aging social engagement physical activity chien-yu.pdf

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Age, social engagement, and physical activity in children

with autism spectrum disorders

Chien-Yu Pan *

Department of Physical Education, National Kaohsiung Normal University, No. 116, He-Ping First Road, Kaohsiung 802, Taiwan

Infrequent or no engagement in social interactions and stereotypic behaviors are two overt and

defining characteristics of autism spectrum disorder (ASD) (American Psychiatric Association, 1994).

To date, motor impairments observed in individuals with ASD have been categorized as associated

symptoms (Ming, Brimacombe, & Wagner, 2007). These characteristics create severe limitations.

Stereotypic behavior, for some children, interferes with learning and may alienate peers and adults

Research in Autism Spectrum Disorders 3 (2009) 2231

A R T I C L E I N F O

Article history:

Received 4 March 2008

Accepted 10 March 2008

Keywords:

Age

Social engagement

Physical activity

Autism

A B S T R A C T

Although engagement in social interactions is one of the key

diagnostic features of autism spectrum disorders (ASDs), few

studies have examined if social engagement related to physical

activity of children with ASD. Age is another variable of interest to

researchers studying behaviors, but has not been explored in

physical activity and social engagement in this population. The

purpose of this study was to examine the associations of age, socialengagement and physical activity in children with ASD. Twenty-five

children with ASD participated. Each childs physical activity and

social engagement was assessed using a uniaxial accelerometer and

the direct observational assessment. Pearson product-moment

correlation coefficients and multiple regression analysis were used

to evaluate the associations and influences of selected variables.

Age had somewhat positive influences on both physical activity and

social engagement, and children with frequent social engagement

with adults had displayed higher levels of physical activity. No

evidence was found to support the notion that children with ASD

become more inactive and more isolate as they age; however,

limitations and directions for future research in this area arediscussed.

2008 Elsevier Ltd. All rights reserved.

* Tel.: +886 7 7172930x3531; fax: +886 7 7114633.

E-mail address:[email protected].

C o n t e n t s l i s t s a v a i l a b l e a t S c i e n c e D i r e c t

Research in Autism SpectrumDisorders

Journal homepage: http://ees.elsevier.com/RASD/default.asp

1750-9467/$ see front matter 2008 Elsevier Ltd. All rights reserved.

doi:10.1016/j.rasd.2008.03.002
mailto:[email protected]://www.sciencedirect.com/science/journal/17509467http://dx.doi.org/10.1016/j.rasd.2008.03.002http://dx.doi.org/10.1016/j.rasd.2008.03.002http://www.sciencedirect.com/science/journal/17509467mailto:[email protected]


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because of its highly unusual and stigmatizing nature. Social isolation from peers prevents the

formation of social relationships, which are essential for early social development. Poor motor

coordination could limit opportunities for this population to successfully participate in physical

activity and place them at risk for developing sedentary lifestyle associated diseases (U.S. Department

of Health and Human Services, 1996). It is not surprising, therefore, that children with ASD tend to

withdraw from participation in physical activity due to the negative social and behavioral outcomes

associated with the symptom. While it appears that the presence of an ASD affects opportunities for

physical activity participation, this issue has received relatively little attention in the literature. Since

ASD is the fastest growing developmental disability and there has been an 85% increase in the number

of school age Taiwanese children being diagnosed with ASD in the last 10 years (Ministry of Education,

2006a), there is a need to better understand how disability-related symptoms such as social

engagement affect certain health behaviors, including physical activity.

Studies that specifically investigate social engagement in children with ASD in inclusive and

natural settings are still relatively sparse.McGee, Feldman, and Morrier (1997)studied the naturally

occurring levels of social behavior of both children with ASD and typically developing children in

inclusive preschool settings, and found that children with ASD spent less time in the proximity of

other children, showed less focus on adults and peers as interactive partners, received fewer social

initiations from peers, used less verbalization towards other children, and engaged in more atypical

behavior.Sigman and Ruskin (1999)found that in comparison with children with other disabilities,

children with ASD spent a larger proportion of time engaged in nonsocial play and a smaller

proportion of time in direct social play with others. Children with ASD were also found to make less

initiation and show less responsiveness to peer initiations compared to controls. In a recent study by

Jahr, Eikeseth, Eldevik, and Aase (2007), the frequency and latency of social interaction with typically

developing children and those with ASD in inclusive kindergarten settings were compared. The results

showed a significant difference in frequency of social interaction between the typical children and

those with ASD and no difference between the groups on latency to initiate interaction.

