Developmental Trajectories of Children with Autism: What the ABLLS Can Tell Us About Their Development

Transcription

1 Developmental Trajectories of Children with Autism: What the ABLLS Can Tell Us About Their Development April Sullivan, York University, IWK Health Centre Mentor: Adrienne Perry, York University October 30, 2008 An appraisal of the Assessment of Basic Language and Learning Skills measure in evaluating outcomes of children with autism enrolled in the publicly funded intensive behavioural intervention program in Ontario 1

2 Executive Summary There are many treatments marketed for children with autism, but most lack empirical evidence (Perry & Condillac, 2003). On the other hand, research supports Intensive Behavioural Intervention (IBI) for children with autism (NRC, 2001; NYSDOH, 1999; Perry, 2002; Perry & Condillac, 2003; Schreibman, 2000). While most IBI studies were conducted in laboratory or university settings, a recent evaluation of Ontario s publicly funded IBI program demonstrated a decrease in symptoms and an increase in adaptive functioning among children with autism receiving IBI (Perry et al., 2008). This study was an important contribution to IBI research because it demonstrated that the treatment could be effectively implemented in the community. However, the Perry et al. study examined changes in pre-post standardized scores, which does not highlight the children s process of improvement, nor does it capture discrete, but clinically important gains that a fine-grained assessment administered throughout IBI would capture. The Assessment of Basic Language and Learning Skills (ABLLS; Partington & Sundberg, 1998) is a fine-grained assessment that is commonly used among professionals offering IBI to children with autism. It can be used to develop treatment goals and track progress over time. However, ABLLS profiles in typically developing children have not been examined, and the reliability and validity of this measure have not been established. This research outlines a three-part study. The first study was designed to explore the typical developmental trajectories of young children on the ABLLS. The second part examined the reliability and validity of the ABLLS. Finally, the third study used the ABLLS, in conjunction with standardized measures of cognitive and adaptive functioning, to explore the developmental trajectories of children with autism enrolled in a publicly funded IBI program. It was expected that this research would provide insight into the developmental trajectories of children with autism receiving IBI in the community. It was also expected that there would be different groups of children for whom IBI would be beneficial to different degrees. Study 1: This study included 14 typically developing children between the ages of 5 and 49 months who were assessed with the ABLLS and standardized measures at three time points over the course of nine months. The results revealed that the ABLLS was most sensitive to changes in development for children between 12 and 48 months of age. Study 2: The reliability investigation included 5 children with autism who were administered independent ABLLS assessments during the same time period. Overall agreement between the two raters was good, but inconsistent results emerged for some subscales. For the validity analysis, sixty children who received assessments with the ABLLS and standardized measures during the same time period were included. The ABLLS was found to correlate with standardized measures of cognitive and adaptive functioning, but it related more strongly with age-based scores from standardized measures. Study 3: The ABLLS was able to capture significant changes in skill development among children with autism enrolled in IBI. In keeping with other IBI studies, there appeared to be two groups of responders. That is, some children with autism progressed rapidly and acquired more skills than a group of children who progressed more slowly. Research examining predictors of response to IBI is ongoing. In summary, the results support the use of the ABLLS in children between 12 and 48 months of age. This developmental range should be kept in mind for clinicians who use this measure to track progress of children with delays in development. Overall, the ABLLS appears to be a valid and reliable tool, but additional research is necessary. In a sample of children with autism receiving IBI, the ABLLS captured changes in development, but there was a lot of variability in the sample. Future research with the ABLLS-Revised (Partington, 2006) is recommended. 2

3 Table of Contents Background... 4 Study 1: Typical Developmental Trajectories on the ABLLS... 4 Purpose.. 4 Methodology.. 4 Results 5 Discussion.. 6 Study 2: Exploring the Reliability and Validity of the ABLLS.. 7 Purpose.. 7 Methodology.. 7 Results. 8 Discussion.. 8 Study 3: Developmental Trajectories of Children with Autism Enrolled in IBI.. 9 Purpose.. 9 Methodology.. 9 Results. 10 Discussion.. 11 Conclusion Knowledge Exchange 12 References Appendix

