The effect of sensory activities on correct responding for children with autism

The effect of sensory activities on correct responding forchildren with autism spectrum disorders

Ginny L. Van Rie *, L. Juane Heflin

Dept. EPSE, Georgia State University, P.O. Box 3979, Atlanta, GA 30302-3979, United States

Adherents to the optimal stimulation theory posit that individuals strive to maintain ideal levels ofarousal in order to function effectively and efficiently (Zentall & Zentall, 1983). According to thistheory, individuals adjust their activity levels depending on whether they are over or under aroused inorder to achieve an optimal level of stimulation conducive to navigating daily life. Therefore, anindividual’s activity level may be a good indicator as to his or her level of arousal. Based onobservations of their activity levels, children with ASD react in typical environments the way typicallydeveloping peers respond in stressful environments (Zentall & Zentall, 1983). Unfortunately, therepetitive and stereotyped behaviors children with ASD employ to achieve their optimal level ofarousal in environments they perceive as stressful (Fisher & Murray, 1991; O’Brien & Pearson, 2004)interfere with their ability to engage with instructional materials and learning activities. Engagementin academic tasks and educational activities is vital for learning. Students who are not engaged are less

Research in Autism Spectrum Disorders 3 (2009) 783–796

A R T I C L E I N F O

Article history:

Received 23 February 2009

Accepted 3 March 2009

Keywords:

Autism

Sensory interventions

Learning outcomes

A B S T R A C T

Sensory-based activities are commonly recommended for students

with ASD, even in the absence of empirical data to substantiate their

effectiveness. A single subject alternating treatment design was

used to assess functional relations between sensory-based ante-

cedent interventions and correct responding in four students with

autism. As individuals with autism constitute a heterogeneous

population, it is not surprising that a functional relation was found

for only two of the four students. Results of this study lead to the

conclusion that sensory-based interventions may be effective for

some but not all students with autism. Implications for evaluating

aptitude by treatment interactions and suggestions for future

research are discussed.

� 2009 Published by Elsevier Ltd.

* Corresponding author. Tel.: +1 404 413 8040; fax: +1 404 413 8043.

E-mail address: [email protected] (G.L. Van Rie).

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likely to learn the material and thus less likely to make academic gains (Logan, Bakeman, & Keefe,1997).

Individuals with ASD may have difficulty reaching the optimal level of arousal required for learningbecause they do not process or respond to sensory stimuli in the same manner as typically developingpeers (Rogers, Hepburn, & Wehner, 2003; Volkmar, Cohen, & Paul, 1986). Ayres (1972) articulated atheory of sensory integration that posits the importance of appropriate responses to sensory input andmodulation of output for effective functioning. Individuals who have difficulty responding to sensorystimuli will over or under react in the presence of the stimuli (Yack, Aquilla, & Sutton, 2002). Theseextreme reactions reflect an individual’s attempt to regain optimal levels of arousal.

Since Ayres proposed the theory of sensory integration, several techniques and methods haveevolved to help individuals with sensory processing difficulties. Although none of the techniques areempirically validated, the theory is that they help individuals register and modulate responses tosensory stimuli (Dunn, 2001). Sensory integration requires participation in activities such as swinging,jumping, and bouncing which are designed to strengthen sensory processing abilities. Theaforementioned activities rely on vestibular and proprioceptive sensory input to allow individualswith sensory dysfunction to regulate these systems and overcome some of their hyper or hyporesponses to sensory stimulation (Heflin & Alaimo, 2007; Yack et al., 2002).

Authors of physiology texts and theoretical guides describe the roles of the vestibular andproprioceptive systems in humans. The vestibular system provides information from the semicircularcanals of the inner ear to the brain which gives an individual a sense of balance and center of gravity(Berthoz, 2000). The vestibular system is the foundation for the functioning of other systems and isclosely tied to auditory functioning (Kashman & Mora, 2005). Difficulty processing vestibularstimulation negatively affects the ability to communicate or process auditory stimulation (Kranowitz,2005). The proprioceptive system relies on feedback from muscles, joints, and tendons and enablesdetermination of how much effort is needed to perform movements such as grasping and lifting and tomodulate tension for walking, writing, chewing, and so forth (Zigmond, Bloom, Landic, Roberts, &Squire, 1999). Individuals who have problems processing proprioceptive stimulation may havedifficulty controlling their body movements (i.e., motor planning; Bundy, Lane, & Murray, 2002). Manyof the stereotyped behaviors commonly seen in individuals with ASD engage the vestibular andproprioceptive systems to either increase or decrease stimulation to these systems in order to reachtheir optimal level of arousal (Heflin & Alaimo, 2007). Unfortunately, these stereotyped and repetitivebehaviors may impede a student’s ability to engage in learning activities and materials.