There is relatively little information regarding accelerometer-determined physical activity in

children with ASD.Rosser-Sandt and Frey (2005)found that physical activity levels were similar inchildren with and without ASD and both groups acquired a majority of daily moderate physical

activity during recess. Pan and Frey (2006) examined physical activity patterns in youth with ASD and

observed that this group met minimum activity recommendations, but were less active than previous

reports on peers without ASD using similar methodology (Mota, Santos, Guerra, Ribeiro, & Duarte,

2003; Trost et al., 2002). In addition, physical activity levels were higher among participants in

elementary school compared to those in middle and high school. Pan (in press) compared the

percentage of time children with and without ASD spent in moderate-to-vigorous physical

activity (MVPA) during inclusive recess settings in Taiwan, and found that children with ASD were

less active during overall recess, lunchtime, first and second morning recess compared to those

without disabilities. All children also fell below 40% of recess time engaged in physical activity.

The inconsistent findings in the literature highlight the difficulty of generalization from theprevious studies using different methodologies. Additional studies are need in various national

and international populations to determine physical activity differs between children with and

without ASD.

Age is one variable of interest to researchers studying individuals behavior. However, to date, very

few studies have examined whether age exerts an influence on the impact of ASD in the daily life of

children. Several researchers have suggested that children with movement problems will increase as

childrens play becomes more complex and rule-bound (Cairney, Hay, Faught, Corna, & Flouris, 2006;

Wall, 2004). This is of concern, particularly in children with ASD who have difficulties understanding

social cues. They are unable to follow the typical course of development in the acquisition and

application of complex physical skills as they age. They will not be able to learn the higher-order

strategic skills required for participation in complex play activities when they are getting older.Despite the lack of research in the potential age influences on social engagement and physical activity

of children with ASD, it is reasonable to assume that the general age impact would also extend to

individuals with ASD since ASD is considered to be uncured and the long-term consequences of ASD

may not be favorable.

C.-Y. Pan / Research in Autism Spectrum Disorders 3 (2009) 2231 23


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The purpose of this study was to examine the associations of age, social engagement and physical

activity in children with ASD when participation in both structured (physical education) and

unstructured (recess) play opportunities are considered. It was hypothesized that age would show a

significant influence on both physical activity and social engagement participation in both free play

and organized settings in children with ASD. In addition, more frequent social engagement behaviors

would be observed in higher physical activity levels of children with ASD.

1. Methods

1.1. Participants and setting

Twenty-five boys with ASD aged between 7 and 12 years (9.28 1.46) volunteered to participate

and returned signed parental informed consent prior to study involvement. Twenty-two of the children

had normal speech patterns, and the remaining three children made a few sentences, as based on parent

reports and the researcher interaction with participants. All children with ASD met the criteria for autistic

disorder of the DSM-IV-Revised system (American Psychiatric Association, 2000) and the Identification

Standard for Students with Special Needs (Ministry of Education, 2006b), as assessed by trained andknowledgeable doctors through medical and psychological assessment in the public hospitals (Executive

Yuan, 2006a). Level of severity (mild, moderate, severe, and very severe) is based on functioning in the

social adaptive skill areas and language comprehension and expression (Executive Yuan, 2006b).

Diagnoses included autism (mild or high-functioning, n = 11; moderate,n = 8) and Aspergers syndrome

(n= 6). None of the children had any additional medical conditions such as epilepsy, cerebral palsy or

motor deficiencies. All the children reside in urban settings and 24 live in a two-parent household. None

were enrolled in a segregated or inclusive school-based physical activity programs or sports teams.

The children with ASD received part-time special education services which were individually

tailored for each child and based on recommendations from multidisciplinary teams of professionals

from regional specialist clinics, parents and educational authorities. No children with ASD had either

full- or part-time staff assistant available throughout the day. Mean height was 136.50 10.79 cm,mean body mass was 35.38 8.55 kg, and mean body mass index (BMI) was 18.81 2.97 kg/m2. These

values were within the normal ranges for Taiwanese children of this age ( Ministry of Education, 2007).

