4 Separate Papers. Write a one-page review, single spaced of each of the assigned readings. Article responses should include a description of the article itself and a reaction to the article. I will a

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4 Separate Papers.

Write a one-page review, single spaced of each of the assigned readings.

Article responses should include a description of the article itself and a reaction to the article. I will attach all articles and by each paper are the dates I need it back by.

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  • Paper 1. 7/11
  • Diagnosis of autism spectrum disorders in 2-year-olds: a study of community practice (Corsello, Akshoomoff, & Stahmer, 2013)
  • A review of methodological issues in the differential diagnosis of autism spectrum disorders in children (Matson, Nebel-Schwalkm & Matson, 2007)
  • Paper 2 7/18
  • The Interpretative Conference: Sharing a Diagnosis of Autism with Families (Nissenbaum, Tollefson, & Reese, 2002)
  • Autism Severity and Qualities of Parent-Child Relations (Beurkens, Hobson, & Hobson, 2013)
  • Paper 3: 7/25
  • Effective Early Intervention: Results From the Model Preschool Program for Children with Down Syndrome and Other Developmental Delays (Fewell & Oelwein, 1991)
  • Parental Perceptions of Supplemental Interventions Received by Young Children with Autism in Intensive Behavior Analytic Treatment (Smith & Antolovich, 2000)
  • Paper 4 7/30
  • Early Intervention for Young Children with Autism: Continuum-Based Behavioral Models (Anderson & Romanczyk, 1999)
  • The Development of a Treatment-Research Project for Developmentally Disabled and Autistic Children (Lovaas, 1993)

4 Separate Papers. Write a one-page review, single spaced of each of the assigned readings. Article responses should include a description of the article itself and a reaction to the article. I will a
lASH1999, Vol. 24, No.3, 162-173copyright 1999 by The Association forPersons with Severe Handicaps EarlyIntervention forYoung Children with Autism: Continuum-Based Behavioral Models StephenR.Anderson Summit Educational Resources Raymond G.Romanczyk State University of NewYork-Binghamton Over the last three decades, instructionalmethodsde­ rived from applied behavior analysis (ABA) haveshown considerable promisefor many youngchildren with au­ tism. The ABA approach establishes a priorithat assess­ ment andintervention methodsmustbe based on gener­ ally accepted rules of scientific evidence. On one hand, the approach hasproduced a rich resource of conceptu­ ally consistent and scientifically validated techniquesthat can be applied in various combinations across many dif­ ferent contexts. On the other hand, this diversity has re­ sulted in someconfusion regarding the precise charac­ teristics of ABA. In this article, the authors first describe many of the common programmatic andmethodologic elements that formthefoundation of the approach. A summary of the scope of the behavioral research is pro­ vided including greater detail on six studies that demon­ strated large-scale interventions. Finally, the authorsde­ scribe components of program modelsthat share com­ mon elements of the ABA approach and use a broad continuum of traditional behavioral techniques. Some specific mythsabouttheapproach aresimultaneously addressed. DESCRIPTORS: applied behavior analysis,inter­ vention methods, programmodels,autism Autism is aserious developmental disabilitythatpro­ vides a complex challenge forparents, professionals, and all thosewho come in contactwith the child. Au­ tism is a syndrome, asopposed to a disease entity, that is characterized by specificbehavioralpatternsand characteristics. Acomplex disorder(BerkellZager, 1999; Cohen & Volkmar, 1997;Matson, 1994;Roman­ czyk, 1994; Schopler & Mesibov, 1988), autismspec­ trum disorder (ASD)hasbeen studied for 50 years, yet Address allcorrespondence andreprint requests for re­ prints toStephen R.Anderson, SummitEducational Re­ sources, 300 Fries Road,Tonawanda, NY 14150-8897. E-mail: [email protected] 162 stillresults incontroversy, misinformation, and is a source ofgreat confusion forparents attempting to make treatment andeducation decisions for theirchil­ dren. For the purposes of this article, we assume that the reader is familiar with the difficult and complex issues of obtaining anaccurate differential diagnosis for young children, as well as with the critical process of obtaining anassessment of thechild’s development (Harris & Handleman, 1994; NewYorkStateDepart­ ment ofHealth, 1999a; Powers & Handleman, 1984; Romanczyk, Lockshin, & Navalta,1994;Schopler & Mesibov, 1988). A general historical readingin the field of autism quickly results in the impressionthatautism is a severe disability for which little evidenceis found for long­ term positive outcome, thatit is difficult to diagnose, and that incidence andprevalence figures are contro­ versial (California Department ofDevelopmental Ser­ vices, 1999). Autismis also strongly associatedwith a great number of”fads” and”movements” thatover the last several decades havepromised much, but consis­ tently have failed to deliver when the harshlight of objective evaluation isfocused onsupposed break­ through procedures (Delmolino & Romanczyk, 1995; Green, 1996a; Olley & Gutentag, 1999; Smith, 1996). Often “models” arepromulgated with littleempirical support, but with a wealthof sincerity and enthusiasm. By studying this history, an appreciationisformed for the complexities ofgenerating aviable model that standsthe test of time and objectiveevaluation. It is in this contextthatwe first describe anapproach that establishes apriori thattheselection ofassessment and intervention approachesmust bebasedongener­ ally accepted rules of scientific evidencefor efficacy. It is a “bottom up”approach, inthat principles and pro­ cedures withdemonstrated efficacy areassembledinto a coherent modelthatis again subjected toempirical validation. This is quite differentfrom the process of developing aconceptual modelandthen seeking to find confirmatory evidence. at FLORIDA INTERNATIONAL UNIV on June 17, 2015 rps.sagepub.com Downloaded from Continuum-BasedBehavioralModels 163 To date, only one nonmedicalapproachmeets the boundary conditions of this model as applied to autism. This approach hasconsistently producedoutcomes that are reproducible, describablein precise terms, are tied to a conceptualization thathas strong and extensive experimental support,and uses, as a necessary compo­ nent, continuing objectiveevaluation. Thisapproach, known as applied behavioranalysis(ABA)in the con­ text of autism, but more generically as behaviortherapy or the behavioral approach,was firstappliedin the treatment of autism more than threedecades ago. Its roots are strongly within a research/academicframe­ work, and it has beenapplied with empirically evalu­ ated success to a wide array of humanproblems (Bar­ low, 1988; Barlow, Hayes, & Nelson, 1984; Spiegler & Guevremont, 1993).Interestingly, perhapsbecause of its focus on objective evaluationratherthanon consen­ sus of opinion, it has not becomepopularized and has often beengrossly misunderstood (cf. Maurice, 1993). Over the past threedecades, systematic researchin­ vestigations have demonstratedthe utility of specific components ofABA. More recently, larger scale out­ come studies again have consistentlydemonstrated that significant impactcan be made for childrenwith autism (New York State Health Department, 1999a). For those who are influencedbyresearch versusanecdotal reports, thereexists a growing and diverse behavioral technology thatcan be applied. One unexpectedout­ come of this extensiveness hasbeen a clustering of be­ havior analysts into several schools with strongly held positions. In ouropinion, theseare divisions based largely on emphasison oneparticular instructional technique oranother, agrouping oftechniques in a certain clustering, or differences in the strategyof ser­ vice delivery. However,all fall within the rubricof ABA. It is our opinionthatno single technique nor collection oftechniques can becorrect (or effective) for every person in every situation. Thus, the databased feedback loop in ABA isinherently aself-correcting mechanism if applied in the contextof clinical decision making. It is our goal in this article to first outlinethe common programmatic andmethodologic elementsof the ABA approach. We discuss some of the features that seemtodefine typical behavioral modelsand within this contextrespond to the many myths that have arisen regardingABA. Programmatic CommonElements It isprobably accuratetostate thatmany models, behavioral analytic and nonbehavioral analytic,share some common programmatic elements.Dawsonand Osterling (1997) reviewed a numberofprograms for children with autism thatmet the boundary condition of having published detaileddescriptions of the pro­ grams and providedintakeandoutcome data(many are reviewed in this special issue of JASH). They pre- sent a series of commonelements thatwere observed that areconsidered triedand true. Moreprecisely, by examining commonelements thatexist across programs that differ significantly in approach,theauthors state that these programmatic commonelements are “un­ likely to reflectanidiosyncratic viewpointor one inves­ tigator’s philosophical attitude”(p. 314).Thesepro­ grammatic commonelements are specific curriculum content, highlysupportive teachingenvironments and generalization strategies,predictable routine,func­ tional approach toproblem behaviors, plannedtransi­ tion, and family involvement. These programmatic commonelements perhapsre­ flect the minimum startingpointforprogram develop­ ment, along with appropriatelytrainedand caring staff, adequate resources, andsupervisory and review mecha­ nisms. Given these as “basics,” thenthe task is to utilize a methodology thatallows each of these elementsto be addressed in anindividualized manner,for children, family, and staff. It is at the pointof selecting specific methodology forinstruction that behavioral and non­ behavioral modelssometimes begin to diverge. Methodologic Common Elements There aremethodologic commonelements within the behavioral approach.First, theapproach views be­ havior as functional andpurposeful, even when func­ tion and purposeare notimmediately discernibleby an observer. Behavioris viewed as the result of a complex blend of variables thatinclude theindividual’s strengths and limitations, physical status, history, and the current social-en vironmen talcircumstances (Romanczyk & Matthews,1998). As with many complex approaches, there areoften subtle differences betweenspecific methodologies andtheories thatareassociated with the approach. Withrespect to autism, ABA is a specific form of the more generalbehavioral model. AnalysisandMeasurement ABA places stress on understandingthebehavior in question, whetherit is theacquisition of a skillthatis currently absentin aperson’s repertoire or the amelio­ ration of aproblem behavior. If emphasis is placed on the analysis level, thenit follows thatthere need to be certain prerequisite steps. The first of these prerequisitesis the objective mea­ surement ofbehavior. Mostmeasurement systems have technical pros and cons, as well as practicalcost effec­ tiveness parameters. Thereis a large body of literature within the field of science in generaland psychology specifically thatindicates humanobservers areprone to a number of very specific errorsinconducting obser­ vations. We are all subject to influences and biases that limit our objectivity. One credible reasonfor this diffi- at FLORIDA INTERNATIONAL UNIV on June 17, 2015 rps.sagepub.com Downloaded from 164 AndersonandRomanczyk culty inobjective measurement is that one of our strengths withrespect toinformation processingis the ability todetectpatterns. However, as with all systems, our ability todetectpatterns is not perfect.We are able to perceive specificpatterns where,in fact, none exists. We can be differentially influencedbyinformation, context, andexperience that have emotional as well as informational content. Often in clinical and educationalservicedelivery, we violate this basic principleofobjectivity so that the in­ dividuals performing assessment, deliveringservices, and evaluating outcomeare one and the same. It is important to stress that the influences that limit our ability to make objectiveobservations are not primarily based on such factorsassophistication, education,fal­ sification, intentional bias, anddeception. Rather,they are based on aninformation processinglimitation that allhumans share.Byunderstanding theseprocesses, we can guard against potentially inaccurateobservations and conclusions. Thus, the sine qua non of theapplied behavior analyticapproach is that objectivemeasures are taken of the individual’s behaviorand that these measures must meet theboundary conditions ofbeing operationally defined,reliable, and valid. Operational definitionssimplytranslate thenormal colloquial reference that we give to certainbehaviors into more objectively definedobservational terms. A good example would be attempting to assess a child who is “anxious.” This is a term that mostindividuals would recognize andbelieve that they have an under­ standing ofwhat itmeans. Difficulty arises with respect to precision and theapplication of suchtermsto spe­ cific individuals. For example, withanxiety, one could view it as a construct,thesummation of a number of different factors that areassumed to becoherent. We can divide the impreciseconstructofanxiety into a number ofcomponents: cognition,self-report, overtbe­ havior, performance, and physiologic. Although anxietyis a useful term for thepurpose of communication concerningaproblem theindividual is experiencing, from abehavioral perspective it would be further defined within the abovecategories. This allows highly individualized assessmentfor a given personas to how specifically anxietyismanifested for the indi­ vidual. ABA emphasizes addressing the specific, unique expression ofbehavior by theindividual. Reliable observations referto the degree to which the various specific behavioral observations conducted by different observers are inagreement. This is typi­ cally done by having two independentobserversper­ form observations and then compareveryprecisely the degree to which they agreeanddisagree on the specific temporal pattern of the behaviors observed.To be in­ dependent, individualsshould not be given specific ex­ pectations such as”medication is beingconsidered,” or “we are seeingproblems with rising anxiety,”or”it’s clear he’s anxious and we need todocument that.”Op- erationalized, unbiased,andreliable observation serves as the basis for hypothesistestingas to factors that may be of importance andinfluence theindividual, and thus leads to the processofconducting afunctional analysis (a point to bediscussed next). Assessing the Child Assessment is a crucialcomponentof any clinical/ educational model.Because thereare as many differ­ ences between youngchildren withautism as similari­ ties among them,assessment must be aconstantfocus point when developing andimplementing acompre­ hensive intervention program.Traditional assessment methods such as the administration ofstandardized psychological, speech,andachievement tests,”survey” assessments such asratingscales, and behavioralassess­ ment all haverelativestrengths andweaknesses. Within thepractice of ABA, therearevarious sub­ components ofassessment. First,assessment of an in­ dividual with autism, particularlya young child, can be a very difficult task. While assessmentisoften some­ what arbitrarily dividedintostandardized psychometric evaluation, socialhistory/family statusassessment, in­ formal observation, and much more rarely,functional assessment, ABA focuses strongly onfunctional assess­ ment (functional analysis). It is not andshould not be seen asincompatible with the assessment methods mentionedabove. For example,standardized assess­ ment, iffeasible andproperly conducted, providesim­ portant information. Suchassessment allows theestab­ lishment of a “marker” as to the currentrepertoire of the child with respecttovarious developmental do­ mains and allows a comparisontoother individuals, as well as relative strengths andweaknesses within the individual. It also serves as a standardizedformatto assess the ability to interactin a social manner with respect to thevarious directions anddemands and in­ terchanges that occur during standardized assessment. Standardized assessment,however,is not necessarily directly useful in the selectionof specific, immediate, short-term goals. Nor is it typically useful in determin­ ing the specific intervention methodology that will be utilized. It is beyondthe scope of this articletoexamine in detail thevarious aspects of the assessmentprocess. We focus on that aspect most specific to the behavioral model, that of functional analysis. Functional analysis is an oftenmisunderstood term, partly because different disciplines have varying defini­ tions. Within ABA, functional analysis is the processof ascertaining empiricallythecontrolling variables that enhanceorinhibit theexpression of abehavior. It is not done byobservation, filling out abehaviorchecklistor scale, nor by consensus amonginvolved parties.Rather, these sources ofinformation are used to form hypoth­ eses as to what factorsmay be involved, and then to test these hypotheses (Iwata,Vollmer, Zarcone, & Rod­ gers, 1993; Miltenberger, 1998). It is aprocessof ob- at FLORIDA INTERNATIONAL UNIV on June 17, 2015 rps.sagepub.com Downloaded from Continuum-BasedBehavioralModels 165 serving, hypothesizing, testing,evaluating, refininghy­ potheses, andrepeating. The essential aspect of functional analysis is the ex­ plicit testing of factors presumedto beimportant, and to conduct the testing in a mannerthathas the potential to clearly disprovethehypothesis. There are many uses for this very powerfulmethodology beyondunder­ standing problem behaviors, and it isparticularly useful for assessment ofchildren withoutverballanguage. While it is oftentechnically difficult and time consum­ ing to perform, the accuracy of the informationob­ tained through functionalanalysis and its directappli­ cability to intervention makeit a most important com­ ponent of ABA. Developing anIndividualized Curriculum The word curriculum has various connotations and meanings for various professionals. In thecontext of this article, curriculummeansasequence of goals: (1) organized fromboththelong-term andshort-term per­ spective’ (2)resulting from focused assessment,(3) re­ flecting the collective prioritiesof involved adults, and (4) tempered by thecurrent developmental level of child. Because thisshould be aninteractive process, and typically involves individualsat various levels of exper­ tise, it is useful to have an outlineordocument that serves as a map (Romanczyk,1996).However, caution must be expressed inthat acurriculum shouldnot be seen as a specific sequenceoflearning and skill activi­ ties that allchildren willprogress throughin asequen­ tial manner. One of the important characteristics ofchildren with autism is unevenlearning ability and skill levels. Thus, individualization ofintervention cannotbeoverstated. While generally anexcellent startingpoint,it is not necessarily most effective to teachall skills in a “typi­ cally developing” sequence.Use of acurriculum must occur within a very tight feedbackloop that assesses not only the logic and priorityof a goal and its subcompo­ nents, but also its interactionwithassessment informa­ tion which includes a child’s currentrepertoire, moti­ vation, andpreferences. A goodcurriculum should have a conceptual structure(we suggest a developmen­ tal sequence), offergreat detail (operalization), and be used in a child specific manner(nonlinear branching). Selecting andSystematically UsingReinforcers It is a truism concerning humanbehavior thatmoti­ vation is animportant component oflearning and main­ taining skills.Motivation can come from a numberof sources. For most individuals,this diversity providesa rich context foracquiring andmaintaining skills. It is also the case thatsome individuals, such aschildren with autism, have impairmentinmotivation. At times, motivation may be quite idiosyncraticandlimited in its extensiveness. Anexample would be childrenwho are not motivated by socialattention andpraise, physical contact, and the sense of accomplishmentforcomplet­ ing a task or solving a problem.Rather,theseindividu­ als might find theirownrepetitive andstereotyped be­ havior moreinteresting andenjoyable, and thusengage in it disproportionately comparedtoprosocial behav­ ior. The termreinforcer describesafunctional relation­ ship thatisempirical innature, not speculative. This is a critical aspectof thebehavioral model:procedural or technique components are not to be used in isolation, detached from the critical processofongoing assess­ ment. The stereotyped andincorrect reinforcement procedure “forchildren withautism who fail to make eye contact, each time they look at you, reinforcethem with a fruit loop,”iscompletely erroneousand misses the point entirely. Alsoerroneous would be the con­ clusion that”eye contact is not getting better even though wekeep reinforcing them with fruit loops.” Even at its most basic level, ABA isintimately tied to continuous assessmentof theindividual and not simply the application ofmisperceived standardtechniques. Promoting Generalization Generalization is a keyconcept. It isoften viewed as the degree to which a behavioror skilllearned under particular conditions andsettings will beexpressed in other conditions and settings. An examplemight be taking pianolessons and being able to performa par­ ticular musical piece quiteadequately athome with the piano teacher, andthen being asked topresent that same piece duringarecital whereperformance may be observed to be significantly impaired. From theinception of ABA, generalization hasbeen a focal concept thatisbound directly to goal selection, teaching, andevaluation ofbehavior. Intheir classic article thatappeared in the first issue of the Journal of Applied BehaviorAnalysis, Baer,Wolf, &Risley (1968) stated thatgeneralization is acentral component of ABA and that “… generalization should be pro­ grammed,ratherthanexpected orlamented” (p. 97). That is, animportant characteristic of ABA isthat the intervention process must explicitly addressstrategies and procedures toteach andpromote generalization across time, setting,people, and tasks. There is anextensive generalization methodologyto be found in thepublished literature. It involves knowl­ edge of stimulus control,stimulus generalization, rein­ forcement schedules,prompthierarchies and fading, setting events, antecedent conditions,responsevariabil­ ity, contingency criteria,use ofmultiple exemplars, set­ tings, people, andcontexts, as well as task analysis and response repertoire assembly.Becausegeneralization can be problematic forcertain individuals, and given the complex factorsthatinfluence generalization, a spe­ cific and detailedplan for generalization shouldbe a part of allintervention programs. at FLORIDA INTERNATIONAL UNIV on June 17, 2015 rps.sagepub.com Downloaded from 166 AndersonandRomanczyk Selecting Intervention Techniques With Documented Effectiveness Froma clinical perspective, selectionofintervention techniques has twocomponents. The first is to ascertain controlled researchevidence concerning specific skills, behaviors, orconditions forindividuals with a similar diagnosis/characteristics that appear inpeer reviewed journals andthat meet generally acceptedcriteriafor well controlled clinical studies. Anecdotes,casestudies, “expert opinions,” theoretical arguments, andappeals to “clinical experience” are not acceptablesubstitutes. Such sources canprovide potentially usefulinformation in order to test hypotheses abouteffectiveness compari­ son of different approaches andprocedures in a re­ searchcontext, butshould not be used as a substitute for controlled researchevidence for clinical practice. Second, the selected intervention must meet the boundaryconditions of theoriginal research param­ eters. Sadly, interventions areoften implemented in name only,thatis,terms are used to label what is being offered, but the specifics of the interventionas actually applied are not consistent with the specifics of the origi­ nal intervention research.Procedural integrityis mea­ sured andevaluated as is theobjective evaluation of the child’s progress. Specifically, anevaluative process known as single subjectmethodology isemployed (Bar­ low et aI., 1984; Hersen & Barlow1981;Sidman, 1988). There are many very powerfultoolscurrently avail­ able to parents, educators, and clinicians who wish to avail themselves of theempirical literature. One cau­ tion that should beraised isthat it isessential in this process toread and review researchreportsintheir original form, rather thanassummaries. Inparticular, the explosion ofinformation on theinternet has suf­ fered greatly bymisrepresentation andinaccuracy. In­ formation isoften “packaged” toprovide noncritical support for aparticular pointof view. In readingthe original research report,one is able to ascertainthe specific characteristics of thechildren whoparticipated, the specifics of the proceduresutilized, the adequacyof the research design, and the degreeandmagnitude of the outcomes. Certainly,it ispossible to have a research study thatdemonstrates a significantstatisticaldiffer­ ence between intervention procedures, but thatdoes not necessarily mean that thissignificant difference rises to the level of clinical significance. We require both statistical significance and substantialchangein the child’s cognitive, social, and family and community life. The task of reviewing suchresearch can seem daunt­ ing. Because ABA isbased on basic principles of hu­ manbehavior, thereis awealth ofresearch available. The published literatureofprofessional journalswas searched forresearch studiesconcerning applied be­ havior analysis and autism(Palmieri, Valluripalli, Arn­ stein, & Romanczyk, 1998). Given the varying termi­ nology, thereareabout 19,000 published articles if one uses applied behavior analysis and its synonyms. While not all this literatureis directly relevantto ABA as an intervention for autism, it underscoresthe vast base of research thatserves as the foundationfor the ABA approachand itsbroadapplicability to a wide range of populations, skills, andbehaviors. Five hundred articles specific to both ABA and au­ tism were found. If we narrowthe focus to research with young childrenwith autism, conductedafter1980, and employ a single subjectresearch methodology, ap­ proximately 90published researchstudies were identi­ fied. These provide supportfor abroad continuum of behavioral techniques thatfocus on the development of skills in social, cognitive, self-help, independence,emo­ tion, language, self-control, attachment,recreation,and academic areas. In short, thereis a large base of researchliterature that addresses specificpopulations, ages,characteris­ tics, and specific educational,clinical, social, and physi­ cal emphases, as well as a substantialbase ofresearch specific to ABA and young childrenwith autism. A full review of thesearticles is not possible here(for exten­ sive reviews, see Matson,Benavidez, Compton,Paclaw­ skyj, & Baglio, 1996; New YorkState Department of Health, 1999b).However, thereareseveral large-scale studies thatbase their conceptualization andproce­ dures on the large researchbase, which we will briefly review. Theyrepresent theimportant endeavorof con­ ducting controlled clinical trials. Six studies havebeen published thatevaluated the benefits ofintensive homebased intervention for chil­ dren with autism. Each of these studies involved at least 1 year of intervention, includedabroad rangeof be­ havioral techniques, andevaluated its effects of a vari­ ety of developmental outcomes(intellectual function­ ing, language, socialinteractions, adaptivefunctioning). The most comprehensive study of homebasedinter­ vention forchildren withautism waspublished by Lovaas (1987). Lovaas assigned preschoolaged chil­ dren to one of two groups: an intensivetreatment group that received anaverage of 40hours ofone-on-one treatment per week or a minimaltreatment control group thatreceived 10 hours or less per week.Each child in the experimental groupwas assigned several well trained therapists whoworked with the child and the parents in thehomefor 2 or moreyears. Pretreat­ ment measures revealedno significant differencesbe­ tween the treatment and control groups. However, posttreatment dataindicated that9 of 19 (47%) chil­ dren in the experimental grouprecovered. Thesechil­ dren were reported to haveachieved normalintellec­ tual and educational functioningin the first grade. In contrast, only 20/0 of thechildren in thecontrol group met this criterion. A follow-up study was conducted when thesechildren reachedamean of age 13 years (McEachin, Smith, & Lovaas, 1993). Evaluationwas done by clinicians blind to the children’spriorhistory at FLORIDA INTERNATIONAL UNIV on June 17, 2015 rps.sagepub.com Downloaded from Continuum-BasedBehavioralModels 167 and intermixed withchildren who had no history of developmental orpsychological disturbance. At this point, 8 of the 9 recovered childrenwere still indistin­ guishable from thecomparison group. Several other investigators (Birnbrauer & Leach, 1993; Sheinkopf & Siegel, 1998;Smith, Eikeseth, Klevstrand, & Lovaas, 1997) have partiallyreplicated the intensive behavioral intervention modeldescribed by Lovaas. In each case, therewereimportant devia­ tions from the modelincluding the fact thatall of these studies provided fewerhours per week (18 to 30 hours rather thanthe 40 hours providedbyLovaas). In each of these studies, children whoreceived thebehavioral interventions showedgreaterimprovement thanchil­ dren in the control groupswhoreceived eitherless in­ tervention oranother type ofintervention. A sixth study byAnderson, Avery,DiPietro, Edwards, and Christian (1987)appears tosupport thesefindings as well, but did not includeacontrol group of comparable children receiving an alternativeapproach. The results of these group studies when mergedwith the results of single subjectresearch methods offer con­ siderable supportfor the positive effects of intensive behavioral interventions for youngchildrenwith au­ tism. Nevertheless, manyquestions remain.AsGreen (1996b) pointed out, it is still unclearwhatvariables are critical tointervention intensity (number ofhours, length of theintervention, proportionofone-to-one to group instruction) and what are the expectedoutcomes when intervention intensityvaries. It is also unclear what particular behavioral techniques (discretetrials, incidental teaching,pivotalresponse training)are most likely to be successful for a given child and in what proportions particulartechniques shouldbe used. The current research islimited inthat it does not allow us to draw comparisons across studies. At thispoint, we can conclude thatthe best outcomes haveoccurred when the children received at least 30 hours of behavioral intervention. Continuum-Based BehavioralModels Since thepublication of Let Me HearYourVoice by Catherine Maurice(1993),requests for ABA services has grown rapidly. Parents,armedwithempirical stud­ ies, often approach localgatekeepers of special educa­ tion services by strongly advocatingfor ABA. The re­ quests have challengedlocal capacity to providequali­ fied personnel and tomeettheextraordinary demand for the number of hours recommended. Theseissues are exacerbated byresistance from some key officials, sometimes basedoninaccurate, butstrongly held be­ liefs about behavioral interventions. Contrary to the beliefs of some, ABA isnot a stag­ nate, single continuum ofprescribed methods.It em­ phasizes the use of methodsthatchange behavior in systematic andmeasurable ways. Theuniquecontribu- tion of this approachis itsinsistence on analysis, repli­ cation, socialimportance, andaccountability (Baeret al., 1968; Sulzar-Azaroff &Mayer, 1991). Arguably,any intervention strategycould be studiedandembraced by behavior analysts,if it can be describedinprecise terms, reproduced, anddemonstrated to be effective. At this point, ABA is anemerging technology thathas consistently producedthe bestoutcomes forchildren with autism. It will continuetoexpand itsbenefit to children withautism if itmaintains itscommitment to studying changes in behaviorinsystematic andmeasur­ able ways. At the same time, it is importanttoremain abreast ofdevelopments outsidethebehavioral com­ munity in biology, medicine,andneuroscience thatmay provide a clue to moreeffective interventions. It is pos­ sible thatacombination ofbehavioral andother inter­ vention strategies mighteventually maximizeoutcomes for some childrenwith autism. For example, it has been empirically demonstrated thatbehavioral interventions and medications aremore effective whencombined than either is alone for many