4 Background: Intensive Behaviorual Intervention (IBI) is a comprehensive treatment approach with a theoretical and empirical basis in the applied behaviour analysis literature. It was originally developed by Lovaas (1987) who reported significant gains among children with autism enrolled in an IBI program from the age of three until age five. A follow-up study revealed that the children maintained their gains at age 13 (McEachin, Smith, & Lovaas, 1993). Although there have been critiques of this research (see Gresham & MacMillan, 1998), these concerns have been adequately addressed (Eikeseth, 2001; Smith & Lovaas, 1997). In addition, the results have been replicated in controlled studies comparing IBI to other forms of intervention (Eikeseth et al., 2002; Sallows & Graupner, 2005; Sheinkopf & Siegel, 1998). The current consensus among many professionals is that IBI is best practice for children with autism (NRC, 2001; NYSDOH, 1999; Perry, 2002; Perry & Condillac, 2003; Schreibman, 2000). One critique of IBI studies involves the feasibility of applying the program in the community where there are fewer resources and less control over relevant factors than would be typically found in university-based research programs. However, a recent review of a community-based program demonstrated the effectiveness of IBI for young children with autism. More specifically, Perry and colleagues (2008) reported a decrease in autism symptoms and an increase in adaptive behaviour following IBI for children with different levels of autism severity and cognitive functioning. A limitation of this research involved the use of a pre-post design to demonstrate gains made by children from baseline to post treatment. As a result, it provided little information about the nature of skill acquisition throughout treatment. In an effort to elucidate developmental trajectories of children with autism in IBI, Sallows and Graupner (2005) used standardized measures annually across four years. The results demonstrated that some children responded more rapidly to IBI and achieved higher scores on standardized measures than other children enrolled in the treatment. However, the standardized measures used in the study, only provide information on skill acquisition in broad domains of development, and are often not sensitive enough to detect changes in children who make modest gains. Therefore, a fine-grained analysis of skill acquisition during IBI treatment is still lacking in the literature. Currently, community-based IBI programs in Ontario use The Assessment of Basic Language and Learning Skills (ABLLS; Partington & Sundberg, 1998) to measure skill acquisition. The ABLLS is a fine-grained assessment tool that can be used to track the development of skills while providing professionals with suggestions for treatment objectives. However, developmental trajectories on the ABLLS for typically developing children have not been adequately explored, and the reliability and validity of this measure has yet to be established. The first purpose of this research was to examine typical developmental trajectories on the ABLLS for young children. The second purpose was to explore the reliability and validity of the ABLLS. Finally, the main objective of this research was to use the ABLLS to clarify the nature of skill acquisition among children with autism enrolled in the publicly funded IBI program. Study 1: Typical Developmental Trajectories on the ABLLS Purpose: The purpose of this study was to explore whether the ABLLS is sensitive to change in children between 5 and 56 months of age (i.e., the approximate developmental levels of the children the measure is intended for). Methodology: This study used ABLLS data for 14 children (8 boys and 6 girls), with a mean age was 24 months (SD = 13.67). The ABLLS includes four broad areas of development: Basic Learning, Academic, Self- Help, and Motor Skills. These four domains encompass 25 skill areas that cover language and learning skills (see Table 1). The appendix includes a description of each skill area with examples of relatively basic and more advanced skills included in each of the areas. The 4

5 ABLLS Protocol is comprised of a set of grids that depict each skill area. A different colour is typically used to code skills mastered at each assessment. This charting system is intended to facilitate the tracking of increasingly complex skill acquisition. For the purposes of this study, the tracking grids were quantified by calculating the cumulative percentage of items completed in each skill area at each assessment. For instance, if there were 20 items in a skill areas and a child had 5 skills at baseline assessment, 10 skills at the second assessment, and 20 skills at the third assessment, the cumulative percentage scores would be 25%, 50%, and 100%, respectively. The authors of the ABLLS (Partington, personal communication, May 29, 2006; Sundberg, personal communication, February, 3, 2007), along with professionals who are familiar with the measure, were consulted about how to appropriately quantify ABLLS data. The children in this study were followed longitudinally for a period of 9 months and were assessed at three time points. Due to parents time constraints, 3 participants only completed the baseline and post assessments. As a result, 11 participants have three assessment points, and 3 participants have two assessment points. Table 1: Skill areas included in the ABLLS Basic Learning Skills Academic Skills Self-Help Skills Motor Skills Cooperation and Reinforcer Effectiveness Visual Performance Receptive Language Imitation Vocal Imitation Requests Labeling Intraverbals Spontaneous Vocalizations Syntax and Grammar Play and Leisure Social Interaction Participation in Group Instruction Classroom Routines Generalized Responding Reading Math Writing Spelling Dressing Eating Grooming Toileting Gross Motor Fine Motor Results: To determine the sensitivity of the ABLLS for detecting change in young children, a cross-sectional representation of the individual baseline data for the total ABLLS score is depicted in Figure 1. The graph indicates that there was very little variability in skill acquisition for children less than 12 months of age, followed by a linear increase in skill level for children up to 48 months of age. It is noteworthy that there was some variability in total skills acquired for two children who were of similar age. That is, for one child who was 28 months of age, 39% of skills were acquired compared to 77% of skills for a 29-month-old child. On the other hand, there was very little variability in total ABLLS score for two 21-month-old children who achieved 26% and 30% of ABLLS skills at baseline. When the individual developmental trajectories were explored over the course of 9 months (see Figure 2), the variability in the sample was markedly reduced, compared to the cross-sectional view of the sample (see Figure 1). The progression of skill acquisition for the 5