Participants schools were located in the same geographical area of high social and economic

deprivation in a large urban city, and all participants received physical education and recess in

inclusive settings without any level of supports. Each school had three morning recesses and three

afternoon recesses, and each recess length was 1020 min in duration. The area of the playground for

all schools was very limited because they were located in a crowded urban city. There was no visible

playground equipment or markings to stimulate play. Children were allowed to take their own balls,

toys, etc. during recess, but there was little evidence of any other equipment being used or being made

available. The physical education lesson was 40 min in duration and children in grades 12 and 36

were required to take 1 and 2 lessons each week, respectively. Twelve of children with ASD attendedregular physical education taught by class teachers, and the remaining 13 children were taught by

physical education specialists.

1.2. Assessment procedures

The study protocol was reviewed and approved by the National Science Council, Taiwan. Study

objectives and methods were individually explained to and written consent and assent obtained from

parents and children, respectively. Stature and body mass measures were collected according to class

teacher reports only if the child was measured at the beginning of the semester this study was

conducted. Otherwise, these measures were collected in school health center with all children dressed

in light clothing and shoes removed for calculation of body mass index (kg/m2) prior to study

involvement.

1.2.1. Physical activity measurement

The childrens physical activity levels and patterns were assessed by GT1M ActiGraph, a uniaxial

accelerometer that measures vertical acceleration of human motion as well as how many steps they

C.-Y. Pan / Research in Autism Spectrum Disorders 3 (2009) 223124


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take. The accelerometer has been used extensively and reported as a valid objective measure of

physical activity in children (Trost et al., 1998). It has also been used in youth with ASD (Pan, in press;

Pan & Frey, 2006; Rosser-Sandt & Frey, 2005) and found that this population can tolerate the

instrument. Consistent with previous studies, the accelerometer was placed in a small nylon pouch

and worn over the right hip with an elastic belt. Prior to data collection, verbal and written instructions

on how to wear and care for the device were provided. All participants also engaged in practice trials

wearing the device.

Participants wore the accelerometer for five consecutive school days during their regularly school

schedules. At the start of each school day, the accelerometers were attached by the research

assistants to the children and participants were then asked to follow their regular daily routine.

Accelerometers were removed at the end of the school day, and the data were immediately

downloaded and re-initialized for the next day. Some participants wore the same monitor every day,

and all occurring times for physical education class and each recess period were recorded by class

teachers and research assistants. Physical activity data were reduced from one physical education

class and one recess period each day for five consecutive school days in accordance with social

engagement observation.

Accelerometers were programmed to collect data in 1-min intervals. Activity counts were analyzed

to determine counts per minute (CPM), time spent in MVPA (3.0 MET) and vigorous physical activity

(VPA; 6.0 MET) using age-specific count cutoffs (Freedson et al., 1997; Trost, Pate, Freedson, Sallis, &

Taylor, 2000). To control for the differences in the monitoring recess and physical education length,

the relative (percentage) time spent in MVPA and VPA, and step counts per minute were calculated

and used in the subsequent analyses.

1.2.2. Social engagement measurement

Social engagement patterns were assessed using the Engagement Check (McWilliam, 1990).Itisan

observational tool that uses momentary time sampling procedure with a 15-s observe and 15-s record

cycle. McWilliam and Bailey (1995) have reported suitable reliability and validity estimates on

children with ASD.For the current study, childs engaged behavior is divided into two types (with adults and peers)

and two forms (interactive and noninteractive) of engagement. Interactive engagement was defined as

the childs focus on another person, and his/her behavior being aimed at producing a social effect.

Interdependent play, mutual organization, gestures, and talking are examples of interactive

engagement. Noninteractive engagement was defined as the child attending to another person or

playing nearby with similar materials. Looking, orienting, tracking, and listening are examples of

noninteractive engagement.

Each child was systematically observed one time in physical education, and one time in recess each

day for consecutive five school days. Observations of the two settings occurred on the same week.

Informal observations on days prior to formal data collection helped reduce reactivity, and

conversations with teachers after the formal observation verified that data were collected on typicalsocial engagement behaviors. The percentage of each social engagement category and the percentage

of total social engagement scores were used in the data analyses.

1.2.3. Observer training and interobserver reliability

Interobserver agreement was calculated by dividing agreements by agreements plus disagree-

ments and multiplying by 100 for each category. Before the study began, four observers were trained

by the researcher to use systematic observation methods and this studys social engagement

instrument. Each observer was required to review the observation instrument and become familiar

with the behavioral definitions. During the training sessions, the observers collected data on the

Engagement Check by watching videotapes of children with ASD in physical education classes and

recess periods previously made by the researcher. When a question arose about how to record aspecific behavior, the researcher and the observers discussed the behavior until all five agreed on the

appropriate recording procedure. Study observations began only after an interobserver agreement of

85% or greater was achieved for each variable across all four observers. Interobserver agreements that

did not meet criterion were addressed by extending the observer training until the interobserver



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agreement criterion was reached. The observers reached an overall agreement of at least 85%

agreement for these data.

