An Analysis of the Effectiveness of Reinforcers Identified via Multiple-Stimulus Without. Replacement Preference Assessments.

Transcription

1 An Analysis of the Effectiveness of Reinforcers Identified via Multiple-Stimulus Without Replacement Preference Assessments Dissertation Presented in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in the Graduate School of The Ohio State University By Christopher Aaron Tullis, M. S. Graduate Program in Education The Ohio State University 2012 Dissertation Committee Dr. Helen I. Malone, Advisor Dr. Sheila Alber-Morgan Dr. Dianne Sainato

2 Copyrighted by Christopher A. Tullis 2012

3 Abstract Preference assessment methodologies have been demonstrated to effectively identify reinforcers for individuals with moderate to intensive disabilities, but the primary method of validating assessment outcomes has been to measure the occurrence of a simple operant response (e.g., card exchange). The effectiveness of a stimulus to function as a reinforcer for a simple operant response may not generalize to more complex responses (e.g., dressing). This investigation presents an exploration of the reinforcing effectiveness of stimuli identified using a preference assessment in basic and complex arrangements for three adolescent males with moderate to intensive disabilities. An MSWO was conducted to identify high- (HP) and low-preference (LP) stimuli. Next, a basic reinforcer assessment was used to determine if the identified HP and LP stimuli functioned as reinforcers with a simple operant response (i.e., card exchange). The item identified as a reinforcer with a simple operant response was then tested using a complex operant response (i.e., discrimination). Data indicated that for one participant, the items identified as HP were not reinforcers under either basic or complex arrangements. For one participant, the HP item was a reinforcer in the basic assessment, but not in the complex assessment. For the last participant, the item identified as a reinforcer maintained effectiveness under both basic and complex assessments. iii

4 To me, because I wrote it. A. Lee Martinez iv

5 Acknowledgments I ve tried to write this over and over, and I do not think I could adequately express how thankful I am to everyone that has helped me along the way. Many of you should get an award, or your own Ph.D. for putting up with an absent son, grandson, cousin, nephew, brother, boyfriend, and friend. My gratitude is endless, and I do not think I would have survived and been successful without your support and encouragement. Jenni, you have been understanding, encouraging, brutally honest, and an overall great girlfriend. I do not think I would have made it through many days without you as a sounding board and supporter. Mom, Jon, Dad, and Mimi, all of you have had nothing but supreme confidence in my abilities as a student. On my worst days, I always knew one of you could give me a pep talk that could change my outlook, and on the best I knew you were prouder of my accomplishments than I could ever be. I hope one day to repay all of you for your patience and support. For the ones with your own Ph.D., thank you for your mentorship and encouragement in the past three years. I have learned an immense amount about myself as a professional and scholar. Thank you! v

6 Vita B.S. Psychology, The University of Georgia Behavior Data Specialist, The Marcus Institute Clinical Specialist I, The Marcus Institute Clinical Specialist II, The Marcus Institute/Autism Center, Children s Healthcare of Atlanta M.S. Educational Psychology, Georgia State University 2009 to present...graduate Research Assistant, The Ohio State University Publications Cannella-Malone, H. I., Wheaton, J. E., Wu, P. F., Tullis, C. A., & Park, J. H. (in press). A comparison of the effects of video prompting with and without error correction on skill acquisition for individuals with severe disabilities. Education and Training in Autism and Developmental Disabilities. Tullis, C. A., Cannella-Malone, H. I., & Fleming, C. V. (in press). Multiple stimulus without replacement preference assessments: An examination of the relation between session number and effectiveness. Journal of Developmental and Physical Disabilities. Cannella-Malone, H. I., Tullis, C. A., & Kazee, A. (2011). An examination of the effects of physical exercise on aggressive behavior in individuals with developmental disabilities. Journal of Positive Behavioral Interventions, 13, vi

7 Tullis, C. A., Cannella-Malone, H. I., Basbigill, A. R., Yeager, A., Fleming, C. V., Payne, D., & Wu, P. (2011). Review of the choice and preference assessment literature for individuals with severe to profound disabilities. Education and Training in Autism and Developmental Disabilities, 46, Cannella-Malone, H. I., Fant, J. I., & Tullis, C. A. (2010). Using the picture exchange communication system to increase the social communication of two individuals with severe developmental disabilities. Journal of Developmental and Physical Disabilities, 22, Cannella-Malone, H. I., & Tullis, C. A. (2010). Use of video modeling to teach individuals with autism spectrum disorders: A systematic review of literature still needed. Evidence-Based Communication Assessment and Intervention, 4, Fields of Study Major Field: Education Area of Emphasis: Special Education & Applied Behavior Analysis vii

8 Table of Contents Abstract... iii! Dedication... iv! Acknowledgments... v! Vita... vi! List of Tables... x! List of Figures... xi! Chapter 1: Introduction... 1! Chapter 2: Literature Review... 10! Chapter 3: Method... 39! Chapter 4: Results... 56! Chapter 5: Discussion... 68! References... 88! Appendix A: Literature Review Data Sheet... 98! Appendix B: Study Recruitment Letter ! Appendix C: Consent Form ! viii

9 Appendix D: Reinforcer Assessment for Individuals with Severe Disabilities ! Appendix E: MSWO Preference Assessment Data Sheet ! Appendix F: MSWO Preference Assessment Treatment Integrity Data Sheet ! Appendix G: Basic Reinforcer Assessment Data Sheet ! Appendix H: Basic Reinforcer Assessment Procedural Integrity Data Sheet ! Appendix I: Complex Reinforcer Assessment Data Sheet ! Appendix J: Complex Reinforcer Assessment Procedural Integrity Data Sheet ! ix

10 List of Tables Table 1. Literature Review Results x

11 List of Figures Figure 1. Example of stimulus card used during basic reinforcer assessments Figure 2. Diagram of the session room Figure 3. Example of tasks taught during reinforcer assessment Figure 4. Preference assessment results for Ike Figure 5. Basic reinforcer assessment for Ike Figure 6. Complex reinforcer assessment results for Ike Figure 7. Preference assessment results for Percy Figure 8. Basic reinforcer assessment data for Percy Figure 9. Complex reinforcer assessment for Percy Figure 10. Preference assessment data for Roy Figure 11. Basic reinforcer assessment for Roy Figure 12. Complex reinforcer assessment for Roy xi

12 Chapter 1: Introduction Research has demonstrated that individuals with moderate to intensive disabilities can indicate clear preferences through methodologically rigorous assessments (e.g., Cannella, O Reilly, & Lancioni, 2005; Lancioni, O Reilly, & Emerson, 1996; Tullis et al., 2011). The identification of preferences and preference assessment methodologies may be useful for several reasons. First, objectively identifying preference for a variety of stimuli may allow for easy identification of items that may have a high degree of reinforcing effectiveness (Cannella et al., 2005). Second, it allows individuals who have limited communication skills to help teachers and other practitioners determine what stimuli are used as reinforcers or to aid in selection of preferred leisure activities. Lastly, objective measures of preference may be a more accurate and sensitive method of determining stimulus preference (Green, Reid, White, Brittain, & Gardner, 1998). Overall, preference assessment methodologies have the potential to enhance the educational and habilitative experiences of individuals with moderate to intensive intellectual and developmental disabilities. Based on the available research, it appears that the identification of preferred stimuli among individuals with moderate to intensive disabilities is increasing, thus potentially increasing their overall quality of life and instruction (Cannella et al., 2005). 1

13 Preference can be defined as a selection, or choice, of one stimulus over another or as elevated interaction with one particular stimulus. For individuals with moderate to intensive intellectual and developmental disabilities, obtaining objective information in relation to preferred items may enhance both quality of life and augment curricular programs (Lancioni et al., 1996). Specifically, preferred items may be used to increase adaptive behavior (i.e., reinforcers). Past research has demonstrated the increased effectiveness of objective measures of preference when compared to subjective measures (Green et al., 1988; Parsons & Reid, 1990; Windsor, Piche, & Locke, 1994). For example, Green et al. (1988) compared the results of caregiver opinion and a more direct, systematic method of determining participant preference. Their data indicated that preferences were more reliably identified with a direct assessment, and that items identified using a direct method were more effective reinforcers. Direct preference assessments may fall into three broad categories based on mode of presentation. In single stimulus (SS) presentation assessments (Hagopian, Rush, Lewin, & Long, 2001), the student is allowed access to stimuli one at a time. Data are collected on the duration of item interaction or approach responses. The item with the highest duration of interaction is classified as highly preferred (HP) and the item with the lowest duration of interaction is classified as low-preference (LP). The remaining items are classified as moderately preferred (MP). One limitation of SS presentation is that the data represent a measure of preference that is unrelated to other stimuli selected for assessment. A second limitation is the total time required to conduct the session. For example, Hagopian et al. (2001) placed a 2 min cap on each trial. Thirteen items were 2

14 assessed (i.e., 13 trials per sessions), and one total assessment was three sessions. The average duration of assessment for each participant was approximately 1 hr and 18 min. In a paired choice (PC) preference assessment (Fisher, Piazza, Bowman, & Amari, 1996), each item is paired with every other item at least once. Pairs of items are presented with a prompt to choose an item. Items that are chosen on the highest percentage of trials are classified as HP and items that are chosen the least are LP. All other items are classified as moderately preferred (MP). Unlike SS methods, the paired presentation yields a measure of relative preference. That is, stimuli are directly compared to other stimuli used in the assessment. One major limitation of the PC preference assessment is efficiency. Depending on the number of items assessed, the PC preference assessment may take an hour or more to complete (DeLeon & Iwata, 1996). Group presentation formats may be conducted in three ways. First, in the multiple-stimulus without replacement (MSWO) preference assessment (DeLeon & Iwata, 1996), a stimulus array is placed in front of the participant, and a prompt is given to choose an item. Once an item is chosen, it is not placed back into the stimulus array for that session. These procedures are repeated until all items in the array are chosen or the student ceases selecting items. The full array is typically presented five times in one full assessment. Similar to the PC preference assessment, a hierarchy of preferred stimuli is identified. Items that are chosen the most are classified as HP, LP items are the stimuli chosen the least, and MP items are the items are all other stimuli. Second, in the multiple-stimulus with replacement (MSW) preference assessment (Windsor et al., 1994), an array of stimuli is presented to the participant, and a prompt is 3