childrenwithattention deficit hyperactivity disorder(Pelham, 1989;Pelham & Murphy, 1986). In short, ABA includesa largenumber of conceptually consistenttechniques thatcan be used in various combinations across manydifferentcontexts. This diversity of proceduraltechniqueshascreated some confusion regardingtheprecise characteristics of quality ABA programs and the limits of its applicabil­ ity. It has sometimes polarizedpractitioners who be­ lieve one particular combination ofbehavioral tech­ niques is moreeffective thananother for allchildren concerned. Compounding theproblem areinexperi­ enced professionals whooften apply a very narrow, rigid range ofbehavioral techniques to verycomplex situations. Parents,administrators, andother profes­ sionals have beenleft to wade throughamyriad of options, oftenwithout sufficient information and tech­ nical ability to evaluatequality.Theseissuescombined with historical misrepresentations havecreated many myths abouttheapproach. There are program modelsthatshare thecommon elements of ABA described earlierandappear to uti­ lize a broad continuum oftraditional behavioral tech­ niques (e.g., Anderson,Campbell, & O’MallyCannon, 1994; Handleman & Harris, 1994;McClannahan & Krantz, 1994;Romanczyk et al., 1994). It is our sense that these types of behavioral programsdraw from the large base of researchstudies specifically addressingthe young child with autism(approximately 90 single sub­ ject designs and six groupstudies) and use a rangeof behavioral techniques (e.g.,incidental anddiscrete tri­ als teaching) andcontexts forlearning (e.g., home basedandintegrated preschoolsettings). At the same time, each programisunique inthat itcombines tech­ niques in differentways and emphasizes, moreor less, one technique oranother. It isimpossible todescribe exactly a “typical”behavioral program.Nevertheless, at FLORIDA INTERNATIONAL UNIV on June 17, 2015 rps.sagepub.com Downloaded from 168 AndersonandRomanczyk we will attempt toidentify somefeatures thatseem to define (distinguish) typicalmodels (hereinafter re­ ferred to ascontinuum basedmodels). We have chosen to do this while simultaneouslyaddressingsome of the myths thathave developed about ABA. Common Features of Continuum BasedModels Multiple Contexts forLearning Myth: ABA is exclusively a homebased intervention model. The most promising outcomesforchildren with autism havebeen reported by Ivar Lovaas in his semi­ nal 1987 paper (described earlier). That study when taken in combination with the partial replications (Anderson et al., 1987; Birnbrauer & Leach,1993; Sheinkopf & Siegel, 1998; Smith et aI., 1997) provides the most detaileddescription ofmultiyear behavioral interventions forchildren with autism. One common element of all ofthesestudies is thatmost interventions occurred in the child’s homewith a latertransition to school. Particularly whenaddressing theneeds of very young children, compelling argumentscan bemadefor providing services in the home: (1) it is a familiar and comfortable settingfor the child, (2) it encouragesac­ tive parent involvement, and (3) it is a naturalcontext for learning many skills (e.g., self-help, independent play skills). However,untilthere aredirect compari­ sons, the strongest statement we canmakeisthat the best outcomes forchildren with autism have been re­ ported byprograms employing a significant periodof home based intervention. On theotherhand, many of the elements commonly found inhomebased programs also can be found in school programsthatuse similar methods (i.e., highly structuredenvironments, careful analysis and measurement ofprogress, functional as­ sessment, individualized curricula,planneduse of rein­ forcers, active programmingofgeneralization, and the use of intervention techniqueswithdocumented effec­ tiveness). Several studies have documentedoutcomesfor chil­ dren served in comprehensive centerbasedprograms using ABA methods. In one study, Fenske,Zalenski, Krantz, andMcClannahan (1985)reported treatment outcomes for agroup ofchildren whoreceived inten­ sive behavioral programming in a school setting. Al­ though the study had some design limitations,the re­ sults indicated thatchildren weremore likely to achieve positive outcomes (regularschoolplacement) if they enrolled in theprogram beforeage 60months and par­ ticipated at least 24 months. Another study byHarris, Handleman, Gordon,Kristoff, and Fuentes(1991) pro­ vided intensive behavioral intervention in a special or inclusive classroom. Changesinintellectual and lan­ guage functioning wereevaluated afterabout 1 year of participation. Onposttesting, thechildren with autism achieved significant improvement intheir ability as measured byformal testing. Since children spendmost of theirwaking hours at home withtheir families, it makes sense to provide most initial trainingintheir home with active parent involvement. Although not all families are willing and able to participate in a homebasedprogram, thereis no reason tosuspect thatquality behavioral interventions applied at school would have significantly differentout­ comes, particularly ifattention was given to the issues of generalization andparent involvement. In summary, homeand school approaches are all found in continuum basedmodels for childrenwith au­ tism. It is also commonto findcombinations ofhome and school approaches in which the child progresses gradually from ahomeprogram to a school program (Anderson, et aI., 1994) over severalmonths. Other models are even moreflexible and the child and staff move continually and do not occupyself-contained classrooms (McClannahan & Krantz,1994). Progression FromIndividual toGroup Instruction Myth: ABA always is characterized byone-to-one intervention. Althoughmanybehavioral models have emphasized theneed forintensive one-to-one to build initial skills (Andersonet al., 1987; Lovaas, 1987; Ro­ manczyk, Matey, & Lockshin, 1994), most programs actively build the requisiteskills for small and large group participation. Individualinstruction makessense when the studenthaslimited attention, respondsidio­ syncratically, requiresphysicalguidance most of the time, lacks basic group readinessskills, and when the child is first introducedtoteaching situations. Although the best outcomes havebeen reported byprograms us­ ing intensive one-to-one trainingfor at least 2 years (Anderson et al., 1987; Lovaas, 1987), therehavebeen no direct comparisons of thebenefits of group versus individual instruction. The potential benefitsof group instruction are fun­ damentally clear and are unlikely to producemuch dis­ agreement amongprofessionals: (1)preparing the child for kindergarten andelementary classrooms, (2) pro­ viding potential forincidental orobservational learn­ ing, and (3) providinganopportunity for social and language interactions withother children. Whatoften seems to be at issue are when to introducegroup in­ struction andwhether there areprerequisite skills. Again, we recommend thatthisbecome an issue of individualization andreasonable balanceratherthan rigid practice. It is also possibletoblend methods by providing one-to-one within agroupcontext (Kamps et al., 1991). In this format, one studentreceives instruc­ tion while the same teachersupervises otherstudents who are working independently(typically on a “back­ ground task”).Thismethod allows the teacherto move back and forth betweenindividual and group instruc­ tion and gives the child an opportunitytoobserve the behavior of other children.In our opinion,flexible at FLORIDA INTERNATIONAL UNIV on June 17, 2015 rps.sagepub.com Downloaded from Continuum-BasedBehavioralModels 169 models that allow fluid changefrom one context to another and movement between individual and group instruction are mostlikely to be successful. Another factor that shouldbeconsidered inchoosing a context forlearning concerns the number ofinstruc­ tional opportunities. Childrenwithautism appear to learn most readily through repetition orpractice on a small set of targeted skills for learning. The number of instructional opportunities areinfluenced by many fac­ tors including the total number ofhours ofintervention per day and the length of theintervention period in months oryears. Inaddition, the size of the instruc­ tional group may exert significant influenceon the number ofopportunities. Typically,as a child moves from individual to smallgrouptolarge group, the num­ ber ofopportunities decreases.This issometimes rea­ sonable andappropriate, particularlywhen the goals are concernedwith the acquisition ofmany kindergar­ ten readiness skills (e.g., followinginstructions givento the group). Although eachsituation must beevaluated individually, it isnecessary tostrike abalance between the level of individualandgroup instruction that each child receives, continually evaluating and prioritizing the goals to be achieved. In summary, the continuum basedmodels oftenem­ phasize one-to-one instructiontobuild aninitial reper­ toire of skills. Every effort is made to move the child along the continuum from one-to-one tosmall group to large group instruction. Utilization ofMultiple Instructional Techniques Myth: ABA exclusively uses teacher led,discrete tri­ als methods. Many parents andprofessionals equate ABA with an instructional techniquecalleddiscrete trials. In discretetrialstraining (Anderson, Taras, & O’Malley Cannon, 1996; Koegel, Russo, & Rincover, 1977; Lovaas, 1981;Luyben, 1998), the instructor pro­ vides a concise instruction, question,oractivity when the child is mostattending. If the childanswers cor­ rectly, the teacher praises enthusiastically and may re­ ward the occurrence of the behaviorwith other signs of approval (a toy, pat on the back,food). If the child fails to respond or responds incorrectly, the instructor deliv­ ers feedback andprovides a prompt toensure that the correct ordesired response occurs. The formand level of the prompt (e.g., physical, gesture,verbal,partial physical) is determined individually but shouldbe im­ mediately successful and easilyfaded. Often, the trialis quickly repeated, giving the child an opportunity to practice what has just been shown. Most of us have learned something at one timeor another using this method and it is unlikely byitself to be very controver­ sial. However, discretetrials methods alsohave become closely associated with other aspectsof the instructional context. Initialinstructional sessionscan be very diffi- cult for the learner with autism and as soon as the in­ structor beginsto set limits (e.g., insisting that the child remain seated), many children resist. To limit the child’smobility and to allow more effective prompting, the instructor and child often sit facingeach other in chairs, with the child’slegsresting between the instruc­ tor’s. The instructor then presents the lesson in the dis­ crete trials format described above.A well trained in­ structor will use a varietyoftechniques to assist and help the child feel comfortable with the situation(e.g., short sessions,introduction offamiliar activities, physi­ cal and verbal assistance, music or preferred activities interspersed withless preferred tasks, teaching an ap­ propriate escaperesponse). Nevertheless, even with the best laidplans, some children withautism willresist the intervention. On the positive side, this formofinstruction often results inrapid learning for many children. On the negativeside, critics argue that the selectionoflessons is too teacher directed and that itminimizes individual choice. However, the goal of the behavior analystis to increase alternative responsesso that the childacquires more freedom ofchoice (Alberto & Troutman, 1999). Children who lack functional communication skills and repeatedly fail toexpress their needs and wants are unlikely to make friends. The discretetrials method had been contrasted with another behavioral approach calledincidental teaching. This approach has been described and demonstrated to be effective formany children (McGee, Krantz,Mason, & McClannahan, 1983). In this method, the instructor assesses the child’s ongoing interests, follows the child’s lead, restricts access to high interest items, and con­ structs alesson within the natural context, with apre­ sumably more motivated child. This model produces rapid learning if the childfrequently exhibitsinterests in objects and activities. On the other hand, if the child does not spontaneously show interest inmany things,it is difficult to find enough instructional opportunities. Furthermore, ultimatelyit isdesirable for a child to learn even insituations orcircumstances that are not inherently interesting. In our opinion, these techniques are both very im­ portant and are not’ necessarily incompatible. At any given point in time, each method may have benefits and limitations. It can beargued that adiscrete trialis a naturally embedded part of an incidental teachingop­ portunity (getting the child’sattention, providing clear instruction, offeringpraise and support). For thisrea­ son, we prefer to use the phrase direct teaching rather than discrete trialstolabel the highly teacher directed situation described above.In adirect teaching situation, most instructors use avariety oftechniques tonaturally motivate children(e.g.,incorporating childchoice, re­ inforcing attempts). In our opinionit is important to think ofdiscrete trials and incidental teachingas end pointsalonga continuum ofteaching contexts and tech- at FLORIDA INTERNATIONAL UNIV on June 17, 2015 rps.sagepub.com Downloaded from 170 AndersonandRomanczyk niques (Table1). Inbetween the two ends is a gradient of situations thatblend teacher directed and child ini­ tiated opportunities forlearning (we have identified one point as activities embedded). Eachpoint along this continuum hasadvantages anddisadvantages and each may be importantforindividuals at any given time in their development. Evenwithin a single session, the best instructors willblend direct teaching andincidental teaching techniques. The decision to teachin a given context is again basedon many individual variablesin­ cluding (but not limitedto) the child’s attention,indi­ vidual distractibility, spontaneousinterestin toys and materials, the lesson being taught,and most impor­ tantly, the child’s progress.Itshould not be a polarized decision but an individualized decisionbasedon indi­ vidual needsandobjectively measuredoutcomes. In summary, it is ouropinionthatcontinuum based models use many differentinstructional techniquesto achieve the desiredresults moving up and down the continuum ofteaching techniques (Table1),matching the approach to the child’s level and most effective style of learning. Opportunities for Social Integration Myth: ABA cannot be applied in socially integrated school settings. Some behavioral researchers have madecompelling argumentsfor thebenefits ofteaching children withdevelopmental disabilities inintegrated settings (Jenkins, Odom, &Speltz, 1989). The underly­ ing assumption isreasonable, thatis, young children with disabilities willimprove byobserving the social and language modelsof their typically developing peers. In fact, many behavioralprogramshavereported the use of a social integrationmodel(Anderson et al., 1994; McGee, Daly, &Jacobs, 1994; Strain &Cordisco, 1994). Although mostbehavior analystsrecognize the importance of socialintegration for manychildren,one can find considerable variabilityas to when the integra­ tion should occur. A few programs havehypothesized thatfor some children, aperiod ofindividual andsegregated small group instruction helps inpreparing thechildren for later inclusionary experiences(Andersonet aI., 1994; Handleman & Harris, 1994).Theseprograms typically provide agradual progression fromindividual (homeor center based) to small group (oftensegregated) to large group instruction (integrated). Many oftheseprograms also report success in transitioning childrentokinder­ garten placements withinregular schools. When inclusion is the choice of parentsand profes­ sionals, it is importanttoremember thatsimple expo­ sure to typically developingchildrenmay not be suffi­ cient to produce measurable gains.Furthermore, close proximity does notprecludethatchildren might dem­ onstrate highlyidiosyncratic patternsofparticipation (Kohler, Strain, & Shearer,1996).There must be an individual focus for the evaluationofinclusion thatin­ cludes parents andteachers. As part of the decision making progress, theseindividuals mustmake decisions about thesequence of thecurriculum and thebalance between individualization and inclusion. The behavioral strategiesandtechniques thatare ap­ plied in segregated settings also can be appliedin inte­ grated settings. Anderson et al. (1994) describedan in­ tegrated settingin which teachersorganized learning centers and the children were free to move among areas as they chose. Specific educationalobjectivesfor each child were embeddedintothese play activities, often using task analysis so thatteaching occurred at the child’s current level and graduallyincreased in com­ plexity. While theseactivities were occurring,students were removed individually or as part of a small group for brief periods ofinstruction onother educational objectives thatwere less easy to embedorthat required significant repetitionfor learning. Methodsfor ongoing assessment anddata driven decision makingwere di­ rectly built into the system. The programemployed be­ havioral practices commonto most quality programs: (1) clearly definedskills to be learned;(2)baseline and ongoing assessment; (3) systematicintroduction of be­ havior intervention methods;and (4) a broadcontext for learning thatincluded directteaching, embedded trials, and incidentalteaching, In summary, thecontinuum-based models typically employ a strategyof acontinuum of services from in­ tense individualized services in aspecializedsetting(or home) tomore typical classrooms withrequired sup­ port. This allows the rapidacquisition of skills and a systematic andplanned approach tointegration. Table 1 A Brief Description of Three DifferentPoints Along a ContinuumofContexts ForLearning Direct teaching Activitiesembedded Incidentalteaching • Usually one-to-one • Highly structured • Teacher directed • Many instructional opportunities • Skills acquired quickly • Distractions minimized • Easier tomanage behavior problems • Generalization may berestricted • Usually small group • Shared teacher/child control • Some naturaldistractions • Typically few instructionalopportunities • Moderate level ofstructure • Challenging to findreinforcing activities • Generalization may beenhanced • Small and large group • Most natural • Child directed • Natural distractions • Challenging to findreinforcing activities • Typically fewer instructional opportunities • Generalization may beenhanced at FLORIDA INTERNATIONAL UNIV on June 17, 2015 rps.sagepub.com Downloaded from Continuum-BasedBehavioralModels 171 Individualized InstructionalCurriculum Myth: ABA does not develop functional skills. A common characteristic ofchildren withautism is the failure togeneralize skills across conditionsand re­ sponses dissimilar from theoriginaltraining. For ex­ ample, children wholearn toidentify severalcommon body parts (nose, ear, eye) when appliedtothemselves, may fail to generalizewhenasked toidentify thesame parts on a doll. Similarly, a child who learnstoimitate simple motor movements (e.g., pat stomach, touch handtohead) could fail to learnthe more general rule (i.e., “Do as I do”). Many of the skills targetedfor initial instruction (e.g., motor imitation,matchingcom­ mon objects,following instructions) are considered functional in that they provide the foundation for teaching many other things(communication, academic, self-care) . During initial training situations, some teachers main­ tain unusually tightcontrol over the instructions pro­ vided, the materialspresented, thechild’s positioning, and other setting conditions. This level of controlis often needed to helpchildren attendto the task, mini­ mize distractions, and break the activity into a series of small steps for learning.Teaching in this manner may lead to rapidacquisition of skills but sometimesmini­ mizes generalization. However,aschildren becomein­ creasingly more responsive toinstruction, it ispossible to simultaneously teachunder more natural conditions or to initiate instruction within anembedded or inci­ dental teaching format.We again referto the impor­ tance of using the full contextcontinuum forlearning (Table 1). For manychildren, instructional targetsare quickly learned andgeneralized tosettings, materials, and con­ ditions different from the learningcontext. For other children, verylittle generalization occurs andmostev­ erything the child learnswill have to be taughtdirectly. The failure togeneralize (ordevelop rulegoverned be­ havior) may be a resultof many variables: (1)poorly selected goals for learning(learned behaviors did not meet anatural community ofreinforcement), (2) fail­ ure of the instructor to actively programgeneralization, and (3) limitations in our currenttechnology toteach and promote generalization for themostchallenging children. It is fair to say that mostchildren willbenefit, to a greater or lessextent, fromintensive behavioral interventions. However,therates oflearning and the range ofoutcomes forchildren may be as broadas the disorder itself (Weiss, 1999). Some childrenfail to dis­ play newly acquiredskillsexcept under highly teacher directed conditions (someonegives them averbal in­ struction, modelsthedesired behavior, orgestures to­ ward materials). Clearly,practitioners of ABA cannot be satisfied withproducing simplebehavior changein highly controlled conditions withoutfullyconsidering how the skill will be used in more natural situations. However, thereis little evidence tosupport analterna­ tive hypothesis that learning in all cases is likely to be more successful whenprovided in thenatural context. Fortunately, there is an emerging set oftechniques (train diversity, incorporate functionalmediators, in­ clude natural communities) that whenapplied system­ atically oftenproduce thedesired results(Stokes &Os­ nes, 1988). It is importanttoprovide anindividual child focus for the use and evaluationofthese instructional techniques. In summary, thecontinuum basedmodels consider many variables whendetermining skills to betaught and the context forlearning to occur. As we stated earlier, acurriculum forchildren withautism cannot be seen as a linearsequence of skills to be learnedinorder. For the very young child, many skill targetsarechosen because they are believed to befunctional indevelop­ ing a foundation forteaching other skills. In the older child, skills are functionalbecausetheyenable the child to live a more independent lifestyle.Onceatarget skill has been selected, other factors may influencethe con­ text in which teachingwill occur (e.g., child’sattention, need forone-to-one). Again,weargue that the indi­ vidual child focus be maintainedand the full context continuum forlearning beavailable. Development of aBehavioral Support Plan Myth: ABA usesaversive techniques tomanage be­ havior problems. Childrenwithautism oftendisplay challenging behaviors that interferewithlearning. It is our sense that allcontinuum basedmodels emphasize methods toteach new skills rather than asingular focus on managing challenging behavior.Initially,problem behaviors arehandled througha richschedule of rein­ forcement that builds adaptive skills. For example, in these programs, much ofearlylearning ishelping the child to acquireandgeneralize the ability to follow simple instructions and to useappropriate behaviorto gain attention orescape fromundesired requests.Many behavior problems improveas the child’sabilityto communicate andrespond to simple instructions im­ proves (Luiselli, 1990). As it was indicatedearlier,the first job of the behavioranalystis to make the sessions fun for the child (e.g., short,familiar, andmotivating). Positive resultscan be enhanced byteaching the child an appropriate communication skill that replacesthe problem behaviors. The directteaching approach de­ scribed aboveoftenis the context forteaching the child the earliest skills to be learned.Gradually, expectations are increased andemerging skills arereinforced during natural school,home,andcommunity contexts. Some behavior problems continuetopersist during or outside the direct teaching contextregardless of well intentioned efforts. At thispoint, welltrained behavior analysts develop anintervention planafter obtaining information throughadetailed functional assessment (O’Neill et al., 1997). In this approach,thebehavior at FLORIDA INTERNATIONAL UNIV on June 17, 2015 rps.sagepub.com Downloaded from 172 AndersonandRomanczyk analyst conducts careful assessments to identify events that reliably predictandmaintain thebehavior. Subse­ quently, a behaviorsupportplan isdeveloped thatis linked to the assessment andmodifies antecedent events, teaches replacement behaviors,and changes maintaining consequences. In summary, the continuumbased models primarily use a skills orientedapproach toimproving the child’s behavior. Whenserious behavior problems do not im­ prove with skill reinforcementandredirection proce­ dures, a careful analysis is conductedand abehavior support plan isdeveloped. Conclusions At this time, controlledresearchindicates thatcom­ prehensive, wellconducted use of ABA offers the most hope for childrenwith autism and theirfamilies. In this article, we first providedthereader with adescription of programmatic andmethodologic commonelements of ABA. It is our opinionthatlittle disagreement exists within the behavioral community regardingthegeneral elements thatshould be presentin a quality program. However, as iscommon with anyapproach, oftenthere are differences in the specific interventiontechniques that are chosen, the proportionof onetechnique versus another, and thesequencing and timing of theiruse. The diversity of these techniqueshascreated confusion regarding thecombination ofbehavioral techniques that is most likely to be effective. It is our opinionthat ABA includes a large numberofconceptually consis­ tent techniques thatcan, and should, be used in various combinations across manydifferentcontexts. References Alberto, P. A., &Troutman, A. C. 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4 Separate Papers. Write a one-page review, single spaced of each of the assigned readings. Article responses should include a description of the article itself and a reaction to the article. I will a
ORIGINAL PAPER Autism Severity and Qualities of Parent–Child Relations Nicole M. Beurkens •Jessica A. Hobson • R. Peter Hobson Published online: 7 June 2012 Springer Science+Business Media, LLC 2012 AbstractThe aim of this study was to examine how severity of autism affects children’s interactions (related- ness) and relationships with their parents. Participants were 25 parent–child dyads that included offspring who were children with autism aged from 4 to 14 years. The severity of the children’s autism was assessed using the calibrated severity metric of the Autism Diagnostic Observation Schedule (Gotham et al. in J Autism Dev Disord 39:693–705,2009). Parent–child dyads were videotaped in 10-min semi-structured play interactions, and qualities of interpersonal relatedness were rated with the Dyadic Coding Scales (Humber and Moss in Am J Orthopsychiatr 75(1):128–141,2005). Quality of relationships between parents and children were evaluated with a parent self- report measure, the Parent Child Relationship Inventory (Gerard in Parent–Child Relationship Inventory (PCRI) manual. WPS, Los Angeles,1994). Multivariate regressionanalysis revealed that severity of autism was inversely related to patterns of parent–child interaction butnotto reported quality of parent–child relationship. We consider the implications for thinking about relatedness and rela- tionships among children with autism, and opportunities for intervention. KeywordsParent–child interaction Autism severity Communication Relationship-based treatment Attachment Introduction When Kanner (1943) rst described the syndrome of aut- ism, he considered the condition to be a biologically based impairment in affective contact between the children and other people. Here he was highlighting a feature of the children’s relatednesstowards others, how they related to strangers (such as Kanner himself) as well as to people with whom they might have an enduring relationship.At the same time, and less centrally, Kanner’s descriptions included reference to the children’s relationships with others, for instance as re ected in their seemingly dimin- ished responses to separation from their parents. The contrast between relatedness and relationships is one between qualities of moment-to-moment social inter- action and interpersonal engagement, and enduring modes of interpersonal relation (whether of attachment, friend- ship, rivalry, hostility or affection) that have speci city to the individuals involved. Relationships are dynamic sys- tems that evolve over time, and are characterized by the endurance and the strength of connectedness between individuals (Reis et al.2000). In the case of relationships between children and parents, they alter as developmental This work was conducted as part of the clinical doctorate of the rst author (NB) carried out at Walden University, and is an adaptation of her dissertation. Portions of the work were presented at the International Meeting for Autism Research (Imfar) in San Diego, CA, May 2011. N. M. Beurkens (&) Horizons Developmental Resource Center, 3120 68th Street SE, Caledonia, MI 49316, USA e-mail: [email protected] J. A. Hobson R. P. Hobson Institute of Child Health, University Collge London, 30 Guilford Street, London WC1N 1 EH, UK e-mail: [email protected] R. P. Hobson e-mail: [email protected] J. A. Hobson R. P. Hobson Tavistock Clinic, 120 Belsize Lane, London NW3 5BA, UK 123 J Autism Dev Disord (2013) 43:168–178 DOI 10.1007/s10803-012-1562-4 needs change (Bugental2000; Harach and Kuczynski2005; Laursen and Bukowski1997). This is notwithstanding that relationships implicate particular qualities of relatedness between or among the people involved in those relation- ships, and that interactions can be viewed in the context of overall relationships (Loulis and Kuczynski1997). Among many forms of dif culty that can affect parent–child rela- tionships, stresses in parenting an atypically developing child can create negative feelings toward the child, alter parent expectations, and lead to a reduced sense of parent- ing competence (Van Hooste and Maes2003). One aim of the present paper is to tease out this dis- tinction between relatedness and relationships as applied to relations between children with autism and their parents. We investigate how the severity of children’s autism is related to independent measures of child-parent interaction (relatedness) on the one hand, and child-parent relationship on the other. Although the study was not intended to examine thedeterminantsof patterns of interaction and relationship within the child-parent system, our aim was to investigate how closely each of these correspond with children’s severity of autism as assessed using the cali- brated severity metric of the Autism Diagnostic Observa- tion Schedule (Gotham et al.2009; Lord et al.2002). The ndings may be relevant for understanding the dynamics of social engagement, and perhaps highlight the potential for fostering optimal development among children with autism. At the outset, it is critical to appreciate the bidirec- tionality of parent–child relations (Bell1968; DeMol and Buysse2008; Kuczynski et al.2003; Sameroff and Chandler1975). Just as children’s characteristics affect their relations with parents so too, interpersonal interac- tions and relationships with adults affect children’s devel- opment and functioning (Sameroff2009). Over time, each participant and the relationship as a whole undergo trans- formation (Fogel2009). It would seem inevitable that a child’s autism will in uence parent–child interactions. As among typically developing and developmentally delayed populations, there are also likely to be forms of parental behaviour that encourage or impede the children’s devel- opment (Siller and Sigman2002). Relatedness, Relationships, and Autism There is limited evidence concerning the relation between autism severity and parent–child interactions and/or rela- tionships, although these are clearly matters of importance (Markus et al.2000). On the level of relatedness, the more verbal and cognitively able the child, the more caregivers tend to engage in mutual play and positive feedback, whereas parents of children with autism who have poorer joint attention and fewer expressive language skills spend more time keeping their child physically contained andoriented to tasks (Kasari et al.1988). When toddlers with autism show higher levels of externalising problems, their mothers use signi cantly more active/physical coping strategies and report greater levels of parenting