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DOI: 10.1177/1362361310392253

2011 15: 625 originally published online 12 April 2011AutismAubyn C. Stahmer, Natacha Akshoomoff and Allison B. Cunningham

community programInclusion for toddlers with autism spectrum disorders : The first ten years of a

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autism 2011SAGE Publicationsand The National

Autistic SocietyVol 15(5) 625641; 392253

1362-3613(2011)

Inclusion for toddlers withautism spectrum disorders

The first ten years of a community program

A U B Y N C . S TA H M E R University of California,San Diego,and Rady Childrens Hospital, San Diego, California

N ATA C H A A K S H O O M O F F University of California,San Diego, and Rady Childrens Hospital, San Diego, California

A L L I S O N B . C U N N I N G H A M University ofCalifornia, San Diego

A B S T R A C T The present quasi-experimental study examines the out-comes for a group of 102 children diagnosed with an autism spectrumdisorder at age 2 who attended an inclusive toddler program (describedby Stahmer and Ingersoll, 2004) until age 3. Outcomes on standardizeddevelopmental assessments indicate significant improvement, with largeeffect sizes, in developmental level, adaptive behavior and communica-tion.Thirty-one of the children (31%) were functioning in the typically

developing range when they exited the program at age 3, after an averageof 8 months of intervention. Predictors of positive outcomes includedlength of time in the program, level of words and gestures use at entryand higher externalizing and lower internalizing behavior CBCL scoresat entry. Implications for serving toddlers with autism in inclusivesettings and suggestions for future research directions are discussed.

A D D R E S S Correspondence should be addressed to: AU BY N S TA HM ER , Child &Adolescent Services Research Center, 3020 Childrens Way, MC 5033, San Diego, CA92123-4282, USA. e-mail: [email protected]

A growing number of children with an autism spectrum disorder (ASD)are now diagnosed before their third birthday, increasing the need forappropriate and effective community intervention programs for toddlers.Researchers and educators alike typically agree that children with ASDbenefit from early intervention services (e.g. National Research Council,2001). Although most intervention researchers recognize the importanceof social integration for children with disabilities, with data indicating thatinclusion can lead to excellent outcomes for preschoolers with ASD (e.g.McGee et al., 1994; Schwartz et al., 2004), there have been few examina-tions of inclusion settings for toddlers with ASD.

K E Y W O R D S

autismspectrumdisorders;

communityprogram;

early

intervention

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Until recently, services for toddlers with ASD have been limited. It maybe assumed that if children with ASD benefit from inclusion in the pre-school years, inclusion in the toddler years may also increase social andlanguage behaviors. In a recent review of comprehensive treatment models

for children with ASD, only three toddler inclusion models had publishedresults. One inclusive program for toddlers with ASD, the Toddler Centerof the Walden Early Childhood Program, has evidenced excellent childoutcomes in both language and social behaviors, with 82 percent of the28 children with ASD in the study using spoken words at program exit and71 percent exhibiting an increase in their ability to play in proximity toother children from entry to exit (McGee et al., 1999). Recently, researchersfrom Project DATA, a toddler inclusion program that includes both indi-vidual and inclusive instruction, provided outcome data for eight toddlerswith ASD (Boulware et al., 2006). All of the children made improvementsand five of the children demonstrated very substantial gains on standardizedassessments. In a study of 20 toddlers with ASD in our own community-based inclusion program, Childrens Toddler School1 (CTS; Stahmer andIngersoll, 2004), we reported IQ gains similar to those reported in researchstudies of young children with ASD in both intensive one-to-one treatmentprograms (e.g. Cohen et al., 2006) and the aforementioned inclusion pro-grams (Boulware et al., 2006; McGee et al., 1999). Children with ASDshowed improvements in both standardized and functional measures ofcommunication, social interaction, adaptive behavior, and play skills, as

well as a reduction in ASD symptoms. These preliminary outcomes are veryimpressive. However, replication of these toddler inclusion results withlarger numbers of children remains important.

Unlike many early intervention outcome research projects, which focuson the use of a single technique such as discrete trial training (e.g. Lovaas,1987), incidental teaching (McGee et al., 1999, 2000), or Floortime(tm)(Greenspan and Wieder, 1998), the majority of publicly funded early inter-vention programs use a combination of methods in their treatment models.Both CTS and Project DATA use models that integrate various evidence-

based techniques and developmentally appropriate practices. Initial studieshave suggested that integration of intervention techniques does not im-pede child progress (Stahmer and Ingersoll, 2004; Dawson et al., 2009).The best practice committees in both New York and California recommendthe use of a combination of treatments based on the needs of the child.However, there have been very few studies examining the efficacy of inte-grating best-practice treatment methods. Additional evidence is neededto validate that a systematic combination of treatments individualized tomeet the needs of the child and family leads to good outcomes for toddlerswith ASD.