15 delivered to choose an item. Once an item is chosen, it is placed back into the stimulus array for the session. These procedures are repeated for five, 10 trial sessions. Lastly, in a free operant (FO) preference assessment (Roane, Vollmer, Ringdahl, & Marcus, 1998), items are arranged at equal distances around the student, who is given free access to the items during the session and only one item at a time can be sampled. Duration of interaction data are collected on each item to determine a HP and LP item. Sessions are typically conducted for 5 min. The major limitation of both the FO and MSW preference assessments is that HP items may be the sole stimuli identified during the assessment. In other words, because participants have free access to all stimuli (FO) or items selected are replaced (MSW), participants may continue to select only one stimulus. Similar to PC assessments, group arrangements yield a relative measure of preference. One of the main advantages of group presentation is efficiency. For example, a traditional MSWO (i.e., DeLeon & Iwata, 1996) may be conducted in approximately 20 min and the FO preference assessment (Roane et al., 1998) has been outlined with a 5 min session cap. Although group arrangements are efficient, they may not be appropriate for use with all students. For example, the MSWO or MSW may not be appropriate for individuals who do not scan the full array. The lack of a scanning skill (i.e., looking from one end of the array to the other) may prevent an individual from responding to the most highly preferred item in the full array and each subsequent array presentation. Similarly, assessments that require the removal of items (e.g., MSWO) may be inappropriate for individuals who engage in tangibly maintained challenging behavior (Roane et al., 1998; Kang et al., 2010). 4

16 Once preferred items are identified using a preference assessment, a test of reinforcing effectiveness is typically conducted. A reinforcer assessment is defined as a direct assessment that systematically presents one or more stimuli contingent upon a target response and measuring reinforcing effectiveness (Cooper, Heron, & Heward, 2007). Reinforcing effectiveness is identified by an increase in the target behavior in relation to baseline responding (i.e., no contingent application of the stimulus). Reinforcer assessments are typically conducted in two ways (Roscoe, Iwata, & Kahng, 1999). In the single-operant (SO) reinforcer assessment, the student may only access reinforcement for engaging in one target behavior. For example, if a card exchange is the target behavior, the student may only access a potential reinforcer if they engage in the card exchange. All other non-targeted behavior is placed on extinction. In contrast, in the concurrent-operant (CO) reinforcer assessment, the student is presented with two options. Typically, the options are correlated with HP and LP stimuli, which are delivered contingent upon a target behavior associated with each option. For example, in a concurrent-operant reinforcer assessment, the student may be presented with the choice of completing math problems or reading sentences. Contingent upon choosing one of the options, the particpant gains access to either the HP or the LP item. SO and CO reinforcer assessments have been demonstrated to be effective in verifying the reinforcing effectiveness of stimuli identified in a variety of preference assessments (Roscoe et al., 1999). Although assessments are effective in demonstrating reinforcing efficacy, assessment type may yield different types of information. In an SO assessment, the student may only access reinforcement by engaging in the target 5

17 response. In other words, the student has two options: (a) engage in the target behavior to gain access to a stimulus (either HP or LP), or (b) fail to engage in the target response and gain access to nothing. Essentially, SO assessments test the reinforcing effectiveness of a stimulus in relation to nothing, yielding a measure of absolute reinforcing effectiveness (Roscoe et al., 1999). In contrast, CO reinforcer assessments yield a measure of relative value (i.e., relative to another stimulus). In other words, the CO reinforcer assessment allows the experimenter or practitioner to determine reinforcer effectiveness in relation to another stimulus. In the SO reinforcer assessment, statements made about responding can only be made about an increase in the target response alone, but not its value in relation to another programmed stimulus. Although both methods are sufficient for identifying a reinforcing effect, concurrent-operant reinforcer assessments may yield more robust effects, because items are directly tested against one another. In typical reinforcer assessments, whether single or concurrent operant, a simple operant response is typically chosen as the target behavior (Piazza, Fisher, Hagopian, Bowman, & Toole, 1996). A simple operant response can be defined as a behavior that requires minimal response effort from the individual. For example, Piazza et al. (1996) targeted in square behavior (i.e., the participant standing in a square) to test the reinforcing effects of edible and leisure stimuli identified in a PC preference assessment. The data from a concurrent-operant reinforcer assessment indicated that HP items identified in the paired-choice preference assessment functioned as more effective reinforcers in comparison to both MP and LP items. Although the results of Piazza et al. and several subsequent studies (e.g., DeLeon, & Iwata, 1996) demonstrated the predictive 6

18 validity of various preference assessment methodologies, the target behaviors selected for reinforcer assessments may limit the generality of the results. Specifically, measuring the occurrence of a simple operant response (e.g., card touch or exchange, in square behavior) may not be analogous to a more complex or difficult behavior (Piazza et al., 1996). More complex behavior may be classified as a complex operant response and can be defined as behavior that requires increased response effort from the individual. For example, asking to play an HP video game may not be equivalent to receiving reinforcement for tying one s shoes. A second, related issue in determining the effectiveness of preferred items to function as reinforcers is the measurement of an increase in a previously taught skill. In reinforcer assessments where a previously taught skill is measured, the contingent application of a HP stimulus demonstrates building the new contingency may strengthen the skill. By definition, a reinforcer increases the future probability of the emission of a target behavior, but in instances where a previously learned behavior is increased, the data observed may not be indicative of a similar effect on a novel behavior. For example, if the target response is a previously learned card exchange, contingent application of an HP stimulus to the exchange may increase its occurrence, which would indicate a reinforcing effect. If the same stimulus is applied to a novel behavior (e.g., math problems), a similar effect along some dimension (e.g., immediacy) may not be observed. Previous reviews have concluded that structured, objective preference assessments are beneficial in identifying items that can be used to increase socially significant target behaviors for persons with moderate to intensive intellectual and 7

19 developmental disabilities (Cannella et al., 2005; Lancioni et al., 1996; Tullis et al., 2011). In recent years, a growing literature base has continued to support their inclusion, but the effectiveness in practice is relatively unknown. In a recent review, Love and colleagues (2009) surveyed early intensive behavior intervention programs to determine general behavioral practices that were implemented. Choice-based preference assessment procedures were reported to be implemented at least daily for 65% of the participating programs. Although the figure reported by Love et al. (2009) is encouraging, data were not provided on the reinforcing effectiveness of stimuli identified in preference assessments. Overall, preference assessment methodologies are a robust and effective practice for individuals with moderate to intensive developmental and intellectual disabilities, but one main limitation exists in the current literature. Reinforcer testing and application to more complex behavior is relatively unknown. Measurement of simple operant responses and previously taught skills hinders conclusions about the applicability of preference assessment results to more complex behavior. As stated previously, the effectiveness of preference assessment methodologies is supported by ample literature and a number of reviews (e.g., Lohrmann-O Rourke & Browder, 1998), but the methodologies used to test the reinforcing effectiveness of preferred stimuli may limit the conclusions drawn about more complex behavior. As such, the current dissertation will address two central areas. First, a review of the preference assessment literature will determine the overall effectiveness of preference assessment methodologies, and identify the types of responses chosen for reinforcer 8

20 assessments and types of reinforcer assessment arrangements chosen to test reinforcer effectiveness. The literature review will be followed by a short discussion of the findings. Second, a study will be described that examined the generality of preference assessment outcomes from simple operant responses to more complex tasks that are found in typical educational environments. The results will be discussed in relation to previous findings on preference for individuals with moderate to intensive intellectual and developmental disabilities. In the literature review, the following research questions were addressed: (a) What types (i.e., simple, complex) of responses were used to determine reinforcer effectiveness? (b) Are simple or complex operant behaviors used most often as the dependent measure of reinforcer assessments? (c) What were the most prevalent methods of determining reinforcing effectiveness (d) What was the overall effectiveness of preference assessment methodologies? and (e) What was the overall effectiveness of reinforcer assessment methodologies? In the subsequent study, the following research questions were addressed: (a) Are MSWO procedures effective in identifying reinforcers using a basic operant behavior for three boys with moderate to intensive developmental and intellectual disabilities? and (b) Are the items determined as reinforcers with a basic response also reinforcers when applied to skills of increasing complexity. 9

21 Chapter 2: Literature Review In this chapter, a review of the literature based on preference assessment methodologies will be described. In the first section, the inclusion criteria and data collection method will be described. In the second section, a brief overview of the studies will be presented. The final two sections will describe the results of the literature search and present a discussion of the findings. Method Search Procedures Electronic searches were conducted using ERIC, PsycINFO, MedLine, and Google Scholar. A time limit was not placed on the articles included in an effort to present the most in depth information possible. The search terms used were preference, preference assessment, multiple-stimulus without replacement preference assessment, single-stimulus preference assessment, paired-stimulus preference assessment, forcedchoice preference assessment, group preference assessment, severe mental retardation, autism, developmental disability, cognitive disability, and intellectual disability. Hand searches were also conducted using the reference sections of the articles identified through the electronic searches to identify a more complete set of articles. Studies were included in this review based on the following criteria: each study (a) was an assessment study concerned with preference, and (b) had at least one 10

22 participant with a moderate to intensive disability where the data could be separated from the other participants. Articles that did not meet the inclusion criteria were excluded from the review. For example, studies were excluded if participants were not sufficiently described such that the reader could determine if the participants had a moderate to intensive disability. For example, Ciccone, Graff, and Ahearn (2007) was excluded because the participants were described as having a diagnosis of a developmental disability and/or autism, but no other information was available to determine the severity of the disability (e.g., limited communication). Studies in which preference assessments were used but were not the focus were excluded. For example, Kodak and Clements (2009) implemented a paired-choice preference assessment to identify items to be used as reinforcers during mand training. The focus of this study was not on the effectiveness of the preference assessment; rather it was on the acquisition of a specific behavioral topography. Seventy-five studies were identified in the initial search, and 66 studies met the inclusion criteria. After identifying studies to be included in the literature review, data were collected using a structured data sheet. Data collected included the reference, sample size, age of participants, stimuli used in the preference assessments, experimental design (if applicable), type of preference assessment used, and the reported findings (i.e., positive, negative, or mixed). Studies included in this review were divided into three categories and are presented in Table 1. Studies in the first category examined the effectiveness of various preference assessment formats and methodologies (e.g., Hanley, Iwata, Lindberg, & 11