stress (Gulsrud et al.2010). Gulsrud et al. (2010) reported how, with an intervention targeting joint attention, mother–child emotional co-regulation improved. From a complementary perspective, parents may in uence the development of their children with autism. Siller and Sigman (2002,2008) studied the extent to which a caregiver’s behaviour was synchronized with a child’s focus of attention and ongoing activity. The researchers videotaped interactions between caregivers and children with autism, and reported a correlation between the synchronization of such relations and children’s subsequent joint attention and language develop- ment. Ruble et al. (2008) reported that parent responsiveness was associated with the children’s propensity to initiate social interactions with adults, and in this case parent interactions were not associated with the child’s adaptive behavior or cognitive level, nor with child and parent demographics (but see Spiker et al.2002). Yet in all such research, one needs to be very cautious about interpreting correlations in terms of cause-effect relations. On the level of relationships, Koren-Karie et al. (2009) reported that secure attachment among children with aut- ism was related to a variety of developmental competencies and greater parental sensitivity, but not to the severity of clinical features of autism (also see van Ijzendoorn et al. 2007). On the other hand, greater severity of autism may be associated with higher levels of individual and family burden (Stuart and McGrew2009). Hoffman et al. (2009) reported a signi cant relationship between child autism severity and parent ill-health, level of depression, and negative perceptions of spouse, as well as the degree of closeness, or attachment level, between mother and child. Indeed, research on a variety of disabilities has yielded evidence that symptom severity is associated with greater levels of burden for parents and the family system, creating more strained relationships (Baker et al.2005; Pakenham et al.2005; War eld2005). There are additional grounds for distinguishing between relatedness and relationships among individuals with aut- ism. On the one hand, there is evidence that across the lifespan, individuals with autism are atypical in various aspects of their interpersonal relatedness. For example, direct observations of infants (e.g., Charman et al.1997), as well as retrospective parental reports (e.g., Wimpory et al. 2000), reveal that even very young children with autism have impairments in the frequency or intensity of eye contact, turn-taking, and referential looking. Among older children with autism, there are reports of the children’s abnormalities in coordinating expressions of affect, ges- tures and eye contact with other people, for example in J Autism Dev Disord (2013) 43:168–178169 123 contexts involving joint action and attention (Kasari et al. 1990), face-to-face interaction (Dawson et al.1990), greetings and farewells (Hobson and Lee1998), and con- versations (Capps et al.1998; Garc ´ a-Pe´ rez et al.2007). On the other hand, there is also evidence that children with autism arenotso atypical in certain features of their attachments. Several published studies indicate how young children with autismdorespond to separation from and reunion with their caregivers, at least in the short-term (e.g., Shapiro et al.1987; Willemsen-Swinkely et al.2000; Sigman and Mundy1989; Yirmiya and Sigman2001). Many (not all) 2- to 5-year-old children with autism are like matched developmentally delayed children in showing somewhat variable mood changes such as fretting when their caregiver leaves them, and upon reunion they tend to spend more time alongside the caregiver than a stranger. When allowance is made for their sometimes idiosyncratic behavior, a substantial number of children with autism are rated as securely attached (Rogers et al.1991; Shapiro et al. 1987). Therefore the children’s relationship with their caregivers is clearly special, even though their qualities of relatedness are atypical. The relatively coherent forms of jealousy seen among children with autism (e.g., Bauminger 2004) may re ect such attachment processes, and account for the dissociation between jealousy and atypicalities in the children’s expressions of other social emotions such as guilt and concern (Hobson et al.2006). In the present study, we employed independent mea- sures of autism severity, parent–child relatedness and parent–child relationship, in order to evaluate the relations among these variables. Children’s performance on the Autism Diagnostic Observation Schedule (ADOS: Lord et al.2002) served as an index of autism severity (Gotham et al.2009). We employed the Dyadic Coding Scales of Humber and Moss (2005) to assess interpersonal related- ness during videotaped semi-structured parent–child inter- actions. The DCS includes ratings of social coordination, communication, appropriate role assumption, emotional expression, responsivity/sensitivity, tension/relaxation, mood, and enjoyment. Finally, the Parent–Child Relation- ship Inventory (Gerard1994) was used to gather systematic parent report of support, satisfaction with parenting, involvement, communication, limit setting, autonomy, and role orientation. Our single prediction was that with increasing severity of children’s autism as assessed on the ADOS, qualities of parent–child relatedness would be negatively affected, as expressed through lower scores on the Dyadic Coding Scales. Although we consider there to be some degree of dissociation between relatedness and relationships in aut- ism, we were uncertain about the degree to which severity of autism might affect parent–child relationships, and made no prediction in this respect.Methods Participants Participants were 25 children with autism aged between 4 and 14 years (M=7.4 years, SD=2.2 years). Although there was a wide age range, the majority of the children (92 %) were aged 10 or younger. The children were mainly male (19 males, 6 females) and took part in the procedures along with the parent identi ed by the family as the primary caregiver (80 % mothers, 20 % fathers). Four of the primary parents were single parents and the remaining 21 were in two-parent households. Primary parents ranged in age from 33 to 61 years. The primary parents were well educated (some college: n=6; college degree_n=11; postgraduate education: n=8). Participants were recruited from autism organiza- tions throughout West Michigan. The ethnic breakdown of child participants was as follows: African American 4 %, Hispanics 4 %, Caucasian 88 %, and Asian 4 %. All partic- ipant children had received a previous clinical diagnosis of an autism spectrum disorder, and this was in keeping with the results of ADOS administration in the present study. Procedure Child participants were evaluated with the ADOS in a clinic setting by the primary researcher, who was trained to admin- ister and score the ADOS at the University of Michigan. The appropriate ADOS protocol was selected based on the age and language level of each child. The two four-year-old children received a Module 1 and a Module 2, the 21 5–10-year-old children received Module 1 (n=5), Module 2 (n=11) or Module 3 (n=5), the 12-year-old child received a Module 3 and the 14-year-old child was administered a Module 2. Parent participants were provided with the PCRI parent questionnaire to read and complete in the clinic setting. The PCRI was scored by the primary researcher using the scoring procedures in the manual. The videotaped parent–child interaction session occur- red within the clinic setting, and consisted of a 10-min interaction period during which the primary parent and child were provided with a standard set of play materials appropriate for the age and developmental level of the child, for instance balls, active games, board/card games, blocks, puzzles, and bean bags. The parent and child were invited to settle and to use the materials together in whatever ways they wished. Parents were asked to set limits and boundaries as they would with the child at home. The parent–child interaction videos were rated by a team of two coders—a primary coder, and secondary coder for reliability—both of whom were blind to the children’s diagnoses, hypotheses and predictions of the study, and the results of all other measures used in the study. 170J Autism Dev Disord (2013) 43:168–178 123 Measures Severity of Autism The Autism Diagnostic Observation Schedule (ADOS; Lord et al.2002) is widely considered a gold standard instrument for identifying clinical features of autism spectrum disorder. The ADOS is a standardized assessment of communication, social interaction, behavior, sensory stereotypies, and play or imaginative use of materials. One of four modules is administered based on the individual’s developmental and language level. Structured activities and materials provide standard contexts in which social interactions, communica- tion, and other behavior relevant to autism spectrum disor- ders are observed. Recently revised algorithms for the ADOS allow for increased speci city in classi cation of clinical features (Gotham et al.2009), as well as increased alignment between the various modules used with participants of differing ages and functioning levels (Gotham et al.2008). A calibrated severity score, called the autism severity metric, is calculated to identify severity of clinical features independent of par- ticipant demographics. This metric, ranging from 1 to 10, allows for standardized comparison of total scores across modules. A severity metric score of 1–3 is considered ‘‘nonspectrum,’’ a severity metric score of 4–5 is considered ‘‘autism spectrum disorder,’’ and a severity metric score of 6–10 is considered consistent with the diagnosis of ‘‘aut- ism.’’ This method of scoring is a departure from the current ADOS manual, but re ects current research conducted by the test authors (Gotham et al.2009), who gave permission for its use in the context of the current study. Patterns of Parent–Child Relatedness The Dyadic Coding Scales were developed by Humber and Moss (2005) to rate qualitative aspects of parent–child interaction for school-age children. While not commercially available, permission for use of this measure for the present study was granted by its developers. Nine domains are rated on a scale of 1–7, indicating the quality of the following aspects of interaction: coordination, communication, partner roles, emotional expression, responsivity/sensitivity, ten- sion/relaxation, mood, and enjoyment. For example, low scores on co-ordination re ect interactions that are unpro- ductive and involve friction between the child and parent; low scores on communication re ect ignoring behavior, withdrawal, incongruent utterances, and/or awkward silen- ces; and low scores on emotional expression indicate intense and/or constricted emotional exchanges. An overall rating is also assigned based on the overall quality of parent–child interaction. Here low scores re ect a sense of indifference, lack of pleasure, and/or con ict.This tool was designed for and used within a study analyzing school-age attachment and mother–child inter- action, and has yielded good inter-rater reliability in a previous study of children with autism (Hobson et al. 2008). In the present study, on the basis of seven cases rated independently, the intra-class correlations (ICC) for each subscale were between 0.83 and 0.98 (where values above 0.80 are considered excellent). Parent–Child Relationship The Parent–Child Relationship Inventory (Gerard1994)is a self-report questionnaire for parents of children ages 3 through 15 years, and takes approximately 15 min to complete. The inventory assesses parents’ views on par- enting and aspects of the parent–child relationship. The seven scales cover parental support, satisfaction with par- enting, involvement, communication, limit setting, auton- omy, and role orientation. For instance, Satisfaction re ects the amount of pleasure and ful llment derived from par- enting (e.g. ‘I get as much satisfaction from having chil- dren as other parents do.’), Involvement has to do with a parent’s level of knowledge of and interaction with the child (e.g. ‘I spend a great deal of time with my child’), Communication concerns parents’ perception of the effectiveness of their communication (e.g. ‘I can tell by my child’s face how he or she is feeling’), and Autonomy focuses on the parent’s ability to promote the child’s independence (e.g. ‘I worry a lot about my child getting hurt’). The scales are rated on a scale of 1 (strongly agree) to 4 (strongly disagree), yielding raw scores,Tscores, and standardized scores for each scale. Higher scores indicate more positive parent–child relationships. Separate scoring sheets and norms are provided for mothers and fathers. The measure was standardized on over 1,100 parents across the United States. Reliability, as determined by internal con- sistency, had a median alpha of 0.82, and the mean test– retest correlations were 0.81. PCRI raw scores are con- verted toTscores, normalized standard scores with a mean of 50 and a standard deviation of 10. ATscore which is more than one standard deviation below the mean (i.e. less than 40) suggests problems in the domain the scale re ects and very lowTscores (i.e. below 30) indicate the possi- bility of very serious problems. Results Descriptive Data Descriptive data from the Autism Diagnostic Observation Schedule (ADOS) calibrated severity metric, the play- based observation coded with the Dyadic Coding Scales J Autism Dev Disord (2013) 43:168–178171 123 (DCS), and the parent-reported features of parent–child relationship on the Parent–child Relationship Inventory (PCRI) are given in Table1, where the standard deviations and ranges convey the substantial ranges of scores on each measure. Calibrated Severity Scores of the ADOS In keeping with the children’s previous clinical diagnosis, scores on the calibrated severity metric of the ADOS ran- ged from 4 (mild autism/Autism Spectrum Disorder) to 10 (severe autism). Autism severity was not associated with chronological age in this sample,r(25)=0.11, NS. Autism severity was also not associated with the ADOS Module the child received,r(25)=-0.23, NS. Parent–child Interaction on the DCS It may be helpful to represent the current results on the DCS in relation to those previously reported by Humber and Moss (2005). As can be seen in Fig.1, children with autism in the current sample received scores that were signi cantly lower than typically developing securely attached children. The effect sizes for these differences were medium for tension/relaxation (d.5) and for overall interaction, coordination, commu- nication, enjoyment and mood (drange=0.71–0.78) for overall interaction, coordination, communication, enjoyment, and mood, and large (drange=0.91–0.98) for emotionalexpression, roles, and sensitivity/responsivity. On the other hand, the children with autism in the present sample received scores that were as low as those received by a parent–child dyads in which children had disorganized/controlling attachment patterns. The effect sizes for comparisons between our autism sample and the disorganised/controlling sample of Humber and Moss were all negligible (drange= 0.07–0.16) with the exception of small effect sizes (drange=0.24 and 0.28) for the sub-scales of overall interaction and emotional expression. This suggests that our autism sample showed marked dif culties in parent–child relatedness. Although several of the children in the current sample were older than those in the Humber and Moss (2005) study, chronological age was not associated with any of the subscales of the Dyadic Coding Scales,r(24) range=0.11 to 0.39, all NS. Parent Report of Relationship Quality On the PCRI, all of the subscales, with the exception of Communication, received mean scores consistent with non- problematic parenting. With regard to the domain of Communication, the meanTscore was in the low range. This score might re ect how parents of children with aut- ism may struggle to communicate well with their children including simple conversation and the ability to talk with their children. Low Communication scores (Tscore 30–39) indicate parental dif culty in talking to a child and in ‘getting through’ to that child. Figure2presents numbers of parents with low (Tscore40) and very low (Tscore30) scores, by individual scales. From Fig.2, it can be seen how most of the parents in the study reported problems with Communication (Lown =11, Very Lown=7). Very lowTscores (less than 30) often indicate the parent feels helpless in his/her attempts to communicate with the child and discover the child’s needs. There were also several parents who reported dif culties with Involvement (Lown=5, Very Lown=1). Items on the Involvement scale re ect the parent’s propensity to spend time with their children and get to know them. Very low scores on this scale can re ect how parents feel there is a great distance between themselves and their children. Autism Severity and Parent–Child Relations Two separate multivariate regressions were conducted to examine the relations between autism symptom severity (ADOS) and a) parent–child interaction (DCS), and b) par- ent–child relationship (PCRI). Ideally, given seven predictor variables, a sample size of 44 participants would have been utilized to achieve an alpha of 0.05 with a large effect size (Green1991). A Bonferroni adjustment was considered, but this would potentially increase the likelihood of committing Table 1Descriptive data for study variables VariableM(SD) Range ADOS 6.88 (1.51) 4–10 DCS Coordination 4.04 (1.43) 2–6 Communication 3.76 (1.71) 1–7 Partner roles 3.80 (1.08) 2–6 Emotional expression 3.40 (1.78) 1–7 Responsivity 3.60 (1.26) 2–6 Attention/relaxation 3.96 (1.51) 1–7 Mood 4.00 (1.58) 1–7 Enjoyment 3.84 (1.49) 1–6 Overall 3.84 (1.37) 2–6 PCRI Support 48.80 (6.22) 36–59 Satisfaction 48.28 (7.93) 33–66 Involvement 44.32 (7.28) 23–53 Communication 35.44 (7.72) 21–53 Limit setting 48.60 (9.22) 23–69 Autonomy 51.12 (9.67) 24–70 Role orientation 51.88 (8.90) 31–64 172J Autism Dev Disord (2013) 43:168–178 123 a Type II error (Nakagawa2004). Therefore, the adjustment was not made for this analysis. The results of the regression for ADOS predicting DCS are shown in Table2. The data suggest that the calibrated severity scores on the ADOS predict the DCS subscale scores of co-ordination, communication, emotional expres- sion, responsivity, and mood, as well as overall scores,F(9, 15)=3.38,p.05. The results were just shy of signi – cance for predicting tension/relaxation and enjoyment, and not signi cant for partner roles. It is plausible that parents and children experience tension and/or enjoyment within their interactions based on factors other than symptom severity. It is important to note that the ADOS Module received by the child was also signi cantly associated with almost all of the DCS subscales (rrange=0.35–0.62). This suggests that general development/language level may also make an important and independent contribution to quality of parent–child interaction. Table3provides partial cor- relations between the children’s calibrated severity scores on the ADOS and the subscales of the DCS, after con- trolling for variance associated with the ADOS Module received. When both ADOS Module and calibratedseverity score were entered into a linear regression, 50 % of the variance (R 2=0.49) in the DCS overall interaction score was explained,F(2, 22)=10.93,p.001. A question arises, whether there are particular items of the ADOS that correspond most closely with subscales of the DCS. The present study was not designed to address this question, especially insofar as items on the ADOS vary depending on the Module employed. On informal review, it was evident that most of the correlations reported between autism Calibrated Severity Scores and the subscales of the DCS (Table3) were very similar to those between uncalibrated ADOS social-affect raw scores (range-0.37 to-0.63), whereas the correlations for ADOS scores on restricted and repetitive behaviour and interests were sub- stantially lower (range-0.12 to-0.34). Not surprisingly, therefore, ADOS indices of social-affect (although raw scores were not calibrated across Modules) were most closely related to the DCS relatedness measures. In contrast with the correlations between autism severity and measures of personal relatedness, autism severity was notsigni cantly associated with any of the PCRI parent– child relationship subscales (where correlations ranged from 0.10 to 0.39). The results of the regression for ADOS predicting PCRI (support, satisfaction, involvement, com- munication, limit setting, autonomy and role orientation) were not signi cant,F(7, 17)=0.94,p=.50. Therefore there appeared to be little relation between ADOS scores and PCRI scores. On the other hand, ADOS Module was related to the Communication subscale of the PCRI, r(25)=0.44,p.05. This suggests that the parent- reported dif culties communicating with children with autism may have been linked to the child’s developmental level/language functioning. Individual differences in scores on the PCRI were not related to observations of parent–child relatedness on the DCS, with only one exception. There was a counter-intuitive nding that the DCS subscale tension/relaxation was inver- sely related to the PCRI subscales of Support (p.05), Limit Setting (p.05), and Autonomy (p.01). One 1 2 3 4 5 6 7 Ov Coord Com Em Ex Enj Mood Role Sens TensTyp-Secure Typ-Dis/Con Autism Fig. 1Scores from the Dyadic Coding Scales from children with autism (current study) and Children without Autism (as reported by Humber and Moss 2005).Note: Typ- Secure=typically developing securely attached children (n=71) and Typ-Dis/ Con=typically developing children with disorganised/ controlling attachment (n=18) 0 5 10 15 20 25 Support Satisfaction Involvement Communication Limit Setting Autonomy Role Orientation PCRI Subscale Number of Parents (out of 25) Low Very Low Fig. 2Number of parents with low (Tscore40) or very low (Tscore30) PCRI scores J Autism Dev Disord (2013) 43:168–178173 123 possible interpretation of this exploratory and unanticipated nding may be that more relaxed parent–child dyads inclu- ded a permissive parent who tended not to set as many limits or promote the child’s independence. Discussion The principal ndings of this study were clear-cut. Within a group of 25 children with autism aged between 4 and 14 years, there was evidence that with increased severity of autism as measured by the calibrated severity scores of the ADOS, qualities of videotaped parent–child interaction such as co-ordination, communication, emotional expres- sion, responsivity, and mood were adversely affected. Therefore features of autism (including those apparent in communication and social interaction) as rated in stan- dardized ADOS assessments were good predictors of less satisfactory parent–child interactions. Impairments in interpersonalrelatednessappeared to constitute an impor- tant bridge between ADOS severity scores and qualities of dyadic interaction.Here the results contrast with another nding, namely the low correlation between the same features of autism severity and aspects of the parent–childrelationshipas reported by the parents. For instance, ADOS severity scores did not predict parental satisfaction, involvement, or communication, where satisfaction re ected the amount of pleasure and ful llment derived from parenting, involvement had to do with a parent’s level of knowledge of and interaction with the child, and communication concerned parents’ perception of the effectiveness of their communication. One possible source of scepticism in interpreting the ndings on relatedness, is whether the results might re ect little more than the outcome of applying similar measures in two settings. However, the differences between the ADOS and the DCS extend beyond the obvious and important contrast between a semi-structured procedure conducted by a stranger (ADOS), and a measure applied to natural parent–child interactions (DCS). A major focus of the ADOS is upon speci c forms of emotional/communi- cative behaviour exhibited by the participant, for instance (depending on the module) facial expression, pointing, eye contact, joint attention, and showing. Although qualities of dyadic engagement such as rapport or shared enjoyment are also taken into account, the emphasis is on particular forms of behaviour exhibited by the child. In contrast, DCS ratings apply to more global qualities of child–adult interaction. In the case of communication, for example, low scores are given for a dearth of communication involving withdrawal and awkward silences, whereas high scores are given for clear, direct and meaningful words and gestures, comfortable silences, and a balance in who does the talking and listening. A low overall rating on the DCS would correspond to disinterest, inaccessibility, lack of pleasure, and the presence of discord and con ict, whereas a high score would be given when there is mutual responsiveness, enjoyment, and harmonious and agreeable interactions with genuine interpersonal interest. Table 2Multivariate regression for ADOS predicting DCS Dependent variablesBSEtpR 2 Power Co-ordination-0.49 0.17-2.92 .01 0.27 0.80 Communication-0.73 0.18-3.99 .00 0.41 0.97 Partner roles-0.18 0.15-1.21 .24 0.06 0.21 Emotional expression-0.58 0.21-2.72 .01 0.24 0.74 Responsivity-0.39 0.15-2.52 .02 0.21 0.68 Tension relaxation-0.39 0.19-2.00 .06 0.15 0.48 Mood-0.44 0.20-2.21 .04 0.18 0.56 Enjoyment-0.34 0.19-1.75 .09 0.12 0.39 Overall-0.50 0.16-3.18 .00 0.31 0.86 pValues uncorrected for multiple comparisons Table 3Correlation coef cients for autism severity and parent– child interaction, including partial correlations with ADOS module controlled DCS subscalerPartialr Coordination-0.52**-0.48* Communication-0.64**-0.65** Partner roles-0.25-0.16 Emotional expression-0.49*-0.45* Responsivity-0.47*-0.41* Tension/relaxation-0.39-0.33 Mood-0.42*-0.36 Enjoyment-0.34-0.27 Overall interaction-0.55**-0.52** *p.05; **p.01 174J Autism Dev Disord (2013) 43:168–178 123 Of course, contrasts between measures do not imply that the phenomena being measured are totally distinct. In the present instance, there is no implication that children’s potential for social relatedness as assessed on the ADOS is independent of child-parent relatedness as evaluated using the DCS. The present ndings suggest just the opposite. The point is that those features of relatedness that are so important for assessing the severity of autism (on the ADOS) arealsoconnected with interpersonal engagement and relatedness in parent–child interactions. When we turn to the ndings on parent–child relation- ships, it should be noted that these are not altogether in keeping with other evidence that children’s symptom severity may have a negative impact on parent–child relationships. Hoffman et al. (2009) reported that chil- dren’s autism symptom severity was related to their rela- tionships with their mothers, speci cally in the areas of attachment and closeness. These results emerged in the context of a study of maternal stress levels, and portray aspects of relationship that differ from those identi ed by means of the PCRI. It was also the case that in the present study, a number of parents’ responses on the PCRI inclu- ded reference to dif culties over communication and involvement with their offspring. The results may be considered from a number of per- spectives. To begin with, they support the conceptual dis- tinction between two partly separable aspects of social experience and behavior: interpersonal relatedness and relationships. Of course it is not possible completely to divorce qualities of moment-to-moment interpersonal con- nectedness and adjustment on the one hand, and features of the relationships between any two individuals engaged in such interactions. Yet if we consider the case of autism, biological factors that might seriously disrupt many aspects of affected children’s relatedness to people do not neces- sarily have the same impact on the children’s relationships. For instance, as Hobson et al. (2006) discuss, patterns of attachment and associated feelings such as jealousy might be spared among individuals with autism, even when their intersubjective engagements (and especially, their feelings forother people) might lack coherence. Results from the present study are in keeping with the view that relationships between children with autism and their parents are not determined by the same factors that appear to constrain certain aspects of interpersonal relatedness. Certain limitations to the study are worth highlighting. Firstly, it remains to establish how speci c is the lack of correlation between ADOS measures of autism severity and parent reports of qualities of parent–child relationships. It would be helpful to compare the present results with ndings when the same ADOS measures are assessed in relation to other forms of parent report, for instance reports on the children’s communicative abilities, so that the degree ofconcordance (or lack of concordance) between these dif- ferent kinds of measure might be evaluated. Secondly, cross- sectional studies such as this need to be complemented by longitudinal research, if one is to trace how far impairments in interpersonal relatedness either shape, or are shaped by, other features of autism. Correlations do not establish the direction in which causal arrows point. In this respect, we stress the dangers of supposing that dif culties in parent– child interactions in uence, rather than re ect, children’s clinical presentation, although of course there may be com- plex cycles of cause and effect. The ndings need to be set within an appropriate theo- retical framework for understanding the development of child-parent relations, from both relatedness and relation- ship perspectives. As discussed in the Introduction, previ- ous research has demonstrated that children in uence their own development through their interactions and relation- ships with parents (Bell1968; Cummings et al.2000; Sameroff and Chandler1975). For example, children’s behavioral and relational dif culties can lead to parenting stress, which may alter parenting behavior and perpetuate the children’s dif culties (Hastings2002). On the other hand, such vicious cycles of interaction are not inevitable, nor need they be pervasive. The present results highlight not only the impact of autism on child–parent relatedness, but also the potential for child–parent relationships to develop despite such challenges. The results may also be considered from the viewpoint of intervention. Research on the bidirectional nature of parent–child interactions has shown that child development can be changed in a positive manner as a result of parents altering speci c interactive behaviors (Arnold et al.1993; Hoagwood et al.2001). Yet in the eld of autism, many interventions do not target the areas of social-communi- cative dif culty that are core features of autism (Charman et al.2004), nor do they follow recommendations to include parents in the treatment process (Howlin2000). Yet again, there is encouraging evidence that interven- tions aimed at creating change in parents and, thus, in parent–child relations may be effective in reducing the severity of autism and/or reducing its impact on the parent– child relationship (Green et al.2010). Training mothers in mindfulness, for example, has led to signi cant reduction in maladaptive behavior of their children with autism (Singh et al.2006). Mothers involved in that study reported an increase in overall parenting satisfaction, increased satisfaction with their parenting skills, and an increase in mindfulness with their children. A program aimed at increasing parental responsiveness to children with autism had a positive impact on the children’s social-emotional development (Mahoney and Perales2003). An intervention designed to reduce problematic behavior in children with autism demonstrated that shifting parents from either an J Autism Dev Disord (2013) 43:168–178175 123 authoritarian or permissive style of parenting to a more authoritative style resulted in positive behavior changes in the child (Whittingham et al.2009). Other studies have also shown that providing training to parents yields improve- ments in joint attention (Aldred et al.2004; Jones et al.2006; Schertz and Odom2007), communication (Symon2005; Vismara et al.2009), school-readiness skills (Ozonoff and Cathcart1998), shared engagement and problem solving (Wieder and Greenspan2003), reduced problematic behavior (Whittingham et al.2009; Solomon et al.2008; Sofronoff et al.2004), and improved emotional co-regula- tion (Gulsrud et al.2010). Training parents of children with autism to interact with their child has been successful at reducing symptoms regardless of initial symptom severity (Solomon et al.2007). Findings such as these stress the importance of under- standing social reciprocity as a two-way street, and changing both children and those with whom they interact (Gernsbacher2006). Interventions for children with autism which focus upon parent–child interaction and target communication may have important implications for the children’s development (Aldred et al.2004; Green et al. 2010; Kasari et al.2008; Wetherby and Woods2006). Indeed, it may prove that rather than implementing speci c ‘training’ procedures, a focus of intervention for children with autism might be the pacing, structuring, and sensitive adjustment of everyday activities that involve children and their parents. This can increase opportunities for deeper interpersonal engagement, co-ordination, communication, and so on, as might happen (for example) in Relationship Development Intervention (Gutstein2009; Gutstein et al. 2007; Hobson and Hobson2011). In keeping with this view, Green et al. (2010) reported signi cant improvement in parent–child synchrony, communication, and shared attention when treatment focussed on the parent–child communication system. Whatever the case in these respects, an important challenge is to determine how best to modify and foster parent–child interaction in order to promote social engagement and social development, given the characteristics and environment of particular children (Howlin et al.2009; Rogers and Vismara2008). AcknowledgmentsNB acknowledges the support of her disserta- tion committee members in carrying out the work, with appreciation to Dr. Magy Martin, Dr. Rodney Ford, and Dr. Andrea Miller. We are deeply grateful to the parents and their children who took part in this project. JH and RPH gratefully acknowledge the Foundation for Autism Research and Remediation (FARR) for grant support that enabled the authors to provide consultation to NB during her dis- sertation, coding on the DCS variables, and preparation of the man- uscript for dissemination. We also thank Fionnuala Larkin and Joanna Shepherd for their assistance with coding. 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4 Separate Papers. Write a one-page review, single spaced of each of the assigned readings. Article responses should include a description of the article itself and a reaction to the article. I will a