Individuals with difficulty processing vestibular and proprioceptive stimulation can be eitherhyper-reactive or hypo-reactive. According to Yack et al. (2002), individuals with hyper-reactivitymay try to escape from or protest bright lights or loud sounds, express discomfort with certainclothing textures, dislike certain smells or tastes and appear overly fearful of heights and movement.In contrast, individuals who are hypo-reactive may not respond to loud noises or painful stimuli, maynot acknowledge other people or things in the environment, may not get dizzy with excessivespinning and may have delayed responses. Different sensory activities are theorized to helpindividuals modulate their sensory systems depending on if they are hypo-reactive or hyper-reactive(Kranowitz, 2005). The impact of the activities are modulated by not only the type of input (e.g.,proprioceptive or vestibular) but also by the quality of the input (e.g., fast vs. slow, loud vs. soft). Slowlinear swinging, sucking, white noise, bear hugs, and playing with fidget toys are a few sensoryactivities that are supposed to help an individual with hyper-reactivity calm down and reach anoptimal level of arousal. Bouncing, jumping, listening to loud fast music, and playing in cold water aretheorized to be alerting activities to an individual who is hypo-reactive to sensory input.

Although there is limited empirical research supporting the use of sensory activities to improvetask engagement for individuals with ASD, it is a common practice within school, occupationaltherapy, and speech therapy settings (Baranek, 2002; Heflin & Alaimo, 2007; Schreibman, 2005) withover 92% of occupational therapists surveyed reporting the use of sensory-based interventions (Olson& Moulton, 2004). A few researchers suggest sensory based therapies may produce positive outcomesin the areas of communication, play skills, and academic functioning for individuals with sensoryprocessing difficulties (Case-Smith & Bryan, 1999; Fertel-Daly, Bedell, & Hinojosa, 2001; Schilling &Schwartz, 2004; Schilling, Washington, Billingsley, & Deitz, 2003; VandenBerg, 2001). However, these

G.L. Van Rie, L.J. Heflin / Research in Autism Spectrum Disorders 3 (2009) 783–796784

studies contain methodological weaknesses that make it impossible to document functional relationsbetween the interventions and the behavioral outcomes. For example, Case-Smith and Bryan (1999)claim that 32 min sensory-based occupational therapy sessions a week were the reason 5 preschoolage boys with ASD improved in the areas of play and engagement. However, the researchers do notgive details of the activities involved in the therapy sessions nor do they account for confoundingvariables that may have contributed to the gains made by the students over the course of the study. Inrecognition of the fact that optimal levels of arousal are necessary for learning and the current lack ofempirical research documenting the link between strategies to improve arousal and learningoutcomes, the purpose of this study is to determine if there is a functional relation between sensoryactivities, such as slow linear swinging and fast bouncing on an exercise ball, and correct respondingfor four children with autism in elementary school.

1. Method

1.1. Participants

Participants for this study were recruited from the first author’s classroom. The study was approvedby Institutional Review Boards at the authors’ University and first authors’ school district. There were sixstudents in the classroom; only the four students with autism were invited to participate in the study.The four participants were diagnosed with autism by a psychologist employed by the school systemusing to DSM-IV-TR criteria (APA, 2000). The Childhood Autism Rating Scale (CARS; Schopler, Reichler, &Renner, 1988) completed by the first author at the time of each student’s evaluation for consideration ofspecial education eligibility in the school system was used as an indication of severity. Districtprocedures were followed in determining that each child was eligible for special education servicesunder the category of autism. All of the participants received special education services in a self-contained classroom in a public elementary school outside a major metropolitan area in thesoutheastern US. The parents of the four students with autism gave permission for their children toparticipate and child assent procedures were followed prior to the start of each session to ensurevoluntary participation. Information about the participants is provided in Table 1.

Joey was an active and alert child. He enjoyed drawing his favorite movie production logos andsinging Christmas carols. He communicated verbally, but often had to be cued when to respond or howto respond to questions. He expressed his wants and needs using three to five word phrases. Joey sat inhis chair during academic tasks but, he was often bouncing around, singing, or looking away frominstructional materials. He required multiple verbal, gestural, and physical prompts to answeracademic questions. Joey was not taking prescription medications during the study.

Troy was energetic and ran or jumped around the classroom on his tiptoes. He liked to draw hisfavorite store logos, watch cartoons aired on public television, and build with blocks. Troy used threeto five word phrases to express his wants and needs, but required prompting to answer questions. Hehad difficulty sitting in his chair and often jumped up out of his chair or ran away from his chair duringacademic tasks. During instruction, Troy engaged in delayed echolalia and started repeating phrasesfrom cartoons and computer games and thus required multiple prompts to engage in academicinstruction. Troy did not take prescription medications during the study.

Table 1Participant information.

Name Age CARSa Cognitive assessments

Al 6 years 3 months 34.5 42b

Carl 6 years 3 months 37.5 48c

Joey 7 years 4 months 51 48b

Troy 6 years 6 months 46.5 58d

a Childhood Autism Rating Scales.b Stanford-Binet Intelligence Scale – Fifth Edition (full scale score).c Wechsler Preschool and Primary Scale of Intelligence – Third Edition (full scale score).d Battelle Developmental Inventory, Second Edition (standard score).