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Outcomes for children with ASD are usually defined by performanceon standardized measures of language, as well as cognitive and adaptivebehavior. Optimal treatment outcomes in comprehensive early and inten-sive behavioral interventions have been related to age at start of treatment,

initial learning rate, nonverbal IQ, imitation ability, and ASD severity (Harrisand Handleman, 2000; Sallows and Graupner, 2005). Longitudinal researchstudies of young children with autism have found scores on standardizedmeasures administered at age 3 to be stronger predictors of outcome inlater childhood compared to scores at 2 years of age (Charman et al., 2005;Thurm et al., 2007). In particular, these studies found that measures of non-verbal IQ at age 2 were predictive of later language scores, while measuresof communication skills at age 3 were a stronger predictor of later languageability. Overall, early language ability and cognitive ability have emerged asthe most robust predictors of overall prognosis for ASD during childhood,adolescence, and adulthood.

It is important to note, however, that a majority of these studiesexamined predictors of outcome in children in one-on-one early interven-tion settings, or where the intervention provided differed across children.More data are needed to support inclusion as an effective intervention fortoddlers with ASD, and to examine predictors of positive outcomes ininclusion settings. The purpose of the present investigation is to presentdescriptive outcome data for a large number of toddlers with ASD enrolledin an inclusive community-based inclusion program and to examine pre-

dictors of positive child outcomes.

Method

ParticipantsParticipants included a total of 102 children with ASD (87 boys, 15 girls)who participated in the Childrens Toddler School for a minimum of 5months (M = 8.3, range 515). Mean age at program entry was 28 months

(range 2133) and mean age at program exit was 36 months (range 3540).The majority of the children attended regularly, with the mean rate ofattendance being 86 percent of available days. The majority of the familieswere two-parent families and all of the children resided with their bio-logical parents (see Table 1).

Eligibility for CTS entry included a DSM-IVdiagnosis (American Psychi-atric Association, 2000) of autistic disorder or pervasive developmentaldisordernot otherwise specified (PDD-NOS) by a community-based clin-ician not associated with this research project, nonverbal mental age (12months), and chronological age of 18 to 30 months. Funding for CTS was

I N C L U S I O N F O R T O D D L E R S W I T H A S D

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provided by the California Part C Early Start program, which requireschildren to exit the program at age 3. All families consented to participatein the program and signed an IRB consent form stating a willingness toallow their own and their childs assessment data to be included in aresearch database. This paper includes children entering in the programbeginning in January, 1998, and exiting by November, 2008.

Measures and procedureAfter referral to CTS for services and before beginning the program, pre-

treatment measures were completed. The children in the study then parti-cipated in the CTS (program described below) for a minimum of fivemonths (M = 8.3). Measures were repeated approximately one monthbefore each child completed treatment in order to provide eligibility infor-mation to the school district. The program psychologist administered astandardized test of developmental functioning to each child at entry andexit. Children completed either the Bayley Scales of Infant Development,2nd Edition (Bayley, 1993), or the Mullen Scales of Early Learning (Mullen,1995) depending upon the date of entry into the program. The same testwas administered to each child at entry and exit. The mental development

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Table 1 Participant demographic information

Time enrolled in the program

Mean (range) 8.33 months (515 months)

Diagnosis

Autistic disorder 55%Pervasive developmental disorder 45%

not otherwise specified

Percent attendancea

Mean (range) 86% (75%97%)

Age at program entry

Mean (range) 28.06 months (2133 months)

Marital status of parents

Married 88%

Separated 1%

Divorced 3%

Single 5%Race/ethnicity of participant children

Asian/Pacific Islander 8%

Black 4%

Hispanic 7%

White 62%

Multi-racial 14%

Unknown/Other 7%

a. Percent of available school days the child came to school.