23 Conners, 2003; O Reilly, Lancioni, & Sigafoos, 2004). Studies included in the second category compared the effects of various preference assessment formats or components within a preference assessment (e.g., Horrocks & Morgan, 2009; Kodak, Fisher, Kelley, & Kisamore, 2009). Finally, studies in the third category examined the underlying mechanisms of preference for individuals with moderate to intensive disabilities (e.g., DeLeon, Frank, Gregory, & Allman, 2009; Glover, Roane, Kadey, & Grow, 2008). For each study, Table 1 reports the number of participants with moderate to intensive disabilities (n), their age, the stimuli provided (e.g., tangible items), the type of reinforcer assessment used (when provided), the response topography of the target behavior used in the reinforcer assessments, the preference assessment format, and the major findings (i.e., positive, negative, or mixed). Eight preference assessment formats were examined in the studies reviewed and included: single stimulus (SS), paired choice (PC), multiple stimulus with replacement (MSW), multiple stimulus without replacement (MSWO), free operant (FO), response restriction (RR), concurrent chains (CC), and questionnaires (Q). In the SS assessment, a single stimulus was presented to the participant. In the PC assessment, participants could choose one of two options. In the MSW and MSWO assessments, an array of stimuli was presented to the participant, who was allowed to choose one item at a time from the array; items were replaced in the array following a choice in the MSW and not replaced in the MSWO. In the FO assessment, items were arranged in an array and participants were allowed to engage with any or all items for the duration of the assessment. In the RR assessment, sessions were similar to the FO assessment, but once an item was determined to be preferred, it was not longer 12

24 included in the array of items. In the CC assessment, participants selected a treatment from an array; following a treatment session, they were given the opportunity to choose what treatment they would receive in the next session. In the Q assessment, the participants parents and/or staff were asked what the participant preferred. Two reinforcer assessment procedures were examined in studies where a validation procedure was used to determine the reinforcing effectiveness of items identified in a prior preference assessment. In SO assessments, the reinforcing effectiveness of one stimulus was evaluated in each phase. For example, in one phase, the HP item was evaluated in isolation, and in a separate phase, the LP item was evaluated. In CO assessments, both HP and LP items were evaluated in the same phase. The findings in Table 1 are classified as positive, negative, and mixed. In the first category, positive indicates that the study successfully identified a preference hierarchy for all included participants or a preference hierarchy was identified and reinforcers identified from the hierarchy, whereas mixed indicates that the study was successful in identifying a preference hierarchy for some, but not all participants, or when a reinforcer assessment was conducted, reinforcers were identified for some by not all participants (e.g., Wilder et al., 2008). In the second category, positive indicates that when two different preference assessment formats were compared, preference hierarchies were identified for all participants, or when a reinforcer assessment was conducted, reinforcers were identified using at least one of the methods for all of the participants (e.g., Horrocks & Mogran, 2009). Mixed indicates that when different preference assessment formats or methodologies were compared, the most effective reinforcers were identified for some, 13

25 but not all participants, or a preference hierarchy was not identified for all participants. In the third category, positive is used to indicate that the high preference stimulus identified was the one that maintained responding under higher response requirements (e.g., DeLeon et al., 2009). Mixed is used to describe results indicating that stability of preference was not maintained for all participants (e.g., Cobigo, Morin, & Lachapelle, 2009) or that some but not all participants had a preference for a particular reinforcement magnitude. Overview of Studies Assessing Preference Forty-three studies assessed the preferences of individuals with moderate to intensive disabilities (Ahearn, Clark, DeBar, & Florentino, 2005; Belfiore, Browder, & Mace, 1994; Bojak & Carr, 1999; Cobigo, Morin, & Lachapelle, 2009; Dattilo, 1986; Dattilo, 1987; Dattilo & Mirenda, 1987; DeLeon, Iwata, & Roscoe, 1997; Derby et al., 1995; Didden et al., 2006; Didden, Lorzilius, Sturmey, Lancioni, & Curfs, 2008; Dozier et al., 2007; Fisher et al., 2005; Fisher et al., 1996; Fleming et al., 2010; Graff & Larsen, 2011; Hagopian et al., 2001; Hanley, Iwata, & Lindberg, 1999; Hanley, Iwata, Lindberg, & Conners, 2003; Hanley, Piazza, Fisher, & Maglieri, 2005; Higbee, Carr, & Harrison, 1999; Higbee, Carr, & Harrison, 2000; Houlihan, Bates-Purple, Jones, & Sloane, 1992; Keen & Pennell, 2010; Kreiner & Flexer, 2009; Lancioni, O Reilly, Campodonico, & Mantini, 1998; Lancioni, O Reilly, Campodonico, & Mantini, 1998; Lancioni, O Reilly, & Oliva, 2002; Lattimore, Parsons, & Reid, 2003; Lim, Browder, & Bambara, 1998; Logan et al., 2001; Mechling & Moser, 2010; Mithaug & Hanawalt, 1978; O Reilly et al., 14

26 2004; Pace et al., 1985; Piazza et al., 1996; Reid, Everson, & Green, 1999; Saunders et al., 2005; Sigafoos & Dempsey, 1992; Smaby, MacDonald, Ahearn, & Dube, 2007; Spevack, Yu, Lee, & Martin, 2006; Wilder et al., 2008; Zhou, Iwata, Goff, & Shore, 2001). For example, Ahearn et al. (2005) used a single stimulus preference assessment to identify preferred stimuli that were presumed to match and not match the sensory properties of stereotypy for two adolescent participants diagnosed with autism and moderate to intensive mental retardation. Items identified as high preference were then provided, and the effects of both matched and unmatched stimuli on levels of stereotypy were assessed using a multi-element design. For both participants, significantly lower levels of stereotypy were observed when either matched or unmatched items were presented. Items presumed to match the sensory properties of stereotypy did not produce lower levels relative to unmatched stimuli, suggesting that the activities that do not match properties of stereotypy could also displace responding. Preference Assessment Comparisons Seventeen studies compared the effects of various preference assessment formats and methodologies (Conyers et al., 2002; DeLeon & Iwata, 1996; DeLeon et al., 1997; Fisher et al., 1992; Graff & Gibson, 2003; Graff, Gibson, & Galiasatos, 2006; Groskreutz & Graff, 2009; Higbee, Carr, & Harrison, 1999; Horrocks & Morgan, 2009; Kodak et al., 2009; Reed, Luiselli, Magnuson, Vieria, & Rue, 2009; Reid et al., 2007; Roane et al., 1998; Roscoe et al., 1998; Thomson, Czarnecki, Martin, Yu, & Martin, 2007; Tullis, Cannella-Malone, & Fleming, in press; Windsor et al., 1994). For example, Kodak et al. (2009) compared the results of selection- (i.e., MSW) and duration-based (i.e., FO) 15

27 preference assessments to identify the method that produced the highest rates of responding for four participants between the ages 2 and 10 with autism and other developmental disabilities. All participants engaged in limited communication and only one followed instructions requiring multiple steps. Following the preference assessments, reinforcer assessments were conducted comparing the HP stimulus from each assessment. For two participants, the HP items identified with the MSW were more effective than the HP items identified with the FO. The remaining two participants engaged in undifferentiated responding during the reinforcer assessments, and the HP items maintained responding equally in the reinforcer assessments. Mechanisms Underlying Preference Six studies evaluated the mechanisms underlying preference in individuals with moderate to intensive disabilities (DeLeon et al., 2009; Glover et al., 2008; Kodak, Lerman, Volkert, & Trosclair, 2007; Lee, Yu, Martin, & Martin, 2010; Milo, Mace, & Nevin, 2010; Roane, Lerman, & Vorndran, 2001). For example, DeLeon et al. (2009) examined if items that differed in placement on a preference hierarchy would have different break points under a progressive ratio (PR) schedule of reinforcement with four participants with moderate to intensive disabilities. Paired choice preference assessments were conducted to identify a hierarchy of leisure items, followed by three randomly ordered PR analyses. Prior to sessions, participants completed a known task three times, and then they were given access to a high, medium, or low preference item. During PR sessions, the same item remained in view and one verbal prompt to complete the task that was presented. The stimulus being assessed was delivered on a PR schedule beginning 16

28 with one response (e.g., single completion, two completions, etc.). The data indicated that participants completed more work when a more highly preferred stimulus was delivered, which supports the conclusion that items on different ends of a preference hierarchy may support different amounts of work. Results The overall results of the current review are presented in Table 1. In this review, the average number of participants with moderate to intensive disabilities was seven (range: 1 105), and participant age ranged from 1 to 76. Non-edible stimuli were assessed in 45 studies, and edible stimuli were assessed in 23 studies. A large number of studies implemented a preference assessment methodology that presented two choices concurrently to the participants (i.e., PC), and group presentations (i.e., MSWO, MSW, FO) were the second most implemented assessment type. Overall, the PC preference assessment was used in 36 studies, an SS preference assessment in 13 studies, the MSWO was studied in nine investigations, the other group presentations (i.e., FO, MSW, and CC assessments) were investigated in five studies each, and questionnaires were used in four studies. To determine the reinforcing effectiveness of items identified in various preference assessments, reinforcer assessments were implemented in 32 studies. When reinforcer assessments were included, CO reinforcer assessments were used in 14 studies, and SO assessments were used in 18. Four studies utilized both methodologies. During reinforcer assessments, simple operant responses (e.g., card touches) were measured in 17