G.L. Van Rie, L.J. Heflin / Research in Autism Spectrum Disorders 3 (2009) 783–796 785

Al was an energetic and happy child. He ran around the classroom pretending to be a superhero orflew planes he built out of interlocking blocks. He loved to play outside and requested the opportunitymultiple times during the day. Al communicated his wants and needs with two to three word phrasesand required prompting to respond to questions. He had difficulty remaining seated during academicinstruction and engaged in constant verbal stimming. Often his verbal stims were unintelligible andincluded nonsense words. Engaging Al in academic tasks was very difficult because of his activity leveland verbal stimming. Al was not on prescription medication until he was removed from the studyduring the replication phase.

Carl was a calm and lethargic child. He often sat quietly in his chair, smiling. He liked to hold small,soft items in his hands such as cotton balls, tissues, or balls. He enjoyed sitting in an adult’s lap orgetting hugs. Carl communicated his wants and needs using one to two word phrases but requiredmodeling to use the correct words and phrases. When presented with academic tasks, Carl wouldavert his eyes from the stimulus and required multiple verbal, gestural, and physical prompts torespond. Carl did not take prescription medications during the study.

1.2. Setting

All four participants were in the same classroom which was approximately 24 ft. � 31 ft. The roomwas divided into a calendar activity area, a 1:1 work area, a small group work area, a large group workarea, a play area, an area for sensory activities, and an area for the teacher’s and paraprofessional’sdesks and materials (one full-time paraprofessional was assigned to the classroom). The pre-academicinstruction activities were implemented in the sensory area of the classroom. The academicinstruction was conducted in a 1:1 work area set up in the back of the classroom that consisted of onesmall table and two chairs. The students were familiar with the 1:1 work area and received instructionin this area throughout the day. The study was conducted between 9:00 and 10:00 daily. Each studentengaged in the intervention and instructional activities with the first author for 15 min daily. Theorder in which the students participated varied daily based on child availability (e.g., due to relatedservice provision, assessments, arrival time).

1.3. Design

An alternating treatment design with replication of the most effective intervention (Barlow &Hayes, 1979) was used to demonstrate a functional relation between the intervention andbehavioral outcomes. Baseline data on correct responses were collected for three sessions or untilthe data were stable. Stability was determined by 50% or less variability around the baseline mean(Alberto & Troutman, 2009). Each student was randomly assigned an intervention or the controlactivity for each session, ensuring that each intervention and the control activity wereimplemented an equal number of times and counterbalanced during the intervention phase.Randomization was accomplished by assigning each condition a number (1 for swinging, 2 forbouncing, and 3 for listening). Two sets of numbers were placed in a hat. Monday morning, the firstauthor drew five numbers out of the hat for a student. The first number drawn was the conditionimplemented on Monday, the second Tuesday, and so forth. The procedure was repeated for eachstudent. After the first week, the condition that was implemented twice the week before wasremoved from the selection. Three sets of instructional materials for two different categories(community helpers and safety signs) were used to guard against practice effect acrossinterventions and the control activity.

Horner, Carr, and Halle (2005) substantiate the need to augment visual analysis of single-subjectdata with more objective outcome measures. In this study, percentage of non-overlapping data (PND;Scruggs, Mastropieri, & Casto, 1987) was calculated to provide an indication of magnitude of changeduring intervention. Although the most commonly used metric for calculating effect size in single-subject research, PND has been criticized as being overly sensitive to outliers and phase length(Marquis et al., 2000). Therefore, an additional metric, the pairwise data overlap (PDO) procedure wascalculated to document intervention effectiveness. PDO has been described as the most reliable of thenon-parametric approaches (Wendt & Scholsser, in press) and requires comparison of overlap for each


baseline data point against all data points in intervention (Parker & Vannest, in press). Only data fromthe intervention phase (excluding replication) were used to calculate PDO.

1.4. Independent variable

The independent variable was the sensory or control activity implemented for 5 min immediatelypreceding academic instruction. The two sensory interventions included slow linear swinging and fastbouncing on an exercise ball. Slow linear swinging was conducted using a sling-seat swing mounted inthe ceiling of the classroom. The first author, who was also the children’s teacher, pushed the student inslow linear patterns for 5 min. Fast bouncing on a ball involved the student sitting on a 65-cm exerciseball while the first author held the student’s hands or waist and helped the student quickly bounce upand down on his bottom on the ball for 5 min. A control activity served as a contrast to the two sensoryactivities. During the control activity, the student chose a story book and listened to a reading by the firstauthor. The control activity was conducted in the same area as the swinging and bouncing activities.