1.3. Statistical analyses

Prior to analysis, physical activity data were examined separately at each setting for theassumptions of multivariate analysis. The residuals were normally distributed, and the assumption of

homoscedasticity was met. None of the cases were identified through Mahalanobis distance as

multivariate outliers, leaving all cases for the final analysis.

Pearson product-moment correlation coefficients were calculated to evaluate the relationship

between age, social engagement, and physical activity. When a variable was significant in the

correlations, it was entered into the multiple regression analysis. For each variable, the partial

correlation is reported, which reflects the contribution of that variable, adjusting for all other

variables.

Changes in multiple correlations squared (R2 change) are reported to demonstrate the amount of

variance explained by each variable. The adjusted multiple correlations squared represent the full

model. Because six physical activity and five social engagement variables are separate measures,prediction of these variables was examined in separate regression models. All statistical analyses were

computed using SPSS Statistical Software Package, Version 13.0. Values are reported as mean S.D.,

with significance set at P< 0.05.

2. Results

Descriptive statistics for physical activity and social engagement behaviors in children with ASD

during physical education and recess are shown in Table 1. The physical education and recess

monitoring time was 34.09 4.18 and 50.20 9.72 min, respectively. On average, children with ASD

were more active physically and socially during physical education than recess.

2.1. Age and physical activity

Table 2shows bivariate correlations of each physical activity variable and children age. Children

age was positively correlated with counts/min (r25= 0.50, P< 0.01) and steps/min (r25= 0.57,

P< 0.01) in recess and positively correlated with 5-min MVPA during physical education ( r25= 0.43,

P< 0.05).

The results of the multiple regression analyses showed that children age was significant in the

three regression models, explaining 22%, 29% and 15% of the variance in children overall physical

activity (counts/min, F1,23= 7.63, P< 0.05; R2 change = 0.25), steps/min (F1,23= 10.76, P< 0.01; R

2

change = 0.32) and 5-min MVPA (F1,23= 5.12, P< 0.05;R2 change = 0.18), respectively.

Table 1

Physical activity and social engagement during PE and recess (n= 25)

PE Recess

Physical activity

Counts/min 1538.35 862.38 1318.61 852.49

MVPA 54.86 24.72 46.84 25.33

VPA 8.30 9.16 5.82 7.20

Steps/min 38.34 20.27 33.55 20.62

5-min MVPA 5.25 11.03 3.61 3.72

10-min MVPA 0.75 2.05 0.76 1.38

Social engagement

Adult-interactive 28.57 27.49 9.34 9.03Adult-noninteractive 0.78 2.47 0.46 1.61

Peer-interactive 60.09 26.34 59.98 33.97

Peer-noninteractive 24.78 27.78 9.58 21.01

Total social engagement 114.22 44.23 79.36 48.80



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2.2. Age and social engagement

Table 3 shows bivariate correlations of each social engagement variable and children age. Childrenage was positively correlated with peer-interactive (r25= 0.48,P< 0.05) and total social engagement

behaviors (r25= 0.48,P< 0.05) during physical education. Children age was not correlated with any

social engagement behaviors in recess.

The results of the multiple regression analyses showed that children age was significant in the two

regression models, explaining 19% and 20% of the variance in children peer-interactive ( F1,23= 6.68,

P< 0.05; R2 change = 0.23) and total social engagement (F1,23= 7.01, P< 0.05; R2 change = 0.23),

respectively.

2.3. Social engagement and physical activity

Table 4 shows bivariate correlations of each physical activity variable and children social

engagement. Noninteractive engagement with adults during physical education was positivelycorrelated with children VPA (r25= 0.74, P< 0.01) and steps/min (r25= 0.51, P< 0.01). None of the

social engagement behaviors was correlated with any physical activity in recess.

Table 2

Bivariate correlations for the physical activity variables and children age during PE and recess

PE Recess

Age

Counts/min 0.34 0.50*MVPA 0.09 0.27

VPA 0.04 0.37

Steps/min 0.16 0.57**

5-min MVPA 0.43* 0.16

10-min MVPA 0.29 0.01

*P< 0.05; **P< 0.01; two-tailed; n = 25.

