 27, 2018;18(1):56. [FREE Full text] [CrossRef] [Medline]
  29. Pan CY, Chu CH, Tsai CL, Sung MC, Huang CY, Ma WY. The impacts of physical activity intervention on physical and cognitive outcomes in children with autism spectrum disorder. Autism. Feb 09, 2017;21(2):190-202. [CrossRef] [Medline]
  30. Milajerdi HR, Sheikh M, Najafabadi MG, Saghaei B, Naghdi N, Dewey D. The effects of physical activity and exergaming on motor skills and executive functions in children with autism spectrum disorder. Games Health J. Feb 01, 2021;10(1):33-42. [CrossRef] [Medline]
  31. Rosenthal-Malek A, Mitchell S. Brief report: the effects of exercise on the self-stimulatory behaviors and positive responding of adolescents with autism. J Autism Dev Disord. Apr 1997;27:193-202. [FREE Full text] [CrossRef]
  32. Liang X, Li R, Wong SH, Sum RK, Wang P, Yang B, et al. The effects of exercise interventions on executive functions in children and adolescents with autism spectrum disorder: a systematic review and meta-analysis. Sports Med. Jan 01, 2022;52(1):75-88. [CrossRef] [Medline]
  33. Bass MM, Duchowny CA, Llabre MM. The effect of therapeutic horseback riding on social functioning in children with autism. J Autism Dev Disord. Sep 2009;39(9):1261-1267. [FREE Full text] [CrossRef] [Medline]
  34. Bremer E, Crozier M, Lloyd M. A systematic review of the behavioural outcomes following exercise interventions for children and youth with autism spectrum disorder. Autism. Nov 2016;20(8):899-915. [FREE Full text] [CrossRef] [Medline]
  35. Ward SC, Whalon K, Rusnak K, Wendell K, Paschall N. The association between therapeutic horseback riding and the social communication and sensory reactions of children with autism. J Autism Dev Disord. Sep 2013;43(9):2190-2198. [FREE Full text] [CrossRef] [Medline]
  36. Bahrami F, Movahedi A, Marandi SM, Abedi A. Kata techniques training consistently decreases stereotypy in children with autism spectrum disorder. Res Dev Disabil. Jul 2012;33(4):1183-1193. [FREE Full text] [CrossRef] [Medline]
  37. Diamond A, Lee K. Interventions shown to aid executive function development in children 4 to 12 years old. Science. Aug 19, 2011;333(6045):959-964. [FREE Full text] [CrossRef] [Medline]
  38. Fang Q, Aiken CA, Fang C, Pan Z. Effects of exergaming on physical and cognitive functions in individuals with autism spectrum disorder: a systematic review. Games Health J. Apr 2019;8(2):74-84. [FREE Full text] [CrossRef] [Medline]
  39. Rosenblatt LE, Gorantla S, Torres JA, Yarmush RS, Rao S, Park ER, et al. Relaxation response-based yoga improves functioning in young children with autism: a pilot study. J Altern Complement Med. Nov 2011;17(11):1029-1035. [FREE Full text] [CrossRef] [Medline]
  40. Su X, McDonough DJ, Chu H, Quan M, Gao Z. Application of network meta-analysis in the field of physical activity and health promotion. J Sport Health Sci. Dec 2020;9(6):511-520. [FREE Full text] [CrossRef] [Medline]
  41. Aleksandrovic M, Jorgic B, Block M, Jovanovic L. The effects of aquatic activities on physical fitness and aquatic skills in children with autism spectrum disorders: a systematic review. Facta Universitatis Series Physical Educ Sport. 2015;13(3):351-362. [FREE Full text]
  42. Cameron KL, Albesher RA, McGinley JL, Allison K, Cheong JL, Spittle AJ. Movement-based interventions for preschool-age children with, or at risk of, motor impairment: a systematic review. Dev Med Child Neurol. Mar 2020;62(3):290-296. [FREE Full text] [CrossRef] [Medline]