1.5. Dependent variable

The dependent variable was the percent of correct responses the student achieved for two differentsets of instructional tasks during academic instruction after each sensory intervention or controlactivity. Three sets of instructional materials for two different categories (community helpers andsafety signs) were created by reviewing the Individual Education Plans of the four participatingstudents. All of the students had objectives to identify community helpers and safety signs. Thestudents knew a few signs from previous instruction (e.g. stop sign, traffic light, enter, exit), so thesesigns were eliminated from the pool. Fifteen novel signs and community helpers were selected from alist of common community helpers and safety signs in the curriculum.

Three sets of five flash cards were created for each category. The flash cards were approximately3.75 in. � 3.75 in. and were created using the Mayer–Johnson Boardmaker program. The pictures werein color and the word labels at the top of the flashcards were deleted. The flash cards were printed oncardstock, cut out in squares and laminated. Joey knew six safety signs and one community helper.Troy knew two community helpers and five safety signs. Carl knew one community helper and nosafety signs. Al did not know any community helpers or safety signs. The first author divided theflashcards into sets that equally dispersed the number of known flashcards. Baseline data are reportedbased on the subsequent division; analysis of responses during baseline substantiates the equivalenceof the sets of flash cards.

One set of flash cards for each category was designated for a specific intervention (i.e. every time astudent bounced on the exercise ball prior to instruction he used the same five flash cards from each ofthe two categories, every time a student was swung prior to instruction he used a different butequivalent set of five flashcards from each of the two categories, and every time a student listened to astory he used a different but equivalent set of five flashcards from each of the two categories). Baselinedata were collected by presenting all 15 community helpers and 15 safety signs to the students whilesitting 1:1 at the same table that would later be used for intervention. The flashcards were presentedone time each in random order and the students were given 5 s to respond by labeling them verbally.The students did not receive corrective feedback during the baseline phase. During intervention theparticipants were presented three trials for each set of five flash cards from the two categories. Thusthe total number of opportunities to respond after each sensory intervention or control activity wasthirty. The number of correct responses was measured using event recording on a data sheet. Correctresponses were indicated using a plus sign and incorrect responses were indicated using a minus sign.The percentage was calculated by taking the total number of correct responses and dividing it by thetotal number of opportunities to respond within each set of academic tasks.

1.6. Procedures

The teacher followed the IRB-approved assent procedure before every session for each student toensure that the students voluntarily participated in the study. According to the pre-determined


randomization schedule, the students were assisted to swing slowly in a linear motion, rapidly bounceon a ball, or to listen to a story for 5 min prior to instruction. A visual timer was set to indicate the endof the pre-instruction activity at which point the first author would announce ‘‘It is time to work.’’ Thefirst author and the student went to the 1:1 work area and the student was presented with two sets ofacademic tasks, one immediately after the other. The first task was to expressively identify fivecommunity helpers and the second task was to identify five community safety signs. The flash cardswere presented randomly with all five community helpers first followed by all five safety signs. Thiswas repeated until the student was presented with three trials of all 10 flash cards for a total of thirtyresponses per session.

After 12 intervention sessions it was determined that Al and Carl needed to respond receptivelyinstead of expressively because they were having difficulty pronouncing the names of the communityhelpers and safety signs. Starting on the twelfth intervention session they were given a field of threeflashcards from the same category for every trial and the location of the correct flashcard wasrandomized for every response. The first author requested the target safety sign or community helperfor the student to select. The student then picked up the flashcard and placed it in the first author’sopen hand.

The instructional procedure consisted of a system of least prompts and the students receivedintermittent secondary reinforcement in the form of praise, tickles, or access to a preferred item such atoy car or figurine while sitting at the 1:1 work table during instruction. The system of least promptsinvolved the first author presenting the flashcard and allowing the student 5 s to respond. After 5 s, ifthe student did not respond, the first author gave a verbal prompt of the initial sound of the target itemto the students responding expressively and a gestural prompt to the students responding receptively.If the student did not respond after 5 s then the first author stated the whole name of the target itemfor students responding expressively and physically guiding the hands of the students respondingreceptively to the target item. Only the students’ responses that were give correctly andindependently after the initial presentation of the flashcard were counted as correct.

The students were considered to have met mastery when they achieved three consecutive sessionswith 80% correct in one condition. Once a student achieved mastery for one condition, the results werereplicated using the instructional materials of the least successful intervention.

1.7. Reliability data

For the purpose of calculating interobserver agreement and treatment fidelity, an independentobserver was trained to collect data on videotaped sessions. An average of 33.6% of sessions werevideotaped across all phases and students (25.6% of the sessions for Joey, 38% of the sessions for Troy,32.3% of the sessions for Al, and 35.7% of the sessions for Carl). Joey had the lowest average ofvideotaped sessions because he participated in the study for the fewest number of sessions.

The independent observer was working on her doctoral degree in special education and wastrained by the first author to determine if the sensory interventions and the control activity wereimplemented with fidelity as well as to take data on correct and incorrect responses during academicinstruction. The second observer recorded data on a data sheet identical to the one the first authorused during instruction and reached 85% agreement for three consecutive sessions at the start of thestudy. During the study interobserver agreement (IOA) was calculated using point-by-pointagreement between the first author and the independent observer. The results of IOA and rangesare presented in Table 2.