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quotient on the Bayley or the early learning composite (ELC) from theMullen was used to determine change in child intellectual functioning. Toassess child adaptive functioning, the program psychologist administeredthe Vineland Adaptive Behavior Scales (Sparrow et al., 1984) to the childs

primary care provider (typically the mother) at entry and exit. Standardscores on each Vineland subdomain were used to compare changes fromentry to exit. In addition, each childs parents completed the Gilliam AutismRating Scale (GARS; Gilliam, 1995), an assessment of severity of autisticsymptoms based on a national sample of individuals with autism. A scoreof 100 indicates a high probability that the child has autism. Lower scoresindicate reduced probability of an autism diagnosis and fewer symptomsindicative of the disorder. Although this assessment was not standardizedfor children under the age of three, it can provide an estimate of changein behaviors associated with autistic behavior.

In order to further assess communication skills, the Preschool LanguageScales, 3 or 4 (depending upon the year of entry into the program;Zimmerman et al., 1992, 2002) was completed by the speech/languagepathologist to provide standard scores of auditory comprehension andexpressive communication.The MacArthur-Bates Communicative Develop-ment Inventories (CDI; Fenson et al., 2006) was completed by each childsparents upon entry and exit. This assessment provides a count of the numberof words produced, phrases understood, and gestures used. The ChildBehavior Checklist for Ages 11/2-5 (CBCL;Achenbach and Rescorla, 2000)

was used to estimate emotional and behavioral problems. Children areconsidered to have significant behavior issues if they score in the clinicalrange (t score 64 or above) on the various scales of the CBCL. The Inter-nalizing and Externalizing Behavior Scales were used for data analyses inthis project.

Data analysisTwo-tailed paired sample t tests were used to determine significant changesin performance on standardized and norm-referenced tests. Paired Wilcoxon

t tests for ranked data were used to determine significant changes in func-tional skills for each behavioral category. A Bonferoni correction was madeto reduce the probability of type 1 error with multiple comparisons suchthat an alpha of .0028 indicated a significant result. With the exception ofthe CDI, standard scores were used in data analyses for all assessments.Standard scores factor in developmental maturation, and are thus a morestringent measurement of child progress.The CDI does not provide standardscores so raw data were used in those analyses.

Developmental trajectory comparisons were also conducted to compareexpected developmental rate with and without intervention. This type of


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data analysis has been used by behavior analysts to assess the magnitude ofchange in one-group designs (see Romanczyk, 2000).The analyses requirethe use of age-equivalent data rather than standard scores.

A principal factor analysis was used to determine the factors used for

the outcome measures when looking at predictors. Assessments coveringmajor areas of deficit in children with ASD were used in the factor analysis.Multiple regression analysis was used to examine predictors of outcome atintake. Based on the literature and best fit of the data, the major predictorvariables used in these analyses included length of time in the program,developmental functioning, adaptive functioning, problem behaviors, socialbehavior, and communication skills.

Overview of the programCTS includes 8 toddlers with ASD: 4 who attend a morning session and 4who attend an afternoon session.The program consists of a total of 21 hoursa week of direct service. This includes 15 hours in the classroom, 4 hoursof individual service outside the classroom, and 2 hours of in-home parenteducation for children with ASD. In addition, parents commit to using thetechniques learned in parent education an additional 10 hours per week athome. However, there was no method to verify the use of these hours.Children receive intensive services in the inclusive classroom 3 hours a dayfor 5 days a week. The 8 typically developing toddlers each attend all dayfor day care purposes. The classroom has a 1:3 teacher to child ratio, is

arranged like a typical toddler classroom, and utilizes a systematic blend ofincidental teaching (McGee et al., 1999), Pivotal Response Training (PRT;Koegel et al., 1989), structured teaching (Lord et al., 1993) and interactive/developmental techniques (Ingersoll et al., 2005) in the context of theclassroom.Two augmentative communication systems, the Picture ExchangeCommunication System (PECS; Frost and Bondy, 1994) and modified signlanguage, are also used with nonverbal children or children who appear toneed visual support to use language appropriately. Interaction with typicallydeveloping toddlers is facilitated throughout the school day. The educa-

tional team works together to plan a curriculum appropriate for all children(typically developing and those with autism). Teachers do not follow aspecific packaged curriculum, but follow developmentally appropriate prac-tices. Teaching occurs during classroom activities such as free play, snack,outside play, special activity (e.g. art), circle time, and self-help activities(e.g. diapering, hand washing). In order to facilitate appropriate program-ming, the most naturalistic teaching strategies are used to meet curriculumgoals. Each toddler with ASD receives individualized instruction, whichmay include discrete trial training (Lovaas, 1987), with one teacher andtwo children, for four hours weekly to allow for teaching specific skills not

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acquired in the classroom setting or that need additional practice. Thefamily education component consists of weekly two-hour home visits witha teacher to help the parents learn naturalistic behavioral techniques. Parentparticipation is an integral part of the program. Parents are involved in goal

setting and development for their children, goal review, choosing appro-priate intervention strategies, developing positive behavioral supports, andin the transition process. Speech and occupational therapy consultation isconducted within the context of the classroom.