Diagnosis of autism spectrum disorders in 2-year-olds: a study of community practice Christina M. Corsello, 1Natacha Akshoomoff, 1,2 and Aubyn C. Stahmer 1,2 1Rady Children’s Hospital San Diego, San Diego, CA; 2University of California, San Diego, CA, USA Background: Longitudinal research studies have demonstrated that experienced clinicians using standardized assessment measures can make a reliable diagnosis of autism spectrum disorders (ASDs) in children under age 3. Limited data are available regarding the sensitivity and speci city of these measures in community settings. The aims of this study were to determine how well a standardized diagnostic observational measure (Autism Diagnostic Observation Schedule – ADOS) functions alone, and with a brief parent measure within a community setting when administered by community clinicians. Methods: Clinical records for 138 children between the ages of 24 and 36 months of age who were evaluated for possible ASD or social/language concerns at a hospital-based developmental evaluation clinic were examined. Evaluations were conducted by community-based clinical psycholo- gists. Classi cation results obtained from standardized diagnostic measures were compared with case reviewer diagnosis, by reviewers blind to scores on diagnostic measures, using The Records-based Methodology for ASD Case De nition that was developed by the Metropolitan Atlanta Developmental Disabilities Surveillance Program. Results: When compared with case review diagnosis, the ADOS demonstrated strong sensitivity and speci city for both Autism versus Not Autism and ASD versus Nonspectrum (NS) diagnoses in this young sample. The Social Communication Questionnaire (SCQ), using the lower cutoff of ‡12, had adequate sensitivity when differentiating Autism from Not Autism, but weak sensitivity when differentiating ASD from NS, missing about 80% of the children with pervasive developmental disorder – not otherwise speci ed. Using either the Modi ed Checklist for Autism in Toddlers or the SCQ in combination with the ADOS did not result in improved speci city over the ADOS alone and led to a drop in sensitivity when differentiating ASD from NS disorders. Conclusions: These results demonstrate that following best practice guidelines, the ADOS can be successfully incorporated into clinical practice with relatively good sensitivity and speci city, and worked well with a referred sample of 2-year-olds. A parent questionnaire did not lead to any improvement in diagnostic classi cation above the ADOS used in isolation. Keywords: Autism, diagnosis, services research. Introduction As awareness of the early signs of autism spectrum disorders (ASD) increases, more physicians routinely screen for the presence of the disorder and children are referred to community diagnostic clinics with suspicion of the disorder at younger ages. The American Academy of Pediatrics has suggested rou- tine screening for ASD at the 18- and 24-month well child visits (Johnson et al., 2007), which can lead to an increase in referrals for diagnosis at early ages. Several studies have found that ASD can be reliably diagnosed in children under 3 years of age by expe- rienced, highly trained clinicians in specialty clinic and research settings (Charman et al., 2005; Lord et al., 2006; Turner & Stone, 2007) and that the greatest accuracy in diagnosis of young children is achieved when using a standardized parent inter- view and a standardized observational measure in combination with clinical judgment (Corsello et al., 2007; Lord et al., 2006; Risi et al., 2006). Given the emphasis on appropriate early intervention and the expense of intensive early intervention services, diagnostic accuracy is crucial. There are relatively few standardized diagnostic measures that have demonstrated strong discrimi- native ability in young children and predictive validity over time (Lord et al., 2006). Two of the most well validated and commonly used measures in research studies are the Autism Diagnostic Observation Schedule (ADOS; Lord, Rutter, DiLavore, & Risi, 2001) and the Autism Diagnostic Interview – Revised (ADI-R; Rutter, Le Couteur, and Lord, 2003). These measures are considered the gold standard in re- search protocols and have become widely known among clinical professionals. Both are available through a US Publisher, but only the ADOS has become widely used by clinicians because the length of the ADI-R makes it dif cult to incorporate into clinical practice. In addition, studies using the ADI-R with children under 3 years of age have reported mixed results, with several reporting an under-iden- ti cation of children with ASD primarily due to less children meeting criteria on the restricted behavior area (Ventola et al., 2006; Wiggins & Robins, 2008). Although the ADOS is widely available and recom- mended as one of the appropriate standardized measures recommended in several Best Practice Guidelines as an appropriate standardized diagnostic observation tool (California Department of Develop- Con ict of interest statement: No con icts declared. Journal of Child Psychology and Psychiatry 54:2 (2013), pp 178–185 doi:10.1111/j.1469-7610.2012.02607.x 2012 The Authors. Journal of Child Psychology and Psychiatry 2012 Association for Child and Adolescent Mental Health. Published by Blackwell Publishing, 9600 Garsington Road, Oxford OX4 2DQ, UK and 350 Main St, Malden, MA 02148, USA mental Services, 2002; Filipek et al., 1999, 2000; National Research Council, 2001), little is known about the effectiveness of this measure when admin- istered by community clinicians who have not met the research training requirements and are not using the ADOS in combination with the ADI-R. The results from studies of the ADOS conducted by community- based clinicians who have achieved reliability are variable depending on clinic type and population evaluated. In an ASD speci c clinic, the ADOS dem- onstrated good sensitivity and speci city in a sample of 2- to 8-year-old children (Mazefsky & Oswald, 2006). On the other hand, the ADOS was not as spe- ci c and resulted in more false-positive ASD classi – cations in a complicated community-based general developmental clinic sample of 2- to 16-year-old children (Molloy, Murray, Akers, Mitchell, & Man- ning-Courtney, 2011). Clinicians working outside an ASD specialty clinic or research setting often have less rigorous training on standardized diagnostic measures, see a lower percentage of children with ASD, and are more likely to evaluate children who are diagnostically complex (Molloy et al., 2011). Clinic-referred samples may be more likely to include children from minority back- grounds, parents with a lower level of education, and families with more disadvantaged circumstances, all factors that have been associated with increased age of diagnosis (Mandell, Ittenbach, Levy, & Pinto- Martin, 2007; Mandell, Novak, & Zubritsky, 2005; Shattuck et al., 2009). Complicated diagnostic pre- sentations, combined with the often limited training of community clinicians on research based mea- sures, may affect measurement accuracy when used in community programs. In addition, most studies on community-based samples compare the classi – cation on the measure with clinical diagnosis that included the scores and observations from the measures. This decreases the objectivity and inde- pendence of the clinical diagnosis. The CDC has developed a method for giving a diagnosis based on a record review (Centers for Disease Control, 2007). This method allows for an outside reviewer to provide a diagnosis without scores or classi cations on measures. The ADI-R is also available, but is less commonly used in clinical practice given the dif culty of obtaining insurance funding for the lengthy inter- view. Aside from the ADI-R, there are very few diag- nostic measures based on parent report. For this reason, many clinicians constrained by funding have resorted to using screening measures as well as parent questionnaires to obtain standardized parent information to augment their clinical interview. One such screening measure, the Social Communication Questionnaire (SCQ; Rutter, Bailey, and Lord, 2003), is based on the ADI-R and is more widely utilized given its brevity. The SCQ has been demonstrated to discriminate ASD from Nonspectrum (NS) diagnoses in children under age 5 with a reduced cutoff (Cor-sello et al., 2007), but little is known about how accurate it is with children under age 3. Another screening measure, the Modi ed Checklist for Aut- ism in Toddlers (M-CHAT; Robins, Fein, Barton, & Green, 2001) is widely used in children under the age of 30 months (Kleinman et al., 2008; Pandey et al., 2008; Robins et al., 2001). Although the M- CHAT can accurately identify many children with ASD, some children without an ASD screen positive for the disorder (Pandey et al., 2008), especially when a follow-up interview is not employed, which is often the case in community clinics (Pandey et al., 2008; Robins & Dumont-Mathieu, 2006). Despite this weakness, without other options clinicians may turn to this screener when evaluating very young children referred for an ASD. Most of the evidence for making an accurate diagnosis in young children is based on studies conducted with experienced and highly trained staff in research settings. We investigated whether these results can be replicated within a community-based sample in a general developmental evaluation clinic with very young children when the clinician, in this case a clinical psychologist, has not received inten- sive training on standardized measures. This study was designed to address the following questions: (a) How well does the ADOS perform when used by community clinicians in a young community-based sample? (b) Does using a brief parent measure (M-CHAT or SCQ) in combination with the ADOS improve diagnostic accuracy in this young community sample? Method Subjects The sample consisted of 138 consecutive children between the ages of 24 and 36 months evaluated for an ASD at a children’s hospital developmental evaluation clinic, between October 2005 and August 2007. IQ was available for all but three of the children in the autism group. SCQ scores were available for 67 children, M- CHAT scores were available for 38 children (seven of these children also had the SCQ), and ADOS algorithm scores (communication + social + restricted and repet- itive + play) were available for 94 children (see Table 1). There was not a signi cant difference between diag- nostic groups in terms of age,F(2, 135) = 1.02,p= .36. There was a signi cant difference in IQ scores between diagnostic groups,F(2, 132) = 6.72,p< .01, with the Autism (AUT) group scoring signi cantly lower than both the pervasive developmental disorder – not other- wise speci ed (PDD-NOS) and Nonspectrum (NS) groups. There was not a signi cant difference in gender be- tween diagnostic groups (v 2(2) = .53). Consistent with the 4:1 male to female ratio typical of children with ASD, male subjects comprised 86% of the AUT group and 90% of the PDD-NOS group. Interestingly, there were many more male subjects (81%) than female subjects in the NS group as well. There was not a signi cant difference between diagnostic groups in doi:10.1111/j.1469-7610.2012.02607.x Diagnosis of autism spectrum disorders in 2-year-olds 179 2012 The Authors. Journal of Child Psychology and Psychiatry 2012 Association for Child and Adolescent Mental Health. terms of race, (v 2(8) = .58) with Caucasian children comprising 41% of the sample, and a much smaller percentage of African American (2%) and Asian (3%) children. Fifteen percent of the sample identi ed themselves as ‘Other’ and race remain unknown for 39% of the sample. There were a large percentage of Hispanic children included in this sample (28%), which is consistent with the Hispanic population in San Diego County. The majority of the sample was English speaking (72%). The remainder of the sample was bilingual (15%), Spanish speaking only (9%) or spoke another language (4%). Twenty three percent of the children in this study were enrolled in Medicaid. Measures The M-CHAT is a 23-item, parent completed, screening questionnaire (Robins et al., 2001), including items assessing early communication and social behaviors as well as atypical behaviors suggestive of an ASD. Each item is checked as ‘yes’ or ‘no,’ indicating abnormality depending on the question. Six of these items are identi ed as critical items. A child’s score is suggestive of a possible ASD if it includes endorsement of abnormality on any two of the six critical items or any three of the 23 total items. The M-CHAT follow-up interview was not used as part of the evaluations be- cause data was collected prior to the publication of studies indicating that speci city was improved with the interview. The M-CHAT was used as a part of the evaluation and clinical interviews were conducted with the family. The SCQ is a 40-item, parent completed, screening questionnaire, based on the initial mandatory probes from the original ADI (Le Couteur et al., 1989). It covers the areas of communication, reciprocal social interactions, and restricted and repetitive behaviorsand interests (Rutter, Bailey, et al., 2003). Each item is checked as ‘yes’ or ‘no,’ and is assigned a point rating of ‘1’ (presence of abnormal behavior) or ‘0’ (absence of abnormal behavior). The rst item is not included in the scoring, as it indicates if the child has suf cient verbal skills for language items to be scored. If the child is not scored as verbal, the six language items are skipped. The points are summed and result in a total possible score of 0–33 for nonverbal children or 0–39 for verbal children. Totals are compared to a cutoff of‡15 for ASD. A lower cutoff score of‡12 has been suggested for children under the age of 5 years (Corsello et al., 2007). There are two different versions of the SCQ: (a) a ‘current’ version designed for children under the age of 5 years and (b) a ‘lifetime’ version designed for children 5 years of age or older, with all questions based on lifetime or past behavior. Given their young age, the current version was used for the children in this study. The ADOS (Lord et al., 2001) is a standardized observational diagnostic measure. It is organized into four separate modules, based on the age and expressive language level of the child, ranging from preverbal toddlers to verbally uent adults. A child meets criteria for a classi cation of autism if the scores in the social and communication domains and the total on the algorithm meet or exceed cutoff scores. All children in this study were administered either module 1 or 2 of the ADOS. In this study, the majority of examiners had not achieved interrater reliability, although all had attended a clinical 2-day workshop on the measure. This was considered to be representative of the use of this measure in a community clinic. ADOS total algo- rithm scores (communication + social + restricted and repetitive + play) were used for data analyses. One of four developmental/cognitive measures was also administered: the Mullen Scales of Early Learning (Mullen, 1995), the Bayley Scales of Infant Development – Second Edition (BSID-II; Bayley, 1993) or Bayley Scales of Infant and Toddler Development – Third Edi- tion (Bayley-III; Bayley, 2005) or the Wechsler Preschool and Primary Scales of Intelligence – Third Edition (WPPSI-III; Wechsler, 2002). In this study, Full Scale IQ scores consisted of the Early Learning Composite from the Mullen, the Full Scale IQ score from the WPPSI-III, the Mental Development Index from the BSID-II, or the mean of the Language and Cognitive standard scores from the Bayley-III. If the child’s scores were below the lowest standard or scaled scores available, ratio IQs were calculated by taking the mean of the age equiva- lents on the measure and dividing by the child’s chro- nological age. The Records-based Methodology for ASD Case De – nition was developed by the Metropolitan Atlanta Developmental Disabilities Surveillance Program (MADDSP) of the Centers for Disease Control and Pre- vention. Records of children with possible ASD were reviewed and coded by clinicians and a determination of autism or ASD ‘caseness’ was made (Centers for Dis- ease Control, 2007). The MADDSP ASD coding scheme includes operational de nitions of each diagnostic cri- terion related to autism and each criterion is rated as present or not present in a report. These are used to determine if a case meets Diagnostic and Statistical Manual, Fourth Edition, Text Revision (DSM-IV-TR) Table 1Age, IQ score, SCQ score, and ADOS total score by clinical diagnosis Clinical diagnosis Autism (n= 56)PDD-NOS (n= 50)Nonspectrum (n= 32) Age (months)M29.77 30.58 30.50 SD3.16 3.39 2.82 Range 24–35 24–35 24–35 IQ aM63.38 73.20 76.28 SD4.18 17.58 21.76 Range 24–102 25–112 13–97 SCQ bM17.16 12.44 9.17 SD6.16 6.35 5.38 Range 3–29 3–24 1–19 ADOS bM23.74 14.08 8.25 SD3.72 6.06 6.25 Range 15–30 3–27 2–22 ADOS, autism diagnostic observation schedule; PDD-NOS, pervasive developmental disorder – not otherwise speci ed; SCQ, social communication questionnaire;SD, standard devi- ation. aSigni cant difference between autism and nonspectrum groups. bSigni cant difference between all three groups. 180 Christina M. Corsello, Natacha Akshoomoff, and Aubyn C. Stahmer J Child Psychol Psychiatry 2013; 54(2): 178–85 2012 The Authors. Journal of Child Psychology and Psychiatry 2012 Association for Child and Adolescent Mental Health. criteria for a speci c ASD diagnosis. The reviewer determines a classi cation of ASD or not based on the information included in the report. Procedure Reports were reviewed for 138 children. Permission to review these records was obtained under the approval of the University of California, San Diego and Rady Children’s Hospital Human Research Protections Pro- grams. Each child was evaluated by one of the eight clinical psychologists in the clinic. The majority of children received the ADOS, either the M-CHAT or the SCQ, and a developmental assessment using either the BSID-II (N= 42), Bayley-III (N= 67), Mullen (N= 14) or WPPSI-III (N= 3). The clinicians had all attended a 2-day training on the ADOS and had consultation from one of the authors (CC or NA) who was research reli- able on the measure. The clinicians did not attend a research workshop or achieve interrater reliability on the measure. For 11 children, a developmental test score was not available and the Adaptive Behavior Composite of the Vineland Adaptive Behavior Scales, Second Edition (Vineland; Sparrow, Cicchetti, & Balla, 2005) was used instead. Each child was given a diagnosis by the psychologist conducting the evalua- tion who then wrote a clinical report that included a summary of the assessment with developmental scores and diagnostic classi cations on the standardized measures. Written clinical reports were coded using the MAD- DSP ASD coding system. The record reviewers (CC and NA) were blind to scores on the measures and nal clinical diagnosis when coding reports, with the goal of listing diagnostic criteria met and providing a second diagnosis that was not in uenced by scores on the measures. Report reviewers rst reviewed reports pro- vided by the CDC along with coding keys and estab- lished reliability at an 80% agreement for symptoms and at a 90% level for overall diagnosis. Thirty percent of the reports were double coded and reliability was maintained at 80% or better for diagnostic criteria and at 90% or better for overall diagnosis. Design We evaluated the diagnostic validity of the measures by comparing the classi cation of the measures alone and in combination with reviewer diagnosis. The discrimi- native validity of the measures was compared alone and in combination by examining the sensitivity (the ability to accurately classify children with an autism or ASD diagnosis: True Positives/(True Positives + False Nega- tives) and speci city (the ability to accurately exclude children without an autism or ASD diagnosis: True Negatives/(True Negatives + False Positives). Compari- sons were made between children with autism (AUT) and those without autism (Not AUT: PDD-NOS and NS disorders), as well as between children with ASD (including Autism and PDD-NOS) and NS. Throughout the analyses, the groups will be referred to in these ways. Clinician and reviewer diagnoses were compared and diagnostic stability was reviewed for the subset of children who returned for a reevaluation as another check of the accuracy of the initial diagnosis. Results Diagnostic validity of standardized measures To determine the validity of the ADOS and SCQ in this community sample, the classi cations on the measures were compared with reviewer diagnosis, blinded to scores and classi cations on the mea- sures as well as clinician diagnosis, based on a review and coding of the written report. When compared with reviewer diagnosis, the ADOS dem- onstrated strong sensitivity and speci city for both AUT versus Not AUT and ASD versus NS diagnoses (see Table 2). The SCQ, using the lower cutoff of‡12 had adequate sensitivity when differentiating AUT from Not AUT, but weak sensitivity when differenti- ating ASD from NS, missing about 80% of the chil- dren with PDD-NOS. Consistent with previous studies, the M-CHAT captured the majority of the children with PDD-NOS and AUT in this 2-year-old sample, but also included 30% of the NS children. Using either the M-CHAT or the SCQ in combination with the ADOS did not result in improved speci city over the ADOS alone and led to a dramatic drop in sensitivity for the ASD versus NS group primarily because the SCQ missed so many of the children with PDD-NOS (See Figure 1). Figure 1 depicts the percentage of children meeting the cutoff scores on each measure compared with their reviewer-identi- ed diagnosis. To determine if age may have affected the diag- nostic discrimination of these two measures, the M-CHAT was evaluated for the younger age group for which it is recommended (30 months and under) and the SCQ evaluated for the children older than 30 months. When discriminating between ASD and NS in this younger group, the sensitivity (.95) and speci city (.75) improved for the M-CHAT. However, the NS sample was extremely small (N= 4). For the SCQ, neither sensitivity (.63) nor speci city (.33) improved when discriminating ASD from NS diag- noses in children over 30 months of age. Table 2Classi cation of autism (AUT) or not autism (Not AUT) and ASD or nonspectrum (NS) on screening and diagnostic measures compared to reviewer diagnosis nSensitivity Speci city AUT versus Not AUT ADOS 118 .84 .80 SCQ‡12 67 .82 .64 M-CHAT 38 .88 .33 M-CHAT or SCQ & ADOS 84 .82 .65 ASD versus NS ADOS 118 .97 .85 SCQ‡12 67 .69 .56 M-CHAT 38 .86 .67 M-CHAT or SCQ & ADOS 84 .76 .85 ADOS, autism diagnostic observation schedule; M-CHAT, modi ed checklist for autism in toddlers; SCQ, social commu- nication questionnaire. doi:10.1111/j.1469-7610.2012.02607.x Diagnosis of autism spectrum disorders in 2-year-olds 181 2012 The Authors. Journal of Child Psychology and Psychiatry 2012 Association for Child and Adolescent Mental Health. Clinician and reviewer diagnostic agreement Clinicians and reviewers agreed 80% of the time. Disagreements were primarily between PDD-NOS and AUT with reviewers more likely to classify the diagnosis AUT than clinicians (See Table 3). Encouragingly, there were no disagreements between AUT and NS disorders. That is, a reviewer never classi ed a child as NS when a clinician clas- si ed a child with AUT or vice versa. Of the ve children that the reviewer classi ed as NS and the clinician classi ed as PDD-NOS, three had received a nonspeci c ASD diagnoses from the clinician (‘Features of PDD-NOS’, ‘PDD-NOS provisional’ and ‘Rule out ASD’). Of the 19 children that were diag- nosed PDD-NOS by the clinician and AUT by the reviewer, all had a suf cient symptom count to meet criteria for a diagnosis of autism and 10 (53%) met criteria for autism on the ADOS. Diagnostic stability Diagnosis often becomes clearer as children grow older (Lord et al., 2006). Diagnosis at follow-up appointments for the small number of children who were reevaluated was reviewed and compared with initial clinical diagnosis, rather than reviewer diag- nosis, as another gauge of diagnostic accuracy. Of the 138 children included in this study, 23% or 32 children were seen for a reevaluation when they were between 35 and 101 months of age, with 72% of the children falling between 4 and 6 years of age. Sev- enteen (53%) of the children remained in the same diagnostic category. As predicted, the AUT and NS diagnoses remained the most stable, with only two shifting from autism to PDD-NOS and two shifting from NS to ASD (one to autism and one to PDD-NOS). The PDD-NOS diagnoses had the most change, with four remaining in the PDD-NOS group, ve moving to autism and ve moving to NS. All the 11 children who were initially diagnosed with AUT and later reevaluated met criteria for AUT on the ADOS when evaluated at the age of 2 years. This included the two children who moved from a clinical diagnosis of autism to PDD-NOS. All but two of the 14 children who were initially diagnosed with PDD-NOS fell within the ASD classi cation (N=8)or autism classi cation (N= 4) on the ADOS when they were initially evaluated. Of the four children who remained within the PDD-NOS group, the three who were given the ADOS fell within the ASD classi ca- tion on the measure. Of the ve children whose clinical diagnosis moved from PDD-NOS to Autism, three received an autism classi cation on the ADOS. All ve of the children who moved from PDD-NOS to NS had an ASD score on the ADOS with one falling within the classi cation of autism. This child was later diagnosed with selective mutism. Of the six children initially diagnosed as NS and later reeval- uated, only two were given the ADOS. One met cri- teria for ASD on the measure and was later diagnosed with autism, whereas the other was NS on the measure and later was diagnosed with an anxiety disorder. Discussion The ADOS worked encouragingly well in this group of young children diagnosed by experienced psycholo- gists in a general developmental clinic. Although the clinicians had not received intensive training on the measure or achieved research reliability, the ADOS demonstrated very good diagnostic discrimination when compared with a diagnosis based on a report review by an expert on ASD who was blinded to cli- nician diagnosis and scores on diagnostic measures. The group of clinicians included in this study had received a 2-day training on the measure and worked closely with clinicians who had achieved research reliability on the ADOS and were available to provide 0 10 20 30 40 50 60 70 80 90 100 Autism PDD-NOS NS Percentage of cases Reviewer diagnosis ADOS Autism ADOS ASD ADOS NS 0 10 20 30 40 50 60 70 80 90 100 Autism PDD-NOS NS Percentage of cases Reviewer diagnosis SCQ AUT SCQ NS Figure 1Reviewer diagnosis agreement with the autism diag- nostic observation schedule (top) and the social communication questionnaire (bottom) Table 3Agreement between clinical diagnosis and reviewer diagnosis Clinical diagnosisReviewer diagnosis Autism PDD-NOS Nonspectrum Autism 55 1 0 PDD-NOS 19 27 5 Nonspectrum 0 4 27 PDD-NOS, pervasive developmental disorder – not otherwise speci ed. 182 Christina M. Corsello, Natacha Akshoomoff, and Aubyn C. Stahmer J Child Psychol Psychiatry 2013; 54(2): 178–85 2012 The Authors. Journal of Child Psychology and Psychiatry 2012 Association for Child and Adolescent Mental Health. consultation and support as needed. Although this level of consultation may not be typical for commu- nity clinicians using the ADOS, this suggests that the ADOS can be an effective diagnostic tool even with very young children in a community-based clinic with experienced clinicians who receive con- sultative support. In contrast with previous studies, classi cation on the parent measure did not improve diagnostic accuracy in this young sample and the combination of the ADOS and a parent measure led to a decrease in sensitivity when differentiating ASD from NS dis- orders. The parent questionnaires used by the cli- nicians in this study were designed for screening rather than diagnostic purposes. These screening questionnaires were completed by parents of young children who may not have the experience or exper- tise to accurately rate the diagnostic behaviors these measures are targeting. This may have contributed to lack of improvement in diagnostic accuracy over the ADOS alone. Most of the longitudinal research studies used the lengthier standardized diagnostic interview, the ADI-R, rather than a parent ques- tionnaire. The ADI-R is administered and scored by experienced clinicians who have a solid under- standing of how to interpret the behaviors that they are coding. Another potential reason for the ineffec- tiveness of the M-CHAT and SCQ as diagnostic measures in this study is that neither one was de- signed to cover the entire age span between 24 and 36 months. Brief diagnostic measures that could be easily incorporated into a clinical diagnostic assessment do not exist for this age group. Although these measures did not improve the accuracy of an ASD diagnosis, the M-CHAT appeared to be effective as a screener in this sample, as the majority of ASD children were captured by this measure. This was interesting given that the major- ity of the children were older than the recommended age. It is important to note that the evaluations in- cluded in this study were conducted prior to the widespread introduction of the follow-up interview for the M-CHAT, which has led to improved speci- city (Pandey et al., 2008). The SCQ, which was designed and tested on an older sample of children initially, missed many children with PDD-NOS, indicating that it is not the best screener or diag- nostic measure in this young age group. This is similar to studies that have found that the ADI-R, on which the SCQ is based, tends to miss children in this age group (Corsello et al., 2007). More research is needed on the SCQ in younger ages, including an evaluation of subscales and items to determine if the pattern of symptoms missed parallels ndings in studies of the ADI-R. Further research may lead to an effective diagnostic and screening measure for children between 2 and 3 years of age, which is important given that this is the group most often initially identi ed and referred and that two mea- sures in combination with clinical judgment leads tothe most accurate diagnosis in 2-year-old children suspected of an ASD. Of the children who were initially evaluated, 22% were reevaluated providing an additional way of assessing diagnostic accuracy of the ADOS in this 2-year-old sample. The ADOS scores at initial eval- uation were fairly good predictors of later diagnosis. Only two children who initially were given a clinical diagnosis of autism and met criteria for autism on the measure, moved into the PDD-NOS group at follow up. The remainder continued to meet criteria for autism. The PDD-NOS group had more variability in diagnosis at follow up, which is consistent with previous studies. Although all but two of the children within this group had an ASD classi cation on the ADOS at the time of the initial evaluation, ve no longer met criteria for an ASD at follow up. The only misclassi cation of autism on the measure at initial evaluation was for a child who was later diagnosed with selective mutism. The remaining children who initially met criteria for PDD-NOS continued to meet for PDD-NOS or moved into a diagnosis of autism. Surprisingly, there was fairly good agreement between reviewer diagnoses, blind to scores on measures and clinician diagnosis, based on report review and coding and the clinician’s clinical judg- ment. This is encouraging as the MADDSP ASD coding system has been used on a broader scale in an older sample of children. The strong agreement between reviewer and clinician suggests that this surveillance methodology also shows promise in a younger sample. However, reports were all from one clinic and were carefully written, included the same measures, and generally the same level of detail leading to greater ease for the reviewer. The use of the ADOS may in uence the observations of the clinician as well as the data that they include in their report ultimately also in uencing the diagnosis of the reviewer even though they were blind to measure scores and classi cation. Diagnostic agreement may not be as easy to achieve in other situations given the variability of measures used and content of reports in the larger community. Limitations This study was based on the practices in a commu- nity clinic and report review. The stringent controls that are in place for a prospective research study were not in place in this study. Each child did not receive all three standardized diagnostic measures, limiting the conclusions that we can draw about the relationship between these measures. An attempt was made to provide a reviewer diagnosis indepen- dent of the clinician generated scores and classi – cation on diagnostic measures using a standardized record review strategy by a research clinician blind to the scores on the diagnostic measures and clini- cian diagnosis. However, the reviewer diagnosis is based on a report written by a clinician who used doi:10.1111/j.1469-7610.2012.02607.x Diagnosis of autism spectrum disorders in 2-year-olds 183 2012 The Authors. Journal of Child Psychology and Psychiatry 2012 Association for Child and Adolescent Mental Health. speci c diagnostic measures to gather information and therefore, subject to the biases of the clinician who wrote the report. In addition, follow-up evalua- tions were only available for a small subset of the sample, again limiting the conclusions that can be made in terms of predictive value of the measure. Summary Within this community-based clinic, the ADOS evi- denced good diagnostic discrimination in a 2-year- old sample when administered by clinicians who had received a 2-day clinical training followed by con- sultative support. Additional research is needed to identify or develop an appropriate ef cient parent report tool to accompany a standardized diagnostic measure, as neither the SCQ nor the M-CHAT addedto the diagnostic accuracy of the ADOS in this sample. Acknowledgements This study was supported by grants from the National Institutes of Health: K23MH071796 (to N.A.) and K01MH065325 (to A.C.S.). We also thank our research assistants, Rebecca Pin˜ on Ruiz, Jasper Estabillo, and Therese Gadomski. Correspondence Natacha Akshoomoff, Department of Psychiatry, 9500 Gilman Drive, 0115, University of California, San Diego, La Jolla, CA 92093-0115, USA; Email: nakshoom [email protected] Key points •The ADOS was effective in a 2-year-old sample in a community clinic when administered by psychologists who had received a 2-day training followed by consultation. •The use of a parent screening measure did not improve diagnostic accuracy over the ADOS alone. •Diagnosis remained stable in the majority of children who were diagnosed with autism or nonspectrum disorders and less stable in toddlers diagnosed with PDD-NOS. •There are no diagnostic parent interviews or questionnaires currently available for this age group that are easily incorporated in a clinical evaluation. References Bayley, N.. (1993).Bayley scales of infant development-second edition (BSID-II)(2nd edn). San Antonio, TX: The Psycholog- ical Corporation. Bayley, N.. 