1.8. Procedural fidelity

A detailed task analysis (see Appendix A) was used to determine treatment fidelity for everysession IOA data were collected. The independent observer reviewed the sessions and took data on thenumber of steps for the task analyses that were completed correctly as well as the steps that werecompleted incorrectly. Procedural fidelity is reported as the percentage of steps completed correctlyfor each intervention and control session videotaped for each participant. The mean treatment fidelityfor Joey and Troy was 100% and the mean for Al and Carl was 99%. The reason treatment fidelity was


99% for Al and Carl was because there were two times for each of them that more than three trials of aparticular flashcard was presented during the receptive intervention phase. The overall treatmentfidelity percentage for this study was 99%.

2. Results

The results of the two sensory and the one control activity on academic performance for thestudents are presented in Figs. 1–4. Since Joey’s data were undifferentiated between the conditions, heparticipated in only a baseline and an intervention phase. Troy participated in three phases: baseline,the alternating treatment intervention phase with expressive responses, and replication of the mosteffective intervention when he reached mastery with one intervention during the second phase. Aland Carl participated in four phases. The first two phases were the same as the phases for Joey andTroy. The third phase was the alternating treatment intervention with receptive responses and thefourth phase was replication of the most effective intervention.

Joey had five sessions in baseline before his data stabilized. He knew a few of the communityhelpers and safety signs during the baseline phase. His responses ranged from 10% to 30% correct witha mean of 21%. During the intervention phase he had 100% non-overlapping data points between thebaseline and intervention data for swinging, 100% for bouncing, and 83% for the control (listening to astory) so that all three interventions would be considered ‘‘highly effective’’ (Scruggs & Mastropieri,1998). The effect size calculated through PDO was 1.0 for bouncing and swinging and .97 for listening,leading to the conclusion that the interventions were indistinguishable in terms of behavioral change.

The data were undifferentiated between the three interventions and Joey reached mastery criteriain all three conditions; in four sessions for swinging, bouncing in five sessions and listening in sixsessions. The mean percentage of correct responses in the swinging condition was 79%, in thebouncing condition was 82%, and in the listening condition was 77%. It took Joey six sessions to reachmastery criteria in the listening condition because he had 1 day at 83% and then dropped back to 77%which was below the mastery criteria. Thus he had to reach 80% or higher again and then have threeconsecutive sessions at 80% correct before he reached the mastery criteria. The swinging interventionwas the most efficient intervention for Joey because he reached mastery criteria in only four sessions.Since the data paths did not fractionate there was no replication phase and thus no functional relationbetween the independent and dependent variables for Joey.

Troy had three sessions in the baseline condition. He knew a few safety signs and communityhelpers prior to the intervention, but his baseline data were stable. His data ranged from 20% to 27%

Table 2IOA and treatment fidelity results.

Joey Troy Al Carl

Baseline

% of sessions taped 20 33.3 33.3 33.3

% Agreement 86.6 90 100 100

Range 86.6–86.6 90–90 100–100 100–100

Intervention phase expressive

% of sessions taped 31.2 25 33.3 33.3

% Agreement 91 96.7 94.2 97.5

Range 86.6–100 90–100 80–100 90–100

Intervention phase receptive

% of sessions taped N/A N/A 29.2 33.3

% agreement N/A N/A 96.9 97.7

Range N/A N/A 93.3–100 90–100

Replication

% of sessions taped N/A 55.6 33.3 42.9

% Agreement N/A 99.3 97.8 96.7

Range N/A 96.7–100 96.7–100 93.3–100

Procedural Fidelity 100% 100% 99% 99%


Fig. 1. Percentage of correct responses for community helpers and safety signs for Joey.

Fig. 2. Percentage of correct responses for community helpers and safety signs for Troy.

Fig. 3. Percentage of correct responses for community helpers and safety signs for Al.


correct responses with a mean of 25% correct for community helper and safety sign identificationduring the baseline phase. There was fractionation between the data paths during the interventionphase. The swinging intervention data path separated from the other two data paths immediately andcrossed only once during session 20. Troy had 92% non-overlapping data points between the baselineand the swinging intervention data, indicating a ‘‘highly effective’’ intervention (Scruggs &Mastropieri, 1998). The PND for bouncing was 22% and PND for listening to a story was 0%,indicating an ‘‘ineffective’’ intervention (Scruggs & Mastropieri, 1998). Troy reached mastery underthe swinging condition in 12 sessions with a range of 27–90% with a mean of 57% correct. The effectsizes calculated for each of the interventions using PDO were .97 for swinging, .52 for bouncing, and.00 for listening to a story.