29 24 studies, and complex operant responses (e.g., vocational tasks) were measured in eight studies. Positive results were observed in a large proportion of the literature base. Fifty of the 66 studies investigating various preference assessment methodologies reported positive results for all participants. Overall, 16 studies reported mixed results, and negative results were not located in the current search. When reinforcer assessments were implemented to validate preference assessment outcomes, 23 studies reported positive results, and eight reported mixed results. A further analysis of the reinforcer assessment procedures indicated that simple operant responses were measured in the majority of the studies surveyed. Overall, 24 studies were located that implemented a simple operant response as the primary target response. In those studies, 19 reported positive outcomes, and five reported mixed results. Negative results were not found in the current literature. Eight studies were located that measured more complex responses, and seven studies reported positive results, and one study reported mixed results. Negative results were not found in the current literature. Discussion Effectiveness of Assessment Methodologies As in previous reviews (e.g., Tullis et al., 2011) the large number of positive results supports the inclusion of preference assessment methodologies in academic, vocational, and behavioral programming for individuals with moderate to intensive intellectual and developmental disabilities. Although negative results were not located in the current literature, mixed outcomes may be viewed as an overall limitation of the 18

30 current preference methodologies. For example, Higbee et al. (2000) examined the results of a brief MSWO preference assessment with nine individuals with moderate to intensive intellectual and developmental disabilities. A three-session MSWO was implemented to determine HP and LP stimuli for each participant. Subsequent SO reinforcer assessments were conducted to determine the reinforcing effectiveness of the HP and LP items. The data indicated that preferred items were identified for all participants, but these items were not effective as reinforcers for six of the nine participants. Similar mixed results for other studies in the current review (e.g., Keen & Pennell, 2010) may indicate that further procedural considerations should be made to increase the effectiveness of preference methodology to a wider range of individuals. For example, expansions could be made to current methodologies to include determining what assessment is most effective with a specific participant profile. It might be useful to provide a decision making model for applying preference assessment methodologies. Karsten, Carr, and Lepper (2011) propose one model for modifying preference assessments with a stimulus array (e.g., MSWO, FO). The Karsten et al. (2011) methodology requires sequential modification of stimulus presentations based on participant behavior. For example, if challenging behavior occurs during the initial MSWO, the next step is to alter procedures to conduct an FO preference assessment. Further expansion of this type of decision-making protocol may allow for increased refinement and a decreased reliance on subjective clinical judgment (i.e., disability status). 19

31 The high number of overall findings are quite encouraging, but a preference assessment alone may not allow for proper identification of reinforcing items. Reinforcer assessments or an objective measure of reinforcer effectiveness (e.g., item engagement, continued choice) may be needed before the complete assessment can be considered beneficial for a variety of academic and community purposes. In the current review, a large number of studies using a simple operant behavior as the target resulted in positive outcomes. Fewer studies with complex behavior as the target were found, and the majority of those studies reported positive outcomes. The positive results of studies using both simple and complex behaviors are promising, but the small number of total studies using complex behavior is a major limitation. Simple operant behaviors are prevalent in the behavioral repertoires of humans, but more complex behavior is also required for many tasks (Green, 2001). In this literature, there significant support for using preference assessments to identify reinforcers for simple target responses, but the support for more complex responses more limited. Response Topographies Reinforcer assessment methodology may limit the generality of preference assessment results to more complex behavior. In the current review, seven studies measured microswitch activation (DeLeon, & Iwata, 1996; Higbee et al., 2000; Higbee et al., 1999; Lee et al., 2010; Logan et al., 2001; Milo et al., 2010), three measured a card exchange (Kodak et al., 2009; Tullis et al., in press; Keen, & Pennell, 2010; Spevack et al, 2006), six measured a complex behavior (e.g., academic, life, or vocational skill; Derby et al., 1995; Graff et al., 2006; Graff & Larsen, 2011; Groskreutz & Graff, 2009; 20

32 Mithaug & Hanawalt, 1978; Wilder et al., 2008), and fifteen measured another arbitrarily selected behavior simple operant behavior (Ahearn et al., 2005; DeLeon et al., 2009; Fisher et al., 1996; Fisher et al., 1992; Fleming et al., 2010; Graff & Gibson, 2003; Kodak et al., 2007; Pace et al., 1985; Paclawskyj, & Vollmer, 1995; Piazza et al., 1996). Overall, the current effectiveness of various preference assessments in identifying preferred items that are also reinforcers has been obtained using simple operant responses. Piazza et al. (1996) suggested the use of a simple free operant response (e.g., a microswitch press) may be advantageous if the focus of the reinforcer assessment is to test the specific contingency and not necessarily teach a skill. One limitation of using a simple response may be that the probability of generalizing a reinforcing effect from one response topography to another may be low. For example, if a HP item is sufficient to reinforce in-seat behavior, it may not be sufficient to teach a more complex skill (e.g., shoe tying). In the current literature, the implementation of simple operant responses was prevalent. These responses constituted 81% of the studies that tested the reinforcing effectiveness of items identified in a preference assessment. The majority of studies noted positive results, indicating that a reinforcer was identified under conditions were a simple operant response was required to gain access to reinforcement. When a more complex operant response was measured, study outcomes were also positive. For example, DeLeon et al. (1997) measured the rate of daily living skill completion in an SO reinforcer assessment for two individuals with profound mental retardation. Towel folding and hand drying were selected as target behaviors. An MSWO 21

33 was conducted for each participant, and a leisure item was selected for use in the reinforcer assessment. Contingent upon completion of the skill, the participant was allowed access to a leisure activity. The data indicated that the leisure activity identified in the MSWO functioned as a reinforcer for both participants. Positive results from the studies where a more complex behavior was targeted (e.g., Derby et al., 1995) are promising, but a demonstration of reinforcer identification with a simple operant behavior that is also observed with a more complex behavior is absent. Given that simple operant responses are more convenient and potentially easier to measure (Piazza et al., 1996), it would seem beneficial to investigate whether the reinforcing effects of items identified in a preference assessment could be replicated across responses. Such an investigation may provide a more complete description of the limits of preference assessment methodologies. Mechanisms Underlying Preference In recent years, there has been a shift from assessing preference and comparing methodologies to investigating the underlying mechanisms of preference. Specifically, the extent to which availability, magnitude, and response effort may impact the effectiveness of an item identified as being highly preferred. For example, Glover et al. (2008) evaluated PR schedules when two stimuli were evaluated under single and concurrent arrangements and found that participants responded more for HP stimuli under PR schedules than low preference stimuli, regardless of the presentation format. During single stimulus arrangements, LP stimuli functioned as reinforcers for two participants. These results suggest that responding for HP stimuli was not disrupted by 22

34 the concurrent availability of a low preference stimulus and that an LP stimulus may be effective as a reinforcer under less effortful response requirements. These studies may have implications for the application of preference assessment methodologies in both clinical and classroom settings. Magnitude, availability, and persistence of a stimulus to function as a reinforcer may be manipulated to increase responding for adaptive behavior or to decrease challenging behavior. For example, during an academic program, reinforcement may be altered on a given dimension, depending on the task difficulty, to increase the probability of task compliance. Additionally, stimulus availability may be structured in a manner to decrease competition between two highly preferred items, which may increase the relative value of stimuli during instructional opportunities. Although the application of strategies such as PR schedules have been argued to be indicators of reinforcer strength, the procedures implemented may not be analogous to more complex behavior (Poling, 2010). In typical PR procedures, a relatively simple operant response is measured (i.e., tape touches), but these results may not generalize to a more naturalistic response observed in a typical setting. For example, Roane, Lerman, and Vorndran (2001) examined the use of PR schedules of reinforcement to determine reinforcer potency of items identified as HP and LP in a PC preference assessment. During PR assessments, simple operant responses were measured (e.g., tape touches). The data indicated that HP items were more likely to maintain the target behavior under increasing response requirements. An additional treatment analysis of challenging behavior indicated that the HP stimulus was also effective in decreasing challenging 23

35 behavior under a noncontingent reinforcement schedule. Although the results of Roane et al. (2001) were positive and demonstrate the replication of reinforcing effects across different response topographies, their results of the replication phase may be limited, in that the target behavior chosen for reduction was self-injury, a behavior that was already in the participant s repertoire. Although the behavior chosen was clinically significant, the information reported by Roane et al. (2001) may only be useful when a researcher or clinician s goal is to identify a stimulus that is reinforcing enough to decrease a specific behavior. Reinforcer potency in relation to skill acquisition, in this case, was not demonstrated. Overall, results of the current literature review also do not support the assumption that reinforcers or reinforcer potency identified under a specific set of conditions applies to all or even similar conditions. An increase in response amount under a PR schedule is a manipulation that can indicate some dimension of reinforcer strength or potency (Poling, 2010; Roane, 2008), but amount of responding is only one way in which response effort can be manipulated. This limitation may be most evident under conditions where long chains of responses are not composed of smaller behaviors with the same topography or response effort. For example, an individual may activate a switch multiple times to gain access to a preferred item, but not wash dishes when the same stimulus is the consequence. Conclusion Overall, preference assessment methodologies are a robust technology for identifying items that function as reinforcers. Additionally, demonstrations of the generality of reinforcer assessment results using simple operant behavior as the 24

36 dependent variable to more complex behavior are absent from the literature. The current method of testing reinforcer potency (i.e., PR schedules) may be adequate for only testing one dimension of reinforcing effectiveness of more complex behavior. This limitation may indicate that preference assessments are useful for identifying reinforcers that are appropriate under some conditions, but not others. Specifically, preference assessments may be sufficient for identifying items that function as reinforcers for simple operant behavior, but not for more complex behavior. 25

37 ! 26 Category/Article Name n Age Stimuli Reinforcer Assessment Assessing Preferences Ahearn et al.. (2005). On the role of preference in response competition. Belfiore et al. (1994). Assessing choice-making and preference in adults with profound mental retardation across community and centerbased settings. Bojak & Carr (1999). On the displacement of leisure items by food during stimuluspreference assessments. Cobigo et al. (2009). A method to assess work task preferences. Dattilo. (1986). Computerized assessment of preferences for severely handicapped individuals Tangible items CO Response Stereotypy, Item engagement Preference Assessment SS Results Positive Drinks N/A N/A PC Mixed Food, leisure N/A N/A MSWO Positive Work materials/ pictures Auditory and visual stimuli N/A N/A PC Mixed N/A N/A PC Positive Continued Table 1. Studies Listed According to Categories With Number and Age of Participants, Type of Stimuli Presented, Reinforcer Assessment Type, Response Topography, Preference Assessment Type, and Results

