Professionals’ Reported Provision and Recommendation of Psychosocial Interventions for Youth With Autism Spectrum Disorder

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Professionals’ Reported Provision and Recommendation of Psychosocial Interventions for Youth With Autism Spectrum Disorder Lillian M. Christon University of North Carolina–Chapel Hill Cassidy C. Arnold Barbara J. Myers Virginia Commonwealth University

Children and adolescents with autism spectrum disorder (ASD) receive intervention services from multiple professionals across disciplines. Little is known about services for youth with ASD in community settings. The purpose of this study was to provide data on professionals’ self-reported practices across different classes of psychosocial interventions for youth with ASD. A multidisciplinary (medicine/nursing, education, occupational/physical therapy, psychology, social work, and speech-language pathology/audiology) sample (N = 709; 86% female; 86% White) of professionals who endorsed providing clinical services to youth with ASD was recruited through convenience sampling (listservs, etc.) and stratified random sampling (online provider listings). Professionals completed a survey on intervention practices with youth with ASD, specifically on their own provision of, as well as their recommendation/referral of, psychosocial interventions (focused intervention practices [FIPs], comprehensive treatment models [CTMs], and other interventions). Hierarchical multiple regression models showed discipline differences in self-reported provision and recommendation of evidence-based FIPs; training variables and unfamiliarity with FIPs predicted rates of providing and recommending.

This research was supported in part by a grant from the Organization for Autism Research. We are grateful to Bryce D. McLeod for his helpful feedback on an earlier version of this paper. Address correspondence to Lillian Christon, Department of Psychology, University of North Carolina–Chapel Hill, Davie Hall Campus Box 3270, Chapel Hill, NC 27599; e-mail: [email protected]. 0005-7894/xx/xxx-xxx/$1.00/0 © 2014 Association for Behavioral and Cognitive Therapies. Published by Elsevier Ltd. All rights reserved.

FIPs were reportedly provided and recommended at higher rates than CTMs. Descriptive data are presented on professionals’ reported practice of other psychosocial interventions (e.g., cognitive-behavioral therapy). This study highlights the usefulness of examining not only provision of services but also recommendation/referral practices: professionals are important sources of information for families. Implications of the results are discussed in terms of the importance of disseminating intervention information to professionals and the need for consensus on terminology used to classify interventions and on criteria used to evaluate intervention efficacy.

Keywords: autism; multidisciplinary; professionals; psychosocial interventions

YOUTH WITH AUTISM SPECTRUM disorder (ASD) have multiple areas of impairment including deficits in social communication and interaction and restricted or repetitive patterns of behavior, interests, or activities (DSM-5; America n Psychiatric Association, 2013). In addition to core symptoms, many youth have accompanying intellectual and/or language impairments and/or comorbid disorders (e.g., anxiety, mood, and behavioral disorders; Simonoff et al., 2008). Given multiple domains of impairment, youth with ASD often receive interventions from professionals from numerous disciplines in diverse settings (e.g., school, outpatient, and medical settings; Goin-Kochel, Mackintosh, & Myers, 2007). These youth also receive services at higher rates than

Please cite this article as: Lillian M. Christon, et al., Professionals’ Reported Provision and Recommendation of Psychosocial Interventions for Youth With Autism Spectrum Disorder, Behavior Therapy (2014), http://dx.doi.org/10.1016/j.beth.2014.02.002

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children with other special health care needs (e.g., medical disorders, emotional/behavioral problems; Montes, Halterman, & Magyar, 2009). This study examines service delivery for youth with ASD from professionals’ perspectives rather than parents’ (e.g., Goin-Kochel et al., 2007), across multiple disciplines rather than within single disciplines (e.g., Hess, Morrier, Heflin, & Ivey, 2008), and examines provider-level factors influencing provision and recommendation of services.

why focus on professionals’ practice? As the prevalence rates of ASD increase, the number of professionals being called upon to provide services to these youth is growing (Chiri & Warfield, 2012). Throughout childhood, it is common for youth with ASD to interact with many different professionals from various disciplines, and receive many types of intervention to address deficits, improve functioning, and reduce problem behaviors (e.g., McLennan, Huculak, & Sheehan, 2008). The disciplines that most frequently provide services to youth with ASD include education, medicine/nursing, occupational/physical therapy, psychology speech language pathology (SLP)/audiology, and social work (e.g., McLennan et al., 2008). Communication across disciplines working with youth with ASD can be difficult, as they “speak different languages, have different research traditions, and bring their own unique perspectives to this population” (Volkmar, Reichow, & Doehring, 2011, p. 374). A focus on professionals’ practices is needed to assess the extent to which elements of high-quality care are being provided to youth with ASD, and to identify areas for improvement in training and education. Navigating the landscape of ASD intervention is particularly challenging for families due to (a) the sheer number of available ASD interventions targeting core and associated symptoms (GoinKochel et al., 2007), (b) the fact that interventions are provided across professional disciplines (McLennan et al., 2008), and (c) the decentralized nature of ASD treatment delivery (Carbone, Behl, Azor, & Murphy, 2010). Confronted with a heterogeneous disorder and many different intervention options, families of youth with ASD must make decisions about which interventions to use and from which professionals. Treatment evaluation research suggests that some interventions do ameliorate the ASD symptoms (e.g., Rogers & Vismara, 2008); however, it is unclear to what extent community professionals are providing and recommending these, or other, interventions. Data on professionals’ practice would help to delineate the current landscape of services for youth with

ASD and would give a rough benchmark against which to evaluate dissemination efforts for specific interventions across professional disciplines.

why examine professionals’ intervention recommendations/ referrals? In addition to providing direct services to youth with ASD and their families, professionals also play an important role in educating families on available services and steering families toward efficacious interventions. One way that professionals guide families toward efficacious interventions is by directly recommending interventions to families and youth, and referring them to appropriate providers if the interventions are outside their scope of practice. One Internet-based study of 498 parents who self-identified as having children with ASD found that parents rely on physicians (48% of parents), educators (49% of parents), and other professionals (e.g., speech-language pathologists, occupational therapists, psychologists; 57% of parents) as important sources of information (Mackintosh, Myers, & Goin-Kochel, 2007). Professionals and the information they provide can act as guides to families of youth with ASD in the intervention decision-making process (e.g., Kennedy Krieger Institute, 2013). A responsibility of professionals is to help families weigh intervention options and provide information about intervention efficacy. To do so, professionals working with children with ASD must be informed about the evidence for different interventions. Given the proliferation of complementary and alternative medicine treatments for ASD and the extraordinary cost or potential risks of some interventions (e.g., chelation; Christon, Mackintosh, & Myers, 2010), it is important for professionals to provide and recommend those interventions that “are likely to produce measurable improvements in the lives of persons with ASD and their families” (Lord & Bishop, 2010, p. 11). Family–professional interactions can steer families either toward or away from interventions with solid research evidence. Despite a general push toward the use of evidence-based interventions (EBIs) and practice across professional disciplines (e.g., Reichow & Volkmar, 2011), little is known about what ASD interventions community professionals recommend when they meet with families—an important, missing data point. To appreciate the value of other treatments and to give appropriate referrals and recommendations about interventions to families, professionals within a particular discipline must have, at minimum, a rudimentary understanding of what other disciplines

Please cite this article as: Lillian M. Christon, et al., Professionals’ Reported Provision and Recommendation of Psychosocial Interventions for Youth With Autism Spectrum Disorder, Behavior Therapy (2014), http://dx.doi.org/10.1016/j.beth.2014.02.002

professionals’ report on practices with youth with asd provide to youth in their mutual care. In a qualitative study of families’ and physicians’ perspectives on coordination of care for youth with ASD, Carbone and colleagues (2010) reported that parents reported wanting more guidance from their children’s pediatricians, especially with regard to selecting interventions and identifying community resources. In addition, Carbone and colleagues (2010, p. 322) summarize a distinct problem in the ASD field: Both parents and pediatricians in our study described a need for interdisciplinary models of care for children with ASDs, yet the current system of care is not integrated . . . The current systems of care exist in silos, with different eligibility requirements and treatment plans that are not integrated between systems. This lack of coordinated care results in confusion for families, mixed messages from different treatment providers and promotes adversarial relationships between various disciplines.