The instructional tasks from the listening condition were used in the replication phase for Troyusing the swinging intervention. During the replication phase, Troy reached mastery in ninesessions with percentages ranging from 40% to 87% with a mean of 63%. There were no overlappingdata points between the listening data path in the intervention phase and the use of the samematerials with the swinging intervention in the replication phase. Since Troy reached mastery inthe replication phase as well, there was a functional relation between swinging and percentage ofcorrect responses for Troy.

Al and Carl had three sessions each during the baseline phase. All three data points for Al were 0%for each of the 10 flashcards used in the three conditions (difficult to distinguish on the graph). Carl’sdata ranged from 0% to 3% with a mean of 2% correct responses for community helpers and safetysigns. During the first intervention phase, Al and Carl were asked to expressively identify communityhelpers and safety signs following the three interventions. After twelve intervention sessions bothstudents were having very limited success under all three conditions. Thus another phase was addedin which their response mode was changed to receptively identifying a requested card from a field ofthree. Their percentage of correct responses increased immediately. Since baseline data were notcollected on the receptive task, the control condition (listening to a story) was used to contrast theeffects of the two interventions (Richards, Taylor, Ramasamy, & Richards, 1999).

Al’s data paths fractionated between the three conditions during the receptive phase. Swingingwas more effective than listening or bouncing. Al reached mastery criteria in the swingingcondition in 14 sessions. His data ranged from 23% to 83% with a mean of 60%. The swinging datapath did cross the bouncing and listening data paths in the middle of the phase, but the swingingdata path fractionated during the last 10 sessions of the phase. Using the listening condition as thecontrol (Richards et al., 1999), PND was 93% for swinging and 39% for bouncing, leading to theconclusion that swinging was ‘‘highly effective’’ while bouncing was ‘‘ineffective’’ (Scruggs &Mastropieri, 1998). PDO was .93 for swinging and .54 for bouncing, corroborating the conclusionsdrawn from the PND analysis.

Fig. 4. Percentage of correct responses for community helpers and safety signs for Carl.


Given the clear fractionation and results of the nonparametric calculations, Al began the replicationphase using the instructional materials from the listening activity while using the swingingintervention. However, a major medication change was instituted at the same time and he did notreach mastery during the replication phase. Thus there was no functional relation between swingingand percentage of correct responses for Al.

Although Carl’s data paths crossed at the beginning of the receptive phase, there is clear datafractionation during the last 19 sessions. Carl reached mastery criteria under the bouncing conditionin 15 sessions. His data ranged from 30% to 87% with a mean of 56%. Using the listening condition asthe control (Richards et al., 1999), PND was 0% for swinging and 60% for bouncing, leading to theconclusion that swinging was ‘‘ineffective’’ while bouncing was ‘‘questionable’’ (Scruggs &Mastropieri, 1998). PDO was .3 for swinging and .84 for bouncing, providing stronger support forthe effect of the bouncing intervention.

Given the clear fractionation and results of the PDO calculations, the instructional materials fromthe swinging condition (being the condition with the poorest performance) were used during thereplication phase with the bouncing intervention. Carl reached mastery in the replication phase inseven sessions with data ranging from 53% to 83% with a mean of 59%. There were no overlapping datapoints between the swinging data path in the receptive phase and the use of the same materials withthe bouncing intervention in the replication phase. There was a functional relation for Carl betweenbouncing on an exercise ball and percentage of correct responses.

2.1. Social validity

Social validity was measured using a subjective survey created by the authors. Ten items weregenerated based on previous experience conducting research and tailored to solicit perceptions of theease and benefit of the two sensory-based interventions and to ascertain if the adults would usesensory-based interventions in the future. The surveys were completed by the paraprofessional whoworked in the classroom as well as the speech and occupational therapists who worked with thestudents. Each question was answered using a Likert scale of 1–5 with one representing ‘‘stronglydisagree’’ and five indicating ‘‘strongly agree.’’

The occupational therapist responded with fives for every item, which indicates that she usedsensory interventions prior to the study, thought the interventions used for the study would be easy toimplement and planned to continue to use sensory interventions with students in the future. Themean score for the paraprofessional was 4.5. The lowest score on her survey was for the questioninvolving the use of sensory interventions prior to the study; however she marked a five for the lastquestion which indicates she intends to use sensory interventions in the future. The speech therapisthad a mean score of 4.8. She indicated that she used sensory interventions with students prior to thestudy, thought the interventions were easy to implement, and intended to continue to use sensoryinterventions with students in the future.

Parents were not queried to assess social validity as they did not observe their children’sparticipation; by the time they saw their children at the end of the day, any effects of the interventionswould have faded. Students were not questioned as they all participated willingly in each of the pre-instruction activities and their cognitive functioning would preclude the ability to differentiate subtlepreferences.