  43. Case L, Yun J. The effect of different intervention approaches on gross motor outcomes of children with autism spectrum disorder: a meta-analysis. Adapt Phys Activ Q. Oct 01, 2019;36(4):501-526. [FREE Full text] [CrossRef] [Medline]
  44. Chan JS, Deng K, Yan JH. The effectiveness of physical activity interventions on communication and social functioning in autistic children and adolescents: a meta-analysis of controlled trials. Autism. May 2021;25(4):874-886. [FREE Full text] [CrossRef] [Medline]
  45. Ferreira JP, Ghiarone T, Júnior CR, Furtado GE, Carvalho HM, Rodrigues AM, et al. Effects of physical exercise on the stereotyped behavior of children with autism spectrum disorders. Medicina (Kaunas). Oct 14, 2019;55(10):685. [FREE Full text] [CrossRef] [Medline]
  46. Howells K, Sivaratnam C, May T, Lindor E, McGillivray J, Rinehart N. Efficacy of group-based organised physical activity participation for social outcomes in children with autism spectrum disorder: a systematic review and meta-analysis. J Autism Dev Disord. Aug 2019;49(8):3290-3308. [FREE Full text] [CrossRef] [Medline]
  47. Huang J, Du C, Liu J, Tan G. Meta-analysis on intervention effects of physical activities on children and adolescents with autism. Int J Environ Res Public Health. Mar 17, 2020;17(6):1950. [FREE Full text] [CrossRef] [Medline]
  48. Petrus C, Adamson SR, Block L, Einarson SJ, Sharifnejad M, Harris SR. Effects of exercise interventions on stereotypic behaviours in children with autism spectrum disorder. Physiother Can. Oct 2008;60(2):134-145. [FREE Full text] [CrossRef] [Medline]
  49. Semple RJ. Review: yoga and mindfulness for youth with autism spectrum disorder: review of the current evidence. Child Adolesc Ment Health. Feb 2019;24(1):12-18. [FREE Full text] [CrossRef] [Medline]
  50. Zhang M, Liu Z, Ma H, Smith DM. Chronic physical activity for attention deficit hyperactivity disorder and/or autism spectrum disorder in children: a meta-analysis of randomized controlled trials. Front Behav Neurosci. 2020;14:564886. [FREE Full text] [CrossRef] [Medline]
  51. Teh EJ, Vijayakumar R, Tan TX, Yap MJ. Effects of physical exercise interventions on stereotyped motor behaviours in children with ASD: a meta-analysis. J Autism Dev Disord. Jul 2022;52(7):2934-2957. [FREE Full text] [CrossRef] [Medline]
  52. Fragala-Pinkham MA, Ball AL, Jeffries LM. Efficacy of lower extremity cycling interventions for youth with intellectual disabilities: a systematic review. Phys Occup Ther Pediatr. 2021;41(4):410-428. [FREE Full text] [CrossRef] [Medline]
  53. Healy S, Nacario A, Braithwaite RE, Hopper C. The effect of physical activity interventions on youth with autism spectrum disorder: a meta-analysis. Autism Res. Jun 2018;11(6):818-833. [FREE Full text] [CrossRef] [Medline]
  54. Lang R, Koegel LK, Ashbaugh K, Regester A, Ence W, Smith W. Physical exercise and individuals with autism spectrum disorders: a systematic review. Res Autism Spectrum Disorder. Oct 2010;4(4):565-576. [CrossRef]
  55. Ruggeri A, Dancel A, Johnson R, Sargent B. The effect of motor and physical activity intervention on motor outcomes of children with autism spectrum disorder: a systematic review. Autism. Apr 2020;24(3):544-568. [FREE Full text] [CrossRef] [Medline]
  56. Sowa M, Meulenbroek R. Effects of physical exercise on autism spectrum disorders: a meta-analysis. Res Autism Spectrum Disorder. Jan 2012;6(1):46-57. [FREE Full text] [CrossRef]
  57. Morley S. Single Case Methods in Clinical Psychology A Practical Guide. England. Routledge; 2018.
  58. Dias S, Ades AE, Welton NJ, Jansen JP, Sutton AJ. Network Meta‐Analysis for Decision Making. Hoboken. John Wiley & Sons; 2018.