Adopting a multidisciplinary perspective is critical to better organize the ASD intervention landscape, as is turning attention to professionals’ intervention recommendations. The ASD intervention literature would benefit from greater clarity on a number of issues. These include identifying who is providing services, what services are being provided and recommended to families, what services are effective in community settings, and what services are adopted by service providers in community settings. This study aims to provide data concerning two of these questions with regard to psychosocial interventions for youth with ASD: (a) Which interventions do professionals report providing? and (b) Which interventions do professionals across disciplines report recommending to families of youth with ASD? Understanding the current landscape of ASD services and service providers will be beneficial as the effort to identify and train service providers ramps up to meet the growing clinical need (Chiri & Warfield, 2012).

the landscape of psychosocial interventions for asd The ASD literature distinguishes between different classifications of psychosocial ASD interventions. The following paragraphs articulate the classifications included in this study. The interventions presented are not an exhaustive list, and a discussion of nonpsychosocial interventions (e.g., pharmacological, sensory/motor) is beyond the scope of this paper. Focused intervention practices (FIPs) can be thought of as the “ingredients” (discrete strategies designed to teach specific skills) that, when combined, comprise “treatment packages” or comprehensive treatment models (CTMs; Odom, ColletKlingenberg, Rogers, & Hatton, 2010). FIPs may be

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implemented as components of larger intervention packages or to supplement treatment approaches (e.g., adapting cognitive-behavioral therapy [CBT] for ASD to include FIPs; e.g., Scarpa, White, & Attwood, 2013). One example of a FIP is visual supports (i.e., using schedules, pictures, arrangement of the environment or visual boundaries, etc.). Many FIPs are backed by strong empirical support (e.g., National Professional Development Center, 2010). Research suggests that, with training, community mental health professionals are able to deliver a package of evidence-based FIPs with integrity, and that this package reduces challenging behaviors in youth with ASD (Brookman-Frazee, Drahota, & Stadnick, 2012). However, little is known about the extent to which ASD professionals are already using FIPs. CTMs are conceptually organized packages of interventions that address a broad array of skills and abilities, and are based on specific theories (Odom, Boyd, Hall, & Hume, 2010). Most of these models are focused on treating young children (ages two to five years) and many are based on behavioral theories (National Research Council, 2001). CTMs have varying levels of empirical support (Rogers & Vismara, 2008). One example is Discrete Trial Training (UCLA Young Autism Project), which has its origins in applied behavioral analysis and uses a one-on-one discrete-trial format to teach skills in a systematic fashion (National Research Council, 2001). Many other psychosocial interventions available for youth with ASD have not yet garnered the research support necessary to be considered “wellestablished” treatments (to use Chambless & Ollendick’s [2001] terminology) or “EBIs” (National Autism Center, 2009). However, some of these other interventions (e.g., CBT, Picture Exchange Communication Systems) have growing evidence bases for their use with youth with ASD (National Autism Center, 2009). Psychodynamic therapy and play therapy do not have substantial empirical support for treating youth with ASD but may be used by professionals (e.g., Josefi & Ryan, 2004). CTMs and other interventions also share some common characteristics, such as including families as providers/coaches (e.g., see National Research Council, 2001, for a review). The purpose of this study is to advance the field’s understanding of professionals’ practice with youth with ASD in community settings. The rates at which professionals across six disciplines reported providing and recommending psychosocial interventions to youth with ASD are presented. We focused specifically on recruiting professionals from different disciplinary backgrounds known to provide

Please cite this article as: Lillian M. Christon, et al., Professionals’ Reported Provision and Recommendation of Psychosocial Interventions for Youth With Autism Spectrum Disorder, Behavior Therapy (2014), http://dx.doi.org/10.1016/j.beth.2014.02.002

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services to youth with ASDs. Based on scope of practice differences between disciplines, it was expected that there would be disciplinary differences in professionals’ self-reported provision and recommendation of evidence-based FIPs to youth with ASD. Further, it was hypothesized that training on EBIs and interventions for ASD would predict professionals’ reported provision and recommendation of evidence-based FIPs, after controlling for discipline differences. Exploratory analyses examined whether professionals reported providing and recommending FIPs or CTMs at higher rates. Descriptive data are presented on reported rates of providing and recommending common characteristics of CTMs and on other psychosocial interventions for ASD.

Method participants Inclusion criteria for participants (N = 709) consisted of (a) being among the six professional disciplines targeted and (b) providing direct clinical services (at least one half-day per week) to at least one youth (ages 0–18 years) with ASD in the past year. Participants endorsed providing services to an average of 37.42 (SD = 57.49) youth with ASD in the past year (range from 1 to 300). Participants reported serving youth ages (participants could “check all that apply,” so the sum is not 100%): 0– 2 years (n = 228; 32.16%), 3–5 years (n = 491; 69.25%), 6–11 years (n = 496; 69.96%), and 12– 18 years (n = 334; 47.11%). Professionals were recruited from the disciplines most frequently identified as providing services to youth with ASD (McLennan et al., 2008): education (i.e., special education teachers, school behavioral specialists, etc.; n = 157), medicine and nursing (i.e., physicians and nurse practitioners; n = 108), occupational and physical therapy (n = 100), psychology (clinical, counseling, school psychologists; n = 163), social work (n = 52), and SLP and audiology (n = 129). Eleven percent (n = 81) of participants had bachelor’s degrees, 52.33% (n = 371) had master’s degrees, and 36.25% (n = 257) had doctoral degrees. The average number of years in practice was 11.10 (SD = 9.55) years. Twelve percent (n = 85) were graduate students. Most participants (n = 591; 83.36%) endorsed having licensure or certification in their professional discipline. Participants ranged in age from 23 to 73 years (M = 39.18; SD = 11.61), and 86% (n = 608) were female. Their races/ethnicities were as follows: American Indian/Alaska Native (n = 5; 0.71%), Asian/Asian American (n = 26; 3.67%), Black/ African American (n = 14; 1.97%), Hispanic/Latino (n = 4.65%), Native Hawaiian/other Pacific Islander

(n = 2; 0.28%), White/Caucasian (n = 606; 85.47%), and biracial or other (n = 23; 3.24%). Participants lived within the United States (48 states and Washington, DC) and endorsed providing services in urban (n = 310; 43.72%), suburban (n = 324; 45.70%), and rural (n = 75; 10.58%) communities. They reported working in a variety of settings, including (participants could “check all that apply,” so the sum is not 100%): schools (n = 273; 38.5%), centers or clinics (n = 262; 37%), private practice (n = 185; 26.1%), hospitals (n = 168; 23.7%), early intervention (n = 77; 10.9%), residential (n = 39; 5.5%), and other settings (n = 56; 7.9%).

procedures The university’s IRB approved all study procedures. Data were collected between December 2011 and May 2012 with two sampling approaches: (a) a nonprobability convenience sample using multiple methods of recruitment (Sample 1, n = 573; 80.81%), and (b) a stratified random sample recruited from online provider listings (Sample 2, n = 136; 19.18%). This two-sample approach aimed to use multiple methodological techniques to increase the validity of the study’s findings in a form of methodological triangulation (Campbell & Fiske, 1959; Dootson, 1995). The purpose of Sample 1 was to increase statistical power and access professionals from many settings. The purpose of Sample 2 was to collect a representative sample of professionals in practice in community settings to address concerns related to self-selection bias in Internet-based survey data. Since a comprehensive list of professionals in community settings providing services to youth with ASD does not exist, the participants in Sample 2 were gathered from online provider listings that families themselves might use to find providers. Sample was controlled for in all study analyses. As an incentive for participating, participants were offered the opportunity to be entered into a drawing for gift cards. Sample 1 was recruited via listserv (Leadership Education in Neurodevelopmental and Related Disabilities, posted twice by their staff; listserv membership was unavailable to the authors), advertisements (e.g., Autism Speaks), newsletters (e.g., Organization for Autism Research), and snowball recruiting (i.e., asking professionals to send the survey to others in their profession). Participants filled out an Internet version of the survey, collected through REDCap electronic data capture tools (Center for Clinical and Translational Research, CTSA Award No. UL1RR031990). To create a sampling frame for Sample 2, six lists of professionals (one per discipline) were created from

Please cite this article as: Lillian M. Christon, et al., Professionals’ Reported Provision and Recommendation of Psychosocial Interventions for Youth With Autism Spectrum Disorder, Behavior Therapy (2014), http://dx.doi.org/10.1016/j.beth.2014.02.002

professionals’ report on practices with youth with asd publicly available “Find a Provider”-type listings across the 50 United States including Washington, DC (N = 17,423 professionals across discipline lists). The lists were generated from all professionals listed for each state from at least two sources for each discipline, one being a list of self-identified ASD providers from a professional organization for each discipline (e.g., American Speech-LanguageHearing Association for speech/language pathologists and audiologists), and the other from a list from an autism- or developmental disability-specific Web site (e.g., Autism Speaks). Professionals were randomly selected from each discipline list (n = 200) via a random number generator in IBM SPSS v19.0 to create a master list of 1,200 professionals. These professionals were mailed a copy of the survey and a reminder postcard 2 weeks later. This postcard reminder also included a link to an Internet version of the survey (identical to the one completed by Sample 1). The sample response rate was low (11.4%, after accounting for returned mailings).