38 27 Dattilo. (1987). Computerized assessment of leisure preferences: A replication. Dattilo & Mirenda. (1987). An application of a leisure preference assessment protocol for persons with severe handicaps. DeLeon et al. (1997). Displacement of leisure resinforcers by food during preference assessments. Derby et al. (1995). Two measures of preference during forced-choice assessments. Didden et al. (2006). Preference in individuals with angelman syndrome assessed by a modified choice assessment scale. Didden et al. (2008). Preference for water-related items in angelman syndrome, down syndrome, and nonspecific intellectual disability. 1 7 Auditory and visual stimuli Leisure activities Food, leisure SO Daily living task N/A N/A PC Positive N/A N/A PC Positive MSWO Positive Leisure items N/A N/A PC Positive N/A N/A N/A Q Positive 81 M = 12 N/A N/A N/A Q Positive Continued

39 ! 28 Dozier et al. (2007). Assessment for behavioral treatment versus baseline conditions. Fisher et al. (1996). Integrating caregiver report with a systematic choice assessment to enhance reinforcer identification. Fisher et al. (2005). Assessing preferences for positive and negative reinforcement during treatment of destructive behavior with functional communication training. Fleming et al. (2010). An evaluation of the use of eye gaze to measure preference of individuals with severe physical and developmental disabilities. Graff & Larsen. (2011). The relation between obtained preference value and reinforcer potency Access to baseline or treatment conditions Various items and activities Access to positive or negative reinforcement Tangible/ edible items N/A N/A CC Positive CO In square PC Positive N/A N//A CC Positive SO Eye gaze PC Positive Edible items SO Daily living PC Positive Continued

40 ! 29 Hagopian et al. (2001). Evaluating the predictive validity of a single stimulus engagement preference assessment. Hanley et al. (1999). Analysis of activity preferences as a function of differential consequences. Hanley et al. (2003). Response-restriction analysis: I. assessment of activity preferences. Hanley et al. (2005). On the effectiveness of and preference for punishment and extinction components of function-based interventions. Higbee et al. (1999). The effects of pictorial versus tangible stimuli in stimuluspreference assessments. Higbee et al. (2000). Further evaluation of the multiple-stimulus preference assessment Edible items, social activities, leisure activities CO In chair behavior SS Positive Activities N/A N/A CC Positive Leisure activities Tangible items Access to Intervention N/A N/A RR Positive N/A N/A FO Positive N/A N/A CC Positive N/A N/A CC Positive Activities SO Switch press SS Mixed Food and leisure items SO Switch press MSWO Mixed Continued

41 30 Houlihan et al. (1992). The simultaneous presentation procedure: use in selecting reinforcers for behavioral intervention. Keen & Pennell. (2010). Evaluating an engagementbased preference assessment for children with autism. Kreiner & Flexer. (2009). Assessment of leisure preferences for students with severe developmental disabilities and communication difficulties. Lancioni et al. (1998). Mobility versus sedentariness in task arrangements for people with multiple disabilities: An assessment of preferences. Lancioni et al. (1998). Task variation versus task repetition for people with profound developmental disabilities: An assessment of preferences. 2 4 Various items and activities Leisure activities Pictures of leisure activities Mobility vs. fixed placement Variable vs. fixed task N/A N/A PC Positive SO Card exchange, pointing FO Mixed N/A N/A PC Positive N/A N/A PC Positive N/A N/A PC Positive Continued

42 ! 31 Lancioni et al. (2002). Engagement in cooperative and individual task: Assessing the performance and preferences of persons with multiple disabilities. Lattimore et al. (2003). Assessing preferred work among adults with autism beginning supported jobs: Identification of constant and alternating preferences. Lim et al. (1998). Effects of sampling opportunities on preference development for adults with severe disabilities. Logan et al. (2001). Preferences and reinforcers for students with profound multiple disabilities: Can we identify them? Mechling & Moser. (2010). Video preference assessment of students with autism for watching self, adults, or peers Activies N/A N/A PC Positive Work materials N/A N/A MSW Positive Drinks N/A N/A PC Positive Various stimuli SO Switch press SS Positive Video clips N/A N/A PC Positive Continued

43 ! 32 Mithaug & Hanawalt. (1978). The validation procedures to assess prevocational task preferences in retarded adults. O Reilly et al. (2004). Using paired-choice assessment to identify variables maintaining sleep problems in a child with severe disabilities. Pace et al. (1985). Assessment of stimulus preference and reinforcer value with profoundly retarded individuals. Piazza et al. (1996). Using choice assessment to predict reinforcer effectiveness. Reid et al. (1999). A systematic evaluation of preferences identified through person-centered planning for people with profound multiple disabilities Tasks CO Task completion PC Positive 1 5 Activities/toys N/A N/A PC Positive Various items SO Motor movement, looking Various items and activities Leisure activies CO In square behavior SS PC Positive Positive N/A N/A SS Mixed Continued

44 33 Saunders et al. (2005). A novel method for testing learning and preferences in people with minimal motor movement. Sigafoos & Dempsey. (1992). Assessing choice making among children with multiple disabilities. Smaby et al. (2007). Assessment protocol for identifying preferred social consequences. Spevack et al. (2006). Sensitivity of passive approach during preference and reinforcer assessments for children with severe and profound intellectual disabilities and minimal movement. Wilder et al. (2008). Identification of olfactory stimuli as reinforcers in individuals with autism: A preliminary investigation Electronic devices N/A N/A CC Mixed Food, drinks N/A N/A PC Positive Social consequences Sensory activities Olfactory stimuli N/A N/A SS post EXT Positive SO Switch press SS Positive SO Sorting PC Mixed Continued

45 Zhou et al. (2001). Longitudinal analysis of leisure-item preferences. 22 M = 41 Leisure activies N/A N/A SS Mixed 34 Preference Assessment Comparisons Conyers et al. (2002). Predicting the relative efficacy of three presentation methods for assessing preferences of persons wit h developmental disabilities. DeLeon & Iwata (1996). Evaluation of a multiplestimulus presentation format for assessing reinforcer preferences. Fisher et al. (1992). A comparison of two approaches for identifying reinforcers for persons with severe and profound disabilities. Graff & Gibson. (2003). Using pictures to assess reinforcers in individuals with developmental disabilities Food N/A N/A PC objects vs. pictures vs spoken Food, leisure SO Switch press MSWO vs. PC vs. MSW Various items CO In square/in chair behavior Edible items, pictures PC vs. SS Mixed Positive Positive SO/CO Switch press PC Positive Continued

46 ! 35 Graff et al. (2006). The impact of high-and lowpreference stimuli on vocational and academic performances of youths with severe disabilities. Groskreutz & Graff. (2009). Evaluating pictorial preference assessment: The effect of differential outcomes on preference assessment results. Horrocks & Morgan. (2009). Comparison of a video-based assessment and a multiple stimulus to identify preferred jobs for individuals with significant intellectual disabilities. Kodak et al. (2009). Comparing preference assessments: Selection- versus duration-based preference assessment procedures Tangible items/pictures CO Vocational tasks Edible items SO Vocational tasks Edible items SO/CO Daily living task Work materials Edible/leisure items PC PC PC N/A N/A PC vs. MSWO CO Card exchange FO vs. MSW Positive Positive Mixed Positive Mixed Continued

47 36 Paclawskyj & Vollmer. (1995). Reinforcer assessment for children with developmental disabilities and visual impairments. Parsons & Reid. (1990). Assessing food preferences among persons with profound mental retardation: Providing opportunities to make choice. Reed et al. (2009). A comparison between traditional economical and demand curve analyses of relative reinforcer efficacy in the validation of preference assessment predications. Roane et al. (1998). Evaluation of a brief stimulus Food, social stimuli, leisure items Various stimuli preference assessment Various stimuli Roscoe et al. (1999). Relative versus absolute reinforcement effects: Implications for preference assessments. SO Gross/fine motor tasks SS vs. PC Positive Food items N/A N/A Q vs. PC Positive Edible items SO Switch press PC vs. MSWO vs. FO Positive CO In square FO Mixed N/A N/A PC vs. FO Mixed Food items SO vs. CO Switch press, letter writing SS vs. PC Mixed Continued

48 37 Reid et al. (2007). Identifying work preferences among supported worked s with severe disabilities: Efficiency and accuracy of a preference-assessment protocol. Thomson et al. (2007). Predicting optimal preference assessment methods for individuals with developmental disabilities. Tullis et al. (in press). Multiple stimulus without replacement preference assessments: An examination of the relation between session number and efficiency. Windsor et al. (1994). Preference testing: A comparison of two presentation methods. Mechanisms Underlying Preference DeLeon et al. (2009). On the correspondence between preference assessment outcomes and progressive Work materials 11 Adults Edible/ tangible N/A N/A MSWO vs. PC vs. Q 1 9 Leisure items CO Card exchange Mixed N/A N/A PC vs. SS Positive MSWO Food, drinks N/A N/A MSW vs. PC Leisure items SO Fine motor task PC Positive Mixed Positive Continued

49 38 Glover et al. (2008). Preference for reinforcers under progressive- and fixedratio schedules: A comparison of single and concurrent arrangements. Kodak et al. (2007). Further examination of factors that influence preference for positive versus negative reinforcement. Lee et al. (2010). On the relation between reinforcer efficacy and preference. Milo, Mace, & Nevin. (2010). The effects of constant versus varied reinforcers on preference and resistance to change. Roane, Lerman, & Vorndran. (2001). Assessing reinforcers under progressive schedule requirements Unspecified SO/CO Unspecified PC Positive SO/CO Unspecified Positive Edible/ CO Item choice PC Positive 1 tangible items CO Item choice Positive 1 CO Item choice Positive Edible items SO Switch press PC Positive Edible items CO Switch press MSWO Positive Leisure items SO Switch press, toggle switch movement, tape touch PC Positive Continued