6 total ABLLS score, depicted in Figure 2, appears linear, but there is some variability in the sample. It is also noteworthy that two children reached a ceiling on the ABLLS between 48 and 56 months of age, demonstrating the reduced sensitivity of the ABLLS for detecting change in children beyond a developmental level of 48 months. 100 % of Total ABLLS Skills Age in Months Figure 1. Cross-sectional view of the Percentage of Total ABLLS Skills at baseline for typically developing children between 5 and 49 months of age. % of Total ABLLS Skills Age in Months Figure 2. Longitudinal view of the Percentage of Total ABLLS Skills acquired over the course of 9 months for typically developing children between 5 and 49 months of age. Discussion: The purpose of this study was to explore whether the ABLLS is sensitive to change in young children. A visual inspection of the information obtained indicates that the ABLLS is sensitive to change in children under the age of 5. This corresponds to the appropriate age group suggested by Partington and Sundberg (1998). The ABLLS appears to capture linear changes in development, and is most sensitive to change among children between 12 and 48 6

7 months of age. There is a floor effect for children less than 12 months of age and a ceiling effect in for children over 48 months of age. A closer look at how the ABLLS captures typical development over time reveals some variability among children of similar ages. However, this variability becomes less pronounced over time as children approach a ceiling on this measure. The variability among participants of similar age may be expected given that the measure captures fine-grained skill development in which children are expected to be somewhat heterogeneous. Since the measure is routinely used to track skill development for an individual child, and profiles are not meant to be compared across children, the variability among children may not affect its utility. A major limitation in this study includes the small sample size, which is especially problematic when looking at the variability in the sample. It is possible that with a larger sample size, more children of similar age would display more homogeneous skill development on the ABLLS. It is recommend that future studies recruit a larger sample of participants and follow children over a longer time frame to help elucidate trajectories on this measure. In addition, the families who participated in this study were recruited through a university and an agency that services people with developmental disabilities. All of the children in this study had at least one parent who has a post-secondary education in child development and experience working with children who have special needs. As a result, children in this study are not diverse and may not be representative of the population as a whole. Study 2: Exploring the Reliability and Validity of the ABLLS In a recent American survey, 57% of professionals who offer behavioural interventions to children with autism reported using the ABLLS curriculum (Carr, 2006). The ABLLS is also the most widely used curriculum and assessment tool in Ontario s publicly IBI program. In addition, the ABLLS has gained popularity in autism intervention research (Aman, Novotny, Samango- Sprouse, et al., 2004; Goin-Kochel, Myers, Hendricks, Carr, & Wiley, 2007). Many professionals choose the ABLLS because it allows for a fine-grained assessment of skills, and the assessment leads directly to discrete treatment goals that can be monitored over time with this measure. Although the ABLLS is a popular assessment tool, there is little information available about its psychometric properties. That is, the developers of the ABLLS, as well as independent researchers, have not yet established whether it is a reliable and valid indicator of skill development. Purpose: The present study focuses on criterion-related validity, or the relationship between the ABLLS and standardized measures of development. Also of interest, inter-rater reliability was examined because the ABLLS is a behavioural measure of skills, which is subject to the interpretation of the observer. Inter-rater reliability is used to refer to the correspondence between the scores obtained by two independent raters and is measured using an intraclass correlation coefficients. Given that the ABLLS is a widely used clinical tool with little information available about the reliability and validity of this measure, the goals of this study were twofold: 1) to examine the validity of the ABLLS, or how it relates to standardized measures of cognitive and adaptive functioning, and 2) to explore the inter-rater reliability of the ABLLS among a group of preschool children with autism. Methodology: To explore the validity of the ABLLS, 69 children with ABLLS assessments and measures of cognitive or adaptive functioning within 2 months of their ABLLS assessments were included in this study. The overall sample consisted of 14 girls and 55 boys who ranged in age from 7 to 88 months (M = 58.12, SD = 21.06). Among the participants were 14 typically 7