measures This study was part of a larger survey of professionals’ practices with youth with ASD. Items followed Dillman, Smyth, and Christian’s (2009) guidelines for question formats and were created in consultation with professionals from the disciplines represented in the study. The survey was reviewed and completed by a pilot group of professionals in the ASD field (n = 7; one per discipline plus the third author) who provided feedback on readability and face validity of items and whether the intervention list represented the full range of ASD interventions. Background and Training Participants responded to demographics, discipline background, and training questions. Specifically, participants provided ratings regarding their training on ASD interventions (“I have received specific education and training on interventions for ASD [via either direct teaching or practical experiences]”) and their training on EBIs (“In my training, an explicit emphasis was placed on using evidence-based interventions [i.e., interventions based on the best scientific evidence]”) on 5-point Likert-type scales: 1 = strongly disagree, 2 = disagree, 3 = neutral, 4 = agree, and 5 = strongly agree. Providing and Recommending Interventions Participants provided ratings on their provision and recommendation of a list of interventions (FIPs, CTMs, and other psychosocial interventions). The lists were not exhaustive of all psychosocial interventions but rather were representative, and certain interventions were combined (e.g., prompting and time delay) to reduce the burden on the

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participants. Participants indicated whether they had provided each of the interventions for ASD (“In the past, how much have you PROVIDED this intervention to treat at least one aspect of ASD?”) using a 5-point Likert-type scale: 0 = never provided or N/A cannot provide (not within my discipline’s scope of practice), 1 = rarely provided, 2 = sometimes provided, 3 = often provided, 4 = almost always or always provided. They also indicated whether they had recommended each of the interventions (“In the past, how much have you RECOMMENDED this intervention to treat at least one aspect of ASD [and/or REFERRED children to an appropriate provider for this intervention]?”) on a 5-point Likert-type scale: 0 = never recommended or recommended AGAINST using, 1 = rarely recommended, 2 = sometimes recommended, 3 = often recommended, and 4 = almost always or always recommended. List of FIPs The list of FIPs was assembled based on the FIPs classified as “evidence based” (through the year 2011) by two key sources: the National Autism Center’s (2009) National Standards Project and the National Professional Development Center’s review of Evidence-Based Practices (2010; also presented in Odom, Collet-Klingenberg, et al., 2010). Composite scores were created to represent average rates of providing and recommending across all of the evidence-based FIPs. List of CTMs A representative list of CTMs was generated from the list of models identified in National Research Council (2001) and Odom, Boyd, et al. (2010), and based on consultation with the pilot group; not all programs in existence were included. Discrete Trial Training (including the Lovaas/UCLA Young Autism Project model) and Pivotal Response Training were classified as CTMs in this study, as they are larger programs of intervention (National Research Council, 2001; Rogers & Vismara, 2008), although both are also classified as evidence-based FIPs by some resources (National Autism Center, 2009; National Professional Development Center, 2010). Composite scores were created to represent average rates of providing and recommending across all of the CTMs included in this study. List of Other Psychosocial Interventions The list of other interventions included some classified as “emerging practices” (e.g., Social Skills Training; National Autism Center, 2009). Other psychosocial interventions, such as certain psychotherapy approaches (e.g., play therapy), and certain common characteristics of interventions (i.e.,

Please cite this article as: Lillian M. Christon, et al., Professionals’ Reported Provision and Recommendation of Psychosocial Interventions for Youth With Autism Spectrum Disorder, Behavior Therapy (2014), http://dx.doi.org/10.1016/j.beth.2014.02.002

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early intervention and intensive interventions [N 25 hours/week], generated from National Research Council, 2001) were also listed. Nonpsychosocial interventions (e.g., medical, speech-language, sensory) were not included in this study. Other Variables Participants identified which interventions—from the list of FIPs, CTMs, and other psychosocial interventions—that they were “unfamiliar” with (these data were part of the larger project, which included questions about perceived efficacy of interventions). Unfamiliarity scores on individual items for all interventions in the survey were used as auxiliary variables in multiple imputation (see Data Preparation section). For the list of FIPs, the unfamiliarity values were summed across interventions to calculate an overall unfamiliarity score, which represented how unfamiliar participants were generally with the list of FIPs. This score was included as a covariate in analyses testing study hypotheses (see Data Preparation section).

data preparation The two samples were combined for data analysis (see Jaccard & Turrisi, 2003, and Williams, n.d., for a rationale) and Sample was controlled for in analyses to address any potential differences between samples. Data were checked for outliers, and outliers were Windsorized. Missing data were addressed using established guidelines (e.g., Schlomer, Bauman, & Card, 2010). Eight percent of data was missing across all variables; a Little’s Missing Completely at Random (MCAR) test was not significant, χ 2 (21,878, N = 709) = 21,858.29, p = .536, suggesting that the data were MCAR (i.e., missing values do not depend on values/potential values of other variables). To assess whether the data better fit a missing at random (MAR) assumption (i.e., missing values are dependent upon another series of measured variables), “missingness” dummy codes were created for all providing/ recommending variables (1 = missing and 0 = not missing) and for unfamiliarity (1 =unfamiliar and 0 = familiar; Schlomer et al., 2010). Chi-square tests of independence indicated that, across all interventions, individuals who were unfamiliar with an intervention were significantly more likely to omit responses to providing and recommending items, suggesting that these data were actually MAR. Given this information, multiple imputation (MI; Rubin, 1987) was used to address missing data. Ten imputed data sets were created and pooled values from analyses on each of the 10 data sets were calculated using Rubin’s (1987) rules for combining parameter estimates. Unfamiliarity was included in

the MI procedure as an auxiliary variable and was controlled for in study analyses (Schlomer et al., 2010). IBM-SPSS v19 does not compute standard deviation (SD) in MI data sets; SD was calculated from pooled values for the standard error of the mean. A Holm (1979) correction was used to correct for multiple analyses; p values from individual tests of regression coefficients related to study hypotheses were included (i.e., discipline and training).

data analysis To address (a) whether there were discipline differences on providing and recommending FIPs and (b) the role of training variables in predicting these variables, a hierarchical multiple regression approach to ANCOVA was used. Discipline was coded into five effect code indicator variables (groups-1; Cohen, Cohen, West, & Aiken, 2003) using unweighted effects coding; each group mean was compared with the unweighted mean of the sample as a whole. In the hierarchical multiple regression, Sample was entered in Step 1 as a design covariate and unfamiliarity was entered in Step 2 as discussed above. Additionally, years in practice in the current discipline and the number of children with ASD provided services for in the past year were entered as covariates in Step 3. Discipline was entered in Step 4 (two iterations were done, with a different discipline coded as the reference group each time, to obtain betas for all disciplines). Finally, these models were used to address whether training on EBIs and training on ASD interventions predicted providing and recommending FIPs (after controlling for all other variables), with these predictors added in Step 5. Only unstandardized beta (β) is presented, as IBM-SPSS v19 does not calculate pooled β coefficients in MI data sets. Cohen’s ƒ 2 was calculated from R 2 (Soper, n.d.) and effect sizes were interpreted using Cohen’s (1992) guidelines: .02 small, .15 medium, and .35 large. Cohen’s d was calculated (Soper, n.d.) and effect sizes were interpreted using Cohen’s (1992) guidelines: .20 small, .50 medium, and .80 large.

Results self-report on providing and recommending fips Professionals’ self-reported mean rate of providing FIPs to youth with ASD across disciplines was 2.04 (SD = 0.92; higher numbers consistent with higher rates), corresponding to “sometimes.” They reported recommending FIPs to youth with ASD across all disciplines at an average rate of 2.34 (SD = 0.71), between “sometimes” and “often.” Across disciplines, the three FIPs reportedly provided and recommended most were reinforcement, visual

Please cite this article as: Lillian M. Christon, et al., Professionals’ Reported Provision and Recommendation of Psychosocial Interventions for Youth With Autism Spectrum Disorder, Behavior Therapy (2014), http://dx.doi.org/10.1016/j.beth.2014.02.002