  59. Hutton B, Salanti G, Caldwell DM, Chaimani A, Schmid CH, Cameron C, et al. The PRISMA extension statement for reporting of systematic reviews incorporating network meta-analyses of health care interventions: checklist and explanations. Ann Intern Med. Jun 02, 2015;162(11):777-784. [CrossRef]
  60. Liberati A, Altman DG, Tetzlaff J, Mulrow C, Gøtzsche PC, Ioannidis JP, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. PLoS Med. Jul 21, 2009;6(7):e1000100. [FREE Full text] [CrossRef] [Medline]
  61. Shim SR, Kim S, Lee J, Rücker G. Network meta-analysis: application and practice using R software. Epidemiol Health. Apr 08, 2019;41:e2019013. [FREE Full text] [CrossRef] [Medline]
  62. Kelley GA, Kelley KS. Exercise and BMI z-score in overweight and obese children and adolescents: protocol for a systematic review and network meta-analysis of randomised trials. BMJ Open. Apr 15, 2016;6(4):e011258. [FREE Full text] [CrossRef] [Medline]
  63. Brignardello-Petersen R, Bonner A, Alexander PE, Siemieniuk RA, Furukawa TA, Rochwerg B, et al. GRADE Working Group. Advances in the GRADE approach to rate the certainty in estimates from a network meta-analysis. J Clin Epidemiol. Jan 2018;93:36-44. [CrossRef] [Medline]
  64. Puhan MA, Schünemann HJ, Murad MH, Li T, Brignardello-Petersen R, Singh JA, et al. GRADE Working Group. A GRADE Working Group approach for rating the quality of treatment effect estimates from network meta-analysis. BMJ. Sep 24, 2014;349(sep24 5):g5630. [FREE Full text] [CrossRef] [Medline]
  65. Salanti G, Del Giovane C, Chaimani A, Caldwell DM, Higgins JP. Evaluating the quality of evidence from a network meta-analysis. PLoS One. Jul 3, 2014;9(7):e99682. [FREE Full text] [CrossRef] [Medline]
  66. McGuinness LA, Higgins JP. Risk-of-bias VISualization (robvis): an R package and Shiny web app for visualizing risk-of-bias assessments. Res Synth Methods. Jan 06, 2021;12(1):55-61. [CrossRef] [Medline]
  67. van Valkenhoef G, Dias S, Ades AE, Welton NJ. Automated generation of node-splitting models for assessment of inconsistency in network meta-analysis. Res Synth Methods. Mar 13, 2016;7(1):80-93. [FREE Full text] [CrossRef] [Medline]
  68. Salanti G. Indirect and mixed-treatment comparison, network, or multiple-treatments meta-analysis: many names, many benefits, many concerns for the next generation evidence synthesis tool. Res Synth Methods. Jun 11, 2012;3(2):80-97. [CrossRef] [Medline]
  69. Désaméricq G, Schurhoff F, Meary A, Szöke A, Macquin-Mavier I, Bachoud-Lévi AC, et al. Long-term neurocognitive effects of antipsychotics in schizophrenia: a network meta-analysis. Eur J Clin Pharmacol. Feb 22, 2014;70(2):127-134. [CrossRef] [Medline]
  70. Yunusa I, Alsumali A, Garba AE, Regestein QR, Eguale T. Assessment of reported comparative effectiveness and safety of atypical antipsychotics in the treatment of behavioral and psychological symptoms of dementia: a network meta-analysis. JAMA Netw Open. Mar 01, 2019;2(3):e190828. [FREE Full text] [CrossRef] [Medline]
  71. Polanin JR, Snilstveit B. Converting between effect sizes. Campbell Syst Rev. Dec 2016;12(1):1-13. [FREE Full text] [CrossRef]
  72. Borenstein M, Hedges LV, Higgins JP, Rothstein HR. Introduction to Meta-Analysis. Hoboken, New Jersey. John Wiley & Sons; 2009.