In the classroom, there are a variety of interesting toys and activities topique childrens interest. Once a child becomes interested in a toy or activitythe teacher uses that opportunity to provide a learning activity derivedfrom individual goals. Teachers are trained to be fun and to act as amagnet for the children to encourage proximity between children withASD and typically developing children. An example of strategy use in theclassroom is as follows: If a child is engaged with a toy, the teacher typi-cally begins an interaction using an incidental teaching model by approach-ing the child and waiting for a response, using an appropriate level of affectand enticement, and increasing the level of structure as necessary. Forexample, the teacher might comment on the childs actions, model anappropriate action or provide a direct instruction depending upon thechilds need. If the child does not respond, the teacher may move to a morestructured technique such as PRT or PECS. All techniques may be used ina single session depending upon the childs needs that day. Children with

ASD are encouraged to observe and interact with typically developing peers.For some children, tolerating proximity to peers is an initial goal, whileother children focus on initiating interactions and imitating actions at circletime or asking each other for additional snack items.

Staffing and trainingAll teachers must possess a minimum of a BA from a four-year institutionand have prior experience working with young typically developing childrenand children with autism or a degree and experience in early childhood

education. All teachers must also meet infant/toddler classroom licensingstandards for the State of California. Each teacher receives extensive trainingin each intervention technique through didactic instruction with the tech-nique training manuals as well as hands-on experience in the appropriateprogram setting. Fidelity of implementation of the program is completedon a quarterly basis through direct observation and checklists completedby the program psychologist. Developmental feedback is provided to eachteacher on a daily basis during the course of teaching.

A more detailed description of the program can be found in Stahmerand Ingersoll (2004).


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Results

Standardized assessmentsResults for standardized and norm-referenced assessments are summarized

in Table 2.

Bayley Scales of Infant Development/Mullen Early Learning ScalesBayley or Mullen scores were unavailable at intake for two children who wereuncooperative during the testing sessions. These children were excluded,leaving 100 children for this analysis. The children exhibited a significantincrease in developmental level as measured by standard scores on theBayley or Mullen from intake (M = 63.9, SD = 13.3) to exit (M = 75.7, SD= 18.3; see Table 2). At intake, only six (6%) of the children were in thetypically developing range (developmental level between 85 and 115), 24(24%) of the children were in the mildly delayed range (developmental levelbetween 70 and 84), and 70 (70%) children were in the significantlydelayed range at intake (developmental level below 70). At exit, 31 (31%)of the children were functioning in the typical range, another 35 (35%) ofthe children were functioning in the mildly delayed range, and 34 (34%)of the children remained in the significantly delayed range. Pearsons chi-square test was used to examine whether the observed frequency distrib-utions were significantly different at intake and exit. Results revealedstatistically significant differences, 2 = 127.7, df= 2,p < .001. Children

functioning in the typical range of development expanded from 6 percentto 31 percent. Additionally 36 of the 70 children (51%) moved out of thesevere range of functioning. Sixteen of the 70 children (23%) functioningin the significantly delayed range at intake were functioning in the averagerange at exit. Fourteen of the 24 children (58%) functioning in the mildlydelayed range at intake increased their functioning to the average rangeafter intervention.

Trajectory changes in mental age based on overall mental age scores onthe Bayley or the Mullen are illustrated in Figure 1. The expected trajectory

was estimated based on developmental level at intake, with the assumptionthat without intervention the same rate of development would continue.Clearly, typical child development does not always take a linear path,however this comparison allows us to illustrate how changes in develop-ment might be altered due to intervention (see Romanczyk, 2000). If therate of change is greater than the expected rate of development, then theintervention is said to have a positive effect on the childs development. Atypical developmental trajectory is illustrated as well. Similar results are seenwhen language and visual spatial development are examined separately; thefigure therefore depicts overall development. Children with ASD increased

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633

Table2

Childrensmeanscoresonstandardizedassessm

entsatprograme

ntryandexit

Entryscore

Exitscore

tscore

pvalue*

Effectsize

Mean(SD)

Mean(SD)

Chronologicalage(87boys,15girls)

28mo(2.74)

36mo(.74)

Developmentalquotient(Bayley[1993]