8 developing children (6 girls, 8 boys) between the ages of 7 and 56 months (M = 25.71, SD = 14.24). The sample also consisted of 31 children diagnosed with autism (5 girls, 26 boys) between the ages of 28 and 88 months (M = 65.87, SD = 15.19), and 24 children diagnosed with pervasive developmental disorder-not otherwise specified (PDD-NOS) (3 girls, 21 boys) ranging in age from 42 to 87 months (M = 67.00, SD = 9.65). Five children with autism or PDD-NOS, who were enrolled in IBI at the time of the study, were recruited to participate in the inter-rater reliability study. The participants ranged in age from 51 to 67 months (M = 60.80, SD = 6.65), and were all boys. Validity Results: The ABLLS was administered along with the Mullen Scales of Early Learning (MSEL; Mullen, 1995) and the Vineland Adaptive Behavior Scales (VABS; Sparrow, Balla., & Cicchetti, 1984). The psychological assessment data (i.e., the VABS and MSEL) were compared to the ABLLS data. When the Total percentage of skills acquired on the ABLLS was compared to the Adaptive Behavior Composite and median age equivalent from the VABS, the correlations were significant, but higher for the age equivalents. Similarly, when the Total Score from the ABLLS was compared to MSEL Composite and median mental age estimates from the MSEL, both were correlated with the ABLLS Total Score, but the mental age estimate was more strongly correlated (see Table 2). Table 2: Correlations between ABLLS Total Score and Standardized Measures of Adaptive and Cognitive Functioning (n vabs = 82, n msel = 60) ABLLS Total Score **p <.001 VABS ABC Scores from Standardized Tests VABS Age MSEL Equivalents Composite.49**.83**.57**.90** MSEL Median Age Equivalent Inter-rater Reliability Results: The repeat administrations of the ABLLS by independent staff were compared using intraclass correlation coefficients (ICC) (McGraw & Wong, 1996) (see Table 5). Intraclass correlation coefficients allow for an examination of the pattern and magnitude of agreement between the two raters (Sattler, 2002). The ICC for the ABLLS total score was high, ICC =.97, p <.001. Discussion: This study was intended to explore the psychometric properties of the ABLLS, that is, the validity of the ABLLS with standardized measures of development, and inter-rater reliability for independent assessors. An examination of the validity of the ABLLS with standardized measures of cognitive and adaptive functioning revealed that the overall ABLLS score was strongly correlated with the composite age equivalent scores from the MSEL and VABS. With respect to inter-rater reliability, the results of the intraclass correlation test indicate that the ABLLS total score had acceptable inter-rater agreement, particularly with age equivalent scores. In summary, this study provides a much needed look at the psychometric properties of a popular curriculum-based assessment tool. It is imperative that the validity and reliability of measures are explored if decisions about treatment goals and gains are to be made based on their results. However, this study is not without its limitations. The first major consideration for future research involves the sample size. The reliability sample, in particular, is quite small (i.e., n = 5) and should be expanded in future studies of the ABLLS psychometric properties. Additional concerns about this sample include the relatively narrow characteristics of the 8