3. Discussion

Teachers employ sensory activities every day in their classrooms, even in the absence of empiricalsupport for these practices (Baranek, 2002; Heflin & Alaimo, 2007; Olson & Moulton, 2004;Schreibman, 2005). The purpose of this study was to investigate the effect of two sensory activities,slow linear swinging and fast bouncing on an exercise ball, on task engagement as measured by thepercentage of correct responses for identifying community helpers and safety signs for elementaryschool aged children with ASD. A control condition, listening to a story for 5 min prior to instruction,served as a contrast to the sensory activities. The results were somewhat mixed. Joey’s data wereundifferentiated and he reached mastery in all three conditions. There was a functional relation for


Troy between swinging and percentage of correct responding. Al’s data fractionated to suggest that hewas more successful with the swinging intervention. Unfortunately, as the study progressed Al’sbehavior at school and at home became more erratic and disruptive. His parents chose to put him onAdderall to help manage his behavior; thus he was removed from the study during his replicationphase before he could reach mastery. Finally, there was a functional relation for Carl betweenbouncing on the exercise ball and percentage of correct responding.

The results of this study provide limited support that the use of sensory interventions may helpsome students with ASD reach their optimal levels of arousal in order to improve their ability tolearn and engage in academic tasks. Equally important, the results provide support for the beliefthat every individual with ASD responds differently to sensory input (Yack et al., 2002) and hasdifferent optimal levels of arousal (Zentall & Zentall, 1983). One of the premises of this study asoutlined in the review of literature was the use of sensory activities to help students achieve anoptimal level of arousal as measured by student learning outcomes. Al and Troy both gave morecorrect responses after the swinging intervention, which incorporates vestibular stimulation andhas been theorized to be calming. As described in the methods section they were both very activestudents who were easily distracted during academic instruction. Their positive response to thelinear swinging intervention supports the theory that slow linear swinging is calming (Yack et al.,2002) and thus enabled these active students to reach an optimal level of arousal as measured byhigher percentages of correct responses for indentifying community helpers and safety signs. Therewere no improvements in correct responding following the alerting activity (bouncing) or thecontrol activity (listening).

Carl was a hypoactive child who usually did not respond to visual stimuli prior to the intervention.After participating in the bouncing intervention, his percentage of correct responding was higher andhe reached mastery criteria during both the receptive intervention and replication phases. His resultssupport the theory that bouncing increases a hypoactive individual’s attention (Yack et al., 2002) andhelped him achieve an optimal level of arousal by activating both his proprioceptive and vestibularsystems. Carl’s had the lowest percentage of correct responding following linear swinging, possiblybecause it exacerbated his lethargy.

The first author, who was also the teacher, anecdotally noted that the latency between thepresentation of the flash cards and the students’ responses were shorter during the swinging conditionfor Joey, Troy, and Al. It was easier to gain their attention and engage them in the instruction after theswinging intervention as compared to bouncing or listening. Whereas the first author and theparaprofessional both reported that Carl had more success with visual motor activities such ascompleting puzzles, shape sorters, and coloring after bouncing on the exercise ball as opposed to theswinging and listening interventions. The paraprofessional who worked with the students asked if shecould have Carl bounce on a ball prior to engaging him in activities that required him to visuallyattend. Thus there were perceptions of positive outcomes for all of the students in regard to specificsensory interventions.

Individuals with autism constitute a heterogeneous population (Heflin & Alaimo, 2007), often withas much variability among them as between them and populations without autism (VanMeter, Fein,Morris, Waterhouse, & Allen, 1997). This variability can result in widely divergent responses to thesame interventions and led to the call to evaluate aptitude by treatment interactions in researchconducted with the population (National Research Council, 2001). In addition to the differencesamong the boys’ activity levels, there also are differences in their age, severity of autism, and cognitiveprofiles. Joey, who responded favorably to all three conditions, was the oldest participant but had thehighest CARS score, reflecting the most severe level of autism among the boys. However, he coulddecode connected text on the 4th grade level with some comprehension so may have had the strongestvisual discrimination abilities; as his teacher, the first author indicated that based on his classroomperformance, his IQ score was probably depressed and inaccurate. Al had the lowest measured IQ andthe most severe behavioral issues, as documented by the family’s decision to initiate medicationtherapy after the data fractionated in the intervention phase. However, his CARS score placed him inthe mild-moderate range of autism in contrast to the other three participants whose scores indicatedsevere autism. Joey and Troy both knew 7 of the 30 community helpers and safety signs at the outset incontrast to Carl who knew one community helper and Al who did not recognize any of the stimuli.


Tentative and preliminary inferences may include that sensory activities may have less impact oncorrect responding for students who already have some academic competence (e.g., Joey’s ability todecode connected text). The only other aptitude by treatment interaction that seems plausible relatesto the participants’ activity and arousal levels.