63.9(13.3)

75.7(18.3)

8.398

.000*

.416

orMullen[1995],n=100)

Adaptivefunctioning(Vineland,n=98)

AdaptiveBehaviorComposite

68.6(8.5)

72.2(10.9)

4.296

.000*

.163

Communication

70.0(10.2)

77.2(14.0)

7.720

.000*

.410

DailyLivingSkills

69.5(7.7)

72.5(9.7)

3.968

.000*

.148

Socialization

69.9(8.5)

74.6(10.9)

5.471

.000*

.243

MotorSkills

83.7(8.5)

85.5(16.9)

1.023

.304

.011

Autismsymptoms(GARS,n=10

1)

Communication

6.9(4.0)

7.8(3.3)

2.140

.035

.049

SocialInteraction

6.9(2.8)

6.4(3.0)

1.844

.069

.025

StereotypedBehavior

8.2(2.9)

7.1(3.3)

3.576

.001*

.110

AutismQuotient

83.8(15.8)

80.8(19.5)

1.370

.174

.009

MacArthurCDI(n=99)

WordsProduced

67.5(80.1)

197.3(141.7)

11.282

.000*

.527

WordsUnderstood

157.2(109.5)

243.6(122.2)

7.589

.000*

.358

EarlyGestures

10.4(3.8)

12.8(4.2)

5.564

.000*

.279

LateGestures

19.8(9.7)

27.4(11.0)

8.007

.000*

.483

PreschoolLanguageScales(N=102)

ReceptiveLanguage

45.6(37.5)

64.8(37.5)

5.149

.000*

.206

ExpressiveLanguage

49.0(37.8)

65.4(39.6)

4.395

.000*

.159

ChildBehaviorChecklist(n=87)

ExternalizingBehavior

57.3(8.0)

58.3(8.8)

1.317

.191

.020

InternalizingBehavior

59.7(8.8)

58.4(8.1)

1.968

.093

.032

*ABonferronicorrectionwasuseds

uchthatapvalueof.0028indicatesa

statisticallysignificantresult.

Note.GARS=GilliamAutismRatingScale(Gilliam,1995);CDI=MacArthur-BatesCommunicativeDevelopmen

tInventories(Fensonetal.,2006).



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on average from a developmental equivalent of 17.6 months at intake to27.5 months at exit testing (performed on average at 35 months of age).This analysis indicates that the childrens rate of development was 63 per-

cent of the typical childrens rate of development at intake and 79 percentof typical childrens rate of development at exit testing, with an overall 16percent increase in developmental progress.

Vineland Adaptive Behavior Scales, Interview Edition Vineland scoresfor entry or exit were unavailable for four children, thus these childrenwere excluded from this analysis. Results are shown in Table 2. Statisticallysignificant changes were seen in the overall adaptive behavior composite.Significant increases in adaptive behavior as determined by standard scores

on the Communication, Daily Living Skills and Socialization subdomainsof the Vineland were evident from intake (Communication M = 70.0; DailyLiving Skills M = 69.5; Socialization M = 69.9) to exit (CommunicationM = 77.2; Daily Living Skills M = 72.5; Socialization M = 74.6). There wasnot a significant change in the Motor Skills domain. On the Communica-tion scale before entry into the program, 49 (50%) of children scored inthe severely delayed range (standard scores less than 70), 44 (45%) in themildly delayed range (7084), and 5 (5%) in the average range of func-tioning (85115). At exit from the program, 30 (31%) of children werefunctioning in the severely delayed range, 39 (40%) of children remained

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634

Figure 1 The expected developmental trajectories for typically developing

children,and children with ASD (based on entry scores) and the actual

developmental trajectory for children with ASD, based on overall age

equivalents on the Mullen (1995) or Bayley (1993) assessments

Developmentalageinm

onths

Intake

Changes in Developmental Age Equivalent over Time

Exit

35

30

25

20

15

16% increase in

developmental progress

Typical Trajectory

ASD Expected

Trajectory

Treatment

Trajectory



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mildly delayed, and 29 (30%) of children were in the average functioningrange. In the Daily Living Skills domain, 6 (6%) of children were function-ing in the average range at entry and 11 (11%) of children in the averagerange at exit. In the Socialization domain, only 4 (4%) of children were

functioning in the average range at entry and 21 (21%) were in the averagerange at exit. Pearsons chi-square test was used to examine whether theobserved frequency distributions were significantly different between intakeand exit. Results revealed statistically significant differences for the Commu-nication, 2 = 123.1, df= 2,p < .001, Daily Living Skills, 2 = 20.0, df=2,p < .001, and Socialization domains, 2 = 79.0, df= 2,p < .001.