50 Chapter 3: Method To investigate the experimental questions presented in Chapter 1, a study was conducted using a single subject experimental design. In this chapter, the methodology implemented is presented. Specifically, this chapter includes a detailed description of the participants, setting, dependent variables, interobserver agreement procedures, procedural integrity procedures, and experimental procedures. Participants and Setting Three boys diagnosed with intellectual and developmental disabilities participated in the study. Participants were selected based on teacher report of a deficit in discrimination skills and a need for systematic assessment to identify preferred items. Additionally, none of the participants utilized a systematic form of communication, but they all had a history of engaging in active selection responses (e.g., physical contact, pointing). Each participant s parent or guardian also returned signed consent form before data collection was initiated. Ike was a 12-year-old male diagnosed with autism. He typically communicated his wants and needs by pointing and through verbal approximations. His current individualized education plan (IEP) goals were number discrimination, coin counting, hygiene skills and color matchingin his classroom, Ike received a combination of small edible (e.g., cookie) and leisure items (e.g., ball) as reinforcement for completing a token. 39

51 board (i.e., three tokens). Tokens were delivered primarily for independent task completion Percy was an 11-year-old male diagnosed with Attention Deficit Hyperactive Disorder, mental retardation, a developmental delay, and a speech delay. His typical form of communication was through vocal approximations and pointing to preferred items. His IEP goals were to decrease challenging behavior during transitions and work, color matching, hygiene skills, and engage in appropriate behavior in the community. In his classroom, Percy received a small edible item as reinforcement for completing a token board (i.e., one token). Tokens were delivered for task completion, transitioning from activity to activity, and general compliance. Roy was an 11-year-old male diagnosed with a developmental delay. His primary form of communication was pointing and reaching for items. Roy s current IEP goals were to increase appropriate toileting, communicate wants and needs, and engage in appropriate behavior in the community. In his classroom, edible and leisure items were delivered as reinforcers, but a systematic system of providing reinforcement was not in place. Of the three participants, two engaged in challenging behavior. During transitions Percy engaged in variable levels of refusal (e.g., saying no ) and aggression. During both transitions and work intervals, Roy engaged in self-injurious behavior (head hitting, hand biting). All participants attended a county funded school for individuals with moderate to intensive disabilities. The school served 88 students, with a typical classroom size of eight students. Typical class activities included functional skills training (i.e., 40

52 cooking, vocational skills) and community instruction (i.e., trips to the grocery store during the school week). The teacher-to-student ratio in each classroom was three staff (i.e., a teacher and two instructional assistants) to eight students. Sessions were conducted in an unused 3.08 m x 2.44 m room at the school. The room was empty except for the materials required for sessions. Materials During all sessions, data sheets printed on 8 ½ x 11 in. copy paper were present. When two individuals collected data, two sheets were present. During preference assessments, and basic and complex reinforcer assessment phases, small snack items were present. Preassessment Reinforcer assessment for individuals with severe disabilities (RAISD). For all participants, a RAISD (Fisher, Piazza, Bowman, & Amari, 1996) was given to the classroom staff to identify potential items for inclusion in subsequent preference assessments. The RAISD (see Appendix A) is a structured questionnaire for individuals with moderate to intensive disabilities that is used to generate a list of potential reinforcing stimuli. It provides questions in relation to visual, auditory, olfactory, edible, tactile, and social stimuli. This questionnaire was selected because previous research (e.g., Fisher et al., 1992; Pace et al., 1985) has demonstrated that items gathered using the RAISD in combination with structured preference assessments is more predictive in identifying items with greater reinforcing effectiveness (i.e., an increase in a target response) than an unstructured list. The RAISD also allows the experimenter to gather 41

53 information about preferred stimuli from significant others to determine initial stimuli to test in subsequent objective assessments. Each staff member was asked to complete a blank copy of the RAISD, instructed to provide specific answers to the questionnaire items, and to note if there were any special conditions where an item seemed to be more preferred. Staff members were also instructed to complete the form independently (i.e., no collaboration between staff, no sharing answers or ideas). Although no concerns were raised about the questionnaire, staff members were encouraged to discuss any concerns with the experimenter if they arose. Items were chosen based on answers to questions contained in the RAISD. For all participants, edible items (i.e., small snacks) were chosen based on the small number of leisure items recommended by staff, and because they were easily restricted during the day. The RAISD was not delivered to parents during this study because of difficulty in returning paperwork and following-up with parents to make sure the forms made it home. Preference Assessment Purpose. A preference assessment was implemented to determine a rank order of preference for the items from the list generated from the RAISD. This assessment was implemented to provide an objective measure of preference based on participant selection. Operational definitions and response measurement. During all preference assessment sessions, data were collected on item selection. A selection was defined as any portion of the participant s hand contacting a stimulus in the array. Contact with multiple items at the same time (e.g., grabbing two items, swiping the array off the table) 42

54 was not scored as a selection, and the trial was restarted (i.e., the items were replaced and the prompt to pick an item was delivered again). Data were collected using a structured data sheet (Appendix B). During all preference assessments, a rank was placed next to the stimulus as it was selected. Sessions were scored as outlined by Ciccone, Graff, and Ahearn (2005). Each selection was assigned a weighted score, which was added together for a total weighted score. For example, the first selection out of an array of six items was assigned a weighted score of 6. If that item was selected first across all five trials, then the overall weighted score would be 30 (i.e., = 30). The high preference (HP) item was defined as the item associated with the highest weighted score, and the lowpreference (LP) item was defined as the item associated with the lowest weighted score. Procedures. All preference assessments were conducted as outlined by Deleon and Iwata (1996). An array of six stimuli was arranged on the table in front of the participant and a prompt to pick a stimulus was delivered by the experimenter (e.g., pick one ). If the participant chose a stimulus, they were allowed to consume the item. While the participant consumed the edible, the array was rearranged by moving the item on the far left of the array to the far right hand side. The array was presented again without the previously selected stimulus. These procedures were repeated until all stimuli were chosen or until the participant did not make a selection within 30 s. The full array of stimuli was presented five times to complete an entire assessment. For all participants, the entire assessment was completed during the course of one day. Basic Reinforcer Assessment 43

55 Purpose. To test the reinforcing effectiveness of items identified as HP and LP during the preference assessment, a basic reinforcer assessment was conducted. In this assessment, a skill the student had in his repertoire, but did not use reliably, was contingently reinforced using either the HP or LP item to determine if either stimulus would lead to an increase in the targeted behavior. Materials. In basic reinforcer assessment phase, two blank 3 x 5 in. index cards were present during baseline. During the reinforcer-testing phase, two 3 x 5 in. index cards with depictions of the HP and LP stimuli printed on one side were present (see Figure 1). Dependent measures and response measurement. During the basic reinforcer assessments, an independent card exchange was chosen as the dependent measure for all participants, and was defined as the participant picking up a stimulus card, approaching the experimenter, and extending the card in the direction Figure 1. Example of stimulus card used during basic reinforcer assessments. 44

56 of the experimenter or placing the card in the experimenter s hand. Data were collected on the number of independent card exchanges for each stimulus (i.e., HP and LP stimuli) in a given session. In other words, during reinforcer testing phases, data were collected on the number of times the participant exchanged each card. Observers collected data on the number of independent card exchanges for each stimulus using golf counters and recorded the level of responding observed at the conclusion of the session on a data sheet (Appendix C). All counters were labeled to correspond with a particular stimulus. For example, if cookies were the HP item, the counter that was used to track card exchanges that resulted in cookies was labeled as HP. Experimental design. To evaluate the reinforcing effectiveness of stimuli identified as HP and LP, a reversal design was implemented (Kazdin, 1982). A reversal design was seleced because card exchanges are likely to decrease to low levels when the reinforcement contingency is withdrawn. During reinforcer assessment phases, high- and low-preference stimuli were presented in a concurrent operant format (Fisher et al., 1992). This arrangement was chosen because it provides a relative value of reinforcing effectiveness and is more likely to demonstrate a clear pattern of reinforcing effectiveness (Roscoe et al., 1999). In the A phase, baseline conditions were in effect, and in the B phase, HP and LP items were concurrently available. The criterion for moving from phase A phase to B phase was three consecutive sessions at zero levels of responding. During reinforcer assessment phases, the requirement to move from the B phase to the A phase was at least three consecutive data points above baseline responding with an increasing trend and differentiation between the data paths for the LP and HP items. For 45

57 Roy, a return to the A phase was initiated after three consecutive sessions of no trend in either data path, and a lack of differentiation between the LP and HP items. Procedures. Baseline. Before each session, the participant was briefly exposed to the contingency associated with each card. They were led to the card and prompted to exchange it with the experimenter. Vocal instructions were also delivered outlining the contingency (i.e., If you give me this card, I will not give you anything. ). During baseline, two blank index cards were placed on two tables on opposite sides of the room. If the participant exchanged either card (i.e., handed it to the experimenter), no consequences were delivered and the card was placed back on the table. Additionally, no programmed consequences were delivered for other appropriate or challenging behavior. All sessions were 5 min in duration, and three to five sessions were conducted in a day. Depending on student availability, some blocks of sessions (no more than three) were conducted back-to-back. Concurrent operant reinforcer assessment. Prior to each block of sessions, the experimenter or reliability data collector brought the participant into the room. Before each reinforcer testing session, one forced exposure was implemented with each participant. The experimenter brought the participant to the appropriate part of the room and delivered a the instruction, If you want this, you can hand me this card. The least intrusive prompt level (e.g., vocal prompt) was then used to prompt a card exchange, and the appropriate stimulus was delivered. One forced exposure trial was conducted with both the HP and LP stimuli. 46