9 sample. Future studies should aim to include children with varying diagnoses, functioning levels, and age. It is also important to include raters with varying levels of training/experience since training may impact administration and scoring of the ABLLS. Investigations of the validity should also encompass additional measures of cognitive and adaptive functioning with current normative data, such as the recently revised Vineland Adaptive Behavior Scales and the Stanford-Binet Intelligence Scale, 5 th edition. This would allow professionals to compare the results of the ABLLS with current population norms. Although there is a strong relationship between the ABLLS-R and the original ABLLS, future investigations should also utilize the ABLLS-R to investigate the reliability and validity of this measure. Study 3: Developmental Trajectories of Children with Autism Enrolled in IBI Previous IBI research has demonstrated the importance of this intervention for young children with autism. Although IBI studies were typically conducted in laboratory or university settings, Perry and colleagues (2008) demonstrated that IBI could be effectively implemented in the community under less than ideal conditions. The present study sought to explore the developmental trajectories of children with autism in a publicly funded IBI program. By using the ABLLS to track progress of children with autism, a fine-grained, longitudinal analysis of skill acquisition was made available. Purpose: The main objective of this study was to explore the pattern of skill acquisition during IBI using longitudinal ABLLS data. Methodology: Seventy-five children with ABLLS assessments who had been enrolled in IBI for at least 12 months (M duration = 26.17, SD = 9.69, range = 12 63) were included in the study. The overall sample consisted of 62 boys and 13 girls who ranged in age from 20 to 71 months (M = 47.24, SD = 14.31). The sample consisted of 43 children diagnosed with autism (35 boys, 8 girls) and 32 children diagnosed with PDD-NOS (27 boys, 5 girls). It is likely that some of the children in this study had comorbid diagnoses (e.g., Fragile X) since these diagnoses did not exclude children from the IBI program. However, no systematic information on comorbid conditions was available. Children diagnosed with autism and PDD-NOS were compared on relevant variables to determine if they could be collapsed into the same group. There were no significant differences in age at the start of treatment, t (73) = 1.04, p =.302, initial cognitive level 1, t (22) = , p =.194, or duration of treatment, t (73).109, p =.914, between the two diagnostic groups. As such, the children diagnosed with PDD-NOS and autism were combined for all additional analyses. Psychologists or Developmental Pediatricians in the community diagnosed all participants in this study. The diagnosis was then confirmed by a Clinical Psychologist with extensive experience with developmental disabilities, prior to beginning IBI. As part of the intake assessment, standardized measures of cognitive and adaptive functioning were administered to participants, along with the Childhood Autism Rating Scale (Schopler, Reichler, & Renner, 1988). Upon completion of the eligibility assessment, children were enrolled in the publicly-funded IBI program in Ontario. The number of hours per week of IBI varied between 20 and 40 hours. However, there were occasions when children received fewer hours due to illness, building tolerance to treatment, or when transitioning out of the program. The duration of IBI ranged from 12 to 63 months (M = 26.17, SD = 9.69). A review of the theoretical background and design of the program has been published by Perry (2002) (also see Perry et al., 2008). 1 Note: information regarding baseline cognitive level was only available for a subset of participants. 9

10 As part of clinical care, staff in the IBI program initially assessed participants using the ABLLS and periodically during treatment. The average length of time between ABLLS assessments was 6 months (SD = 3.10), but the time between assessments varied widely from 1 to 25 months. The number of ABLLS assessments available for a particular child varied between 1 and 9 (M = 3.92, SD = 1.63). Forty children were assessed at the beginning of IBI and are considered to have baseline data. Results: Prior to examining developmental trajectories of children with autism enrolled in IBI, pre-post scores from cognitive, adaptive, and symptom severity measures were compared using paired t-tests. The results indicated that their estimated IQ scores, mental ages, and adaptive functioning significantly improved. Furthermore, there was a significant reduction in autism symptom severity (see Table 3). Table 3: Comparison of Psychological Assessment Intake and Exit Scores Intake M (SD) Exit M (SD) Full Scale IQ (n = 16) (13.87) (30.35) <.001 Mental Age (n = 16) (10.52) (22.55) <.001 VABS Adaptive Behavior Composite (n = 66) Median VABS Age Equivalent (n = 66) (8.90) (19.87) (5.18) (17.35) <.001 CARS Total (n = 67) (4.09) (5.13) 6.89 <.001 t p To examine the developmental trajectories of children with autism, total ABLLS scores were plotted over the course of IBI (see Figure 3). This illustrates that the percentage of skills acquired increase as children progress through IBI, but there is a lot of variability in response to treatment. Percentage of ABLLS Skills Acquired Months in Treatment Figure 3: Individual growth plots of the percentage of total ABLLS skills acquired during IBI. 10