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professionals’ report on practices with youth with asd

effect). Training on ASD interventions significantly predicted reporting higher rates of providing FIPs (β = .077, p = .013), while training on EBIs did not (β = .038, p = .205). For recommending FIPs, the final model was significant, F(11, 691) = 60.09, p b .001, and explained 48.90% of the variance (adjusted R 2 = .481; Cohen's ƒ 2 = .946, large effect). In Step 1, the variance accounted for by Sample was significant, yet had a quite small effect size (1.80%, p b .001; Cohen's ƒ 2 = 0.018); membership in the stratified random sample predicted reporting higher rates of recommending FIPs (β = .206, p b .001). In Step 2, unfamiliarity accounted for significant additional variance (42.80%, p b .001; Cohen's ƒ 2 = 0.749, large effect); reporting being familiar with the list of FIPs predicted reporting higher rates of recommending them. Step 3 (containing years in practice and number of children with ASD served) did not account for significant additional variance (p = .230). Step 4 (discipline) explained a significant, yet small portion (2.40%, p b .001; Cohen's ƒ 2 = 0.024, small effect) of additional variance (discipline differences are presented later). Finally, Step 5 (training variables) accounted for a significant and small (1.60% additional variance, p b .001; Cohen's ƒ 2 = 0.016, small effect) amount of additional variance. Training on EBIs (β = .083, p b .001) significantly predicted reporting higher rates of recommending FIPs,

supports, and task analysis, and the three reportedly provided and recommended the least were structured work systems, joint attention interventions, and modeling/video modeling (see Tables 1 and 2). The final model for predictors of providing FIPs was significant, F(11, 691) = 61.26, p b .001, and explained 49.40% of the variance (adjusted R 2 = .486; Cohen’s ƒ 2 = .976, large effect). In Step 1, Sample did not account for significant portion of the variance (p = .351). In Step 2, unfamiliarity explained significant additional variance (28.60%, p b .001; Cohen's ƒ 2 = 0.400, large effect); reported familiarity with the FIPs predicted reporting providing them. Step 3 (containing years in practice and number of children with ASD provided services for in the past year) added significant additional explanatory power to the model (3.30%, p b .001; Cohen's ƒ 2 = 0.034, small effect). However, neither years in practice (β = –.002, p = .613) nor number of children with ASD served (β = .000, p = .462) explained the unique variance after accounting for the influence of the other variables in the model. Step 4 (discipline) accounted for a significant portion of additional variance (16.50%, p b .001; Cohen's ƒ 2 = 0.198, medium effect); discipline differences are discussed later. Finally, Step 5 (training variables) was a significant predictor of providing FIPs for youth with ASD (0.80%, p = .005; Cohen's ƒ 2 = 0.008, small

Table 1

Mean Ratings of Providing Evidence-Based Focused Intervention Practices (FIPs) Interventions

Education (n = 157)

Medicine/ Nursing (n = 108)

OT/PT (n = 100)

Psychology (n = 163)

Social Work (n = 52)

SLP/ Audiology (n = 129)

Total (n = 709)

M

SD

M

SD

M

SD

M

SD

M

SD

M

SD

M

SD

Antecedent-based interventions Differential reinforcement Functional behavior assessment FCT Joint attention interventions Modeling/video modeling Naturalistic interventions Peer-mediated/training Positive behavior supports Prompting and time delay Reinforcement Response interruption/redirection Self-management Social stories Structured work systems Task analysis Visual supports Mean rate of providing:

3.05 2.87 2.53 2.66 1.76 2.07 2.78 2.28 2.83 3.19 3.30 2.54 2.29 2.24 1.74 3.09 3.28 2.65

1.00 1.09 1.32 1.43 1.42 1.35 1.34 1.27 1.14 1.07 1.07 1.15 1.04 1.22 1.44 0.88 0.93 0.60

1.10 1.11 0.82 0.66 0.61 0.54 0.61 0.55 1.20 0.85 1.39 1.17 0.85 0.61 0.48 1.05 0.88 0.87

1.27 1.32 1.23 1.18 1.22 1.13 1.14 1.14 1.42 1.22 1.43 1.27 1.14 1.05 0.90 1.30 1.31 0.82

2.09 2.24 1.40 1.55 1.51 1.90 2.40 1.93 2.29 2.43 2.73 2.09 2.51 2.03 1.23 3.01 2.90 2.21

1.15 1.11 1.34 1.34 1.35 1.32 1.39 1.16 1.25 1.11 1.13 1.00 1.03 1.13 1.24 0.93 1.12 0.58

2.39 2.57 2.05 1.68 1.08 1.21 1.44 1.28 2.17 2.07 2.92 2.05 1.94 1.72 0.71 2.39 2.29 1.95

1.35 1.34 1.43 1.46 1.25 1.23 1.48 1.32 1.38 1.35 1.28 1.24 1.23 1.24 1.07 1.26 1.25 0.85

1.99 2.00 1.44 1.62 1.24 1.53 1.33 1.42 2.49 2.04 2.68 2.09 1.97 1.90 0.89 2.50 2.16 1.90

1.28 1.36 1.36 1.36 1.48 1.29 1.43 1.34 1.33 1.41 1.25 1.31 1.30 1.34 1.22 1.20 1.44 0.80

2.12 2.09 1.62 2.27 2.24 2.20 2.67 1.92 2.38 2.66 2.74 2.16 1.96 2.25 0.97 2.68 3.13 2.30

0.57 0.57 0.61 0.65 1.37 0.59 0.69 0.58 1.25 0.61 0.58 0.53 0.53 0.57 0.57 0.56 0.60 0.74

2.22 2.24 1.75 1.83 1.44 1.60 1.96 1.61 2.25 2.29 2.70 2.05 1.94 1.82 1.04 2.49 2.52 2.04

1.33 1.33 1.44 1.52 1.52 1.38 1.62 1.36 1.38 1.44 1.36 1.25 1.25 1.33 1.33 1.30 1.41 0.92

Note: Ratings were from 0 (never) to 4 (almost always/always). OT/PT = occupational therapy/physical therapy; SLP = speech language pathology; FCT = functional communication training; peer-mediated/training = peer-mediated/training interventions. Please cite this article as: Lillian M. Christon, et al., Professionals’ Reported Provision and Recommendation of Psychosocial Interventions for Youth With Autism Spectrum Disorder, Behavior Therapy (2014), http://dx.doi.org/10.1016/j.beth.2014.02.002

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christon et al.

Table 2

Mean Ratings of Recommending Evidence-Based Focused Intervention Practices (FIPs) Interventions

Antecedent-based interventions Differential reinforcement Functional behavior assessment FCT Joint attention interventions Modeling/video modeling Naturalistic interventions Peer-mediated/training Positive behavior supports Prompting and time delay Reinforcement Response interruption/redirection Self-management Social stories Structured work systems Task analysis Visual supports Mean rate of recommending:

Education (n = 157)

Medicine/ Nursing (n = 108)

OT/PT (n = 100)

Psychology (n = 163)

Social Work (n = 52)

SLP/ Audiology (n = 129)

Total (n = 709)

M

SD

M

SD

M

SD

M

SD

M

SD

M

SD

M

SD

2.95 2.90 2.63 2.70 1.70 2.12 2.88 2.31 2.72 3.12 3.27 2.51 2.27 2.34 1.64 3.08 3.30 2.65

1.08 1.07 1.29 1.39 1.47 1.30 1.29 1.28 1.22 1.07 1.05 1.13 0.98 1.20 1.42 0.94 0.93 0.59

2.41 2.17 2.15 1.72 1.14 1.01 1.38 1.76 2.31 1.66 2.61 2.03 1.57 1.64 1.07 2.00 2.54 1.86

1.24 1.20 1.34 1.36 1.14 1.28 1.38 1.44 2.31 1.37 1.13 1.24 1.22 1.28 1.35 1.33 1.24 0.80

2.17 2.15 1.77 1.74 1.57 1.93 2.51 2.23 2.32 2.47 2.73 1.91 2.46 2.39 1.28 2.93 3.07 2.28

1.03 1.06 1.25 1.32 1.31 1.22 1.32 1.11 1.21 1.07 0.95 1.04 0.97 0.98 1.24 0.93 1.03 0.57

2.88 2.93 2.67 2.13 1.29 1.57 2.05 2.09 2.54 2.39 3.24 2.35 2.11 2.25 1.04 2.72 2.95 2.37

1.10 1.10 1.19 1.39 1.25 1.17 1.46 1.16 1.20 1.17 0.97 1.11 1.09 1.14 1.30 1.12 1.01 0.69

2.41 2.22 2.16 2.01 1.31 1.52 1.83 2.27 2.74 2.28 2.87 2.17 2.21 2.25 1.25 2.86 2.77 2.24

1.00 1.17 1.31 1.36 1.41 1.26 1.40 1.23 1.18 1.32 0.98 1.28 1.08 1.36 1.36 1.00 1.08 0.63

2.18 2.07 2.06 2.40 2.24 2.24 2.82 2.22 2.39 2.63 2.68 2.13 2.05 2.38 1.04 2.68 3.23 2.38

1.11 1.11 1.17 1.28 1.33 1.20 1.18 1.19 1.17 1.22 1.20 1.03 1.08 1.04 1.39 1.14 0.95 0.70