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4 Separate Papers. Write a one-page review, single spaced of each of the assigned readings. Article responses should include a description of the article itself and a reaction to the article. I will a
Effective Early Intervention: Results From the Model Preschool Program for Children with Down Syndrome and Other Developmental Delays Rebecca R. Fewell, Tulane University, and Patricia L. Oelwein, University of Washington The effectiveness of an intervention program for young children enrolled in outreach sites of the Model Preschool Program for Children with Down Syndrome and Other Developmental Delays was investigated. The rate of development during intervention was compared to the rate of develop- ment at pretest across six domains of development. Subjects were 194 chil- dren with special needs, 92 of whom had Down syndrome. Results for the total group of children and for the group of children with Down syn- drome are reported on two tests, the Classroom Assessment of Develop-mental Skills (CADS) and the Battelle Developmental Inventory (BDI). For the total group, the rate of development during intervention was significantly greater than the rate of development at pretest across all developmental domains of the CADS. This finding was true for five of the six domains when analyses were limited to children with Down syn- drome. On the BDI, results were available on 75 of the 194 children, 45 of whom had Down syndrome. Significant differences were found on six of the seven domains. When the rates of the 45 children with Down syn- drome were analyzed, significantly higher rates were found on three of the seven domains. These results support the effectiveness of one of the original model programs of the Handicapped Children’s Early Education Program. As states continue to make decisions on the implementation of Public Law 99-457, it is important that researchers and service TECSE 11(1), 56-68 (1991) © PRO-ED Inc. at FLORIDA INTERNATIONAL UNIV on June 17, 2015 tec.sagepub.com Downloaded from MODEL PRESCHOOL PROGRAM, 57 providers make available to decision makers information on what has been learned about effective models and practices for early intervention. In 1968 Congress passed the Handicapped Children’s Early Educa- tion Assistance Act, which funded 24 experimental early intervention programs to develop curricula and model programs that others might be able to replicate. These original programs were remarkably suc- cessful and have provided generations of subsequent programs with exemplary models of quality intervention. This article describes one of these original models and shares outcomes from the replication sites of this program. The Model Preschool Program (MPP) for Children with Down Syndrome and Other Developmental Delays was one of the original centers funded under the above-referenced act. The MPP began in 1971 as a program of the Experimental Education Unit, Child Develop- ment and Mental Retardation Center, at the University of Washing- ton. In the first few years the MPP focused entirely on children with Down syndrome; however, this changed quickly as it became apparent that the MPP could be used effectively with other developmentally delayed children. Four objectives guided the services of the MPP. First was the emphasis on planning and implementing specific programs to increase the children’s rate of development in six skill areas: gross and fine motor, cognition, receptive and expressive communication, and social/ self-help. A test-teach-test model using a curriculum-based assessment tool served as the core of this systematic and individualized instruc- tion (assessment, setting of goals and objectives, programming, imple- mentation, and evaluation). In all areas of instruction, children were guided through the stages of learning, including acquisition, fluency, transfer, and generalization of basic skills. A second objective required the involvement of the parents in the children’s instruction. When possible, parents attended their children’s classes, mastered the instructional strategies that were being imple- mented in the classrooms, and provided further instruction using the same developmental, academic, and behavioral management techniques that were being used successfully in the school. Decades later, parents attributed much of their child’s success to the continuity between what was happening in the program and the carryover implemented by the family. A third objective for this program was to provide a site for qual- ity training for university students and others in the field who wanted to study these principles. This objective, focusing on professional train- ing, led to the successful establishment of numerous outreach sites of at FLORIDA INTERNATIONAL UNIV on June 17, 2015 tec.sagepub.com Downloaded from 58, TOPICS IIM EARLY CHILDHOOD SPECIAL EDUCATION 11:1 the MPP throughout the United States and in many foreign countries. The replication of this project was the fourth objective of this program. In 1975 the MPP became one of the first early intervention pro- grams for young children with disabilities to be validated by the Joint Dissemination and Review Panel, now known as the Program Effec- tiveness Panel. As more sites asked to replicate the MPP, the developers found that the program could be successfully implemented with chil- dren and in sites that differed considerably from those served in the original model. The MPP was implemented in large and small schools, with children from birth through age 12, in programs that were self- contained and integrated (see Fewell &C Oelwein, 1990), in classes that had different child-to-teacher ratios, in urban and rural settings, with certified, advanced degree teachers and paraprofessionals, in public and private sites, and in programs that varied in the length of time in instruction, number of days of instruction, and length of the academic school year. What did not differ were the standards of implementation required of all sites if they were to be named as a cer- tified outreach site. Staff in all of these sites had to master the cur- riculum and the implementation of the MPP. They were evaluated through on-site observations by trainers from the MPP. Outreach sites that successfully met program standards, and continued the model program activities for at least 2 years, could apply to be “turnkey” sites and train others in the model. This plan, which took a program developed in the far northwest corner of the United States and expanded it throughout the country, proved to be successful and cost-effective. In this article, we report developmental outcomes of children in the United States who participated in outreach sites of the MPP pro- gram. This study was part of a larger study investigating the impact of this program on children with disabilities in outreach sites through- out the world. We addressed three problems that have been cited as concerns in previous early intervention studies (Dunst &C Rheingrover, 1981; Oelwein, Fewell, & Pruess, 1985; Odom & Fewell, 1983; Smith, 1986). First, the same intervention program was provided to a large sample of young children with disabilities. Second, sites were located in many different states, yet all were certified and monitored. Third, a sample of 75 of the 194 children were assessed on a nation- ally standardized test that included the domains of the curriculum- based assessment measure, the results of which could be used to provide the validation of the outcomes of the curriculum-based measure. at FLORIDA INTERNATIONAL UNIV on June 17, 2015 tec.sagepub.com Downloaded from MODEL PRESCHOOL PROGRAM, 59 Method Subjects Subjects for this study were 194 children with disabilities, all enrolled in outreach sites of the MPP. Ninety-two of the children had Down syndrome. The major handicapping conditions of the other chil- dren in this study were mental retardation from causes other than Down syndrome, severe communication disorders, behavior disorders, neurological impairments, orthopedic handicaps, and multiple handi- caps. In the total group were 115 males and 79 females whose mean chronological age at posttest was 63 months, with a range of 8 to 144 months. In the group of children with Down syndrome were 47 males and 45 females with a mean age of 57 months and a range of 8 to 144 months. Intervention Sites All of the subjects in this study were served in sites that had offi- cially adopted the MPP. Information about the 14 sites represented in this study is reported in Table 1. Sites differed in the number of weeks or months of intervention, the number of days during each week of intervention, and the length of day in which the model was imple-mented. The sites also differed in the total number of minutes that children were placed in settings with peers without known disabili- ties. In a recent article (Fewell & Oelwein, 1990), we reported that the time (average number of minutes per week) of integration in the classrooms was not a factor strong enough to account for significant differences in the intervention rates of development of the students. Instrument Staff at all sites were provided training on the assessment mea- sure used in this program, the Classroom Assessment of Development Skills (CADS) (Oelwein, Fewell, & Pruess, 1988), or on the earlier /ersion of the test. The CADS was a new version of the Developmen- :al Sequence Performance Inventory (Oelwein, Fewell, & Pruess, at FLORIDA INTERNATIONAL UNIV on June 17, 2015 tec.sagepub.com Downloaded from 60, TOPICS IN EARLY CHILDHOOD SPECIAL EDUCATION 11:1 Table 1. Sites and School Characteristics City, state Coral Gables, FL Chehalis, WA Sumner, WA Vancouver, WA Columbus, GA Fayetteville, GA King wood, TX Gering, NE Alcorn, MS Naches, WA Grandview, WA Eureka, CA Ada, OK Santa Cruz, CA Note. S = suburban location; center. n 34 22 29 11 17 19 8 5 6 3 8 9 16 7 R = rural location; Geographic area S R R S S R S R R R R R R S P = private school; PS = = public school; DC School type P PS DC DC P/PS DC P PS PS PS PS PS PS PS = developmental 1984), a test that had been used in the earlier phases of the MPP. There were no administrative differences in the two instruments; however, all changes were explained to staff at the sites. The CADS is a curriculum-based assessment that includes six developmental domains (gross and fine motor, cognitive, receptive and expressive communication, social/self-help) and covers the age range from birth to 8 years. The test includes 288 items of equal weight spread over seven developmental levels. Two scores, a Developmen- tal Age Score and a Developmental Quotient Score, are obtained for each of the six developmental domains. The CADS serves as an assess- ment tool and as a basis for identifying objectives for instruction. Once students attain objectives, subsequent objectives are set from the CADS. During the development of the CADS, several investigations were conducted. The CADS was field tested in outreach sites in 1985-86, revised in the summer of 1986, and used to measure program effective- ness for the 1986-87 school year. Correlations between the subtests of the CADS and the subtests of the Battelle Developmental Inven- tory (BDI) (Newborg, Stock, Wnek, Guidubaldi, & Svinicki, 1984) ranged from .80 (personal-social/self-help) to .92 (cognitive), and were highly significant. Procedure All subjects were tested in September or when they entered the program, and again in May, June, or September or when they exited at FLORIDA INTERNATIONAL UNIV on June 17, 2015 tec.sagepub.com Downloaded from MODEL PRESCHOOL PROGRAM, 61 the program, if prior to the scheduled posttesting period. The minimum time between testing for all subjects was 3 months and the maximum time was 13 months. The average time between pre- and posttesting was 9 months. In addition to the CADS, staff at five sites (Coral Gables, Colum- bus, Fayetteville, Kingwood, and Santa Cruz) administered the BDI. The BDI battery includes the following domains: personal-social, adap- tive, motor (gross and fine), communication (reception and expres- sion), and cognition. The entire battery takes about IV2 to 2 hours. It is recognized as one of the most frequently given tests in the field today, largely because of the wide age span it covers (birth to 8 years) and because the test covers all domains central to intervention pro- grams (Mott et al., 1986). Data Analysis Data gathered on the CADS and on the BDI were analyzed accord- ing to the procedure recommended by Snyder-McLean (1987) for reporting norm-referenced program evaluation data. After reviewing several widely used procedures, Snyder-McLean recommended a simple procedure comparing a pretest Developmental Quotient with an Inter- vention Developmental Quotient. In this three-step procedure, the rate of development a child demonstrates during intervention (IR) is cal- culated by subtracting the child’s Developmental Age (DA) at pretest- ing from age at posttesting and then dividing that difference by the months in intervention. The final step is to test whether significant differences exist between the IR and the developmental rate at pretest (DRP). A series of t tests were used to test these differences across the six domains of the CADS and seven domains of the BDI. Results The results are presented for the total group on the CADS and the BDI and for the group of children with Down syndrome on the same two measures. Table 2 presents the mean IRs, DRPs, differences between IRs and DRPs, standard deviations, and t and p values for the total group. IRs were significantly higher than DRPs in every domain of the CADS. at FLORIDA INTERNATIONAL UNIV on June 17, 2015 tec.sagepub.com Downloaded from 52, TOPICS IN EARLY CHILDHOOD SPECIAL EDUCATION 11:1 fable 2. Difference Between Intervention Rate and Developmental Rate at Pretest on CADS Domains All subjects Domain Gross motor Fine motor Cognitive Communication (receptive) Communication (expressive) Social/self-help n 175 194 193 186 187 191 Mean IR .92 1.09 1.23 1.12 1.11 1.11 SD .733 .847 .733 .789 .837 .844 Mean DRP .66 .67 .68 .64 .54 .68 SD .252 .264 .269 .266 .275 .253 Difference IR/DRP .26 .42 .55 .48 .56 .43 f 4.76 7.07 9.78 8.11 8.93 7.01 P .000 .000 .000 .000 .000 .000 Note. CADS = Classroom Assessment of Developmental Skills; IR = intervention rate; DRP = developmental rate at pretest. Males = 115; females = 79. Mean age at posttest = 63 mos.; range = 8 to 144 mos. Mean interval, pre- to posttest = 9 mos.; range = 3 to 13 mos. BDI results for the total group [n = 75) are reported in Table 3. Significantly different scores were found in six of the seven develop- mental domains. The IR for gross motor development was higher than the DRP; however, this difference failed to reach an acceptable level of significance. Table 4 presents for the Down syndrome subgroup the same information as presented in Table 2. In five of the six domains of the CADS, IRs were significantly higher than DRPs. In the area of gross motor development, the IRs were not significantly different from DRPs. Table 5 presents the results on the BDI for the children with Down syndrome. There were significant differences between the IRs and the DRPs on three (cognitive, personal-social, and adaptive) of the seven tests. On the remaining four tests, there were no signifi- cant differences between the two rates. Discussion The purpose of this study was to investigate the effectiveness of the model program in increasing the mean rates of developmental skill acquisition in young children with disabilities. Two additional objec- tives were important in this study: (1) to investigate the use of a new edition of the model program’s earlier test and curriculum, and (2) to determine whether program effectiveness would be reflected in a nation- ally standardized test of early child development. at FLORIDA INTERNATIONAL UNIV on June 17, 2015 tec.sagepub.com Downloaded from MODEL PRESCHOOL PROGRAM, 63 Table 3. Difference Between Intervention Rate and Developmental Rate on BDI Domains All subjects Domain Gross motor Fine motor Cognitive Communication (receptive) Communication (expressive) Personal/social Adaptive n 75 75 75 75 75 75 75 Mean IR .74 .92 .82 .72 .70 .98 .94 SD .966 1.279 .616 .907 .972 .903 .768 Mean DRP .54 .57 .49 .43 .44 .44 .41 SD .164 .190 .207 .220 .194 .222 .205 Difference IR/DRP .20 .35 .33 .29 .26 .54 .54 t 1.70 2.28 4.42 2.54 2.32 5.01 5.81 P .093 .025 .000 .013 .023 .000 .000 Note. BDI = Battelle Developmental Inventory; IR = intervention rate; DRP = developmental rate at pretest. Males = 48; females = 27. Mean age at posttest = 54 mos.; range = 8 to 117 mos. Mean interval, pre- to posttest = 9 mos.; range = 4 to 13 mos. Table 4. Difference Between Intervention Rate and Developmental Rate at Pretest on CADS Domains Down syndrome subjects Domain Gross motor Fine motor Cognitive Communication (receptive) Communication (expressive) Social/self-help n 88 92 92 88 89 90 Mean IR .75 .98 .94 .99 .83 .94 SD .615 .784 .516 .811 .600 .760 Mean DRP .68 .71 .74 .68 .56 .72 SD .229 .247 .262 .210 .220 .212 Difference IR/DRP .06 .27 .21 .31 .28 .22 f .98 3.33 3.30 3.37 3.84 2.76 P .330 .001 .001 .001 .000 .007 Note. CADS = Classroom Assessment of Developmental Skills; IR = intervention rate; DRP = developmental rate at pretest. Males = 47; females = 45. Mean age at posttest = 57 mos.; range = 8 to 144 mos. Mean interval, pre- to posttest = 9 mos.; range = 3 to 13 mos. The results of this study provided evidence that rates of develop- ment in young children with disabilities were significantly higher during intervention than when the children entered the program. These find- ings were true for all subtests of the CADS, and on six of the seven subtests of the nationally standardized test, the BDI. When the analysis was limited to children with Down syndrome, effects were more mixed. Significantly higher rates of development were found during interven- tion on five of the six subtests of the CADS and on three of the seven subtests of the BDI. at FLORIDA INTERNATIONAL UNIV on June 17, 2015 tec.sagepub.com Downloaded from 64, TOPICS IN EARLY CHILDHOOD SPECIAL EDUCATION 11:1 Table 5. Difference Between Intervention Rate and Developmental Rate at Pretest on BDI Domains Down syndrome subjects Domain Gross motor Fine motor Cognitive Communication (receptive) Communication (expressive) Personal/social Adaptive n 45 45 45 45 45 45 45 Mean IR .73 .66 .63 .48 .39 .93 .79 SD .937 .603 .605 .760 .700 .801 .737 Mean DRP .52 .54 .43 .39 .42 .40 .36 SD .134 .169 .207 .191 .160 .232 .200 Difference IR/DRP .21 .12 .20 .08 -.03 .53 .43 t 1.47 1.21 1.99 .64 -.29 4.31 3.72 P .148 .232 .053 .523 .777 .000 .001 Note. BDI = Battelle Developmental Inventory; IR = intervention rate; DRP = developmental rate at pretest. Males = 28; females = 17. Mean age at posttest = 55 mos.; range = 8 to 106 mos. Mean interval, pre- to posttest = 9 mos.; range = 4 to 13 mos. It is interesting to note the areas of development in the children with Down syndrome in which developmental rates during interven- tion failed to be significantly different from rates at program entry. No significant difference was found in the two motor domains or the two language domains. A number of authors have suggested that these two domains may be particularly problematic for children with Down syndrome (Cunningham, 1987; Hanson, 1988; Share &c French, 1982). In the domain of motor development, the norms for children with Down syndrome have been reported in two key sources. Cunningham (1987) reported on the age at which developmental milestones were accomplished in children who were provided home intervention dur- ing their early years. For example, consider the following reported milestones: standing alone (18 months for children with Down syn- drome versus 11 months for normally developing children); walking alone (23 months versus 12 months); and walking down steps with help (36 months versus 17 months). Likewise, Share and French (1982) reported that some skills emerge considerably later in children with Down syndrome (walking upstairs with one hand held at 55 months versus 18 months), yet other skills were less delayed (jumping from a bottom stair at 54 months versus 36 months; riding a tricycle at 60 months versus 36 months). These delays suggest that children with Down syndrome are developing their motor skills at about one-half at FLORIDA INTERNATIONAL UNIV on June 17, 2015 tec.sagepub.com Downloaded from MODEL PRESCHOOL PROGRAM, 65 the rate of nonhandicapped children. Even though on both measures of gross motor development used in this study (CADS and BDI) the mean rates of development improved during the course of interven- tion, it may be that the length of time in the intervention was simply too short to have an impact on skills that are less responsive to instruc- tional change. These results are consistent with our previous report that gains in the gross and fine motor development of children with Down syndrome failed to reach an acceptable level of significance (Oelwein et al., 1985). In the area of communication development of children with Down syndrome, significant gains were reported on the CADS but not on the BDI. In expressive language on the BDI, the mean rate of develop- ment during intervention actually decreased from the rate at pretest. It has been reported frequently in the literature that children with Down syndrome have significant delays, as well as qualitative differences, in expressive communication (Sandall, 1988; Smith & Oiler, 1981; Stoel-Gammon, 1980). Perhaps this is attributable to the fact that non- verbal communication skills are assessed at earlier ages, and children with Down syndrome acquire and use these skills at ages and in ways that are more consistent with normally developing peers. As children age, tests require language skills that involve the acquisition and use of symbolic representations—skills that may develop more slowly in children with Down syndrome. The intervention program was effec- tive in teaching early language skills that had been derived from objec- tives taken from the CADS, but it was difficult for children with Down syndrome to demonstrate these skills on the BDI, particularly when test items required the use of symbols. Another possible explanation for the differences in the area of communication deserves further consideration. The two tests differ on the total number of items in domains and age ranges. This is par- ticularly true in the communication sections, with the CADS includ- ing considerably more items than the BDI. The impact of this is that children have more opportunities to demonstrate possible gains. A fur- ther difference between the two tests relates to their purpose. The CADS is the basis for the curriculum; thus, test items are designed to serve as goals and objectives for instruction. This is not the case with the BDI. It is expected that students will demonstrate greater gains when a test-teach-test model serves as the basis for instruction. The finding that results on an independent measure (the BDI) support the results of the CADS strengthens the possibility that the instructional at FLORIDA INTERNATIONAL UNIV on June 17, 2015 tec.sagepub.com Downloaded from 66, TOPICS IN EARLY CHILDHOOD SPECIAL EDUCATION 11:1 model program has a positive effect on children with special learning needs. It is clear that further investigation is needed on this subsec- tion of the CADS. There are other aspects of this study that convey information about the impact of intervention and about the role of measurement. The results reported here are particularly encouraging, given the type of statistical analysis used. In this study we used a developmental rate to measure change. In a number of studies that have used this method, which is equivalent to achieving change in developmental quotient scores, studies have reported disappointing results (Bailey & Bricker, 1985; Holmes, Britain, Simpson, & Hassanein, 1987). In the Holmes et al. (1987) study, the intervention rates of children with Down syn- drome decreased dramatically, from a mean of 90 to a mean of 73 during the intervention period. Although the population of that group was younger than that reported in this study, Holmes et al. reported that chronological age accounted for only 3.2% of the variance when entered into the regression equation. It is important to examine some of the characteristics of the MPP that might point to traits of effective programs. The model was well grounded in an approach to instruction that included the use of a devel-opmental curriculum, sequenced in all domains of development, that was taught through a test-then-teach model using systematic, individ-ualized instruction. Data were taken frequently, and pre- and post- test scores were shared with the model site. Parents were central to the implementation, and all staff were trained in the model and moni- tored in their adherence to the basic principles. Sites were allowed flex- ibility in the size of classes, age of students, and frequency, intensity, and duration of instruction. Whether states select this model or other models for implementation, they may want to be aware of these key elements in making decisions for future programs. The knowledge that this particular model has been tested in many sites and over several years using a number of dependent measures, and has repeatedly been found to be effective, adds support for its efficacy (Oelwein et al., 1985). Finally, a few points of caution need to be raised. First, this study is not a true experimental design, as there were no control or contrast groups or random assignment to groups. This kind of design would help answer questions as to whether this particular model program is more effective than a contrasting program. All that can be said is that the children’s developmental rates during the program were sig- nificantly higher than when they entered the program. Second, the at FLORIDA INTERNATIONAL UNIV on June 17, 2015 tec.sagepub.com Downloaded from MODEL PRESCHOOL PROGRAM, 67 investigators were not able to separate completely the test examiners from those responsible for conducting the intervention. Both psychol- ogists and teachers participated in the administration of these tests. Although data were reported directly to the study investigators, there were some instances in which teachers had knowledge of pretest results. While this is not a good practice in research, it is consistent with the instructional model advocated by this program. Specifically, teachers are encouraged to teach those skills in which the children fail to demon- strate competency. This was done on the CADS but not on the BDI. Third, the length of this intervention and the actual time in instruc- tion can be factors that influence outcomes. This was not examined in the study, but should be examined in future research. In conclusion, despite the weaknesses described, the study pro- vides additional support for the effectiveness of this instructional model. This study, with its population of 194 subjects, including a subgroup of 92 subjects with Down syndrome, is one of the largest multisite studies of children with special needs to receive a single, validated early intervention program. These results add support to the theoretical basis of P.L. 99-457 and the movement to invest more resources in the edu- cation of young children with handicaps and their families. References Bailey, E.J., & Bricker, D. (1985). Evaluation of a three-year early intervention demonstration project. Topics in Early Childhood Special Education, 5(2), 52-65. Cunningham, C. (1987). Down’s syndrome: An introduction for parents. London: Souvenir Press. Dunst, C, & Rheingrover, R. (1981). An analysis of the efficacy of infant interven- tion programs with organically handicapped children. Evaluation and Program Planning, 4, 287-323. Fewell, R.R., & Oelwein, P.L. (1990). The relationship between time in integrated environments and developmental gains in young children with special needs. Topics in Early Childhood Special Education, 10(2), 104-116. Hanson, M.J. (1988). Effects of gross-motor activities on development. In V. Dmitriev &c P.L. Oelwein (Eds.), Advances in Down syndrome (pp. 167-173). Seattle: Special Child Publications. Holmes, G.E., Britain, L.A., Simpson, R.L., & Hassanein, R.S. (1987). Develop- mental progress of five groups of disabled children attending an early interven- tion program. Physical and Occupational Therapy in the Pediatrics, 71(1), 3-18. Mott, S.E., Fewell, R.R., Lewis, M., Meisels, S.J., Shonkoff, J.P., & Simeonsson, R.J. (1986). Methods for assessing child and family outcomes in early childhood special education programs. Topics in Early Childhood Special Education, 6(2), 1-15. at FLORIDA INTERNATIONAL UNIV on June 17, 2015 tec.sagepub.com Downloaded from 68, TOPICS IN EARLY CHILDHOOD SPECIAL EDUCATION 11:1 Newborg, J., Stock, J.R., Wnek, L., Guidubaldi, J., & Svinicki, J. (1984). Battelle developmental inventory. Allen, TX: DLM. Odom, S., & Fewell, R.F. (1983). Program evaluation in early childhood special education: A meta-evaluation. Educational Evaluation and Policy Analysis, 6(4), 445-460. Oelwein, P.L., Fewell, R.R., & Pruess, J.B. (1984). Developmental sequence per- formance inventory. Unpublished manuscript, University of Washington, Seattle. Oelwein, P.L., Fewell, R.R., &c Pruess, J.B. (1985). The efficacy of intervention at outreach sites of the Program for Children with Down syndrome and Other Devel- opmental Delays. Topics in Early Childhood Special Education, 5(2), 78-87. Oelwein, P.L., Fewell, R.R., & Pruess, J.B. (1988). Classroom assessment of devel- opmental skills. Unpublished manuscript, University of Washington, Seattle. Sandall, S.R. (1988). Parent-child interaction: Learning to take turns. In V. Dmitriev &c P.L. Oelwein (Eds.), Advances in Down syndrome (pp. 261-269). Seattle: Special Child Publications. Share, J., & French, R. (Eds.). (1982). Motor development of Down syndrome chil- dren: Birth to six years. (Available from J.B. Share, 13546 Riverside Dr., Sherman Oaks, CA 91423) Smith, N.L. (1986). Evaluation alternatives for early intervention programs. In L. Bickman 8t D.L. Weatherford (Eds.), Evaluating early intervention programs for severely handicapped children and their families (pp. 185-207). Austin, TX: PRO-ED. Smith, B.L., 8c Oiler, D.K. (1981). A comparative study of premeaningful vocaliza- tions produced by normally developing and Down syndrome infants. Journal of Speech and Hearing Disorders, 46, 46-51. Snyder-McLean, L. (1987). Reporting norm-referenced program evaluation data: Some considerations. Journal of the Division of Early Childhood, 11, 254-264. Stoel-Gammon, C. (1980). Phonological analysis of four Down’s syndrome children. Applied Psycholinguistics, 1, 31-48. at FLORIDA INTERNATIONAL UNIV on June 17, 2015 tec.sagepub.com Downloaded from