11 It appears that children who are have fewer skills on the ABLLS at baseline progress more slowly through IBI than those who have more skills at baseline. However, there are some children who had very few skills at baseline who do respond rapidly to IBI. Other researchers who have examined longitudinal data for children with autism enrolled in IBI have found that there are two groups of responders to treatment: rapid and moderate (Birnbrauer & Leach, 1993; Goin-Kochel et al., 2007; Howard, Sparkman, Cohen, Green, & Stanislaw, 2005; Sallows & Graupner, 2005). A review of the data presented below suggests that there are two groups of responders to IBI in this sample as well. Future research will help to determine if groups of treatment responders can be statistically separated in this sample. Discussion: This study explored pre-post psychological data, along with longitudinal ABLLS data from a publicly funded IBI program in Ontario. The results from standardized measures of cognitive ability, adaptive functioning, and symptom severity revealed that, as a group, children with autism made significant gains in treatment. However, a visual inspection of ABLLS data indicates that response to treatment did vary among children. In fact, children appeared to cluster into two groups, relatively rapid responders and moderate responders, which corresponds to the results of other IBI studies (Birnbrauer & Leach, 1993; Goin-Kochel et al., 2007; Howard, Sparkman, Cohen, Green, & Stanislaw, 2005; Sallows & Graupner, 2005). It appears that children who began the program at a lower level of functioning were less likely to respond rapidly to IBI. Future analyses should help to clarify if initial developmental level, or other pre-treatment variables, can significantly predict response to treatment. Conclusion The results of this study support the use of the ABLLS to track skill acquisition in children between 12 and 48 months of age. However, not all aspects of the ABLLS will be applicable to children in this age group. There are some skill areas that may be appropriate for children beyond 48 months of age (e.g., academics), while others may be more appropriate for younger children (e.g., vocal imitation). Professionals who use this tool should be cognizant of the developmental level of the child and the ability of the various skill areas on the ABLLS to capture developmentally appropriate skill development. The results of this study also provide support for inter-rater reliability and validity of the ABLLS as a whole, but caution should be exercised when looking at individual skill areas of the ABLLS. Exploring typical developmental trajectories and psychometric properties of the ABLLS were important steps in clarifying the strengths and limitations of this measure. By having this information available, parents and professionals have a better understanding of how to appropriately use the ABLLS. An exploration of developmental trajectories on the ABLLS for children with autism enrolled in IBI revealed that the measure is sensitive to change. It captured increases in skill development among children in this study, and highlighted different degrees of response to treatment. Future research will help to clarify if response to treatment, as captured by the ABLLS, can be predicted before treatment begins or within the first few months. This would help clinicians develop appropriate goals and treatment placements for young children with autism by providing an empirical basis to help guide decisions about service delivery. If researchers who claim that treatment programs need to be individualized for children with autism are correct (Schreibman, 2000) then this study should help to clarify the predictors of change in developmental trajectories for children with varying levels of impairment. In doing so, clinicians may be better able to determine which children will likely benefit from IBI and in what way. In the coming months, additional analyses will also explore how children with autism developed in discrete skill areas on the ABLLS. 11

12 Knowledge Exchange Preliminary results from this study were shared with the Clinical Directors of the IBI programs where the data was collected, and with the author of the ABLLS. In addition, the results were presented at local and international conferences in an effort to reach both parents and professionals (see list of conferences below). As additional analyses are completed, the results of this study will be submitted for publication and shared with the public through a writeup in autism society newsletters. The results will also be shared with the Ontario Association for Developmental Disabilities and the Ontario Association for Behaviour Analysis. I believe that these would be effective ways to transfer knowledge, but I also look forward to working with the Centre to develop more strategies for knowledge exchange. Conference Presentations To Date: Sullivan, A., Perry, A., Freeman, N., & Bebko, J. (June, 2007). A Closer Look at The Assessment of Basic Language and Learning Skills Tracking System: Reliability, Validity and Its Use in Tracking Progress of Children with Autism. Poster presented at the Canadian Psychological Association 69 th Annual Convention, Halifax, Nova Scotia, Canada. Sullivan, A., Paszti, A., Szikszai, P., Joseph, L., & Perry, A. (November, 2007). Inter-rater reliability of the ABLLS in preschool children with autism. Poster presented at the 15 th Annual Ontario Association for Behavioural Analysis Conference, Toronto, Ontario, Canada. Sullivan, A., Rosenthal, H., & Perry, A. (November, 2007). Gender differences in developmental trajectories among children with autism enrolled in IBI. Poster presented at the 15 th Annual Ontario Association for Behavioural Analysis Conference, Toronto, Ontario, Canada. Sullivan, A., Perry, A., Freeman, N., & Bebko, J. (May, 2007). Developmental trajectories of young children with autism enrolled in an IBI program: What the ABLLS can tell us about their progress. Oral presentation at the Association for Behavior Analysis 33 rd Annual Convention, San Diego, California, USA. Sullivan, A., Perry, A., Freeman, N., & Bebko, J. (February, 2007). Using the ABLLS to capture changes in developmental trajectories of children with autism enrolled in an IBI program. Poster presented at the Association for Behavior Analysis International 2007 Autism Conference, Boston, Massachusetts, USA. Sullivan, A. & Perry, A. (November, 2006). Developmental trajectories of typically developing children captured by the ABLLS. Poster presented at the 14 th Annual Ontario Association for Behavioural Analysis Conference, Toronto, Ontario, Canada. 12