2.56 2.49 2.31 2.18 1.57 1.77 2.32 2.15 2.50 2.49 2.95 2.22 2.11 2.22 1.23 2.72 3.02 2.34

1.14 1.17 1.30 1.41 1.41 1.33 1.44 1.22 1.25 1.28 1.09 1.17 1.12 1.20 1.60 1.14 1.07 0.71

Note: Ratings were from 0 (never) to 4 (almost always/always). OT/PT = occupational therapy/physical therapy; SLP = speech language pathology; FCT = functional communication training; peer-mediated/training = peer-mediated/training interventions.

whereas training on ASD interventions did not (β = .038, p = .115). A Holm correction was applied to variables related to study hypotheses (discipline and training variables) and discipline differences on self-reported providing and recommending FIPs were examined. Each discipline’s mean was compared with the unweighted grand mean of the sample (Cohen et al., 2003) and regression coefficients represent the unique contribution of each discipline’s membership after controlling for the other variables in the model. Consistent with hypotheses, there were significant differences between disciplines on selfreported providing FIPs, Step 4; F(9, 693) = 72.70, p b .001, such that the education (β = .529, p b .001), occupational/physical therapy (β = .177, p = .004), and SLP/audiology (β = .220, p b .001) disciplines reported providing significantly more FIPs than the sample grand mean, and the medicine/ nursing (β = –.824, p b .001) discipline reported providing significantly fewer FIPs than the sample as a whole. After correcting for multiple comparisons, the psychology (β = –.237, p = .011) and social work (β = .028, p = .734) disciplines did not differ significantly from the sample grand mean. Furthermore, discipline significantly predicted rates of selfreported recommending FIPs, Step 4; F(9, 693) = 69.05, p b .001, though this finding is primarily due to the education discipline (β = .203, p b .001)

recommending significantly more than the sample grand mean. All other disciplines’ reported rates of recommending did not differ significantly from the sample grand mean after correcting for multiple comparisons (medicine/nursing, β = –.111, p = .037; occupational/physical therapy, β = –.075, p = .120; psychology, β = –.063, p = .114; social work, β = .074, p = .243; and SLP/audiology, β = –.028, p = .512).

self-report on providing and recommending ctms Descriptive data on professionals’ self-reported rates of providing and recommending CTMs are presented in Table 3. Professionals reported most commonly providing and recommending applied behavioral analysis, DIR/floortime, and discrete trial training, while they reported providing and recommending LEAP, the Early Start Denver Model, and SCERTs the least. Average self-reported rates of providing and recommending FIPs were compared with average self-reported rates of providing and recommending CTMs using exploratory paired samples t tests. Professionals reported providing, t(708) = 43.44, p b .001; Cohen’s d = 1.40, large effect, and recommending, t(708) = 50.22, p b .001; Cohen’s d = 1.78, large effect, FIPs significantly more than CTMs. The average self-reported rates of providing (M = 0.90, SD =

Please cite this article as: Lillian M. Christon, et al., Professionals’ Reported Provision and Recommendation of Psychosocial Interventions for Youth With Autism Spectrum Disorder, Behavior Therapy (2014), http://dx.doi.org/10.1016/j.beth.2014.02.002

Mean Ratings of Providing and Recommending Comprehensive Treatment Models (CTMs) Interventions

ABA: DIR/floortime: Discrete trial training: ESDM: LEAP: PRT: RDI: SCERTS: TEACCH: Verbal behavior:

Education (n = 157)

Providing Recommending Providing Recommending Providing Recommending Providing Recommending Providing Recommending Providing Recommending Providing Recommending Providing Recommending Providing Recommending Providing Recommending

Mean rate of providing: Mean rate of recommending:

Medicine/ Nursing (n = 108)

OT/PT (n = 100)

Psychology (n = 163)

Social Work (n = 52)

SLP/Audiology (n = 129)

Total (n = 709)

M

SD

M

SD

M

SD

M

SD

M

SD

M

SD

M

SD

2.80 2.75 1.22 1.21 2.02 1.93 0.67 0.74 0.34 0.46 1.51 1.49 0.97 0.93 0.78 0.73 1.41 1.33 1.81 1.75 1.35 1.33

1.49 1.43 1.49 1.43 1.49 1.44 1.03 1.09 0.70 0.81 1.42 1.38 1.30 1.25 1.17 1.12 1.45 1.38 1.62 1.59 0.60 0.58

0.56 2.19 0.49 1.28 0.44 1.14 0.42 0.94 0.25 0.68 0.41 0.91 0.41 0.93 0.39 0.67 0.57 1.17 0.57 0.96 0.45 1.09

1.14 1.41 1.06 1.35 1.11 1.20 0.97 1.14 0.58 1.07 0.98 1.21 0.83 1.08 0.85 0.96 1.07 1.25 0.92 1.16 0.65 0.76

0.90 1.42 1.87 1.96 0.62 0.85 0.52 0.59 0.36 0.57 0.56 0.62 0.83 0.99 0.83 0.83 0.94 1.11 0.68 0.83 0.81 0.98

1.26 1.24 1.55 1.51 1.00 1.07 0.85 0.89 0.67 0.88 0.93 0.91 1.16 1.07 1.12 1.10 1.09 1.21 1.07 1.10 0.54 0.53

1.82 2.76 0.91 1.27 1.10 1.69 0.52 0.77 0.23 0.37 0.64 0.87 0.47 0.63 0.44 0.57 0.87 1.34 0.81 1.08 0.78 1.13

1.57 1.26 1.37 1.37 1.33 1.37 0.93 1.11 0.56 0.71 1.05 1.15 0.91 1.00 0.89 0.93 1.23 1.30 1.28 1.33 0.60 0.55

1.02 1.95 1.04 1.37 0.53 0.74 0.39 0.50 0.37 0.66 0.40 0.58 0.91 1.09 0.48 0.55 0.81 1.03 0.77 0.92 0.67 0.94

1.41 1.42 1.39 1.41 1.02 1.16 0.79 0.84 0.78 1.10 0.81 0.90 1.32 1.35 0.89 0.96 1.18 1.19 1.28 1.25 0.68 0.70

1.50 2.03 1.59 1.76 1.01 1.11 0.56 0.71 0.39 0.55 0.75 0.85 0.94 1.14 0.96 1.04 1.29 1.37 1.18 1.26 1.02 1.18

0.69 1.31 0.62 1.42 0.61 1.23 0.41 1.06 0.32 0.90 0.51 1.12 0.52 1.29 0.48 1.25 0.56 1.32 0.65 1.35 0.61 0.61

1.60 2.29 1.18 1.45 1.07 1.36 0.53 0.73 0.32 0.52 0.79 0.95 0.74 0.92 0.66 0.74 1.03 1.26 1.04 1.20 0.90 1.14

1.62 1.41 1.46 1.41 1.44 1.44 0.96 1.09 0.75 1.04 1.20 1.22 1.22 1.17 1.12 1.14 1.30 1.36 1.52 1.46 0.69 0.63

Note: Ratings were from 0 (never) to 4 (almost always/always). OT/PT = occupational therapy/physical therapy; ABA = applied behavior analysis; DIR =; ESDM = Early Start Denver Model; LEAP =; PRT = pivotal response training; RDI = relationship development intervention; SCERTS =; TEACCH = .

professionals’ report on practices with youth with asd 9

Please cite this article as: Lillian M. Christon, et al., Professionals’ Reported Provision and Recommendation of Psychosocial Interventions for Youth With Autism Spectrum Disorder, Behavior Therapy (2014), http://dx.doi.org/10.1016/j.beth.2014.02.002

Table 3

10

Mean Ratings of Providing and Recommending Other Psychosocial Interventions Interventions

AAC: CBT: C/T aided instruction: Early intervention: Imitation-based int.: Intensive intervention: Parent/family coaching: PECS: Play therapy: Psychodynamic therapy: Scripting: Social skills training:

Education (n = 157)

Providing Recommending Providing Recommending Providing Recommending Providing Recommending Providing Recommending Providing Recommending Providing Recommending Providing Recommending Providing Recommending Providing Recommending Providing Recommending Providing Recommending

Medicine/ Nursing (n = 108)

OT/PT (n = 100)

Psychology (n = 163)

Social Work (n = 52)

SLP/Audiology (n = 129)

Total (n = 709)

M

SD

M

SD

M

SD

M

SD

M

SD

M

SD

M

SD

2.28 2.45 0.97 0.99 1.74 1.84 3.03 3.56 0.85 0.80 1.70 1.89 2.55 2.71 2.37 2.45 1.37 1.32 0.33 0.33 1.80 1.81 2.46 2.55

1.30 1.18 1.15 1.09 1.38 1.30 1.49 1.08 1.15 1.15 1.54 1.50 1.49 1.42 1.24 1.18 1.39 1.40 0.70 0.75 1.18 1.18 1.19 1.10