58 During reinforcer testing phases, two cards (i.e., one depicting the HP and one the LP item) were placed at opposite ends of the room. The participant was placed in the center of the room and given a prompt to choose an item (e.g., Let me know what you want. ). The initial prompt was the only prompt delivered during sessions. Contingent upon an independent card exchange, the participant was allowed to consume the item. For example, if the participant exchanged a card for a cookie, he was allowed to eat a small piece of the cookie. While the participant was consuming the item, both stimulus cards were removed. They were replaced when the participant finished eating. The participant was placed back in their original position, and no other prompts were delivered. Reinforcer assessment sessions were 5 min in duration, and three to five sessions were conducted per day. Depending on student availability, some sessions (no more than three) were conducted back-to-back. Complex Reinforcer Assessment Purpose. To test the effectiveness of items previously identified as reinforcing with a more complex response, a complex reinforcer assessment was conducted. In this assessment, a skill the student did not have in his repertoire was contingently reinforced with the item that was demonstrated to function as a reinforcer in the basic reinforcer assessment to determine if the stimulus led to an increase in the targeted behavior. Materials. Items present in the complex reinforcer assessment phase were nine 2 x 2 in. stimulus cards. The color discrimination task included a red, yellow, and blue card. The color and shape discrimination task included a card with a green triangle, a card with a gray circle, and a card with a black rectangle. The color, size, and shape 47

59 discrimination stimulus cards included a 3.5 x 2.5 in. orange star, 1 x ½ in. brown arrow, and a 2 x 2 in. purple pentagon. All stimulus cards were exactly the size and shape presented above. Other materials present during all sessions were two moveable filing cabinets approximately 3 ft in height, a 4 x 2 ft table, and three chairs (Figure 2). Filing Cabinet Chair Table! Figure 2. Diagram of the session room used for all preference and reinforcer assessments discrimination tasks. Dependent measures and response measurement. In all reinforcer assessment sessions, data were collected on the number of independent responses across novel. Correct responding was defined as responding correctly to the discriminative stimulus that occurred in the absence of physical or modeled prompts. For example, an independent response to touch the green square was scored if the participant pointed to the green square after the experimenter delivered the discriminative stimulus (e.g., Touch green ). All other responses were scored as either model or physical prompts. A 48

60 model prompt was defined as any instance of the experimenter pointing with an extended finger placed on or in the direction of the correct stimulus. A physical prompt was defined as any instance of the experimenter physically touching the participant s hand and leading it to the correct stimulus. Data were collected in each session using a structured data sheet (Appendix D). After the participant engaged in a response, the observer placed a mark next to the appropriate prompt level. Tasks. Three novel discrimination tasks with differing response requirements were chosen to verify the reinforcing effects of the basic reinforcer assessment. Tasks were chosen based on teacher report of student skill level. Figure 3 depicts examples of the discrimination tasks. The first discrimination task was a single-feature discrimination. In this task, the participant was required to discriminate the color of an object from a linear array of three stimuli that were the same shape and size (i.e., two distracter colors). To control for carryover from one task to another, colors that were chosen for inclusion in the single-feature discrimination task were not chosen for inclusion in subsequent tasks. The second discrimination task was a two-feature discrimination. In this task, the participant was required to make a discrimination based on color and shape. As in the color discrimination task, colors and shapes that were targeted in the two-feature discrimination task were not included in subsequent tasks. In the third discrimination task, a three feature discrimination was taught. This task consisted of a discrimination based upon color, shape, and size. Experimental design. To evaluate the effects of contingent application of HP reinforcers identified in the MSWO assessment, a multiple probe across tasks design was 49

61 Figure 3. Example of tasks taught during reinforcer assessment. The top row is an example of the first discrimination task. The middle and last rows depict examples of the second and third tasks, respectively 50

62 Implemented (Horner & Baer, 1978). A multiple probe design was chosen because control may be demonstrated across tasks, without implementing a second baseline condition. Discrimination is not a behavior that is likely to return to baseline levels once reinforcement is removed, so an experimental design that does not require a reversal to a previous baseline condition was necessary to demonstrate experimental control. Additionally, the multiple probe design was chosen to avoid continued exposure to baseline conditions where reinforcement was not present. In the initial baseline, criterion to change phases was stable responding for at least three consecutive sessions below mastery defined as any responding that was not 100% correct. Criterion to change phases from baseline to teaching in subsequent tasks was the presence of a reinforcing effect in the previous tasks. A reinforcing effect was defined as at least a 30% increase over the mean baseline responding in the target response with an increasing trend across at least three consecutive sessions. Once a reinforcing effect was observed with one task, the next task was taught. No more than three sessions of one task were conducted in a single sitting. If the participant s responding during tasks that were in intervention decreased to baseline levels or trended opposite mastery for at least three consecutive sessions, a second fivesession MSWO was conducted to determine if the item used as a reinforcer remained HP. If the original item was no longer the HP item, the top ranked item from the second MSWO was delivered as the reinforcer in subsequent teaching sessions. If the original item remained HP, changes were made to the prompting procedure or other aspects of teaching. 51

63 Procedure Baseline. During baseline, tasks were presented to the participant, and the experimenter delivered the appropriate discriminative stimulus (S D ). For example, if the skill tested in baseline was a single-feature discrimination, the experimenter delivered the prompt to touch a specific color (e.g., Touch green ). No other programmed consequences were delivered for correct responding, incorrect responding (i.e., no additional prompts), or challenging behavior. During baseline, three target stimuli per task were probed to determine the level of responding in the absence of reinforcement. Each stimulus in a task (e.g., blue) was probed 3 times. All sessions for each task were nine trials in length to allow for baseline to be collected for all targets. Teaching. To allow for teaching to occur for all three stimuli in the array, all sessions were nine trials in length (i.e., three trials per target stimulus). Discrimination tasks for Percy and Ike were initially taught using a least-to-most prompting hierarchy. In the first level of the prompt hierarchy, the experimenter delivered the S D (e.g., Which one is yellow? ). If the participant responded correctly, he was allowed access to the HP item identified in the MSWO. If the participant did not respond correctly after 5 s, the experimenter delivered a model prompt paired with the S D (e.g., Which one is yellow? while pointing to the yellow oval). Physical guidance was provided if the participant did respond correctly within 5 s of the model prompt. If he responded correctly, the next trial was initiated. Reinforcement was not delivered for prompted responses during this prompting procedure to avoid reinforcing prompted responses. 52

64 In sessions 11 and 21 for Percy and Ike, respectively, a transfer trial was added to the least-to-most prompting hierarchy. The transfer trial consisted of an extra opportunity after a prompt to engage in the target response independently. For example, if the participant did not engage in the correct response, the experimenter prompted the response using least-to-most prompting, and then represented the S D, allowing the participant a chance to engage in the correct response and gain access to reinforcement. For, Roy least-to-most prompting with a transfer trial was initiated from the start of teaching. A spatial fading procedure was initiated for Roy and Ike in sessions 28 and 34, respectively. This teaching procedure was initiated after reassessment of preferred stimuli for Roy, and reassessment and an alteration in teaching procedures (i.e., adding a transfer trial) for Ike did not result in an increase in skill acquisition. During the first fade, the target stimulus was placed 3 in. from the edge of the table, and the remaining stimulus cards were placed 9 in. from the edge of the table. In the second fade, the target stimulus was placed 6 in. from the edge of the table, and the remaining stimuli in the array remained identical to first fade. During the terminal phase, all stimulus cards were placed 9 in. from the table s edge. Least-to-most prompting with a transfer trial remained in place as a prompting procedure. Spatial fading was not implemented with Percy, because his responding did not consistently remain at low levels. Interobserver Agreement and Procedural Integrity A second, trained observer who either attended sessions or viewed taped sessions collected interobserver agreement (IOA) and procedural integrity. Two observers were 53

65 graduate students, and one was an instructor at the experimenter s university. Before collecting IOA or procedural integrity data, all operational definitions were vocally described to the second observer. The first three sessions of IOA data collection were training sessions. After each session, the experimenter checked the IOA data to determine if an acceptable level of agreement (at least 95%) was achieved. After three consecutive sessions of at least 95% agreement, the observer was considered trained. If IOA fell below 95% agreement for three consecutive sessions, the observer was retrained. For all observers, further training was not needed. The second observer was given an identical data sheet to that of the experimenter for IOA data collection. For procedural integrity, a second data sheet was given to the observer with a list of steps included in the phase (see Appendix E). Procedural integrity was trained by the experimenter outlining the steps in the procedure and then role-playing the appropriate steps. During preference assessment phases, a second observer collected IOA and procedural integrity data for 33% of all assessments conducted. IOA was calculated by dividing the number of agreements by the total number of observations in the assessment. Percentage of IOA agreement for all preference assessments was 100%. Procedural integrity was calculated by dividing the number of correct steps completed by the experimenter by the number of possible steps implemented in the assessment. Procedural integrity for all preference assessments was 100%. In the basic reinforcer assessment, a second observer was present for 52%, 39%, and 55% for Ike, Roy, and Percy, respectively. The mean agreement for Ike was 99% (range: %). For Percy and Roy, IOA was 100%. Procedural integrity was 54

66 collected in 52%, 39%, and 55% for Ike, Roy, and Percy, respectively, with an integrity score of 100%. During the complex reinforcer assessment phase, a second observer collected data for 44%, 43%, and 38% of sessions for Ike, Roy, and Percy, respectively. The mean agreement was 100%, 100%, and 99% (range: %) for Ike, Roy, and Percy, respectively. Procedural integrity was collected in 44%, 43%, and 38% of sessions for Ike, Roy, and Percy respectively, with an integrity score of 100% for all participants. 55

67 Chapter 4: Results In this chapter, the results of this study will be described for each participant. Figures 4, 7, and 10 depict the results for the first and second MSWO assessments for Ike, Percy, and Roy, respectively. Figures 5, 8, and 4 depict the results for the basic reinforcer assessment for Ike, Percy, and Roy, respectively. Finally, figures 6, 9, and 12 depict the results for the complex reinforcer assessments for Ike, Percy, and Roy, respectively. Ike Preference assessments. Results for Ike s MSWO preference assessments are presented in Figure 4. In the first preference assessment, items were ranked from most to least preferred in the following order: dried pineapple, raisins, Oreo cookies, Goldfish crackers, Teddy Grahams, and peanuts. In the second MSWO, items were ranked from most to least preferred in the following order: dried pineapple, Oreo cookies, Teddy Grahams, Raisins, Goldfish Crackers, and peanuts. In the basic reinforcer assessment, dried pineapple was the HP item and peanuts were the LP item. Dried pineapple was also used as the reinforcer in the complex reinforcer assessments. Basic reinforcer assessment. Data for Ike s reinforcer assessment are presented in Figure 5. A basic reinforcer assessment was only conducted after the first MSWO. During baseline, Ike exchanged the card once (M = 0.2, range: 0 1). When the concurrent 56