Symptoms of ASD

Gilliam Autism Rating Scale GARS scores were unavailable for one child

at program exit, thus he was excluded from this analysis. There was not asignificant decrease in severity of autism from intake to exit as measuredby the GARS. At both entry (M = 83.8) and exit (M = 80.8), the GARSAutism Quotient fell within the below-average probability of autism range.No statistically significant changes were seen in either the communicationor socialization domain scaled scores. A statistically significant decrease wasseen in the stereotyped behavior domain scaled scores, indicating fewerstereotyped behaviors after intervention.

CommunicationParent report of vocabulary on the CDI increased significantly overall in theareas of words produced and understood, as well as the use of both earlyand late gestures (see Table 2). Standardized scores on the PLS-3 or PLS-4also showed a statistically significant increase over time. At entry, the averagelanguage standard scores were in the significantly delayed range while atexit scores increased to the mildly delayed range on average.

BehaviorScores on the CBCL did not change over time. However, the majority of

children did not show clinically significant behavioral issues according tothis measure at either time point. At entry into the program, only 20children had Externalizing Behavior scores in the clinical range and 26 hadclinically significant scores on the Internalizing Behavior scale. Similarlyat exit, 20 children had clinically significant scores on the ExternalizingBehavior scale and 22 children had clinically significant scores on the Inter-nalizing Behavior scale.


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Predictors of best outcomePrincipal component analysis using direct oblimin rotation was conductedto examine the dimensionality of the outcome assessments. An initial explor-atory factor analysis (EFA) of all of the measures described above suggested

that a 2-factor solution best explained the data. The variance explained bythe solution was 77.7 percent. Factor 1, the Developmental Factor, wasconceptualized as a measure of overall developmental level, and accountedfor 49.3 percent of the variance. The three items that had significantloadings on the Developmental Factor were the overall developmental levelas measured by the Bayley or the Mullen (.89), and the Vineland Social(.89) and Communication (.93) domains. Factor 2, the Behavior Factor,consisted of three items related to behavior: the GARS autism quotient(.77), and the CBCL Internalizing (.87) and Externalizing (.87) Behaviorscales. This factor accounted for 28.3 percent of the variance. These factorscores were used as the outcome variables for use in the regression analysis.

Predictors of outcomeMultiple linear regression was employed to determine which of the entryassessments or variables could be used to predict outcome as measured bythe Developmental and Behavior Factors at exit. First, we examined the rela-tionship between the entry variables that contributed significantly to eachoutcome factor. We did this in order to replicate previous studies that havefound a relationship between pre-treatment IQ and pre-treatment adaptive

behavior and treatment outcomes.When entered as a group, pre-treatmentIQ and Vineland Communication and Social domain scores significantlypredicted those same scores at outcome with an adjusted R2 = .58 [F(85)= 36.91, p < .001]. Surprisingly, when these variables were entered intothe equation separately, pre-treatment IQ was not significantly related to theDevelopmental Factor scores at exit. The Vineland Communication standardscores contributed the most variance (B = .05; = .48;p = .000), followedby Vineland Socialization standard score (B = .03; = .24;p < .05).

Next, we examined how entry variables not included in the Develop-

mental Factor at entry predicted the outcome results.Variables that did notsignificantly contribute to the regression were removed in order to developthe best explanatory model. Since no a priori hypotheses had been madeto determine the order of entry of the predictor variables, a direct methodwas used for the multiple linear regression analyses. Five entry variablesproduced the strongest predictor of the Developmental Factor at exit withan adjusted R2 = .54 [F(90) = 17.60,p < .001]. These included numberof months in the program, CBCL Internalizing and Externalizing BehaviorScale scores, and the number of gestures and number of words producedas measured by the CDI (see Table 3).

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When examining the Behavior Factor, we also examined the relationshipbetween the entry scores of the assessments used in the outcome variablefirst. Pre-treatment scores on the CBCL Externalizing and InternalizingBehavior scales and the GARS autism quotient significantly predicted thosesame scores at outcome, R2 = .46 [F(85) = 36.91,p < .001]. When thesevariables were entered into the equation separately, the CBCL Internalizingscale was not significantly related to the outcome Behavior Factor.The CBCLExternalizing scale contributed the most variance (B = .05; = .45; p

inclusion of toddlers_autism

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