4 Separate Papers. Write a one-page review, single spaced of each of the assigned readings. Article responses should include a description of the article itself and a reaction to the article. I will a
The Interpretative Conference: Sharing a Diagnosis of Autism with Families Michal S. Nissenbaum, Nona Tollefson, and R. Matthew Reese With the recent reauthorizations of Public Law 94-142, there has been a greater push to identify and treat children with autism. As a result, autism is currently diagnosed and treated at younger ages, and nonmedical professionals who work with young children increasingly face the task of informing parents that their child has autism. To examine professionals’ and parents’ perceptions of giving and receiving a diagnosis of autism, 11 nonmedical professionals and 17 parents of children with autism participated in a series of interviews that were transcribed, unitized, and categorized using Lincoln and Guba’s (1985) method of naturalistic inquiry. Based on the interview data, nine recom- mendations for practice were developed. The recommendations provide guidelines that nonmedical professionals can consult when faced with the task of sharing a diagnosis of autism. utism is classified as a Pervasive Developmental Disorder (PDD) .JL in the Diagnostic and Statisti- cal Manual of Mental Disorders-Fourth Edition (DSM-IV; American Psychiatric Association, 1994). Pervasive Develop- mental Disorders are characterized by impaired and deviant social and commu- nication skills, as well as stereotypical behaviors and restricted interests that manifest prior to 3 years of age (APA, 1994). Autism is frequently considered a &dquospectrum&dquo disorder (Wing, 1996) in that the manifestation of symptoms can range from severe to mild. Similarly, autism affects children with a range of cognitive, social, and communication abilities (Tanguay, 2000). According to the DSM-IV, Pervasive Developmental Disorders include Autis- tic Disorder, Rett’s Disorder, Childhood Disintegrative Disorder, Asperger’s Dis- order, and Pervasive Developmental Dis- order Not Otherwise Specified (PDD NOS). For the remainder of this article, the generic term of autism is used to de- scribe individuals who demonstrate char- acteristics of any of the pervasive devel- opmental disorders. The cause of autism is not clearly un- derstood. The current literature supports the biological basis for autism (Burger & Warren, 1998; Cook, 1998; Kontantar- eas & Homatidis, 1999); however, there are no tests to measure the biological markers of autism at this time. Therefore, professionals must rely on observations of behavior over a period of time (Lord & Risi, 1998). Currently, measures are available to observe and assess character- istics of autism, and many of these mea- sures focus specifically on atypical behav- iors associated with autism, as well as the child’s ability to use social and commu- nication skills. The literature suggests that most cases of autism can be reliably diagnosed between the ages of 3 and 5 years (Filipek et al., 1999; Lord & Rossi, 1998). With the increase in the number of children being diagnosed with autism, the literature on treatments and inter- ventions to assist children and their fam- ilies has also increased (Campbell, Schop- ler, Cueva, & Hallin, 1996; Gresham, Beebe-Frankenberger, & MacMillian, 1999; Howlin, 1998; Rogers, 1998). However, literature focused on inform- ing parents that their child has autism is limited. Literature on collaboration, parent- professional relationships, and partnerships offers various models that professionals can use to conference and collaborate with families (Dunst, Trivette, & Deal, 1988; Fine & Gardner, 1994; Fine & Simpson, 2000; Turnbull & Turnbull, 1997; Wise, 1995). These process-oriented models, written for school personnel such as teachers and school psychologists, pro- vide guidelines for working collabora- tively with families over an extended pe- riod of time. However, the assessment and interpretative conference for a diag- nosis of autism frequently occurs in a fi- nite amount of time. In these cases, pro- fessionals do not have the luxury of frequent and repeated visits with the fam- ily. Instead, the assessment occurs over a few days in a clinic setting with an inter- pretative conference scheduled soon af- terward. The majority of literature examining the interpretative conference is directed toward physicians who diagnose specific disabilities, such as Down syndrome (Cunningham, Morgan, & McGuckin, 1984; Pueschel, 1985; Sharp, Strauss, & Lorch, 1992), physical disabilities (Turner & Sloper, 1992), cystic fibrosis (jedlicka- Kohler, Gotz, & Eichler, 1996; Quittner, DiGirolamo, Michel, & Eigen, 1992), cancer (Greenberg et al., 1984), and chronic illness (Myers, 1983). These dis- at FLORIDA INTERNATIONAL UNIV on June 16, 2015 foa.sagepub.com Downloaded from 31 abilities often present with clear biologi- cal markers. This body of literature dis- cusses how the diagnosis could be shared with families around the time of birth but does not consider how parents and pro- fessionals felt about diagnosis and treat- ment suggestions offered during the early childhood years. Furthermore, there is limited information on how nonmed- ical professionals, such as educators and psychologists, should inform families that their child has a disability such as autism. Although many of the recom- mendations described in the medical lit- erature may be applicable to nonmedical professionals, these professionals have rarely been considered in most of the studies. Shea (1993) wrote one of the few ar- ticles about giving a diagnosis of autism to parents. She offers suggestions for the interpretative conference that include setting goals for the conference, stating the diagnosis, and allowing families to react emotionally to the diagnosis. Shea also emphasizes the importance of the physical setting, the use of language, and a discussion of the child’s future. How- Table 1 Information on Professional Participants Table 2 Information on Parent Participants Note. Participants 10 and 11 are spouses. Participants 12 and 13 are spouses. ever, her chapter does not consider par- ents’ and professionals’ perceptions of how the interpretative conference was conducted. The present study examined families’ and professionals’ perceptions of the in- terpretative conference that informed parents their child has autism. Both fam- ily members and professionals reported their perceptions of autism and discussed their reactions to giving and receiving the diagnosis. Based on this information, recommendations for the interpretative conference are offered. Method Participants Twenty-eight participants were inter- viewed for this study: 11 professionals who have diagnosed autism and 17 par- ents of children with autism. Professionals. Eleven professionals from a medical center and a preschool were interviewed. The medical center was located in a large midwestern city (a Center for Excellence in Developmental Disabilities Education Research and Ser- vice), and the preschool was located in a smaller midwestern city (affiliated with the local public school district’s Early Childhood Special Education Program). In both settings, transdisciplinary or in- terdisciplinary teams offer assessments and provide a variety of diagnoses, in- cluding autism. Table 1 provides demo- graphic information for the sample of 11 I professionals. Families. Table 2 provides demo- graphic information for the 17 family members. The majority of the partici- pants were from affluent White families residing in one of the wealthiest counties in the country. Most participants worked outside of the home and had at least a college education. Although one partici- pant was a single mother, a majority of the participants interviewed were mar- ried. Two of the 15 mothers interviewed were the wives of the two fathers who participated in the study. Most family at FLORIDA INTERNATIONAL UNIV on June 16, 2015 foa.sagepub.com Downloaded from 32 members had a biological child between 2 and 5 years of age who had received a diagnosis of autism, Asperger syndrome, or PDD NOS within the past year. Diag- noses were obtained from various set- tings across the country and were not limited to the areas served by the profes- sionals who were interviewed. Two par- ents (both mothers) did not complete the study. One mother moved and did not leave a forwarding address or phone number. The second mother indicated that she no longer chose to participate in the study due to time constraints. In- formation obtained from their first round of interviews was included in the data analysis. Procedure Recruitment of Participants. Pro- fessionals were individually approached by the first author in the work environ- ment and given an overview of the study. Professionals were asked to participate if they had experience diagnosing autism or other pervasive developmental disorders and if they were not physicians. All 11 professionals approached agreed to participate, and a time was set for the first interview. Two approaches were used to recruit family members. A letter describing the study was sent by the medical center to 60 families of children who had recently received a diagnosis of autism or another pervasive developmental disorder. Only two parents agreed to participate using this method of recruitment. The first au- thor recruited 15 family members by at- tending local parent support groups for families who have children with autism. An overview of the study was presented to the parent support groups. Parents who were interested in participating and had a child who had recently received a diagnosis of autism or another pervasive developmental disorder provided their names and telephone numbers on a sign- up sheet. The researcher then called all individuals who volunteered to partici- pate, answered any questions regarding the study, and set a meeting for the first interview. Reports and records were not collected regarding the child’s diagnosis of autism. Parent report and the first au- thor’s clinical judgment of autism were used instead.. , =- Data Collection. Collection of the data was organized into three phases based on Lincoln and Guba’s (1985) method of naturalistic inquiry. During Site Visit 1 (SV-1), the primary objective was to conduct unstructured interviews with the participants. Questions for Pro- fessional SV-1 were developed based on recurring themes in the literature. Pro- fessionals in the field and family members of children with autism reviewed the questions for relevancy. Questions for Parent SV-1 were based on themes in the literature and information obtained dur- ing Professional SV-1, and they were subjected to a review by professionals and family members. Site Visits 2 (SV-2) and 3 (SV-3) were conducted in order to obtain more specific information and to clarify information obtained in the previ- ous interview(s). Professionals partici- pated in three rounds of interviews and parents completed two rounds of inter- views. The sequence of interviews was as follows: Professional SV-1, Parent SV-1, Professional SV-2, Parent SV-2, Profes- sional SV-3. Most interviews with the professionals were conducted at the medical center or the school site. A few interviews were conducted in the professionals’ homes, and one was conducted at a neutral loca- tion due to scheduling difficulties. All family interviews were conducted at the participants’ homes. Interviews were recorded and lasted between 30 and 60 minutes. Prior to the first interview, professionals and families signed consent forms. To ensure confidentiality, all par- ticipants were assigned a code number that was written on the audiotape and on any notes taken during the interview. In- terviews were transcribed and unitized using word processing software. Approx- imately half of the interviews were tran- scribed by the first author, and the re- maining interviews were transcribed by a professional transcriptionist. When the transcriptionist returned the interviews, the first author reviewed them for accuracy. Data Analysis. The first author con- tinuously analyzed the data using Lin- coln and Guba’s (1985) method of nat- uralistic inquiry. Data analysis followed each round of interviews. Initially, inter- views were reduced to individual units of information that represented single ideas or thoughts. Units of information were assigned individual codes based on the following guidelines: a-b-c (a = phase of the study, b = person interviewed, c = in- dividual idea or thought from the inter- view ; see the Appendix). Each unit of information was then placed into a cate- gory that contained other units of simi- lar information. Definitions describing the characteristics of the units placed in that category were developed. Categor- ies were further refined and/or altered based on information obtained in subse- quent interviews. Collapsing the data into categories was a dynamic process. At least three units of similar information from different sources provided triangulation for data included in each category. Tri- angulation helped ensure reliability of data and information. Other means of ensuring reliability in- cluded a methodological log and a mem- ber check. The methodological log doc- umented the date of the methodological change and an explanation of the reason the change was made. A five-person member check was conducted. Partici- pants from the study included one mother, one professional from the school setting, and one professional from the medical center. The remaining two par- ticipants had experience sharing a diag- nosis of autism with families but did not &dquo participate in the study. Member check participants were selected by the re- searcher based on their willingness and availability to participate in the member check activity. The first author furnished the member check participants with copies of the categorization system, the interpretation of the interviews, and the list of recommended practices. Member check participants were asked to inde- pendently review the documents and provide the first author with feedback within 2 weeks. Comments provided by the member check participants were in- corporated into the final drafts of the in- at FLORIDA INTERNATIONAL UNIV on June 16, 2015 foa.sagepub.com Downloaded from 33 terpretation and the list of recommenda- tions for practice. Resu Its The 65 interviews with participants yielded 2,260 units of information that were combined into seven categories and subcategories. Table 3 provides the fre- quency of responses for each of the seven categories. Family stories and miscella- neous comments are not discussed in this article. Perceptions of the Definition and Outcomes of Autism Professionals described autism as a con- troversial disability’ that has a social stigma associated with it.2 Even though it is becoming more widely known,3 pro- fessionals still described autism as a &dquotouchy label,&dquo4 a &dquosensitive subject,&dquo5 and a &dquoheavy-duty diagnosis.&dquo6 Profes- sionals described characteristics of autism as variable7 and encompassing numerous areas of development, such as language skills,8 motor skills,9 social skills,io sen- sory modulation and learning difficul- ties.l2 Many parents described autism as a &dquodeath sentence&dquo13 or &dquolifelong sen- tence.&dquo14 Prior to receiving the diagno- sis, parents reported having an inaccurate understanding of the characteristics asso- ciated with autism.15 In fact, some par- ents thought that all people with autism were like the character in the movie Rain Man.16 Prior to the diagnosis, many parents suspected something different or unusual about their child However, only a few parents suspected that their child had autism. 18 Most had never heard of autism, and as a result, they did not sus- pect that their child had the disorder.19 Table 3 Frequency of Responses in Categories * ’ . Some parents made excuses for the un- usual behaviors, such as their child’s &dquofrenulum is too tight&dquo20 or their child acts similar to a relative.21 Following the diagnosis, parents’ perceptions of their child ranged from feeling sorry for their child22 to being exceptionally proud of the child’s progress despite having autism.23 Parents and professionals presented different perspectives regarding out- comes for individuals with autism. Parents offered a positive outlook,24 whereas professionals typically described negative outcomes.25 In fact, many professionals indicated they would be devastated if their child was diagnosed with autism.26 Parents described their child as being &dquosalvageable &dquo27 and felt their child would &dquorecover&dquo from autism, 28 particularly if interventions were provided.29 How- ever, it is interesting to note that most families reported a negative perception of their child’s prognosis when the diagno- sis was first made.3o Although many parents currently be- lieve that there is a positive future for their child,31 some anticipated a negative outcome32 and questioned if their child would always exhibit characteristics of autism.33 Others indicated it would be difficult to determine the exact outcome because the severity of the characteris- tics34 and intensity of the interventions affect the outcome.35 Professionals described children with autism as always having characteristics of autism, thus resulting in a lifelong dis- ability36 with no cure.3~ Although many professionals described negative out- comes,3g a few indicated that the out- comes varied.39 Positive outcomes might be more likely if the diagnosis and inter- ventions were implemented early40 and if the child exhibited less severe autistic be- haviors.41 Many professionals felt that parents had unrealistic views of the out- comes of autism,42 with most expecta- tions being too positive.43 Although only a few parents described professionals as having a negative out- look on autism,44 even fewer felt that professionals had a positive outlook.45 Most parents believed that professionals did not have an awareness of the out- at FLORIDA INTERNATIONAL UNIV on June 16, 2015 foa.sagepub.com Downloaded from 34 come46 because they did not share any perceptions with families.47 One mother summed up her thoughts of the profes- sionals’ lack of awareness by stating, The people that we went to, I think are very good at diagnosing, but I don’t think that they really thought about the out- comes. They were thinking about the di- agnosis right now and what this child had. … [They] mentioned absolutely nothing about what we could look for down the road with him and I don’t even think that was on their minds at that point.4g Professionals and parents indicated that professionals’ perceptions of the out- comes of autism affect how the profes- sional might discuss the prognosis.49 How the Diagnosis of Autism Is Presented to Families Professionals reported completing vari- ous tasks when preparing to give the di- agnosis of autism to a family. Many pro- fessionals emphasized the necessity of a good assessment to evaluate the child’s functioning and behaviors5o and to get to know the family.51 Professionals often meet with other team members to dis- cuss the data52 and results.53 As a team, professionals also discuss how informa- tion should be shared,54 who should be present,55 and the placement of individ- uals around the room.56 Professionals take the time to arrange the room5~ and determine the location of the child dur- ing the meeting.58 Many professionals, particularly those who diagnosed chil- dren in the school setting, reported con- sulting literature or research to obtain additional, updated information regard- ing autism.59 Professionals also prepare a packet of information on autism,6o complete essential paperwork,61 draw vi- sual aides,62 write a preliminary report,63 and develop recommendations64 prior to the interpretative conference. Profession- als complete these tasks regardless of whether the family suspects autism.65 In communicating the diagnosis of autism to a family, professionals attempt to use nonverbal communication skills,66 reflective listening, and simple lan- guage.67 When stating the actual diag- nosis of autism, professionals try to be honest 68 without overwhelming parents with too much information. The profes- sionals thought that pointing out the child’s strengths69 was also important, especially at the end of the meeting, so that the family leaves on a positive note.70 In addition, some stated that &dquoa little humor and a few smiles can help take the edge off.,,71 Professionals dis- cuss the DSM-IV criteria for autism or explain how the child’s behavior meets the criteria for diagnosis.72 Educating the families about how autism differs from the disability that they might have sus- pected was also considered to be impor- tant.~3 Professionals often share scores by presenting graphical pictures that dem- onstrate ranges.~4 Almost all professionals attempt to ob- tain the parents’ level of understanding, feelings toward, and acceptance of the di- agnosis.~5 Professionals might ask ques- tions such as &dquoAm I blowing you out of the water? Am I getting at what you need? Did you come here today with a specific purpose in mind, and have I ad- dressed that? &dquo~6 Similarly, professionals try to answer all of the parents’ ques- tions. Professionals indicated that it is typically easier to give a diagnosis when there is a suspicion of autism because they do not have to convince parents that their child meets the criteria. Instead, the professional can begin talking about treatment options.~g Adversely, the less knowledge families have about autism, the more time professionals spend ex- plaining the diagnosis Following the diagnosis, professionals described how they might discuss the prognosis with families. Many profes- sionals inform parents that they cannot speculate on the prognosis.80 However, a few suggest improvement with appro- priate interventions,81 whereas others in- form parents that the child might always present with characteristics of autism.82 Professionals reported that the age of the child influences how the prognosis is dis- cussed. Many felt that the younger the child, the easier it is to discuss the po- tential improvement the child might make.83 With younger children, profes- sionals also discuss the necessity of a re- assessment to help determine the child’s long-term prognosis.84 When discussing interventions, only one professional indicated that she dis- cusses different treatment options.85 Professionals at the school setting often recommend that families pursue a med- ical evaluation.g6 Although professionals typically do not offer specific recommen- dations, many are concerned with how the families will access services in the community Parents sought evaluations to obtain a better understanding of their children.88 Most indicated that the evaluation was a positive experience.g9 Most parents re- called that when relaying the diagnosis, professionals sent positive nonverbal messages,90 such as listening well; having relaxed body language; and showing humor, empathy, compassion, and a gen- uine interest in the child and family. The environment91 and a relaxed atmo- sphere92 also helped parents feel com- fortable when hearing the diagnosis. Some parents were discouraged by pro- fessionals’ nonverbal behaviors, includ- ing having a tense or rigid body posture, looking at a watch, eating lunch, or al- lowing numerous interruptions while giving the diagnosis to a family.93 Parents indicated that these behaviors conveyed a lack of interest in the discussion.94 Parents also indicated that the lan- guage used to discuss the diagnosis was important. Although some parents felt that the diagnosis was not clearly stated,95 others felt it was stated too bluntly.96 In fact, one mother suggested that the di- agnosis was stated so bluntly that it was &dquokind of just thrown all at us. Like BOOM! We were not expecting it at all The DSM-IV criteria9g and the profes- sionals’ own words were used to describe autism.99 For the most part, parents felt that professionals attempted to use sim- ple and clear language100 to explain why the child had autism-101 Professionals often gave examples of the child’s behav- ior during the evaluation. 102 The child’s strengths were also discussed,lo3 which professionals considered reinforcing for parents.104 One mother even indicated that the professional praised her ability in handling her child’s behaviors.105 Some parents recalled that the professionals en- couraged them to ask questions. 106 at FLORIDA INTERNATIONAL UNIV on June 16, 2015 foa.sagepub.com Downloaded from 35 Other parents reported having a dis- cussion with the professionals about their child’s prognosis. Only a few parents re- ported hearing a positive prognosis for their child;107 more parents indicated that they recalled a negative progno- sis.lo8 Although some parents recalled that recommendations were not of- fered,109 many indicated that recom- mendations and resources were dis- cussed.110 Some recommendations, such as behavioral techniques, were even modeled.111 Packets of information on autism were frequently distributed, but some parents felt that the information was too technica1,112 inaccurate,113 and not comprehensive.114 One mother even described the reading materials as &dquotwo inches of crud to read.&dquo115 Yet, others felt the reading materials were useffil. 116 Parents were pleased with the quality of the written reports.117 Who Should Give the Diagnosis? Parents recalled that psychologists typi- cally provided the diagnosis of autism 118 although a variety of other professionals, including speech pathologists, physical therapists, occupational therapists, pedi- atricians, and nurses,119 were represented at the interpretative meeting. Profession- als from both sites reported that the psy- chologist on the team usually shared the diagnosis.l2o Many professionals inter- viewed from the school setting, including the psychologist, indicated that giving the diagnosis of autism was not their re- sponsibility but that of a medical profes- sional These school-based profes- sionals stated that they preferred not to give the diagnosis because autism is a medical diagnosis, and therefore not a di- agnosis that they should make. However, many stated that a team of professionals was capable of making a diagnosis,122 particularly if a pediatrician was pres- ent.123 Nonmedical professionals at the medical center routinely give a diagnosis of autism to families. Some parents reported that the title of the professional did not have an effect on their acceptance of the diagnosis,124 but others indicated that it did influence their reaction.125 These parents believed that the title implies that professionals possess expertise in the area of autism. Families and professionals suggest that profes- sionals must have prior experience work- ing with children with autism and their families. These prior experiences should include knowledge of children126 (par- ticularly children with autism),12~ skill in administering tests to children with autism,128 and practice interpreting re- sults with families.129 Personality characteristics described as important when informing families that their child has autism include compas- sionl3O and honesty.131 Professionals mentioned that having the ability to un- derstand how well the families are ac- cepting the diagnosis of autism is also es- sentia1.132 When to Give the Diagnosis Some professionals drop hints through- out the course of the evaluation133 in order to raise the level of parents’ aware- ness regarding unusual behaviors. Most wait until the entire evaluation is over in order to decrease the likelihood of mis- perception by parents. 134 During the in- terpretative conference, all professionals have tried offering the diagnosis first, fol- lowed by a rationale as to why the child meets the criteria.135 Professionals have also described the child’s behaviors first and then stated the diagnosis. Although some professionals preferred to give the diagnosis first,136 others thought it was useful to talk about the child’s behaviors and then tie it together with a diagnosis in the end.l3~ The determination of when to state the diagnosis is dependent upon the family.138 Factors that profes- sionals consider are whether the parents suspect autism,139 whether the parents are ready to accept the diagnosis,140 and whether the family indicates that they want to know the diagnosis up front.141 Hedging the Diagnosis Many parents reported that professionals did not clearly state the diagnosis of autism.142 Professionals offered various reasons for why they would hedge a di- agnosis. Overwhelmingly, professionals reported that they consider the emotionsof the family and how much information the family can handle.143 Professionals also stated that for very young children, the diagnosis is not as important as ob- taining the appropriate services.144 Pro- fessionals also attributed their hesitancy to a fear of giving the diagnosis145 or a lack of confidence.146 A lack of training on autism,l4~ a poor evaluation,148 or even the young age of the child149 can result in fear or feelings of incompetence. Thoughts Regarding Giving Scores Most participants indicated that hearing scores obtained during the evaluation was helpfiil.150 One father stated that scores are helpful because &dquoknowledge is power.&dquo151 Similarly, a professional of- fered that sharing scores is important be- cause &dquoif your bottom line [score] is going to call them a label, then they have a right to know why.&dquo152 However, another pro- fessional questioned the appropriateness of providing scores because &dquoit’s confus- ing and 2 days later it is not going to mean diddley.&dquo153 Location of the Child During the Interpretative Conference Although some children were out of the room,154 most parents recalled their child being in the room155 when the di- agnosis was given. Parents who did not mind their child in the room156 sug- gested the child was too young to com- prehend the discussion.l5~ Yet, some parents preferred their child be out of the room158 because he or she might under- stand what was being discussed. 