0.56 2.05 0.57 1.41 0.54 1.85 1.12 3.52 0.51 0.60 0.47 1.48 0.93 2.20 0.51 1.98 0.63 1.14 0.29 0.36 0.54 1.40 0.72 2.20

1.17 2.05 1.02 1.41 1.02 1.85 1.64 0.96 0.99 0.60 1.06 1.53 1.47 1.52 1.04 1.98 1.21 1.14 0.72 0.36 0.97 1.40 1.26 2.20

1.91 2.27 0.79 1.07 1.61 1.78 3.01 3.50 0.91 0.94 0.75 1.17 2.83 3.05 2.02 2.38 1.76 2.01 0.35 0.55 1.42 1.49 2.09 2.51

1.32 1.09 1.07 1.14 1.24 1.17 1.33 0.91 1.11 1.13 1.15 1.18 1.32 1.18 1.13 1.01 1.40 1.22 0.68 0.82 1.05 1.04 1.12 0.98

0.95 1.80 1.70 1.88 0.71 1.48 2.11 3.65 0.60 0.60 0.91 1.79 2.00 2.75 1.07 1.98 1.07 1.07 0.30 0.27 1.69 1.98 2.06 2.75

1.21 1.28 1.21 1.07 1.11 1.24 1.71 0.83 1.02 1.01 1.33 1.47 1.54 1.24 1.28 1.26 1.34 1.24 0.78 0.70 1.19 1.16 1.30 1.06

0.98 1.82 1.67 1.90 0.91 1.43 1.79 3.27 0.77 0.76 0.55 0.73 2.27 2.72 1.13 1.59 1.95 2.01 0.70 0.62 1.80 1.85 2.47 2.86

1.25 1.33 1.39 1.20 1.22 1.16 1.80 1.28 1.10 1.05 1.09 1.17 1.54 1.37 1.32 1.33 1.49 1.37 1.02 0.90 1.31 1.24 1.41 1.15

2.52 2.63 0.78 0.97 1.83 1.93 3.11 3.66 1.21 1.21 1.12 1.58 2.88 3.05 1.99 2.18 2.07 2.18 0.39 0.42 1.88 1.90 2.43 2.54

1.03 0.97 1.14 1.09 1.14 1.11 1.29 0.78 1.29 1.45 1.41 1.43 1.24 1.17 1.14 1.03 1.40 1.31 0.73 0.78 1.20 1.18 1.19 1.11

1.61 2.20 1.07 1.33 1.26 1.74 2.45 3.56 0.81 0.81 1.01 1.56 2.26 2.75 1.58 2.15 1.41 1.54 0.36 0.39 1.54 1.76 2.05 2.56

1.46 1.28 1.20 1.22 1.33 1.22 1.70 0.96 1.17 1.20 1.44 1.49 1.60 1.33 1.38 1.22 1.44 1.36 0.77 0.88 1.22 1.17 1.36 1.14

Note: Ratings were from 0 (never) to 4 (almost always/always). OT/PT = occupational therapy/physical therapy; AAC = augmentative and/or alternative communication; CBT = cognitive-behavioral therapy; C/T = computer/technology; PECS = picture exchange communication system.

christon et al.

Please cite this article as: Lillian M. Christon, et al., Professionals’ Reported Provision and Recommendation of Psychosocial Interventions for Youth With Autism Spectrum Disorder, Behavior Therapy (2014), http://dx.doi.org/10.1016/j.beth.2014.02.002

Table 4

professionals’ report on practices with youth with asd 0.69) and recommending (M = 1.14, SD = 0.63) CTMs were low (“never” to “rarely”).

self-report on providing and recommending other psychosocial interventions Descriptive data are provided for professionals’ self-reported ratings of providing and recommending other psychosocial interventions for ASD (Table 4). Professionals reported providing and recommending early intervention, social skills training, and parent/family coaching the most. They reported providing psychodynamic therapy, imitation-based interventions, and intensive intervention the least, and recommending psychodynamic therapy, imitation-based interventions, and CBT the least. Examination of psychotherapy approaches using an exploratory paired samples t test suggested that professionals reported providing, t(708) = 5.56, p b .001; Cohen’s d = 0.26, small effect, and recommending, t(708) = 3.35, p = .001; Cohen’s d = 0.16, very small effect, play therapy significantly more than CBT for youth with ASD, although the effect sizes for these differences were very small and professionals reported providing and recommending both interventions only “rarely” to “sometimes.”

Discussion Professionals reported that they provide and recommend a range of psychosocial interventions to youth with ASD. Disciplines differed in their self-reported provision and recommendation of evidence-based FIPs (e.g., modeling, visual supports) consistent with study hypotheses. Discipline was a medium-sized predictor of self-reported provision and a small-sized predictor of selfreported recommendation of FIPs. As such, discipline membership may matter more in terms of what professionals report they are providing (interventions within their scope of practice) than what they report they are recommending (i.e., recommending interventions that other disciplines may provide): an encouraging finding for the multidisciplinary ASD field. Physicians and nurses reported providing significantly fewer evidencebased FIPs than the average professional in the sample, which is likely reflective of the composition of the FIP list, as these practices may not fall within medicine/nursing professionals’ scope of practice. Further, physicians and nurses may not have the time (Migongo et al., 2012) to implement FIPs during office visits, and indeed, this is beyond their scope of practice. These professionals are focused on the medical concerns (as opposed to treating core ASD symptoms) of children with ASDs and are

11

presumably providing interventions that are not found on the FIP list (e.g., medication management; Oswald & Sonenklar, 2007). Disciplines also differed in self-reported rates of recommending FIPs. These differences were due to educators reporting that they recommend more FIPs than the average professional in the sample. Of note, after correcting for multiple analyses, the medical/ nursing discipline’s reported rate of recommending FIPs did not differ significantly from the rest of the sample. This highlights the importance of turning attention to recommendation/referral practices. Scope of practice may limit direct provision of services, however, pediatric physicians and nurses are often first-line resources for parents who have questions about their children’s development and which interventions, if any, are appropriate. Efforts of the American Academy of Pediatrics (2013) have aimed to raise physicians’ awareness to the intervention options available for ASD, including resources on implementing FIPs (e.g., differential reinforcement). Future work may focus more closely on recommendation/referral practices of professionals. Training mattered in regard to self-reported practice, at least to a small extent. Those who endorsed having more training on ASD interventions reported providing more FIPs, while training on EBIs did not. However, endorsing having more training on EBIs predicted reporting recommending more FIPs, while training on ASD interventions did not. Training is a multifaceted construct, and was measured in this study by single items. Future studies should examine training variables in a more nuanced fashion. However, these findings do underscore the potential importance of professionals receiving training not only on ASD-specific interventions but also broad training on EBIs. Although not related to a specific study hypothesis, the unfamiliarity variable is also worth mentioning. This is an obvious point, but one worth stating outright: lower self-reported intervention familiarity predicted lower self-reported rates of providing and recommending the interventions. This stresses the importance of training professionals on the landscape of EBIs, including ones that they will not personally provide, as a way to increase the odds that children will receive high-quality interventions (e.g., Pagoto et al., 2007). Depth of training may vary based on a particular discipline’s scope of practice and the likelihood of actually providing the intervention. In contrast to FIPs, on the whole, professionals reported rarely providing or recommending CTMs in this study. This was true for CTMs classified as evidence based (e.g., discrete trial training; Rogers & Vismara, 2008), as well as the other CTMs

Please cite this article as: Lillian M. Christon, et al., Professionals’ Reported Provision and Recommendation of Psychosocial Interventions for Youth With Autism Spectrum Disorder, Behavior Therapy (2014), http://dx.doi.org/10.1016/j.beth.2014.02.002

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christon et al.

listed. This is interesting given the amount of attention that CTMs have received in the literature and in the public. There are drawbacks to namebranded CTMs (Mesibov & Shea, 2010; Rogers & Vismara, 2008), which may be related to study findings. Training on name-branded interventions may be difficult for professionals to obtain, and families may face challenges in accessing and paying for specific name-branded interventions in community settings. In addition, there is a lack of clarity on which elements of these models are the efficacious ingredients, and which patient characteristics influence efficacy. Rogers and Vismara (2008, p. 31) assert that it would be helpful to “point out commonalities between the brand-name interventions and others, and to document empirically the specific generic efficacious practices underlying the effects in the brand-name program.” Moving forward, adopting a modular intervention approach (e.g., Chorpita, Taylor, Francis, Moffitt, & Austin, 2004) may be a useful direction for the ASD intervention field. For instance, Brookman-Frazee and colleagues’ (2012) intervention program used a tailored combination of FIPs to allow for a greater degree of treatment individualization, while relying on evidence-based FIP components. In the future, the evidence-based FIPs could be assembled and tested in a modular comprehensive treatment model format. At the time the survey was conducted (2011), the other psychosocial interventions included were not classified as evidence-based. However, there are varying levels of evidence for the efficacy of augmentative/alternative communication, CBT, computer/ technology-aided instruction, picture exchange communication systems, imitation-based interventions, scripting, and social skills training as interventions for youth with ASD; early intervention, intensive intervention, and parent/family coaching have been identified as key intervention characteristics (National Autism Center, 2009; National Research Council, 2001). Of these other interventions, professionals reported providing and recommending early intervention, parent/family coaching, and social skills training the most, whereas imitation-based interventions, intensive interventions, and CBT were provided and recommended the least. Exploratory analyses demonstrated that professionals report providing and recommending play therapy significantly more than CBT for youth with ASD, despite the growing emerging evidence for the efficacy of CBT for youth with ASD (see Scarpa et al., 2013; Wood Fujii, & Renno, 2011). Psychodynamic therapy is not considered to have evidence for treating ASD; encouragingly, professionals report “never” to “rarely” providing or recommending this intervention.