13 References Aman, M. G., Novotny, S., Samango-Sprouse, C, Lecavalier, L, Leonard, E., Gadow, K. D., King, B. H., Pearson, D. A., Gernsbacher, M. A., & Chez, M. (2004). Outcome measures for clinical drug trials in autism. CNS Spectrums, 9, Birnbrauer, J. S., & Leach, D. J. (1993). The Murdoch early intervention program after 2 years. Behaviour Change, 10, Carr, J. E. (November, 2006). Early and intensive behavioral intervention for autism: A survey of intervention procedures. Invited Address at the Ontario Association for Behavioural Analysis Annual Conference, Markham, Ontario. Eikeseth, S. (2001). Recent critiques of the UCLA Young Autism Project. Behavioral Interventions, 16, Eikseth, S., Smith, T. Jahr, E. & Eldevik, S. (2002). Intensive behavioral treatment at school for 4- to 7-year-old children with autism: A one-year comparison controlled study. Behavior Modification, 26, Goin-Kochel, R. P., Myers, B. J., Hendricks, D. R., Carr, S. E., & Wiley, S. B. (2007). Early responsiveness to intensive behavioral intervention predicts outcomes among preschool children with autism. International Journal of Disability, Development and Education, 54, Gresham, F. M., & MacMillan, D. L. (1998). Early intervention project: Can its claims be substantiated and its effects replicated? Journal of Autism and Developmental Disorders, 28, Howard, J. S., Sparkman, C. R., Cohen, H. G., Green, G. G., & Stanislaw, H. (2005). A comparison of intensive behavior analytic and eclectic treatments for young children with autism. Research in Developmental Disabilities, 26, Lovaas, O. I. (1987). Behavioural treatment and normal educational and intellectual functioning in young autistic children. Journal of Consulting and Clinical Psychology, 55, 3-9. McEachin, J. J., Smith, T., & Lovaas, O. I. (1993). Long-term outcome for children with autism who received early intensive behavioral treatment. American Journal on Mental Retardation, 97, McGraw, K. O., & Wong, S. P. (1996). Forming inferences about some intraclass correlation coefficients. Psychological Methods, 1, Mullen, E. M. (1995). Mullen scales of early learning: AGS edition. Circle Pines, MN: American Guidance Service. National Research Council (NRC) (2001). Educating children with autism. The Committee on Education and Interventions for Children with Autism. Division of Behavioral and Social Sciences and Education. Washington, DC: National Academy Press. 13

14 New York State Department of Health (NYSDOH ) (1999). Autism/Pervasive Developmental Disorders. Clinical practice guidelines technical report. New York: Author. Partington, J. W. (2006). Assessment of Basic Language and Learning Skills-Revised (The ABLLS-R): An assessment, curriculum guide, and skills tracking system for children with autism or other developmental disabilities. Pleasant Hill, CA: Behavior Analysts Inc. Partington, J. W. & Sundberg, M. L. (1998). The Assessment of Basic Language and Learning Skills. Pleasant Hill, CA: Behavior Analysts Inc. Perry, A. (2002). Intensive early intervention program for children with autism: Background and design of the Ontario preschool autism initiative. Journal on Developmental Disabilities, 9, Perry, A. & Condillac, R. A. (2003). Evidence-based practices for children with autism spectrum disorders. Toronto, ON: Children s Mental Health Ontario. Perry, A., Cummings, A., Dunn Geir, J., Freeman, N. L., Hughes, S., LaRose, L., Managhan, T., Reitzel, J., & Williams, J. (2008). Effectiveness of intensive behavioral intervention in a large, community-based program. Research in Autism Spectrum Disorders, 2, Perry, A. & Factor, D.C. (1989). Psychometric validity and clinical usefulness of the Vineland Adaptive Behavior Scales and AAMD Adaptive Behavior Scale for an autistic sample. Journal of Autism and Developmental Disorders, 19, Sallows, G. O., & Graupner, T. D. (2005). Intensive behavioral treatment for children with autism: Four-year outcome and predictors. American Journal on Mental Retardation, 110, Sattler, J. M. (2002). Assessment of children: Behavioral and clinical applications, 4 th edition. San Diego: Author. Schopler, E., Reichler, R. J., & Renner, B. R. (1988). The Childhood Autism Rating Scale (CARS). Los Angeles, CA: Western Psychological Association. Schreibman, L. (2000). Intensive behavioural/psychoeducational treatments for autism: Research needs and future directions. Journal of Autism and Developmental Disorders, 30, Sheinkopf, S. J., & Siegel, B. (1998). Home-based behavioral treatment of young children with autism. Journal of Autism and Developmental Disorders, 28, Smith, T., & Lovaas, O. I. (1997). The UCLA Young Autism Project: A reply to Gresham and MacMillan. Behavioral Disorders, 22, Sparrow, S. S., Balla, D. A., & Cicchetti, D. V. (1984). Vineland Adaptive Behavior Scales (VABS). Circel Pines, MN: American Guidance Service. 14