Table 3

Bivariate correlations for the social engagement variables and children age during PE and recess

PE Recess

Age

Adult-interactive 0.18 0.19

Adult-noninteractive 0.24 0.11

Peer-interactive 0.48* 0.12

Peer-noninteractive 0.17 0.15

Total social engagement 0.48* 0.19

*P< 0.05; two-tailed; n = 25.

Table 4

Bivariate correlations for the physical activity and social engagement variables during PE and recess

Counts/min MVPA VPA Steps/min 5-min MVPA 10-min MVPA

PE Recess PE Recess PE Recess PE Recess PE Recess PE Recess

AI 0.18 0.12 0.18 0.19 0.23 0.13 0.08 0.06 0.25 0.09 0.01 0.06

ANI 0.33 0.15 0.33 0.23 0.74** 0.16 0.51** 0.11 0.02 0.29 0.12 0.17PI 0.28 0.10 0.04 0.11 0.04 0.05 0.05 0.06 0.16 0.06 0.33 0.14

PNI 0.03 0.10 0.15 0.16 0.23 0.03 0.09 0.12 0.11 0.22 0.24 0.24

TSE 0.28 0.04 0.06 0.04 0.35 0.00 0.17 0.09 0.32 0.08 0.05 0.03

**P< 0.01; two-tailed; n = 25.



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The results of the multiple regression analyses showed that noninteractive engagement with

adults was significant in the two regression models, explaining 53% and 23% of the variance in children

VPA (F1,23= 27.86,P< 0.01;R2 change = 0.55) and steps/min (F1,23= 8.26,P< 0.01;R

2 change = 0.26),

respectively.

3. Discussion

Factors (age and social engagement) thought to be determinants for physical activity in children

with ASD were partially found to be related to physical activity in this study. Age in particular did

not support the notion that children with ASD are more likely to be inactive as they age. Infrequent

social engagement rate did not widen with age as the activity-deficit hypothesis proposed by

researchers (Bouffard, Watkinson, Thompson, Causgrove Dunn, & Romanow, 1996; Wall, 2004).

Furthermore, the overall activity levels were not dependent on social engagement either during

physical education or in recess setting, indicating that those who engaged more in social interactions

were no more physically active than peers who engaged less socially. However, the noninteractive

engagement with adults was positively correlated with childrens VPA and steps/min during physical

education.

An interesting note related to age and physical activity from the current sample was the positive

relationships between age and both the overall physical activity and step counts in recess and the

positive relationship between age and 5-min MVPA during physical education. This is not supportive

ofKozub and Ohs findings (2004)of negative relationships between age and total bouts of MVPA in

individuals with visual impairments, using RT3 activity monitors. This is also not supportive of the

same inverse relationships between age and minutes of moderate physical activity measured using

RT3 monitors in individuals with intellectual disability (Kozub, 2003). However, in an earlier study of

Longmuir and Bar-Or (2000) using a self-report questionnaire, physical activity estimates do not

support a marked age-related decline in individuals with cerebral palsy, muscular dystrophy, or visual

impairments, but a decline in physical activity with age was observed in youth with chronic medical

conditions. In the general population, age-related declines are noted for both males and femalesbetween the ages of 8 and 18 years (Thompson, Baxter-Jones, Mirwald, & Bailey, 2003). The

inconsistent findings in the literature highlight the importance of using objective assessment

methods, support the examination of physical activity patterns within various environments, and

confirm the need to measure the physical activity of specific subgroups to avoid generalizations across

different disabling conditions.

Most of previous studies from aforementioned above in youth with and without disabilities have

documented a negative relationship between age and physical activity. Pan and Frey (2005) used

accelerometer to assess the influence of age on physical activity in youth with ASD, and found a

significant negative association between age and youth physical activity. Results of the current

investigation confirm the importance of age as a significant physical activity correlate in children with

ASD, but do not reinforce the magnitude of decline in physical activity with age. The failure to find aconsistent age influence may be because the age span of the current study is not broad enough to

include adolescents. Most youth in the Pan and Freys study (2005) were in middle or high school, and

reported no recess time and decreased physical education requirements, while elementary school age

children had access to these physical activity resources. It may be the case that greater decline in

physical activity do not emerge until mid- to late adolescence. This may be particularly true for

organized sports, which become increasingly competitive in high school and where children can

exercise greater autonomy in their choices. To date, no published studies have examined whether

Taiwanese adolescents with ASD participate in fewer activities than others of the same age. Further

work should examine this question with this population.