Further thought must be given to the best ways to disseminate information about EBIs to professionals across disciplines. Providing and recommending EBIs requires many things of professionals, such as staying current with ongoing empirical research and engaging in continuing education (Volkmar et al., 2011). This study suggests that dissemination efforts should target professionals who are discussing treatment options with families. Familiarity influenced rates of recommending and families depend on professionals to recommend interventions for their children with ASD (e.g., Mackintosh et al., 2007). Multidisciplinary training and collaboration should also be a component of dissemination efforts for ASD interventions.

future directions There are many potential barriers to implementing EBIs in community settings including unfamiliarity with EBIs (Pagoto et al., 2007), lack of organizational support (Beidas & Kendall, 2010, and funding concerns (Shattuck & Grosse, 2007). Consideration of the best ways to train professionals across disciplines on the rapidly changing ASD intervention field is imperative. Existing (free) resources may be helpful (e.g., see National Professional Development Center, 2010; Ohio Center for Autism and Low Incidence, 2014). The National Professional Development Center (Wong et al., 2014) has released a new update on EBIs for children, youth, and young adults with ASD. Future work should focus on understanding barriers to implementing EBIs for ASD, and identifying education and training tools (e.g., ongoing consultation; Beidas, Edmunds, Marcus, & Kendall, 2012) that could increase use of EBIs. There is a disconnect between the ASD literature and the literatures within each discipline, both in terms of terminology used to classify interventions, and criteria used to evaluate interventions. There is not a uniformly accepted method of defining classes of psychosocial interventions for ASD. Odom, Boyd, et al. (2010) and Odom, Collet-Klingenberg, et al. (2010) have made an important first step in distinguishing between FIPs and CTMs. A key next step is to further classify and categorize interventions across disciplines in an effort to organize the intervention landscape (e.g., Wong et al., 2014). Second, there is not a uniformly accepted method of how to classify interventions as evidence based or efficacious (e.g., National Autism Center, 2009; Rogers & Vismara, 2008). For instance, Reichow et al. (2008) provides a novel way to examine efficacy of interventions specifically for ASDs, providing rubrics for evaluating diverse methods across a range of quality indicators. Also, little is known about how client factors (e.g., cognitive ability) and different treatment characteristics (e.g., intensive intervention)

Please cite this article as: Lillian M. Christon, et al., Professionals’ Reported Provision and Recommendation of Psychosocial Interventions for Youth With Autism Spectrum Disorder, Behavior Therapy (2014), http://dx.doi.org/10.1016/j.beth.2014.02.002

professionals’ report on practices with youth with asd mediate and moderate the efficacy of ASD interventions. An agreed-upon method for defining efficacy and data on mediators and moderators of outcome are important for moving the field forward.

limitations There are limitations to this study. Moderators and mediators of intervention effects were not incorporated, and some interventions listed may be most appropriate for youth of a certain age and cognitive level (e.g., CBT for high-functioning ASD; Scarpa et al., 2013), which may limit the interpretation of the findings. Further, the psychosocial interventions included in this study do not provide an all-inclusive account of the wide range of ASD interventions. Most youth with ASDs receive other interventions (e.g., sensory/motor interventions; McLennan et al., 2008). Other research approaches (e.g., qualitative and medical records review) could contribute to the identification on a more comprehensive list of interventions received by youth with ASD. Also, self-report data collection methods were used in this study for practical reasons (e.g., sampling professionals across settings) but should introduce caution in interpreting the data. Brief definitions of each intervention were provided in the questionnaire, but there are no assurances that professionals across different disciplines defined interventions the same way. Also, self-reports on practice should not be misconstrued to mean that these professionals implement the practices with integrity (e.g., dose of intervention, accuracy, and competence in delivery). Quality of professionals’ delivery of ASD interventions is likely related to variability in treatment outcome (e.g., Symes, Remington, Brown, & Hastings, 2006). Future work should focus on assessing the treatment integrity of ASD intervention implementation, as professionals’ self-reports of their own behavior may not be reliable (Symes et al., 2006). Finally, it is necessary to comment on the samples used. The convenience sample was self-selecting and a response rate could not be estimated. Also, the stratified random sample of provider listings had an 11.4% response rate, which is quite low, and there is potential for nonresponse error (Dillman, Smyth, & Christian, 2009). It is possible that the same characteristic that led to participation in the convenience sample also led to participation in the second sample and that this (unknown) characteristic may also be related to rates of providing and recommending. Measures were taken to address sample differences (Sample was controlled for in analyses). The amount of variance added by controlling for Sample was extremely small and likely of little practical relevance. The dual recruitment strategy was used with consideration to the critique that is often leveled

13

at Internet studies—that the respondents are a select sample, potentially not representative of the full target population—but findings should still be interpreted with caution. Finally, there were few males and minority race/ethnic groups in the final sample, but this may reflect those in practice; population demographics of professionals providing services are not known. Generally, efforts were made to ensure that the study sample provided as representative a picture as possible of the target population of professionals who treat youth with ASD.

Conclusion Professionals working with children with ASDs report providing and recommending many psychosocial interventions, though at different rates across disciplines and across intervention classes. Self-reported rates of providing and recommending interventions for ASD were related to professionals’ reported familiarity with the interventions, training on EBIs, and training on ASD interventions. It is important to consider the role of recommendation/referral behavior as well as direct provision of clinical services when training professionals. While efforts have been made to categorize/classify psychosocial interventions for ASD, more work is needed to organize the treatment landscape and attention should be given to identifying the best ways to train professionals to provide and recommend EBIs for youth with ASD. Conflict of Interest Statement The authors declare that there are no conflicts of interest.

References American Academy of Pediatrics. (2013). Autism: Caring for children with autism spectrum disorders, a resource toolkit for clinicians (2nd ed.) [Software and available for download]. Retrieved from https://www.nfaap.org/netforum/ eweb/dynamicpage.aspx?site=nf.aap.org&webcode=aapbks_ productdetail&key=d830e6db-10a1-49f0-8ef1-83a8 4284de8f. American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Arlington, VA: American Psychiatric Publishing. Beidas, R. S., Edmunds, J. M., Marcus, S. C., & Kendall, P. C. (2012). Training and consultation to promote implementation of an empirically supported treatment: A randomized trial. Psychiatric Services, 63(7), 660–665. Beidas, R. S., & Kendall, P. C. (2010). Training therapists in evidence-based practice: A critical review of studies from a systems-contextual perspective. Clinical Psychology: Science and Practice, 17(1), 1–30. Brookman-Frazee, L. I., Drahota, A., & Stadnick, N. (2012). Training community mental health therapists to deliver a package of evidence-based practice strategies for school-age children with autism spectrum disorders: A pilot study. Journal of Autism and Developmental Disorders, 42(8), 1651–1661. Campbell, D. T., & Fiske, D. W. (1959). Convergent and discriminant validation by the multitrait-multimethod matrix. Psychological Bulletin, 56(2), 81–105.

Please cite this article as: Lillian M. Christon, et al., Professionals’ Reported Provision and Recommendation of Psychosocial Interventions for Youth With Autism Spectrum Disorder, Behavior Therapy (2014), http://dx.doi.org/10.1016/j.beth.2014.02.002

14

christon et al.