159 In ad- dition, parents need time to grieve with- out having to worry about their child. One mother explained why she preferred her child out of the room: Definitely it was better not to have him there because that’s a real big blow to give to parents. They need to deal with their emotions, or at least in our case, we needed to deal with our emotions and kind of get figured out how we were going to think about this and how we were going to deal with it. We needed time.l6o at FLORIDA INTERNATIONAL UNIV on June 16, 2015 foa.sagepub.com Downloaded from 36 Like parents, some professionals pre- ferred the child in the room,161 and oth- ers preferred the child out of the room when parents were told the diagnosis of autism. Some professionals thought that children in the room, particularly young children with autism, do not understand the conversation162 and can provide com- fort for parents.163 However, others were concerned children might understand164 or distract parents by misbehaving.165 Hope Many parents cried when discussing the need for hope.166 Hope provides parents with a sense of optimism for the fu- ture.l6~ One mother said hope was &dquowhy we wake up everyday. There is nothing that any of us cannot go through if we believe there is hope for progress.&dquo168 Another mother stated that hope is the &dquocarrot in front of our face.&dquo169 Parents suggested that hope can be provided by being positive, describing the child’s potential for improvements discussing the positive effect of early interven- tion,171 and providing examples of suc- cess stories.l~2 z Interventions Some parents were pleased with available interventions for individuals with au- tism,l73 but a majority expressed dis- pleasure.l~4 Similarly, professionals also described positivel75 and negativel76 perceptions of interventions. Although most families recalled receiving general recommendations, they would have pre- ferred receiving information about spe- cific interventions 177 because such infor- mation would have assisted them in accessing services178 and would have provided a sense of direction.l~9 Families speculated that specific recommenda- tions were not offered because of pro- fessionals’ lack of knowledge 180 and con- cern for legal issues. 181 Professionals stated that the child’s service providers should develop appropriate interventions be- cause they have a better rapport and un- derstanding of the child.182 A speech pathologist stated that I tend to be a lot more general because even though I’ve spent time evaluating the child, I really haven’t got a chance to get in and manipulate things to see how they respond. I think when you really get in and you get down and dirty on the floor, I think that’s when you start to see more of the individualness and more of &dquothat’s not going to work&dquo because you’re actually try- ing.183 z Benefits of Receiving a Diagnosis . Parents said that relief is a benefit of a di- agnosis because they no longer feel they are to blame184 and they have an expla- nation for themselves185 and others186 as to why their child exhibits unusual be- haviors. The diagnosis serves as a &dquowake- up call because you realize that you just don’t have a child that’s, like, late talking or slow developing or whatever. You realize that you’ve got to do some- thing.&dquo18~ A diagnosis of autism assists parents in obtaining informationl88 and access to services.189 Specifically, an early diagnosis is necessary to increase the like- lihood of progress. 190 Reactions to Giving and . Receiving a Diagnosis of .. , Autism Professionals stated that they experience emotional and physiological changes when giving the news of autism to par- ents. Most emotions are negative, in- cluding feeling sad,191 wanting to cry,192 feeling empathy for families,193 and having doubts about the diagnosis of autism.194 The most common and over- whelming emotion expressed is nervous- ness,195 particularly when professionals are uncertain of parents’ reactions.196 Professionals also described experiencing physical changes, such as nausea,l9~ in- creases in body temperaturel98 or heart rate,199 thirst,200 headache,201 and tired- ness, when informing families that their child has autism.2o2 Speech patterns are altered due to heavy breathing,203 stut- tering,204 or word retrieval difficul- ties.205 These emotional and physiologi- cal changes are often so overwhelming that professionals dread the interpreta- tive conference.206 These changes are often intensified when the family does not suspect autism.207 Parents under- stand that giving a diagnosis is difficult for professionals. 208 Professionals’ physiological and emo- tional reactions can have either a positive or negative effect on the presentation of the diagnosis. The positive effect is that empathy and sensitivity toward parents is increased.209 Negative effects include rushing, 210 failing to give relevant infor- mation,211 jumbling words,212 present- ing an unclear diagnosis,213 and using poor eye contact.214 These reactions may reinforce parents’ doubts in the pro- fessionals’ ability to make a diagnosis of autism2l and cause parents to become upset or uncomfortable.216 In fact, a so- cial worker felt that parents &dquocan sense the tension in our voices and I think they react to it. They know that something is wrong with their child just by our be- havior. Our anxiety brings out their own anxiety. &dquo217 Professionals reported that their emo- tional and physical reactions did not af- fect their discussion of the prognosis or interventions.219 In fact, professionals reported that discussing the prognosis was easier than presenting the diagno- sis,22o especially if a thorough discussion of the diagnosis was presented.221 Overall, professionals believe that par- ents’ main positive reaction is relief 222 Most reactions to the diagnosis of autism are negative, such as denial, 223 emotion- ality,224 misperception of the diagno- sis,22s and no longer listening to the professional.226 Parents also react by be- coming angry with or disliking the pro- fessional.227 An occupational therapist stated that parents often &dquohate the mes- senger&dquo228 because he or she is telling the family something they do not want to hear. Many professionals admitted they would have a negative reaction if their child was diagnosed with autism.229 Most professionals described three groups of parents based on their prior knowledge of the diagnosis: parents who suspect autism,230 parents who suspect delays but not autism,231 and parents who do not recognize any problem.232 Parents’ reactions to the diagnosis vary and are dependent on the degree to which they suspect autism.233 Parents at FLORIDA INTERNATIONAL UNIV on June 16, 2015 foa.sagepub.com Downloaded from 37 who do not recognize a problem often have the most negative reactions.234 Par- ents suspecting a problem other than autism have a mixture of positive and negative reactions, including relief,235 re- ceptiveness,236 denial,237 anger,238 dev- astation,239 and a feeling of being over- whelmed.240 Parents suspecting autism typically have positive reactions,241 such as relief,242 acceptance of the diagno- sis,243 and receptiveness to additional in- formation.244 Professionals attribute some parents’ failure to accept the diagnosis to poor understanding of typical child develop- ment,245 incorrect and negative percep- tions of autism,246 characteristics of the family,247 and concern about the reac- tions of the extended family.248 In addi- tion, some parents continue to deny any problems,249 and as a result they make excuses for their child’s unusual be- haviors.250 The child’s age at the time of diagnosis is related to acceptance251 be- cause parents have difficulty differentiat- ing between typical and atypical behavior in young children.252 One professional suggested that parents of younger chil- dren &dquostill envision this perfect child. There has not been enough time for them to realize how abnormal the be- havior is. We burst their picture of their child.&dquo253 When parents suspect a dis- ability other than autism, the conference can be difficult because parents have a &dquopreconceived notion of the reasons for their child’s behaviors. &dquo254 Some profes- sionals indicated that parents from a high socioeconomic status and with a high level of education often have difficulty accept- ing a diagnosis of autism255 because Most of those [low SES] people didn’t ex- pect much in the beginning, but the peo- ple who just break down and sob and shake and just can’t get over it are the people who had such high expectations to begin with…. So I think the higher functioning people just find it a tremendous assault to their egos.256 Parents reacted to the diagnosis by crying;257 expressing relief,258 surprise,259 devastation,26o or helplessness;261 and wanting additional information about autism.262 Some parents did not believe the diagnosis,263 and some even became angry264 or questioned the professional’s ability.265 Many parents were concerned about how the other parent, extended family, and friends would accept the di- agnosis.266 Suspecting autism decreased the likelihood of shock.267 Many parents and professionals said family members went through a grieving process after hearing the diagnosis.268 Regardless of their reaction, families did not feel that a diagnosis of autism influenced their in- teractions with their child.269 Parental reaction to the diagnosis of autism varied. Although some families had a negative reaction,270 others were hopeful because early intervention could be initiated and changes could be made.271 One father summed up his op- timism nicely: It was so clear to us that there was some- thing wrong. We could not deny that he Table 4 Quick Reference of Recommendations for Practices When Informing Families Their Child Has Autism was acting and developing inappropriately. It seemed out of the ordinary compared to our experience with our other son and with other children that we had met. What was even better was we could get some early in- tervention and get started while he was still young. We were so glad to get it and get an early jump on this. I have heard from many families that they got their diagnosis when their child was older and they lost so much critical time for interventions. 272 Discussion Based on the findings of this study, rec- ommendations for practice were devel- oped that professionals may find useful in sharing a diagnosis of autism with a fam- ily. Table 4 offers a quick reference to the recommendations. Recommendations for Practice Become Knowledgeable About Au- tism. Professionals need to be knowl- edgeable about the diagnosis, prognosis, and treatment of autism. Knowledge al- lows professionals to feel more confident in their abilities and decreases the likeli- hood that the parent will question the professional’s ability. Increased aware- ness of the diagnosis and treatments for autism may result in an earlier diagnosis, which, in turn, will allow the child to re- ceive services at a younger age. Profes- sionals’ expertise in the area of autism makes parents more confident of the vi- ability of the diagnosis and the recom- mendations for interventions. Establish a Family-Friendly Setting. Families need to feel comfortable, be- cause the interpretative conference can be stressful for both professionals and parents. The room should include com- fortable chairs or tables. Families and professionals should be seated as an inte- grated unit, and provisions must be made for both the child and the parents to be comfortable. Having tissues nearby does not disrupt the flow of the meeting if par- ents become upset. Understand the Family’s Needs. Learning that a child has autism often has at FLORIDA INTERNATIONAL UNIV on June 16, 2015 foa.sagepub.com Downloaded from 38 a profound effect on the family (Selig- man & Darling, 1997; Turnbull & Turn- bull, 1997 ; Webber, Simpson, & Bentley, 2000). Professionals must provide infor- mation about autism that the family un- derstands and that allows the family to seek appropriate interventions. Each family is unique in their needs and per- ceptions of autism. It is essential that pro- fessionals obtain an understanding of these needs and perceptions so that they can tailor the interpretative conference to the family. This information influences how the diagnosis is presented, the type of information shared, and the order in which the information is shared. Impor- tant areas to consider are prior knowl- edge of autism, diagnosis first versus overview first, location of the child, and sharing scores. It is essential that profes- sionals determine what information the family would find most useful. Use Good Communication Skills. The diagnosis should be presented clearly in language that parents under- stand. In addition, professionals should use reflective listening and other nonver- bal communication skills to put parents at ease. The interpretative conference should not be rushed and should be as relaxed as possible. Provide a List of Resources and In- terventions. Providing a list of inter- ventions and community resources is es- sential because it assists families in quickly obtaining access to services. Given the variety of interventions avail- able for children with autism, it is not surprising that parents want professionals to help them locate appropriate treat- ments for their child. Resources should be accurate and include phone numbers or the name of the individual(s) to con- tact. Although many professionals warn against giving specific interventions, rec- ommended treatments should be as spe- cific as possible based on the information obtained during the evaluation. Addi- tionally, prioritizing interventions is use- ful because it helps families determine which interventions are the most impor- tant to pursue. Provide Follow-up. The importance of follow-up with families cannot be overemphasized. Parents may be so over- whelmed at the interpretative conference that they stop listening to the profes- sionals. As a result, they miss important information. Similarly, after parents have had the opportunity to consider the di- agnosis and recommendations, they may have additional questions. Professionals can provide follow-up with a phone call or letter a few weeks after the interpreta- tive conference. When providing follow- up, professionals should help families by answering questions, providing addi- tional information, and assisting them to access interventions. Discuss Prognosis. Parents want in- formation about their child’s future de- velopment. Although professionals can- not predict the future, they should share their thoughts regarding the prognosis for children with autism. Although the child might always exhibit characteristics associated with autism, with intensive early intervention, improvements can be made. Provide Hope. Professionals must impart a sense of optimism to families about their child’s future. This optimism assists families in confronting the diag- nosis and obtaining interventions for their child. Hope gives families the mo- tivation to continue tackling the difficul- ties that often arise as a result of the char- acteristics and behaviors associated with autism. Hope can be provided to families by discussing the child’s strengths and likelihood of improvement in the future with the implementation of appropriate interventions. , . Recognize That It Is Not Unusual for Professionals to React to Giving a Diagnosis of Autism. Based on the re- sults of this study, it is apparent that giv- ing a diagnosis of autism elicits many negative reactions from professionals. Al- though it is expected that hearing a di- agnosis of autism is difficult for families, it is important to consider the difficulty that professionals experience when giv- ing the diagnosis. Questioning of one’s abilities, nervousness, increased heart rate, and quickened breathing are com- mon. Professionals need to be aware of the difficulty and realize that these reac- tions are not unusual. However, these re- actions must not be allowed to have a negative effect on the interpretative con- ference because they may influence how parents accept the diagnosis. Limitations Recommendations are based primarily on information provided by mothers who were married, White, and from one of the wealthiest counties in the nation. Even though attempts were made to re- cruit mothers and fathers from a variety of backgrounds, few families from cul- turally diverse and low-income homes chose to participate. Similarly, single- parent families, foster families, adoptive families, and same-sex parental relation- ships were not represented in this study. As a result, this study does not provide information about how fathers or fami- lies from a variety of parental relation- ships, cultures, and socioeconomic levels would react to learning that their child has autism. Furthermore, information about the severity of the child’s disability was not available. The severity of the child’s disability could influence families’ perceptions of a diagnosis of autism. Next Steps There is a need for further research to gain a better understanding of profes- sionals’ perceptions of the importance and utility of educational and medical de- finitions of autism. This information will help professionals clarify who is responsi- ble for giving diagnoses and will assist families in locating funding for interven- tions. In addition, perceptions and reac- tions to the diagnosis of autism need to be explored for different cultural, ethnic, socioeconomic, and family configura- tions. Such information would be useful in developing an inventory to help pre- dict families’ perceptions of autism and their needs and reactions to the diagno- sis. Such information could assist profes- sionals in addressing the recommenda- at FLORIDA INTERNATIONAL UNIV on June 16, 2015 foa.sagepub.com Downloaded from 39 tion for understanding the family’s needs. Professionals identified three different groups of parents (i.e., suspecting autism, suspecting a disability other than autism, not suspecting any problem). Further research is needed to increase our understanding of why professionals are willing to state the diagnosis of au- tism clearly to some groups of parents and not to other groups. Families want to leave the interpretative conference with hope. Additional research is needed to learn how professionals can provide hope to families. Although professionals might be em- ploying many of the recommendations offered in the present study, many of the recommendations are not being imple- mented because of time and financial constraints at their work sites. Providing a comfortable setting, an adequate follow-up, and a list of interventions might require substantial changes in the allocation of money and time. For exam- ple, money is needed to create a com- fortable environment for families and children. This might include architec- tural and interior design changes or the purchase of interesting toys to occupy the child. Additionally, professionals must be given release time from daily responsibilities to provide follow-up ser- vices to families or to visit various com- munity resources and interventions. Pro- viding follow-up and visiting various programs is time consuming but impor- tant if professionals are to provide fami- lies with accurate interventions and assist families in obtaining the best services possible for children with autism. ABOUT THE AUTHORS Michal S. Nissenbaum, PhD, has an academic appointment in the Department of Psychiatry and a clinical appointment at the Develop- mental Disabilities Center at the University of Kansas Medical Center. Her current interests include working with infants, toddlers, and preschoolers with disabilities and their families and assessment and interventions for young children with autism. Nona Tollefson, PhD, is a professor of educational psychology and re- search at the University of Kansas. She cur- rently teaches courses in qualitative and quan- titative assessment. R. Matthew Reese, PhD, is director of training at the Kansas CEDDARS and the coordinator of psychology at the Devel- opmental Disabilities Center at the University of Kansas Medical Center. He holds academic appointments in the Department of Human Development and Family Life and the Depart- ment of Pediatrics. Address: Michal S. Nis- senbaum, Developmental Disabilities Center, University of Kansas Medical Center, 3901 Rainbow Blvd., Kansas City, KS 66160-7340; e-mail: [email protected] NOTES 1SV1-P&Upsi1-CE 2SV1-P&Upsi3-O, SV2-P&Upsi3-E 3SV1-OT2-B, SVI -SL2-Q 4SV1-PO1-N 5SV1-PO1-D 6SV1-P&Upsi3-N 7SV1-PO1-AT, SV1-OT1-DM 8SV1-PO1-AK, SV1-PT1-R 9SV1-PO1-AK 10SV1-OT2-S, SV2-PT1-R 11SV1-OT1-M 12SV1-P&Upsi1-AB 13SV1-FM7-K, SV1-FD2-Q SV1-FD1-BS, SV1-FM1-AR 14SV1-FM7-K, SV1-FM11-AC, SV1-FM4-AS 15SV1-FD2 -BQ SV1-FM10-J, SV1-FM15-AO, SV1-FM3-B, SV1-FM7-BX 16 SV1-FM2-X, SVI -FM4-AN 17 SV1-FM1-W, SV1-FM11-BV, SV1-FM2-H, SV1-FM7-&Upsi, SV1-FM9-DF 18SV1-FM1-F, SV1-FM2-AW, SV1-FM8-D, SV1-FM11-F, SV1-FD1-D, SV1-FD2-N 19SV1-FD2-BQ SV1-FM10-J, SV1-FM15-AO, SV1-FM3-B, SV1-FM7-BX 20SV1-FM5-AW 21SV1-FM10-G, SV2-FM9-K 22SV1FM15-P 23SV1-FM3-X 24SV1-FM7-AA, SV1-FD2-BF, SV1-FM-7- BK, SV2-FM9-I, SV2-FM5-A, SV2-FM1-D, SV1-FD1-AV, SV2-FM11-A, SV1-FM7-AQ 25SV1-SL2-AR, SV1-P&Upsi2-AV, SV1-SL3-M, SV1-SO1-AL, SV1-PO1-BH, SV2-P&Upsi3-J, 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SV1-FM14-E, SV1-FM13-E 100SV1-FM10-N 101SV1-FM7-B, SV1-FM6-A, SV1-FM2-B, SV1-FM15-L, SV1-FM1-C 102SV1-FD1-QR, SV1-FM10-M, SV1-FM2-G, SV1-FM5-X, SV1-FM3-R, SV2-FD1-AA, SV2-FM2-Q, SV2-FM10-P, SV2-FM7-W, SV2-FM9-X 103SV1-FM14-AG, SV1-FM5-&Upsi, SV1-FM8-N 104SV1-FM8-N 105SV1-FM5-W 106SV1-FM13-AG, SV1-FM8-X, SV1-FM1- BA, SV1-FM10V 107SV1-FD1-L, SV1-FM11-AG 108SV1-FM7-Q, SV1-FM6-W, SV1-FM3-AM, SV1-FM15-R 109SV2-FM2-G, SV2-FM4-B, SV2-FM10-E 110 SV1-FD2-AC, SV1-FM10-S, SV1- FM13-K, SV1-FM2-AI, SV2-FM9-AI, SV1- FM5-L, SV1-FM8-AA, SV2-FM6-P 111SV1-FD2-AO, SV1-FM11-BA, SV2- FD2-M 112SV1-FM2-AH 113SV1-FM1-E, SV2-FM1-I 114SV1-FM9-F 115SV1-FM4-AF 116SV1-FM1-K, SV1-FM5-AG, SV1-FM8-J 117SV1-FM11-A&Upsi, SV1-FM4-P 118SV1-FD1-K, SV1-FD2-X, SV1-FM7-BQ, SV1-FM14-P 119SV1-FD2-H, SV1-FD1-C, SV1-FD15-H, SV1-FM14-B, SV1-FM2-AX, SV1-FM3-P, SV1-FM6-H, SV1-FM9-I 120SV1-PT1-R, SV1-SO1-Q, SV1-OT1-BQ, SV1-P&Upsi1-I, SV1-OT2-S 121SV1-PT1-S, SV1-SO1-A, SV1-OT2-S, SV3- P&Upsi1-L, SV1-PO1-AD, SV1-OT1-AC, SV2- OT1-T, 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SV2-SL3-AL, SV2-PT1-V, SV2-SL1-EC 137SV1-SL1-AE, SV1-P&Upsi1-BQ, SV1-SL3-P, SV2-PT1-U, SV2-P&Upsi2-U, SV2-SL1-N, SV2- P&Upsi1-Q SV2-OT2-AA 138SV1-SL3-AN, SV1-SO1-CF, SV1-OT1-A, SV2-PT1-T 139SV2-P&Upsi2-V, SV2-SO1-F 140SV2-POI1-V, SV2-SL2-L 141SV2-OT2-Z 142SV1-FM15-N, SV1-FM12-AE, SV1- FM11-E, SV1-FD2-J, SV1-FD1-M, SV2- FM11-E 143SV3-P&Upsi3-D, SV3-SL1-P, SV3-P&Upsi2-B, SV3- OT1-L, SV3-PO1-K, SV3-SO1-K 144SV3-OT2-A, SV3-SL3-L 145SV3-PT1-A, SV3-P&Upsi1-M, SV3-SL2-O 146SV3-OT1-K, SV3-P&Upsi1-N, SV3-SL3-M 147SV3-P&UpsiS-B, SV3-SO1-A 148SV3-P&Upsi3-E, SV3-PO1-A 149SV3-OT2-C, SV3-P&Upsi2-A, SV3-SL3-K 150SV1-FM4-K, SV2-FM15-S, SV2-FM11-R, SV2-FM6-V, SV2-FM1-AE, SV2-FD2-L, SV2-FM5-S 151SV2-FD2-L 152SV1-OT1-BG 153SV1-SL1-DA 154SV2-FM6-X, SV2-FM9-X, SV2-FM14-R, SV2-FD2-H 155SV2-FD2-AN, SV2-FM1-AM, SV2-FM5-V, SV2-FM11-W, SV2-FM12-N, SV2-FM13-X, SV2-FM15-V 156SV2-FM2-N, SV2-FM4-P, SV2-FM5-O, SV2-FM7-V, SV2-FM10-M, SV2-FM11-N, SV2-FM13-K, SV2-FM15-P 157SV2-FM2-N, SV2-FM4-P, SV2-FM5-O, SV2-FM7-V, SV2-FM10-M, SV2-FM11-N, SV2-FM13-K, SV2-FM15-P 158SV1-FM14-C, SV2-FM6-R, SV2-FM12-O, SV2-FM14-J 159SV1-FM14-C, SV2-FM12-O 160 V2-FM14-J 161SV3-P&Upsi2-M, SV3-OT2-J, SV1-OT2-BJ, SV3-P&Upsi3-I, SV3-SO1-D, SV1-OT2-1, SV3- P&Upsi3-W 162SV3-P&Upsi3-I, SV3-SO1-D 163SV1-OT2-I, SV3-P&Upsi3-W 164SV1-P&Upsi3-&Upsi, SV3-P&Upsi3-J, SV3-PT1-E, SV3- P&Upsi1-F, SV3-SL2-G 165SV3-SL1-F, SV3-P&Upsi2-G, SV3-OT1-F, SV3- PO1-E 166SV2-FM2-O, SV2-FM4-Q at FLORIDA INTERNATIONAL UNIV on June 16, 2015 foa.sagepub.com Downloaded from 41 167SV2-FM6-S, SV2-FM15-D, SV2-FM14-K, SV2-FM11-O, SV2-FM13-L, SV2-FM9-V, SV2-FM7-F, SV2-FM4-Q SV2-FD2-I, SV2- FM5-P, SV2-FM1-G, SV2-FM10-N, SV2- FM12-Q 168SV1-FM5-BJ169SV2-FM5-P 170SV1-FM14-AI, SV1-FM15-AQ SV2- FM10-O, SV2-FD2-J, SV2-FM6-T 171SV1-FM12-R, SV2-FM2-R, SV2-FM7-G, SV2-FM5-Q 172SV1-FM11-AI, SV2-FM11-P, SV2-FM14-L 173SV1-FD2-BA, SV1-FM3-AV, SV1-FM4- BR, SV1-FM7-AG, SV2-FM2-C 174SV1-FD1-AH, SV1-FM7-CX, SV1-FD1-W, SV1-FD2-BG, SV1-FM10-AD, SV1-FM15- X, SV1-FM4-BK, SV1-FM5-AH, SV1-FM6- AC, SV2-FM7-R 175SV1-OT2-AO, SV1-PO1-AF, SV1-P&Upsi2-V, SV1-SO1-BE 176SV1-P&Upsi2-AZ, SV1-OT2-AD, SV1-SO1- BK, SV2-OT2-E 177SV2-FM15-I, SV2-FD2-G, SV2-FM14-M, SV2-FM1-AH, SV2-FM7-U, SV2-FM10-L, SV2-FD1-V, SV2-FM4-G 178SV1-FM4-CF, SV1-FM7-V, SV1-FD1-AS, SV1-FM5-AO, SV1-FM6-AB, SV2-FM4-J, SV2-FM9-Q, SV2-FM1-M, SV1-FM2-AT 179SV1-FM10-C, SV1-FM5-Q, SV1-FM4-CH, SV2-FM11-M, SV1-FD1-BE, SV1-FM14- AN, SV1-FM2-AR, SV1-FM7-CI 180SV1-FM5-BG, SV2-FM4-F 181SV1-FD2-AZ, SV1-FM2-AO 182SV3-SL3-J, SV3-SL2-N, SV3-PT1-J, SV3- P&Upsi2-L, SV3-SL1-N, SV3-OT2-P, SV3- P&Upsi3-Q SV2-P&Upsi2-G 183SV3-SL1-N 184SV2-FM6-H, SV2-FM9-M, SV2-FM2-K 185SV2-FM13-N, SV2-FM1-V, SV2-FM11-U 186SV1-FM6-AI, SY2-FM9-N, SV2-FM13-F 187SV2-FD1-N, SV2-FM10-J, SV2-FM1-R, SV2-FM6-G 188SV1-FM1-G, SV1-FD2-V, SV2-FM6-AJ, SV1-FM8-O, SV1-FM13-Q, SV2-FD1-P, SV2-FM10-F, SV2-FM9-AA, SV2-FM13-O, SV2-FM1-W, SV2-FM6-W 189SV1-FM13-AJ, SV1-FM15-AJ, SV2-FM2- L, SV2-FD1-M, SV2-FD2-E, SV2-FM5-J, SV2-FM11-G, SV2-FM12-F, SV2-FM14-F, SV2-FM15-N 190SV2-FD1-O, SV2-FM6-E, SV2-FM14-G, SV2-15-F, SV1-SL3-CI, SL1-OT1-CV, SV1- OT2-AV, SV1-PO1-AG 191SV1-I-PT1-D, SV1-I-P&Upsi1-V, SV1-P&Upsi3-D, SV1-SL2-T, SV1-SL3-A, SV2-SL3-H 192 V1-PT1-Z, SV1-SL3-O, SV1-P&Upsi1-D, SV1- OT2-G 193SV1-SO1-AK, SV1-SL3-L, SV1-P&Upsi1-W 194SV1-SL3-R, SV1-SL1-V, SV1-P&Upsi3-M, SV1- P&Upsi2-AN 195SV1-PO1-W, SV1-P&Upsi1-M, SV1-P&Upsi3-ZT, SV1-SL1-I, SV1-SL2-AD, SV1-SL3-T, SV1- OT1-S, SV1-SO1-AF 196SV1-P&Upsi1-H, SV1-OT1-N, SV1- P&Upsi2-H, SV1-P&Upsi3-C, SV1-SL3-Q SV1-SO1-Z 197SV1-P&Upsi1-L, SV1-P&Upsi3-A, SV1-OT1-T, SV1- SL1-J, SV1-SL3-ZX 198SV1-P&Upsi1-K, SV1-P&Upsi3-ZS, SV1-SL2-1, SV1- L3-I, SV1-SO1-O 199SV1-P&Upsi1-G, SV1-PT1-H, SV1-SL2-&Upsi 200SV1-SO1-AG 201SV1-PO1-U 202SV1-P&Upsi2-L, SV1-SL1-EA, SV1-SL3-G 203SV1-SL1-N 204SV1-P&Upsi2-J205SV1-PT1-ZZ 206SV1-PT1-G, SV1-SL2-AC, SV1-SL3-B 207SV1- P&Upsi2-A, SV1-P&Upsi3-G, SV1-SL3-D, SV1-PO1-P 208SV1-FD1-O, SV1-FM9-CV, SV1-FM4-I, SV1-FM3-AT, SV1-FM13-N 209SV2-SL3-D, SV2-SL2-A, SV2-P&Upsi2-E, SV2- PT1-A, SV2-SL3-B, SV2-OT1-A, SV2- OT2-A 210SV2-SL3-A 211SV2-PT1-B, SV2-SL3-C 212SV2-P&Upsi3-A 213SV2-PO1-A, SV2-SL1-A 214SV2-PO1-B 215SV2-P&Upsi2-A, SV2-OT1-AD 216SV2-P&Upsi1-A, SV2-P&Upsi2-C, SV2-P&Upsi3-C, SV2-OT2-B, SV2-SO1-A 217 SV2-SO1-A 218 SV2-SL3-N, SV2-P&Upsi2-B, SV2-P&Upsi3-F 219 SV2-P&Upsi1-C, SV2-P&Upsi2-D, SV2-PT3-H 220 SV2-SL3-N, SV2-P&Upsi2-B, SV2-P&Upsi3-F 221 SV2-SL3-N 222SV1-PT1-K, OT2-R, SV1-SL2-B, SV1-SO1- CC, SV1-PO1-AO 223SV1-OT2-H SV1-PO1-ZZ, SV1-SO1-BR, SV1-SL1-BO, SV2-P&Upsi1-K 224SV1-OT2-L, SV2-SL3-AC, SV2-OT1-C 225SV1-OT1-BZ, SV1-P&Upsi2-K, SV2-OT1-R, SV3-SL3-I 226SV1-PO1-F, SV1-SL2-AH, SV1-OT1-CG, SV1-SL1-F 227SV1-PO1-E, SV1-SL3-W, SV1-OT1-DF, SV1-P&Upsi1-AF, SV1-SL1-E, SV1-SO1-CK, SV1-OT2-M, SV2-OT1-K 228SV1-OT1-DF 229SV1-OT2-J, SV1-SL3-BV, SV1-P&Upsi1-ZZ, SV1-SL1-Q 230SV2-PT1-B, SV1-OT2-AS, SV1-PT1-B 231SV1-SL3-&Upsi, SV1-SL1-I, SV1P&Upsi2-D, SV2- OT2-F, SV2-P&Upsi11-BE 232SV1-OT1-X, SV1-SL1-D, SV1-P&Upsi1-D, SV2-OT1-L, SV2-P&Upsi1-I, SV2-OT2-O, SV2- P&Upsi3-L 233SV1-P&Upsi1-A, SV1-P&Upsi2-F, SV2-OT2-Q 234SV1-P&Upsi3-AE, SV1-PT1-AA, SV1-OT2-N, SV1-SL3-CK, SV2-OT1-S, SV2-SL2-J, SV2- SL1-H, SV2-PT1-L 235SV1-SL2-AS, SV2-SL2-I, SV3-SO1-E 236SV1-SL1-B 237SV2-PO1-G, SV2-OT1-M, SV2-P&Upsi3-M 238SV2-SL3-AB, SV2-P&Upsi2-AC 239SV1-SL3-CL, SV3-OT2-K, SV3-OT1-G, SV3-PT1-F, SV3-SL3-G 240SV2-P&Upsi2-N 241SV1-PT1-V, SV1-P&Upsi2-AH, SV2-P&Upsi3-K, SV1-SL3-CP, SV2-SL1-J, SV1-PT1-O 242SV1-OT1-DB, SV1-SL3-CJ, SV1-P&Upsi2-B, SV2-PT1-K, SV2-P&Upsi3-O 243SV1-SL1-BI, SV1-SL2-AQ, SV2-OT1-J, SV2-SL2-E 244SV1-PT1-AD, SV1-OT2-AX, SV1-P&Upsi3- AA, SV1-OT1-DE, SV1-P&Upsi1-BB, SV1-SL1- BM, SV2-PT1-N, SV2-P&Upsi2-M, SV2-PO1- H, SV2-OT2-P, SV2-P&Upsi3-N 245SV1-PO1-O, SV1-P&Upsi2-AO, SV1-SO1-CA, SV3-P&Upsi2-J, SV3-OT2-T 246SV3-OT1-I, SV3-OT2-M, SV3-SL1-K, SV3- PT1-H, SV3-P&Upsi1-1, SV3-P&Upsi3-A 247SV3-P&Upsi3-O, SV1-PT1-X, SV1-SL2-A&Upsi 248SV3-OT2-R, SV3-SL2-J 249SV3-OT2-S, SV3-SL1-L, SV3-P&Upsi2-O, SV3- PO1-L 250SV1-PO1-BG, SV1-SL1-BT, SV1-SL2-S, SV1-OT1-R, SV3-P&Upsi2-N, SV3-SL2-L 251SV1-OT1-Z, SV3-PO1-H 252SV2-OT1-W, SV2-OT2-AH, SV2-P&Upsi2-X 253SV2-SO1-G 254SV3-P&Upsi1-G, SV3-P&Upsi2-H, SV3-PO1-F, SV3-P&Upsi1-G, SV3-SL2-H 255SV1-SO1-AA, SV2-PO1-F, SV3-SL2-J 256SV1-SO1-AA 257SV1-FM1-J, SV1-FM5-AX, SV1-FM9-BM, SV1-FM13-U, SV1-FM14-I 258SV1-FM1-H, SV1-FM4-AO, SV1-FM5- AR, SV1-FM7-AN, SV1-FM8-F, SV1- FM10-I, SV1-FM11-AK, SV1-FM12-C, SV1-FM14-F 259SV1-FD1-AF, SV1-FM2-C, SV1-FM11-R 260SV1-FM1-&Upsi, SV1-FM3-L, SV1-FM4-AK, SV1-FM5-CF, SV1-FM7-C, SV1-FM12- AH, SV1-FM15-O 261SV1-FM4-CD, SV1-FM7-AZ 262SV1-FD1-I, SV1-FD2-M, SV1-FM1-AB, SV1-FM2-M, SV1-FM3-C, SV1-FM4-C, SV1-FM5-AE, SV1-FM7-I, SV1-FM8-AC, SV1-FM9-&Upsi, SV1-FM12-L, SV1-FM13-X, SV1-FM14-&Upsi, SV1-FM15-V 263SV1-FM9-Q, SV1-FM15-BF 264SV1-FM3-M, SV1-FM7-BE, SV1-FM9-AJ, SV1-FM15-AI 265SV1-FM2-T, SV1-FM4-G, SV1-FM7-CC 266SV1-FM4-A&Upsi, SV1-FM2-V, SV1-FM15-T, SV1-FM1-AS, SV2-FM1-E, SV2-FM6-N at FLORIDA INTERNATIONAL UNIV on June 16, 2015 foa.sagepub.com Downloaded from 42 267SV1-FD1-AN SV1-FD2-O, SV1-FM1-AD, SV1-FM2-&Upsi, SV1-FM3-AF, SV1-FM4- AJ, SV1-FM11-AN, SV1-FM13-G, SV1- FM14-O, SV1-FM15-AR 218SV1-FD1-AG, SV1-FD2-U, SV1-FM3-AB, SV1-FM5-AM, SV1-FM7-CA, SV1-FM8-K, SV1FM11-AB, SV1-FM12-AJ, SV1- FM14-H, SV1-FM15-AK, SV2-FM12-E, SV2-FM10-D, SV1-SL2-H, SV1-P&Upsi3-AN, SV1-POI-Z&Upsi 269SV1-FM11-AM, SV1-FM5-A&Upsi, SV1-FM9- CG 270SV2-FM2-H, SV2-FM11-F, SV2-FM12-D, SV2-FM13-E, SV2-FM15-J 271SV2-FD1-L, SV2-FD2-D, SV2-FM7-M, SV2-FM11-F 272SV2-FD2-D REFERENCES American Psychiatric Association. (1994). Diagnostic and statistical manual of mental disorders (4th ed.). Washington, DC: Au- thor. Burger, R. A., & Warren, R. P. (1998). Pos- sible immunogenetic basis for autism. Men- tal Retardation and Developmental Dis- abilities Research Reviews, 4, 137-141. Campbell, M., Schopler, E., Cueva, J. E., & Hallin, A. (1996). Treatment of autistic dis- order. Journal of American Academy of Child and Adolescent Psychiatry, 35, 134- 143. Cook, E. H. (1998). Genetics of autism. Mental Retardation and Developmental Disabilities Research Reviews, 4, 113-120. Cunningham, C. C., Morgan, P. A., & McGucken, R. B. (1984). Down’s syn- drome : Is dissatisfaction with disclosure of diagnosis inevitable? Developmental Medi- cine and Child Neurology, 26, 33-39. Dunst, C., Trivette, C., & Deal, A. (1988). Enabling and empowering families. Cam- bridge, MA: Brookline Books. Filipek, P.A., Accardo, P. J., Baranek, G. T., Cook, E. H., Jr., Dawson, G., Gordon, B., et al. (1999). The screening and diagnosis of autistic spectrum disorders. Journal of Autism and Developmental Disorders, 29, 439—484. Fine, M., & Gardner, A. (1994). Collabora- tive consultation with families of children with special needs: Why bother? Journal of Educational and Psychological Consultation, 5, 283-308. Fine, M. J., & Simpson, R. L. (2000). Col- laboration with parents and families of chil- dren and youth with exceptionalities (2nd ed.). Austin, TX: PRO-ED. Greenberg, L. W., Jewett, L. S., Gluck, R. S., Champion, L. A., Leikin, S. L., Altieri, M. F., & Lipnick, R N. (1984). Giving in- formation for a life threatening diagnosis. American Journal of Diseases of Children, 138, 649-653. Gresham, F. M., Beebe-Frankenberger, M. R, & MacMillian, D. L. (1999). A se- lective review of treatments for children with autism: Description and methodolog- ical considerations. School Psychology Review, 28, 559—575. Howlin, P. (1998). 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Washington, DC: National Association of School Psycholo- gists. at FLORIDA INTERNATIONAL UNIV on June 16, 2015 foa.sagepub.com Downloaded from 43 ’ APPENDIX Codes A. Phase of Study: SV-1 Site Visit 1 (interview 1) SV-2 Site Visit 2 (interview 2) SV-3 Site Visit 3 (interview 3) B. Participants: (followed by the number) Family Members FM Mother (1-15) FD Father (1-2) – Professionals &dquo PY Psychologist (1-3) ’ ,.. PT Physical Therapist (1) ’ ’ ° OT Occupational Therapist (1-2) .. SL Speech/Language Pathologist (1-3) . ’ . ’ ’ SW Social Worker (1) . ’ . ’ ’ PO Other Professional (1 ) ’° – C. Individual Idea or Thought: the individual idea or thought obtained from the interview (e.g., M, AQ, BX) For example, SV1-PY2-K = individual idea or thought (K) obtained during Psychologist 2’s Site Visit 1 interview at FLORIDA INTERNATIONAL UNIV on June 16, 2015 foa.sagepub.com Downloaded from
4 Separate Papers. Write a one-page review, single spaced of each of the assigned readings. Article responses should include a description of the article itself and a reaction to the article. I will a