  73. Stanmore E, Stubbs B, Vancampfort D, de Bruin ED, Firth J. The effect of active video games on cognitive functioning in clinical and non-clinical populations: a meta-analysis of randomized controlled trials. Neurosci Biobehav Rev. Jul 2017;78:34-43. [FREE Full text] [CrossRef] [Medline]
  74. Pustejovsky JE, Chen M, Hamilton B, Grekov P. scdhlm: a web-based calculator for between-case standardized mean differences (Version 0.7.2). jepusto. 2023. URL: https://jepusto.shinyapps.io/scdhlm [accessed 2023-02-01]
  75. Higgins JP, Thompson SG. Quantifying heterogeneity in a meta-analysis. Stat Med. Jun 15, 2002;21(11):1539-1558. [CrossRef] [Medline]
  76. Hunter JE, Schmidt FL. Methods of Meta-Analysis Correcting Error and Bias in Research Findings. Thousand Oaks. SAGE Publications; 1990.
  77. Andreato LV, Esteves JV, Coimbra DR, Moraes AJ, de Carvalho T. The influence of high-intensity interval training on anthropometric variables of adults with overweight or obesity: a systematic review and network meta-analysis. Obes Rev. Jan 18, 2019;20(1):142-155. [CrossRef] [Medline]
  78. Warner RM. Applied Statistics: From Bivariate Through Multivariate Techniques 2nd Edition. Thousand Oaks. SAGE Publications; 2012.
  79. RStudio Team. RStudio: Integrated Development for R. Boston, MA. RStudio, PBC; 2020.
  80. Béliveau A, Boyne D, Slater J, Brenner D, Arora P. BUGSnet: an R package to facilitate the conduct and reporting of Bayesian network meta-analyses. BMC Med Res Methodol. Oct 22, 2019;19(1):196. [FREE Full text] [CrossRef] [Medline]
  81. Guidance notes for registering a systematic review protocol with PROSPERO. University of York Centre for Reviews and Dissemination. May 2016. URL: https://www.crd.york.ac.uk/prospero/documents/Registering%20a%20review%20on%20PROSPERO.pdf [accessed 2021-09-01]
  82. Hoffman JA, Miller EA. Addressing the consequences of school closure due to COVID-19 on children's physical and mental well-being. World Med Health Policy. Sep 20, 2020;12(3):300-310. [FREE Full text] [CrossRef] [Medline]
  83. Patrick SW, Henkhaus LE, Zickafoose JS, Lovell K, Halvorson A, Loch S, et al. Well-being of parents and children during the COVID-19 pandemic: a national survey. Pediatrics. Oct 2020;146(4):e2020016824. [CrossRef] [Medline]
  84. Peçanha T, Goessler KF, Roschel H, Gualano B. Social isolation during the COVID-19 pandemic can increase physical inactivity and the global burden of cardiovascular disease. Am J Physiol Heart Circ Physiol. Jun 01, 2020;318(6):H1441-H1446. [FREE Full text] [CrossRef] [Medline]
  85. Bellomo TR, Prasad S, Munzer T, Laventhal N. The impact of the COVID-19 pandemic on children with autism spectrum disorders. J Pediatr Rehabil Med. Nov 23, 2020;13(3):349-354. [CrossRef]
  86. O'Sullivan K, Clark S, McGrane A, Rock N, Burke L, Boyle N, et al. A qualitative study of child and adolescent mental health during the COVID-19 pandemic in Ireland. Int J Environ Res Public Health. Jan 25, 2021;18(3):1062. [FREE Full text] [CrossRef] [Medline]


ASD: autism spectrum disorder
EF: executive function
MeSH: Medical Subject Headings
NMA: network meta-analysis
PAIS: physical activity intervention strategies
PICOS: Population, Intervention, Comparison, Outcome Measures, and Design
PRISMA: Preferred Reporting Items for Systematic Reviews and Meta-Analyses
PRISMA-NMA: Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols for Network Meta-Analyses
RCT: randomized controlled trial
RoB: risk of bias
SMD: standardized mean difference


Edited by A Mavragani; submitted 17.06.22; peer-reviewed by L Ardigò, X Cheng; comments to author 16.02.23; revised version received 09.04.23; accepted 10.04.23; published 28.06.23.

Copyright

©Longxi Li, Anni Wang, Qun Fang, Michelle E Moosbrugger. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 28.06.2023.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Research Protocols, is properly cited. The complete bibliographic information, a link to the original publication on https://www.researchprotocols.org, as well as this copyright and license information must be included.