Children with ASD in the current study engaged in more peer-interactive interactions as they age,

and the total social engagement rate was higher as children become older during physical education.This is not consistent with Oh, Mehmet, and Kozubs (2004) study, indicating that there was no

significant relationships between age and social engagement during physical education in students

with visual impairments. The lack of age effect among individuals with visual impairments may have

been due to vision and communication challenges resulting in initial overall low rate of social



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engagement (Zanandra, 1998). It is likely that the factors influencing this behavior are different since

the presence of a disability significantly alters life experience (Seligman, 1999). The symptoms of ASD

are considered to be modifiable when favorable environmental interaction has been provided to make

subsequent interactions easier, resulting in both improved skill and motivation to interact (Mundy,

Henderson, Inge, & Coman, 2007). Although the impact of environment elements is beyond the scope

of the current study, physical education is usually more structured and supervised than recess and

students interaction is required, making it an ideal opportunity for the promotion of childrens social

engagement. Participants in the current study were observed paying more attention to teacher/peer

demonstration, feedback and learning outcomes during physical education; whereas the majority of

the children with ASD were observed spending the most of time not interacting in recess. More

research is needed to determine if the unique elemental characteristics play a role in social

engagement of children with ASD.

Age-related trends in physical activity and social engagement are an important concern for health

professionals given that ASD was considered to be unmodifiable until recently. Compared to their

typically developing peers, children with ASD may be more likely to perform poorly in school and are

at greater risk for emotional and behavioral problems as they age. However,Mundy et al. (2007)shed

new light on this concept, suggesting that favorable environmental and social interaction has the

potential to make subsequent positive behaviors. Such favorable interactions can result in not only

improved social skills (Thomas & Smith, 2004) and physical fitness (Lotan, Isakov, & Merrick, 2004),

but also in reduction of stereotypic behavior (Prupas & Reid, 2001). The positive age-related trends

found in physical activity and social engagement of the current participants is supportive of this

notion. It appears from the results of the current study identified above that the divergence in activity

with age hypothesis (Bouffard et al., 1996; Wall, 2004) is also not supported. Behaviors of children

with ASD can be explained to some extent by the self-determination model (Wehmeyer & Garner,

2003), indicating that behavior is a function of environmental as well as personal factors, which in

turn, both environmental and personal factors affect individuals behaviors. Therefore, physical

activity and social engagement behaviors of children with ASD may be more affected by social and

environmental constraints than the actual impairment.Noninteractive engagement with adults during physical education is positively related to both

VPA and steps/min, suggesting that as adult-noninteractive engagement behaviors increased,

physical activity levels increased. This is expected because each participant received regular attention

and encouragement from the teacher during physical education, which may have been responsible

for some increase in social engagement and physical activity. Within the physical education class,

participants were provided an opportunity to develop the necessary skills to interact with their

teacher. The teachers presence and use of verbal and nonverbal curing have been sufficient to

perpetuate the social engagement and physical activity behavior in physical education class.

However, results of the current study do not support the earlier finding indicating that there was no

significant relationships between social engagement and physical activity in individuals with visual

impairments during physical education (Oh et al., 2004). This finding may be due to children withvisual impairments in the previous study being from a segregated blind school where more

competent children may not have opportunity to find highly skilled playing partners and friends of

similar interests to engage physically and socially. More studies are needed to determine if setting is a

determinant of social or activity patterns in individuals with ASD.

These data represent an initial attempt to study age, social engagement and physical activity in

children with ASD. However, the convenience sampling and the low sample size limit the inferences of

these findings. Regardless, this study is important because it is the first attempt to identify

relationships between age, social engagement and physical activity in children with ASD. Findings

indicate differences in the relationships between age, social engagement and physical activity

among children with various types of disabilities. Further work with a larger sample of children

with ASD in a longitudinal design is necessary to properly identify the age and social engagementinfluences on physical activity. In addition, the impact of other symptoms influences such as

language and motor coordination on physical activity of children with ASD is of interest. Additional

information is needed to better understand the influences of physical activity for intervention in

children with ASD.



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Acknowledgments

This research was supported by grant NSC 95-2413-H-017-010, National Science Council, Taiwan.

The author would like to thank Yu-Feng Wang, Ching-Yi Hsu, Hsiang-Chun Huang, and Chi-Hung Tien

for their assistance with data collection. Special thanks to all children who participated in this study

and parents of children for supporting this project.

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