PARENTALPERCEPTIONSOFSUPPLEMENTAL INTERVENTIONSRECEIVEDBYYOUNG CHILDRENWITHAUTISMININTENSIVE BEHAVIORANALYTICTREATMENT Tristram Smith*and Michelle Antolovich Department of Psychology, Washington State University, USA Parents of children with autism in applied behavior analytic treatment were surveyed on their use and perceptions of supplemental treatments. In study 1, respondents (Nˆ121) reported enrolling their children in an average of seven supplemental interventions, most commonly non-behavior- analytic speech therapies (85%), megavitamins (61%), Sensory Integration Therapy (56%), and elimination diets (50%). In study 2, parents (Nˆ24) were interviewed about these four inter- ventions and typically reported little or no bene®t. Factors that parents cited as in¯uencing their decision to obtain supplemental interventions for their children varied substantially, depending on the individual intervention. Because of the extensive use of unvalidated interventions that parents deemed unhelpful, it seems important to reduce children’s participation in such interventions. However, because of the diverse in¯uences on parents’ decisions to obtain the interventions, a multifaceted strategy may be needed. Copyright# 2000 John Wiley & Sons, Ltd. Applied behavior analytic (ABA) treatment for children with autism has been the topic of many hundreds of studies since the early 1960s (Matson, Benavidez, Compton, Paclawskyj, & Baglio, 1996) and has long been recognized as the intervention having the most empirical support for these children (e.g., DeMyer, Hingtgen, & Jackson, 1981). Nevertheless, children with autism who participate in ABA treatment may also receive various other forms of intervention, such as speech therapy (Prizant, Schuler, Wetherby, & Rydell, 1997), Sensorimotor Integration Therapy (Ayres, 1972), play therapy (Greenspan, 1992), psychotropic medication (Campbell & Hueva, 1995), and alternative medicine, including elimination diets and megavitamin therapies (Rimland & Baker, 1996). These interventions may complement behavior analytic treatment by enhancing children’s skills or reducing maladaptive behaviors that hinder children’s progress, such as aggression or stereotypies. Conversely, they may undermine Copyright# 2000 John Wiley & Sons, Ltd. Behavioral Interventions Behav. Intervent.15: 83±97 (2000) * Correspondence to: Tristram Smith, Department of Psychology, Washington State University, P.O. Box 644820, Pullman, WA 99164-4820, USA. E-mail address: [email protected] this treatment by diverting limited resources into interventions that are ine€ective or even harmful (Jacobson, Mulick, & Schwartz, 1995). Given the potential costs and bene®ts of these supplemental interventions, information about their use is important to obtain. Though investigators have noted that supplemental interventions appear quite common (e.g., Green, 1996), precise data are sparse with regard to the rate at which children with autism receive these interventions, when and why their parents select them, and how e€ective parents perceive them to be. Aman, Van Bourgondien, Wolford, and Saphare (1995) found that, in a community sample, individuals with autism were more likely to receive standard psychotropic medications (such as the ones mentioned above) than alternative medicine. However, this ®nding may not apply to individuals in ABA treatment because the combination of such treat- ment with alternative medicine is often recommended to families (e.g., Rimland, 1998). Informal surveys have suggested that families may evaluate alternative medicine interventions such as megavitamins more favorably than standard psychotropic medicine (e.g., Rimland, 1987), but it is unclear whether this ®nding would be replicable in a more comprehensive investigation. A peer-reviewed survey indicated that parents gave positive ratings to one sensorimotor therapy, Auditory Integration Training (AIT), which is intended to reduce hypersensitivity to sounds (Rimland & Edelson, 1987). However, well studied ABA procedures also exist to address this problem (Charlop-Christy & Kelso, 1997, pp. 169±175). Therefore, parents of children in ABA treatment may have a di€erent perspective on AIT than the parents in the study by Rimland and Edelson (1994). The purpose of the present investigation was to obtain additional infor- mation on supplemental interventions received by children who were par- ticipating in one form of ABA treatment (the UCLA Treatment Model; Smith, Donahoe, & Davis, in press). Study 1 surveyed a wide range of supplemental interventions, while study 2 focused in more detail on the most common interventions identi®ed in study 1. STUDY 1 Method Participants Surveys were sent to all families (Nˆ290) receiving workshop consultations from the Multisite Young Autism Project (MYAP) in the United States on how to implement the UCLA Treatment Model (Smithet al., in press) for their 84 T. Smith and M. Antolovich Copyright# 2000 John Wiley & Sons, Ltd.Behav. Intervent.15: 83±97 (2000) children with autism. All families were self-referred. Children in these families were under ®ve years old at treatment onset and had received a diagnosis of autism from a licensed psychologist or physician unaliated with MYAP. At the time of this mailing (December, 1995), MYAP sites were as follows: Northwest Young Autism Project (NYAP; Director: Tristram Smith, Ph.D.), University of California Ð Los Angeles (Director: O. Ivar Lovaas, Ph.D.), Central Valley Autism Project (Modesto, CA; Directors: Mila Amerine-Dickens, M.S., and Howard Cohen, Ph.D.), and Bancroft School (Haddon®eld, NJ; Directors: Scott Wright, B.S., and Kathy Dyer, Ph.D.). Consultations (described by Smithet al., in press) consisted of 1±3 day workshops every 2±3 months for children, their families, and paraprofessional therapists who had been hired by the families to implement the treatment. Procedure Based on a review by Smith (1996) of interventions commonly o€ered to children with autism besides ABA treatment, a 15 minute, written survey (avail- able from the ®rst author) was developed for parents to check o€ which interventions their children had received at any point in their lives and to rate the impact of these interventions as positive, negative, or neither. The survey con- tained space for parents to write comments, if they wished, about particular interventions and to list interventions that were omitted from the survey but implemented with their child. The investigators sent survey forms and stamped, self-addressed envelopes to the directors of each site in MYAP. The directors then distributed the forms and envelopes to all families receiving consultations from their site. All forms included a cover sheet stating that the information was anonymous and that participation was voluntary. Classroom interventions were excluded from the present report because the UCLA treatment includes procedures for helping children adjust to such settings. The survey included the following interventions, which, with the exception of some speech therapies and the ®rst four biomedical interventions listed, are viewed with skepticism by most researchers (Smith, 1996). .Non-behavior-analytic speech therapies (Prizantet al., 1997). .Sensorimotor therapies: (a) Sensory Integration Therapy (SIT; stimulating children’s skin and vestibular system through activities such as brushing parts of children’s bodies, squeezing parts of their bodies, swinging on hammocks, and spinning in circles on specially constructed chairs; Ayres, 1972); (b) Auditory Integration Therapy (determining sound frequencies to which children may be sensitive and then using headphones to listen to music from Supplemental interventions 85 Copyright# 2000 John Wiley & Sons, Ltd.Behav. Intervent.15: 83±97 (2000) which these frequencies have been ®ltered out; Rimland & Edelson, 1994); (c) Facilitated Communication (using an adult facilitator to guide children’s hands as they type on a keyboard; Biklen, 1993). .Individual therapies: (a) psychoanalysis ( providing as much freedom as possible in an atmosphere of warmth and love, so that children can overcome disrupted relationships with parents; Bettelheim, 1967); (b) the Greenspan (1992) model (helping children `form a sense of their own personhood’ ( p. 5) through playful, emotion-laden interactions with therapists and parents); (c) humanistic play therapy ( playing with toys in a setting where children receive unconditional positive regard; DesLauriers & Carlson, 1969); Gentle Teaching (exhibiting unconditional and authentic valuing of children so that bonding occurs between children and parents; McGee & Gonzales, 1990); Options ( providing individualized, loving attention to a child in a residential setting for most of the child’s waking hours; Kaufman, 1976); Holding Therapy ( forcibly holding the child so as to cause `the autistic defense . . . to crumble’ (Welch, 1987, p. 48). .Biomedical treatments: (a) antidepressants, (b) neuroleptics, (c) amphet- amines, (d) anticonvulsants, (e) anxiolytics ((a)±(e) reviewed by Campbell & Hueva, 1995), ( f ) megadoses of B6 with magnesium (Rimland, 1987), and (g) elimination diets (diets in which children are forbidden to consume additives such as preservatives or certain foods such as dairy products, wheat, or yeast; Crook, 1987). Results and Discussion Of the 290 surveys sent out, 121 (42%) were returned. Children reportedly had received an average of seven supplemental interventions (range 0±15). As shown in Table 1, the most frequently used interventions were (a) non-behavior-analytic speech and language therapy (85%), (b) megadoses of B6 with magnesium (61%), (c) Sensory Integration Therapy (56%), and (d) elimination diets (50%). Apart from these interventions, parents reported 20 diverse, additional inter- ventions, as listed in Table 1. Individual therapies such as Gentle Teaching and standard psychotropic medications such as Selective Serotonin Reuptake Inhi- bitors (SSRIs) were rarer than sensorimotor therapies and alternative medicine. Parents tended to rate supplemental interventions, regardless of type, as bene- ®cial (50%) or neutral (38%). They seldom deemed interventions harmful (9%). Overall, then, children in this study were participating in numerous supple- mental interventions, and parents often rated these interventions highly. Because of the low return rate (42%), these results may not have been representative of all 86 T. Smith and M. Antolovich Copyright# 2000 John Wiley & Sons, Ltd.Behav. Intervent.15: 83±97 (2000) families in MYAP. For example, parents who endorsed many supplemental treatments may have been more inclined than other parents to respond to the survey. Even so, it is evident that many families’ investment in supplemental interventions was very high. STUDY 2 The present study was designed to examine when and why parents decided to obtain supplemental interventions for their children and what speci®c bene®ts they attributed to these interventions. Of particular interest were (a) whether the onset of ABA treatment was associated with changes in the use of supple- mental interventions (e.g., whether children’s participation in such interventions increased or decreased), (b) how parents learned about the interventions, (c) what Table 1. Supplemental treatments used by workshop and clinic clients at UCLA and replication sites (Nˆ121) Therapy No. of respondents Helpful Harmful Neither/unsure Speech therapy a 103 61 3 39 Sensorimotor Tx Sensory Integration 68 38 1 29 Auditory Integration 36 18 0 15 Facilitated Commun. 7 5 0 2 Psychotherapy Psychoanalysis 7 0 2 5 Greenspan Model 12 6 3 3 Humanistic Play Tx 4 1 0 3 Gentle Teaching 1 0 1 0 Options 2 0 0 2 Biomedical Tx Antidepressants b 24 11 7 6 Antipsychotics c 511 3 Amphetamines d 11 7 2 2 Elimination diets e 60 39 0 20 B6‡Mg 74 28 1 41 aSpeech therapy based on a theoretical orientation other than behavior analysis. bFluoxetine (13), clomipramine (3), imipramine (2), paroxitine (1), ¯uvoxamine (1), unspeci®ed (4).cRisperidone (1), thioridizine (1), clonidine (1), unspeci®ed (2).dMethylphenidate (7), pomadine (3), d-Amphetamine (1).e(Includes reports of multiple diets): Feingold diet (6), elimination of other foods Ð dairy (33), gluten/wheat (24), casein (8), sucrose (6), yeast (5), chocolate (4), other/unspeci®ed (11). Note: No reports of the use of Holding Therapy or anxiolytic and anti-convulsant medications. Additional behavior analytic treatment (32); other interventions: occupational therapy (5), music therapy (4), physical therapy (2), Kaplan Visual Therapy (special eyeglasses, 2), gammaglobulin infusions (1), Cranial Vascular Therapy (1), therapeutic horseback riding (1), chiropractics/herbal therapy (1), residential treatment (1). Supplemental interventions 87 Copyright# 2000 John Wiley & Sons, Ltd.Behav. Intervent.15: 83±97 (2000) factors were most in¯uential in the parents’ decision to utilize the interventions, and (d) what behavioral changes parents noted. The study focused on the four interventions that 50% or more of the respondents in study 1 reportedly used (speech therapy, megavitamins, Sensory Integration Therapy, and elimination diets). Method Participants Participants were 24 of the 25 primary caregivers for children receiving workshop consultations from the authors’ treatment site (NYAP). The criteria for enrolling children and the format of the workshop consultations were the same as in study 1. Twenty participants were the biological mothers of the children receiving workshops; 19 of these mothers were married to the children’s biological fathers at the time of the study, while the other was a single parent. The remaining four respondents were children’s biological fathers (all married to the children’s biological mothers at the time of the study). Seventeen mothers were homemakers; ®ve were professionals such as teachers or nurses; and two were business executives. Fathers’ occupations included one homemaker, four teachers, three business executives, six professionals in engineering or comput- ing, four administrators or small business managers, two unskilled manual laborers, one skilled manual laborer, and one clerical worker. The mean number of children per household was 2.36 (SDˆ1.08, rangeˆ0±5). Thus, families were above average in the proportion of two-parent households, mothers who were homemakers, and fathers who were employed in professional occupations; they also had an above-average number of children (Berk, 2000). The mean chronological age of their children with autism was 54.09 months (SDˆ14.27). Children had received a mean of 13.24 months (SDˆ9.56) of ABA treatment with workshop consultations from NYAP. Procedure Telephone interviews were conducted with each participant by an NYAP workshop consultant who was naõ Ève as to children’s histories with supplemental interventions. The interview (available from the ®rst author) was 30±60 minutes in length. The interviewer asked a series of standardized questions about each of the four interventions (speech therapy, megavitamins, Sensory Integration Therapy, and elimination diets) on the following topics: (a) starting and stopping 88 T. Smith and M. Antolovich Copyright# 2000 John Wiley & Sons, Ltd.Behav. Intervent.15: 83±97 (2000) date(s) for the intervention, (b) speci®c intervention techniques implemented, (c) the source from which parents ®rst learned about the intervention (other parents, service providers, or publications), as well as the source that was most in¯uential in their decision to obtain the intervention, (d) features of the inter- vention itself that contributed to their decisions (e.g., research support, theory or philosophy underlying the intervention, or recommendations by parents or professionals), and (e) particular problems that spurred parents to start the intervention at the particular time they did. After receiving a response to each standardized question, the interviewer had the discretion to seek clari®cation by asking individual follow-up questions. The interviewer also asked parents to rate the e€ects of the intervention for their children on a scale from 1 (much worse) to 5 (much improved), with 3 denoting no change. Parents made one rating for each of six domains: language and communication, aggression and tantrums, social skills, self-stimulatory and ritualistic behaviors, play skills, and self-help. The interviewer wrote down responses verbatim and, after the completion of the interview, coded the responses. To check reliability, an independent rater, who was an NYAP workshop consultant, independently coded 25% of the interviews. The interviewer and rater received no training except for one hour of instruction on coding speech therapy techniques into the following categories: .model based (e.g., Greenspan (1992) approach); .structured (speci®c activities and target behaviors for sessions selected by therapist, but no particular instructional format (e.g., discrete trials) used); .naturalistic (Wilcox & Shannon, 1998): (a) responsive adult interactions (expanding on the child’s utterances and commenting on his/her activities) or (b) global interactive activities (e.g., turn taking or other activities). Results and Discussion Interrater reliability was acceptable (96% agreement across responses). Table 2 summarizes the types of intervention children received and parent ratings of the e€ects of these interventions. As in study 1, parents were more likely to report positive than negative e€ects. However, they almost always reported that positive e€ects were small. Indeed, there were only two reports of major gains: one parent described large improvements across behavioral domains with speech therapy, and another parent described similar improve- Supplemental interventions 89 Copyright# 2000 John Wiley & Sons, Ltd.Behav. Intervent.15: 83±97 (2000) Table 2. Types of supplemental interventions and parent ratings of ecacy Speech therapy (nˆ19)Diets (nˆ7)SIT (nˆ10)Vitamins (nˆ11) Type Structurednˆ8 Global interactionsˆ3 Structured‡globalˆ3 Unknownˆ3Dairynˆ1 Wheatˆ1 Dairy‡wheatˆ2 Wheat‡yeastˆ2 Dairy‡wheat‡yeastˆ1Vestibular stimulationnˆ2 Tactile stimulationˆ2 Pressure‡vest.ˆ2 Pressure‡Tact.ˆ2 Pressure‡vest.‡tact.ˆ3B6‡Mgnˆ7 B6‡Mg‡DMGˆ4 Months of Tx (M(SD)) 15.68 (9.32) 5.43 (3.91) 8.60 (6.55) 4.00 (2.75) Amount of Tx (M(SD)) 1.19 (0.69) hours/week n.a. 1.33 (1.09) hours/week Milligrams/day: B6: 352.50 (185.81) Mg: 195.31 (94.72) Parent ratings (M(SD)) a Language 3.55 (0.76) 3.57 (0.78) 3.27 (0.47) 3.36 (0.67) Tantrums/aggression 3.21 (0.71) 3.43 (0.98) 3.27 (0.47) 3.46 (0.69) Social skills 3.37 (0.60) 3.43 (0.78) 3.46 (0.69) 3.36 (0.67) Ritualistic behavior 3.21 (0.71) 3.14 (0.78) 3.27 (0.47) 3.55 (0.82) Play 3.21 (0.71) 3.43 (0.78) 3.18 (0.41) 3.46 (0.69) Self-help 3.21 (0.63) 3.50 (0.84) 3.18 (0.41) 3.27 (0.67) aRatings of behavioral change from 1 (much worse) to 5 (much better), with 3 denoting no e€ect. No statistically signi®cant di€erences between groups. 90 T. Smith and M. Antolovich Copyright# 2000 John Wiley & Sons, Ltd.Behav. Intervent.15: 83±97 (2000) ments with megavitamins and diets. 1Seven parents who reported continuing with speech therapy, despite low ratings of ecacy, indicated that they did so because they received funding for this intervention. Two parents also cited funding as a reason for continuing SIT. Except for megavitamins, the particular techniques used in each intervention reportedly varied across children (Table 2). Such variation could perhaps have been expected for speech therapy because service providers hold diverse theor- etical orientations (Berkell Zager, 1999) and because children with autism exhibit a wide range of communication de®cits. It may also have been predictable for diets because parents selected particular regimens based on their obser- vations of foods to which their children might be sensitive. However, the range of SIT techniques was more dicult to account for, given that service providers shared a speci®c theoretical orientation and repertoire of therapeutic techniques. Parent interviews and reports on ®le did not indicate a clear assessment procedure for selecting particular techniques. Thus, although previous reviews of SIT have centered on the extent to which its theory and therapy are supported by research (e.g., Arendt, MacLean, & Baumeister, 1988), its assessment procedures may also warrant scrutiny. 1The report of major gains with speech therapy was made by the parent of one child who received intervention based on the Greenspan (1992) model prior to the onset of ABA treatment. This report received some corroboration from an increase in verbal IQ from 61 to 80 during this period, as measured by the Wechsler Preschool and Primary Scales of Intelligence Ð Revised (Wechsler, 1989), administered by an examiner independent of the authors’s clinic. Greenspan’s model emphasizes having a parent or therapist interrupt children’s activities (e.g., stopping them from turning the wheels on a car) so that children must communicate with the adult in order to resume the activity. This approach could be viewed as a form of incidental teaching (Hart & Risley, 1968) and hence may be bene®cial for some children. However, the child who reportedly made large gains with this approach in the present study was concurrently receiving other services ( participating in a regular education class with a full-time aide). Hence, the e€ects of speech therapy for this child were unclear. The one report of major gains with diets and megavitamins, which the parent introduced simultaneously to the child 5 months after the onset of ABA treatment, could not be corroborated. For example, according to records from the child’s logbook for ABA treatment, the following were the number of mastered responses in all instructional programs in which multiple responses were being trained, as recorded during each workshop consultation before and after the onset of diets and megavitamins. Nonverbal Imitation Ð (B)efore: 10, 15, 37, (A)fter: 44, 44‡; Receptive Commands Ð B: 5, 8, 34, A: 38, 50; Receptive Action Labels Ð B: 1, 23, 32, A: 41, 60; Expressive Action Labels Ð B: 0, 30, 36, A: 40, 60; Receptive Opposite Pairs Ð 0, 1, 3, A: 6, 11, 28; Answering Conversational Questions Ð B: 0, 2, 14, A: 16, 16‡; Counting (one-to-one correspondence) Ð B: 10, A: 10, 15, 20. All workshop consultations occurred 10±12 weeks apart. To determine whether an intervention might have been ecacious even though the parent reported no change, all interventions that were introduced after the onset of ABA treatment were examined. No signi®cant bene®ts were detected, when `signi®cant bene®ts’ were de®ned as a 50% increase in the rate of acquisition in any ABA instructional program in which multiple responses were being trained. (An example of a signi®cant bene®t would be a 50% increase in the number of mastered responses from one workshop consultation to the next before the onset of the supplemental intervention (e.g., from 4 to 6 to 9), and a 75% increase after (e.g., from 9 to 16 to 28).) Because the analyses in this note were unplanned and uncontrolled, they must be viewed with caution. Supplemental interventions 91 Copyright# 2000 John Wiley & Sons, Ltd.Behav. Intervent.15: 83±97 (2000) Table 3 summarizes parents’ responses about when and why they obtained supplemental interventions. As shown, 19 of 24 reported that their children had received non-ABA speech therapy. (Four of the other ®ve, not included in the table, reported that their children had received speech therapy that was closely coordinated with their ABA treatment, though most noted that they switched therapists two or three times before ®nding one willing to work in this manner.) According to parent report, 18 of 19 began speech therapy prior to ABA treatment, with 15 of these 18 remaining in the intervention after starting ABA treatment (13 continuing to the time of the present study). By contrast, mega- vitamins, SIT, and elimination diets tended to start after ABA treatment and, with the possible exception of diets, tended to stop before the present study. Table 3. When and why parents sought supplemental interventions Speech (nˆ19)Diets (nˆ7)SIT (nˆ11)Vitamins (nˆ11) When a Before ABA onlynˆ3nˆ0nˆ2nˆ2 During ABA only 1 6 5 9 Before‡after ABA b 15140 Source of information a Medical personnel 12 0 2 0 Educators 3 0 2 0 Other professionals 3 0 6 0 Parents 1 5 0 2 Autism publications 0 2 1 9 Reason for obtaining tx a Recommendation Service provider 9 0 4 0 Parent 1 4 0 2 Author on autism 0 1 0 3 Research 0 2 0 5 Theory 0 0 4 0 Intuitive appeal 9 0 1 1 Enjoyment for child 0 0 2 0 Child problem spurring tx a Language 19 0 1 0 Disruptive behavior 0 4 7 4 Ritualistic behavior 0 1 2 0 Slow progress in ABA 0 1 0 2 None 0 1 1 5 ap50.05 for 2(speech therapy versus all other interventions combined) 2(most common response for speech therapy versus all other responses combined) chi-square. bNumber of children currently in intervention: speech (15), diets (4), SIT (3), vitamins (4). 92 T. Smith and M. Antolovich Copyright# 2000 John Wiley & Sons, Ltd.Behav. Intervent.15: 83±97 (2000) Most parents indicated that they learned about speech therapy from the medical personnel who diagnosed their children with autism. However, they said they typically learned about SIT from service providers for their child (speech thera- pists, educators, and, in one case, a behavioral consultant), while they received information about megavitamins and diets primarily from other parents or from nontechnical publications on autism ( parents most often citedAutism Research Review International). Additional di€erences emerged regarding which aspects of interventions were attractive to parents (Table 3). Professional recommendations and intuitive appeal were reportedly the main in¯uences on the decision to obtain speech therapy. Professional recommendations were also commonly cited for SIT, but never for megavitamins or diets, which were usually said to have been selected based on parent recommendations, research evidence, or advice given by writers on autism. Unsurprisingly, parents almost always indicated that delayed lang- uage was the problem that spurred them to initiate speech therapy. However, they tended to identify disruptive behaviors as the impetus for megavitamins, SIT, and diets. Across interventions, parents reported that the problems they sought to alleviate were longstanding concerns rather than acute crises. GENERAL DISCUSSION Most children with autism in the present investigation received many supple- mental interventions in addition to ABA treatment. Parents were more likely to rate interventions as helpful than harmful, but almost always indicated that any improvements were small and isolated to a few behaviors. Factors that in¯uenced parents’ decisions to obtain supplemental interventions for their children di€ered substantially, depending on the individual intervention. For example, most parents stated that they learned about speech therapy at the time their children received a diagnosis of autism, and that the source tended to be professionals involved in this diagnosis. They indicated that they did not become aware of other interventions until later, typically ®nding out about SIT from their children’s therapists, about diets from other parents, and about megavitamins from nontechnical autism publications, especially newsletters. Most children reportedly started speech therapy before ABA treatment and continued it to the time of the present investigation, whereas they tended to start the other treatments after ABA treatment and then stop them. Parents kept their children in some interventions that they considered ine€ective, reportedly because they received funding for doing so. Supplemental interventions 93 Copyright# 2000 John Wiley & Sons, Ltd.Behav. Intervent.15: 83±97 (2000) The present investigation had several limitations. First, almost all families in the present study had two parents, with at least one working in a profes- sional occupation. Moreover, families were self-referred and were obtaining consultations on how to set up and run their own treatment programs in their homes, as opposed to utilizing services already available in their communities. Thus, they appeared to have above-average socioeconomic status and high motivation to secure assistance for their children. These circum- stances may have led them to initiate more interventions of all types than is usual for families in other ABA treatment programs. Also, as previously noted, the use of supplemental interventions may have appeared especially high because of the return rate in study 1 (42%). In addition to these possible biases, the reliance on parental reports in studies 1 and 2, as well as the small sample for some interventions in study 2, may have yielded information that was sometimes unreliable. Finally, because of the limitations of such reports, it was not possible to assess the quali®cations of those who implemented supplemental interven- tions or the ®delity with which these interventions were applied. Despite the foregoing shortcomings, however, the present investigation revealed extensive use of supplemental interventions by one group of children with autism in ABA treatment. Moreover, this use appeared to increase rather than decrease after the onset of ABA treatment. Such increases have also been reported in other clinical populations receiving a variety of interventions (Lam- bert & Bergin, 1994, pp. 175±176). Investigators have interpreted this phenom- enon as evidence that individuals were reinforced for seeking help and hence were predisposed to obtain additional help. Such an interpretation may apply to parents in the present investigation. However, the parents themselves took a di€erent view, reporting that they started supplemental interventions after ABA treatment mainly because they did not ®nd out about the interventions until then. As with many other interventions for behavior problems (Seligman, 1995), parents more often rated supplemental interventions favorably than unfavor- ably, though they generally described bene®ts as modest. Controversy exists over the extent to which such favorable ratings re¯ect genuine improvement (Seligman, 1995), as opposed to response bias (e.g., motivation to describe an intervention as worthwhile after having devoted time, e€ort, and resources to it; Jacobson & Christensen, 1996). In the present study, parent reports appeared grossly consistent with data from behavior observations, except for one uncorroborated report of large improvements (Footnote 1). To obtain more detailed information on the correlation between parent report and other evalu- ations, future research should focus on interventions that, in contrast to those investigated in this study, have clearly de®ned, speci®c, objectively measured behavioral goals. 94 T. Smith and M. Antolovich Copyright# 2000 John Wiley & Sons, Ltd.Behav. Intervent.15: 83±97 (2000) The frequent use of supplemental interventions and the tendency to rate these interventions favorably indicate that, despite their often questionable research basis, supplemental interventions have high social validity (Schwartz & Baer, 1978; Wolf, 1978). Moreover, this social validity appears to be a function of multiple antecedents and consequences. Antecedents cited by parents included professional referrals, parent recommendations, and information suggesting that interventions had scienti®c support. Consequences included not only perceived bene®ts from the interventions but also other favorable outcomes such as increase funding for their children. Given the prevalence of supplemental interventions, treatment outcome studies on children with autism may need to include measures of such inter- ventions. Studies to data have not done so (cf. Smith, 1999). Also, because most of these interventions were unsupported by methodologically rigorous research (New York State Department of Health, 1999) and were described by parents as providing little or no bene®t, it seems important to reduce their use. In view of the multiple antecedents and consequences associated with such interventions, this may be a complex undertaking. For example, professionals have often recommended that investigators combat questionable interventions by reporting their ®ndings in the popular media and rebutting credulous stories that appear in such outlets. This strategy might be e€ective with interventions such as mega- vitamins, for which nontechnical publications on autism were reportedly the primary in¯uence. However, it might not be e€ective with other interventions such as diets or SIT, for which person-to-person recommendations rather than the popular media were most frequently cited. Educating parents and pro- fessionals on how to evaluate whether treatment recommendations are scienti®c- ally sound may help with these interventions. However, education by itself may be insucient. Parents in the present study often reported that they kept their children in interventions, despite having concluded that the interventions were unhelpful, because they received funding to do so. Besides education, therefore, it may be necessary to in¯uence the policies of funding agencies. In general, then, professionals are likely to need a multifaceted approach to reduce the use of supplemental interventions. 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