15 Appendix Skill Area A. Cooperation & Reinforcer Effectiveness Description Accepting reinforcement, making choices, seeking approval for task completion. E.g., Takes reinforcer when offered; Waits appropriately if reinforcer is delayed. B. Visual Performance Attending to and manipulating nonverbal stimuli. E.g. Match identical objects to sample; Correctly draws lines through simple mazes. C. Receptive Language Understands and follows instructions. E.g., Responds to name; Follows multiple component sequence instruction. D. Imitation Motor imitation. E.g., motor imitation with objects; Spontaneously imitates actions of others. E. Vocal Imitation Imitation of spoken language. Also targets articulation, tone and prosody. E.g., Imitates sounds; Spontaneous imitation of phrases. F. Requests Ability to request reinforcers and information. Takes into consideration complexity of vocal requests. E.g., nonverbal (gestures) used to request desired items; Spontaneous requests. G. Labeling Ability to label and describe objects and events in one s environment. Takes into consideration complexity of expressive language. E.g., Labels reinforcers; Spontaneous labeling. H. Intraverbals Ability to respond to verbal cues. Includes knowledge of the function, feature and classification of objects and answering questions. E.g., Fill in words from songs; Answer novel questions; Tells stories. I. Spontaneous Vocalizations Ability to spontaneously use language. E.g., vocalizes identifiable speech sounds; Spontaneous conversation. J. Syntax & Grammar Appropriate use of syntax and grammar in phrase speech. E.g., Correct word order; uses irregular plurals. K. Play & Leisure Appropriate play with toys and others. E.g., explores toys in the environment; engages in outdoor interactive games 15

16 Skill Area Description L. Social Interaction Applies appropriate social skills. E.g., shows interest in others; appropriately maintains attention of others. M. Group Instruction Attends to instructors in group settings. E.g., sits appropriately in small groups; learns new skills in group instruction format. N. Classroom Routines Demonstrates appropriate behaviour in classroom settings. E.g., lines up when requested; works independently; follows daily classroom routines. P. Generalized Responding Demonstrates knowledge acquired with a variety of stimuli and in multiple settings. E.g., generalizes across stimuli; generalizes language skills. Q. Reading Pre-academic and academic reading skills. E.g., receptive letter recognition; reads passages and answers questions. R. Math Development of math skills. E.g., rote counting with prompts; tells time; understands comparative number concepts. S. Writing Written language skills. E.g., marks on paper; prints numbers and letters. T. Spelling Includes letter matching and spelling. E.g., matches individual letters; spells words in written form. U. Dressing Development of independent dressing skills. E.g., pulls pants up and down; adjusts clothing when necessary. V. Eating Development of independent eating skills. E.g., eats finger foods; keeps eating area clean. W. Grooming Development of appropriate grooming skills. E.g., washes hands; blows nose when needed. X. Toileting Development of independent toileting skills. E.g., urinates in toilet; uses restroom without assistance. Y. Gross Motor Development of gross motor skills. E.g., creeps on stomach; hangs from bar. Z. Fine Motor Development of fine motor skills. E.g., places objects in form box; squeezes glue from a bottle. 16