Carbone, P. S., Behl, D. D., Azor, V., & Murphy, N. A. (2010). The medical home for children with autism spectrum disorders: Parent and pediatrician perspectives. Journal of Autism and Developmental Disorders, 40(3), 317–324. Chambless, D. L., & Ollendick, T. H. (2001). Empirically supported psychological interventions: Controversies and evidence. Annual Review in Psychology, 52, 685–716. Chiri, G., & Warfield, M. E. (2012). Unmet need and problems accessing core health care services for children with autism spectrum disorder. Maternal and Child Health Journal, 16(5), 1081–1091. Chorpita, B. F., Taylor, A. A., Francis, S. E., Moffitt, C. E., & Austin, A. A. (2004). Efficacy of modular cognitive behavior therapy for childhood anxiety disorders. Behavior Therapy, 35, 263–287. Christon, L. M., Mackintosh, V. H., & Myers, B. J. (2010). Use of complementary and alternative medicine treatments by parents of children with autism spectrum disorders. Research in Autism Spectrum Disorders, 4(2), 249–259. Cohen, C., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied multiple regression/correlation analysis for the behavioral sciences (3rd ed.). Hillsdale, NJ: Erlbaum. Cohen, J. (1992). A power primer. Psychological Bulletin, 112(1), 155–159. Dillman, D. A., Smyth, J. D., & Christian, L. M. (2009). Internet, mail, and mixed-mode surveys: The tailored-design method. Hoboken, NJ: Wiley & Sons. Dootson, S. (1995). An in-depth study of triangulation. Journal of Advanced Nursing, 22, 183–187. Goin-Kochel, R. P., Mackintosh, V. H., & Myers, B. J. (2007). Parental reports on the use of treatments and therapies for children with autism spectrum disorders. Research in Autism Spectrum Disorders, 1, 195–209. Hess, K. L., Morrier, M. J., Heflin, L. J., & Ivey, M. L. (2008). Autism treatment survey: Services received by children with autism spectrum disorders in public school classrooms. Journal of Autism and Developmental Disorders, 38(5), 961–971. Holm, S. (1979). A simple sequentially rejective multiple test procedure. Scandinavian Journal of Statistics, 6, 65–70. Jaccard, J., & Turrisi, R. (2003). Interaction effects in multiple regression (2nd ed.). Newberry Park, CA: Sage. Josefi, O., & Ryan, V. (2004). Non-directive play therapy for young children with autism: A case study. Clinical Child Psychology and Psychiatry, 9(4), 533–551. Kennedy Krieger Institute. (2013). Autism knowledge and media questionnaire–1.0.2. Retrieved from http://dashboard. ianexchange.org/DataExplorer.aspx?FDID=92. Lord, C., & Bishop, S. L. (2010). Autism spectrum disorders: Diagnosis, prevalence, and services for children and families. Social Policy Report, Sharing Child and Youth Development Knowledge, 24(2), 1–26. Mackintosh, V. H., Myers, B. J., & Goin-Kochel, R. P. (2007). Sources of information and support used by parents of children with autism spectrum disorders. Journal on Developmental Disabilities, 12(1), 41–51. McLennan, J. D., Huculak, S., & Sheehan, D. (2008). Brief report: Pilot investigation of service receipt by young children with autistic spectrum disorders. Journal of Autism and Developmental Disorders, 38(6), 1192–1196. Mesibov, G. B., & Shea, V. (2010). Evidence-based practices and autism. Autism, 15(1), 114–133. Migongo, A. W., Charnigo, R., Love, M. M., Kryscio, R., Fleming, S. T., & Pearce, K. A. (2012). Factors relating to patient visit time with a physician. Medical Decision Making: An International Journal of the Society for Medical Decision Making, 32(1), 93–104.

Montes, G., Halterman, J. S., & Magyar, C. I. (2009). Access to and satisfaction with school and community health services for U.S. children with ASD. Pediatrics, 124(Suppl. 4), S407–S413. National Autism Center. (2009). National standards project: Addressing the need for evidence-based practice guidelines for autism spectrum disorders. Randolph, MA: Author. National Professional Development Center. (2010). Evidencebased practices. Retrieved from http://autismpdc.fpg.unc. edu/content/evidence-based-practices. National Research Council. (2001). Educating children with autism. Washington, DC: National Academy Press. Odom, S. L., Boyd, B. A., Hall, L. J., & Hume, K. (2010). Evaluation of comprehensive treatment models for individuals with autism spectrum disorders. Journal of Autism and Developmental Disorders, 40(4), 425–436. Odom, S. L., Collet-Klingenberg, L., Rogers, S. J., & Hatton, D. D. (2010). Evidence-based practices in interventions for children and youth with autism spectrum disorders. Preventing School Failure: Alternative Education for Children and Youth, 54(4), 275–282. Ohio Center for Autism and Low Incidence. (2014). Autism internet modules (AIM). Retrieved from http://www. autisminternetmodules.org/. Oswald, D. P., & Sonenklar, N. A. (2007). Medication use among children with autism spectrum disorders. Journal of Child and Adolescent Psychopharmacology, 17(3), 348–355. Pagoto, S. L., Spring, B., Coups, E. J., Mulvaney, S., Coutu, M. F., & Ozakinci, G. (2007). Barriers and facilitators of evidence-based practice perceived by behavioral science health professionals. Journal of Clinical Psychology, 63(7), 695–705. Reichow, B., & Volkmar, F. R. (2011). Evidence-based practices in autism: Where we stand. In B. Reichow, P. Doehring, D. V. Cicchetti, & F. R. Volkmar (Eds.), Evidence-based practices and treatments for children with autism (pp. 3–24). New York, NY: Springer. Reichow, B., Volkmar, F. R., & Cicchetti, D. V. (2008). Development of the evaluative method for evaluating and determining evidence-based practices in autism. Journal of Autism and Developmental Disorders, 38(7), 1311–1319. Rogers, S. J., & Vismara, L. A. (2008). Evidence-based comprehensive treatments for early autism. Journal of Clinical Child and Adolescent Psychology, 37(1), 8–38. Rubin, D. B. (1987). Multiple imputation for nonresponse in surveys. New York, NY: Wiley & Sons. Scarpa, A., White, S. W., & Attwood, T. (Eds.). (2013). CBT for children and adolescents with high-functioning autism spectrum disorders. New York, NY: Guilford Press. Schlomer, G. L., Bauman, S., & Card, N. A. (2010). Best practices for missing data management in counseling psychology. Journal of Counseling Psychology, 57(1), 1–10. Shattuck, P. T., & Grosse, S. D. (2007). Issues related to the diagnosis and treatment of autism spectrum disorders. Mental Retardation and Developmental Disabilities Research Reviews, 13, 129–135. Simonoff, E., Pickles, A., Charman, T., Chandler, S., Loucas, T., & Baird, G. (2008). Psychiatric disorders in children with autism spectrum disorders: Prevalence, comorbidity, and associated factors in a population-derived sample. Journal of the American Academy of Child and Adolescent Psychiatry, 47(8), 921–929. Soper, D. (n.d.). Free statistics calculators. Retrieved from http://www.danielsoper.com/statcalc3/default.aspx.

Please cite this article as: Lillian M. Christon, et al., Professionals’ Reported Provision and Recommendation of Psychosocial Interventions for Youth With Autism Spectrum Disorder, Behavior Therapy (2014), http://dx.doi.org/10.1016/j.beth.2014.02.002

professionals’ report on practices with youth with asd Symes, M. D., Remington, B., Brown, T., & Hastings, R. P. (2006). Early intensive behavioral intervention for children with autism: Therapists’ perspectives on achieving procedural fidelity. Research in Developmental Disabilities, 27(1), 30–42. Volkmar, F. R., Reichow, B., & Doehring, P. (2011). Evidencebased practices in autism: Where we are now and where we need to go. In B. Reichow, P. Doehring, D. V. Cicchetti, & F. R. Volkmar (Eds.), Evidence-based practices and treatments for children with autism (pp. 365–391). New York, NY: Springer. Williams, R. (n.d.). Interaction effects and group comparisons. Retrieved from www.nd.edu/~rwilliam/stats2/l51.pdf. Wong, C., Odom, S. L., Hume, K., Cox, A. W., Fettig, A., Kucharczyk, S., … Schultz, T. R. (2014). Evidence-based

15

practices for children, youth, and young adults with autism spectrum disorder. Retrieved from http://autismpdc.fpg.unc. edu/node/707. Wood, J. J., Fujii, C., & Renno, P. (2011). Cognitive behavioral therapy in high-functioning autism: Review and recommendations for treatment development. In B. Reichow, P. Doehring, & F. R. Volkmar (Eds.) Evidence-based practices and treatments for children with autism (pp. 197–230). New York, NY: Springer.

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Please cite this article as: Lillian M. Christon, et al., Professionals’ Reported Provision and Recommendation of Psychosocial Interventions for Youth With Autism Spectrum Disorder, Behavior Therapy (2014), http://dx.doi.org/10.1016/j.beth.2014.02.002