According to the results of this study, the swinging intervention may be beneficial for studentswith autism who are hyperactive and easily distracted. The bouncing intervention may be helpfulfor students with autism who are lethargic and unresponsive to academic stimulation. There maybe some challenges to implementing sensory interventions in other classrooms. The classroom thatwas used for this study was equipped with a suspended swing which may not be available in allclassrooms. However, if a suspended swing is not available alternative interventions could includethe use of a rocking chair or going outside to the playground to use a swing. One limitation of usinga swing outside would be other extraneous variables such as transition time, difficulties withstudents transitioning from being outside for a brief period of time then returning to academicinstruction, the distractions of other playground equipment, and so forth. There is the potential thatthese interventions might be helpful for students prior to other academic tasks such as fine motortasks, hand eye coordination tasks, visual tracking tasks, and other academic tasks that require thestudents to attend and focus on instructional materials. The swinging intervention may activate thevestibular system to promote optimal arousal in students who are hyperactive while the bouncingintervention may incorporate the vestibular and proprioceptive systems to help students who arehypoactive.

Several limitations were noted during the course of this study. One concern regarding the design ofthis study was the amount of time it required for the students to have multiple exposures to the sameset of flashcards. Since this was an alternating treatment design there were three sets of equivalent butdifferent flashcards. Only one session was conducted every school day and each student was exposedto each set of flash cards one to two times per week. Therefore it took several weeks for each student tosee each set of flashcards several times and that may have affected how long it took each student tolearn the community helpers and safety signs. This leads to the next limitation which was timeconstraints. Due to the breaks in the school schedule for holidays, there were interruptions in theresearch and breaks up to 2 weeks between sessions. Another limitation is that two of the students hadto change to receptive responses during the study. The students should have been evaluated at thebeginning of the study to determine if they could pronounce all of the names of the communityhelpers and safety signs prior to the start of the study. Finally no formal measures of sensory deficitswere conducted during the study to determine which sensory intervention might be the mostbeneficial for each student. This limitation reflects applied practice as few teachers have access tooccupational therapists with the time to conduct formal sensory assessments.

Future research should include measures of sensory deficits of the participants in addition toteachers’ impressions prior to the interventions to determine which sensory intervention should be mostbeneficial for each participant. Yack et al. (2002) suggest it is important to determine if a student withASD who exhibits sensory processing difficulties is hyperactive or hypoactive in order to provide the bestsensory activity intervention. Commonly used assessments to determine sensory sensitivity are theSensory Integration and Praxis Test (SIPT; Ayres, 1989) and the DeGangi-Berk Test of Sensory Integration(TSI; DeGangi & Berk, 1983). Although an empirical question for evaluating aptitude by treatmentinteractions, it will be important for researchers to adequately describe participants so that practitionerswho cannot secure formal assessment can compare their students to those participating in the studies.

Since this was a single subject design replications of the current study are necessary to providesupport and generalizability to the findings of this study. Five minutes was selected as the length for thepre-instruction sessions since it was perceived that was enough time to benefit from the activities butwouldn’t represent too much lost instructional time. The ideal duration for the sensory activities is anempirical question that should be explored. Future research should evaluate the effect of sensoryactivities on task engagement as measured by latency between task demand and response. Additionally,it would be interesting to determine how long the effects of the sensory activities last. In this study, theparticipants were asked to engage in an academic task immediately after the sensory activity and theinstructional session lasted no more than 10 min. Since the paraprofessional asked to have Carl bounceon a ball prior to other activities later in the day, the effects apparently wore off at some point.


This study is an important addition to the current body of literature regarding sensoryinterventions and the learning outcomes of students with autism. Teachers are currently usingsensory interventions with students with autism on a daily basis, but there is limited research tosupport the practice (Heflin & Alaimo, 2007; Schreibman, 2005). This study is one of the fewstudies available with data-based support for the use of sensory interventions for studentswith autism. Three out of four students responded positively to sensory interventions andincreased their percentages of correct responding immediately following the interventions;however the sensory activities were differentially effective. Future replications of this study andadditional research in the area of sensory interventions and learning outcomes for students withautism are necessary.

Appendix A. Treatment Fidelity Checklist

Student: _________________________________________ Date: _______________

Number Yes No Step Description

1. Did the teacher ask the student, ‘‘do you want to (swing, bounce, read)?’’

2. If the student responded yes, did the teacher take the student to the correct area? If the

student responded ‘‘no’’ did the teacher stop?

3. Did the student sit correctly to swing, bounce or read?

4. Did the teacher help the student swing/bounce or read for 5 minutes?

5. After five minutes, did the teacher direct the student to the work table?

6. Is the student sitting at the work table?

7. Did the teacher present the student with an academic task?

8. Did the teacher ask the student to verbally label or receptively identify a community helper?

9. Did the teacher repeat the request to identify 4 additional community helpers?

10. Did the teacher ask the student to verbally label or receptively identify a community

safety sign?

11. Did the teacher ask the student to verbally label or receptively identify 4 additional community

safety signs?




safety sign?

15. Did the teacher ask the student to verbally label or receptively identify 4 additional

community safety signs?




safety sign?

19. Did the teacher ask the student to verbally label or receptively identify 4 additional

community safety signs?

20. Did the student have a total of 30 opportunities to respond during the academic instruction

session?


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The effect of sensory activities on correct responding for children with autism