68 Total Score Pineapple Raisin Oreo Goldfish Teddy Graham Peanut Item Figure 4. Preference assessment results for Ike. Black bars represent the first MSWO, and the gray bars the second MSWO. operant phase was implemented, he engaged in a higher level of card exchanges with the HP item (M = 13.8, range: 11 15) than the LP item (M = 0.8, range: 0 2). In the second baseline phase, Ike s responding returned to previously observed levels (M = 0.17, range: 0 1). When the concurrent operant phase was reinstated, responding initially increased. Beginning in session 20, a decrease in responding was observed for the HP item, and responding increased for the LP item. In session 25, responding for the HP item became elevated and responding for the LP item decreased. Overall, a sizeable amount of differentiation was observed between the HP (M = 10.5, range: 1 18) and LP stimuli (M = 1.62, range: 0 6). Complex reinforcer assessment. Data for Ike s complex reinforcer assessment are presented in Figure 6. Under baseline conditions, Ike engaged below mastery responding for color discrimination (M = 20%, range: 0 33%) color and shape 57

69 20 Baseline Reinforcer Assessment Baseline Reinforcer Assessment Number of Responses HP 4 2 LP Session!! Figure 5. Basic reinforcer assessment for Ike across baseline and concurrent operant phases. discrimination (M = 30%, range: 0 44%); and color, shape, and size discrimination (M = 33%, range: 11 56%). When least-to-most prompting was implemented for color discrimination, a slight increasing trend was observed (M = 34%, range: 22 56%). In session 21, a transfer trial was introduced in the color discrimination task, and responding remained stable at below mastery levels then decreased to levels observed in baseline (M = 31%, range: 0 56%). In session 33, a second MSWO was implemented to determine if the dried pineapple was still the HP item. A change in reinforcers was not initiated because of agreement between the first and second preference assessments. When spatial fading was introduced in session 34, responding at the first and second fades increased to elevated levels (M = 95%, range: %), but decreased to baseline levels once the 58

70 Baseline Least-to-Most Least-to-Most + Transfer Trial MSWO Readministered Fade 1 Fade 2 Terminal Fade 2 Terminal!" #" $!" $#" %!" %#" &!" &#" '!" '#" #!" ##" (!" (#" Color Percentatge of Independent Trials Color and Shape!" #" $!" $#" %!" %#" &!" &#" '!" '#" #!" ##" (!" (#" Color, Shape and Size Sessions Figure 6. Complex reinforcer assessment results for Ike. 59

71 terminal array was introduced (M = 28%, range: 22 33%). The second fade was reintroduced, and responding increased to levels previously observed in the first fade phases (M = 95%, range: %), but again decreased to below mastery levels once the terminal array was implemented (M = 30%, range: 22 33%). Percy Preference assessments. Results for Percy s MSWO preference assessments are presented in Figure 7. In the first MSWO, items were ranked from most to least preferred in the following order: Goldfish crackers, dried pineapple, peanuts, raisins, pretzels, and dried cranberries. In the second MSWO, items were ranked from most to least preferred in the following order: dried pineapple, Teddy Grahams, dried cranberries, peanuts, pretzels, and Goldfish crackers. In the basic reinforcer assessment, Goldfish crackers were the HP item and the LP item was dried cranberries. Goldfish crackers were used initially as a reinforcer in the complex reinforcer assessment. After the second MSWO, dried pineapple was the HP item used in the remaining complex reinforcer assessment sessions. Basic reinforcer assessment. Data for Percy s reinforcer assessment are presented in Figure 8. Under baseline conditions, Percy did not make any card exchanges. When the first concurrent operant phase was implemented, Percy allocated more responding to the HP item (M = 6.5, range: 0 9) in relation to the LP item (M = 0.25, range: 0 1). In the subsequent baseline phase, Percy s responding returned to zero levels, replicating the initial baseline phase. In the final concurrent operant phase, an overall increasing trend in responding and a large amount of differentiated responding was observed between the HP (M = 6.2, range: 2 10) and LP stimuli (M = 0.9, range: 0 3). 60

72 Total Score Goldfish Pineapple Peanuts Raisin Teddy Grahams Teddy Pretzel Cranberry Item Graham Figure 7. Preference assessment results for Percy. Black bars represent the first MSWO and gray bars represent the second. Complex reinforcer assessment. Data for Percy s complex reinforcer assessment are presented in Figure 9. Under baseline conditions, Percy engaged in below mastery criterion for color identification (M = 22%, range: 11 33%). Under the initial baseline 61

73 10 Baseline Reinforcer Assessment Baseline Reinforcer Assessment 8 Number of Responses HP LP Sessions!! Figure 8. Basic reinforcer assessment data for Percy. conditions for color and shape identification (M = 11%, range: 0 33%), responding was below mastery. In the color, shape, and size identification baseline, responding remained below mastery and was variable for the duration of data collection (M = 40%, range: 11 89%). When least-to-most prompting was introduced in the color identification task, responding increased slightly, but remained below mastery levels (M = 40%, range: 22 66%). In session 11, a transfer trial was added to the least-to-most procedure, and responding initially increased, but then decreased to baseline levels (M = 50%, range: 11 77%). In session 18, a second MSWO preference assessment was implemented to determine if the item delivered as a reinforcer continued to be preferred. Agreement between the two assessments was not found, and the new HP item was delivered in subsequent sessions. In the second color identification baseline, responding was slightly 62

74 Baseline Least-to- Most Least-to-Most + Transfer Trial MSWO Readministered Baseline Least-to-Most + Transfer Trial!" #" $!" $#" %!" %#" &!" &#" '!" '#" #!" Color Percentatge of Correct Trials Color and Shape!" #" $!" $#" %!" %#" &!" &#" '!" '#" #!" Sessions Color, Shape, and Size Figure 9. Complex reinforcer assessment for Percy 63

75 elevated, but it remained below mastery levels (M = 38%, range: 11 77%). Percy s responding increased when color identification was put back into intervention with a different high-preference item, and responding increased in relation to baseline responding (M = 64%, range: %), In the second color and shape baseline, responding was low and on a decreasing trend (M = 21%, range: 11 44%). Overall, responding increased when the color and shape task was placed into intervention, but remained variable (M = 40%, range: 22 55%). Roy Preference assessments. Results for Roy s MSWO preference assessments are presented in Figure 10. In the first MSWO, items ranked from most to least preferred in the following order: Teddy Grahams, Oreo cookies, peanuts, Goldfish crackers, pineapple, and raisins. In the second MSWO, items ranked from most to least preferred in the following order: Oreo cookies, raisins, peanuts, Teddy Grahams, Goldfish crackers, and pineapple. In the basic reinforcer assessment, Teddy Grahams were used as the HP item and raisins were the LP item. Teddy Grahams were used initially in the complex reinforcer assessment. After the second MSWO, Oreo cookies were used as the HP item. Basic reinforcer assessment. Data for Roy s reinforcer assessment are presented in Figure 11. Under baseline conditions, Roy engaged in no card exchanges. When the first concurrent operant phase was implemented, very little differentiation between the HP and LP stimuli was observed. Although little differentiation was observed, Roy engaged in a higher level of overall allocation to the HP stimulus (M = 1.5, range: 0 4) in relation to the LP stimulus (M = 0.6, range: 0 3). In the subsequent baseline phase, Roy s 64

76 responding returned to zero, replicating the initial baseline phase (M = 0.25, range: 0 1). In the final concurrent operant phase, a small amount of differentiated responding was Total Score Teddy Graham Oreo Peanuts Goldfish Pineapple Raisin Item Figure 10. Preference assessment data for Roy. The black bars represent the first MSWO, and the gray bars represent the second MSWO. 10 Baseline Reinforcer Assessment Baseline Reinforcer Assessment Number of Responses HP LP Sessions!! Figure 11. Basic reinforcer assessment for Roy across baseline and concurrent operant phases. 65

77 observed between the high-preference (M = 1.7, range: 1 3) and low-preference stimuli (M = 0.3, range: 0 1). Complex reinforcer assessment. Data for Roy s complex reinforcer assessment are presented in Figure 12. During the initial baseline phase for color discrimination, Roy s responding was below mastery levels and stable (M = 26%, range: 22 33%). Baseline responding in the color and shape discrimination task (M = 33%, range: 11 56%), and in the color, shape, and size discrimination task (M = 28%, range: 0 44%) remained low and stable for the duration of data collection. Responding in the color discrimination task increased slightly above baseline levels when intervention was introduced (M = 36%, range: 22 66%). In session 18, a second MSWO was conducted to determine if the item identified as reinforcing during the basic reinforcer assessment continued to be HP. Agreement between the two assessments was not found, and the new HP item was used in subsequent sessions. After the second MSWO, baseline was reinstated for the color discrimination task. Responding returned to levels observed in the first baseline (M = 32%, range: 22 44%). In the second teaching phase with least-to-most prompting and a transfer trial, correct responding remained low, replicating the results observed in the first teaching phase (M = 32%, range: 11 55%). In session 28, spatial fading was introduced. During the first and second fades, correct responding increased and was variable, stabilizing in session 38 (M = 91%, range: %). When the terminal goal was tested, responding decreased to near baseline levels (M = 37%, range: 33 44%). When the second fade was reintroduced, responding increased to high levels replicating the first fading phases (M = 83%, range: %). 66

78 In the final terminal phase, responding decreased to near baseline levels, and was variable (M = 37%, range: 11 77%) Baseline MSWO Readministered Least-to-Most + Transfer Trial Baseline Least-to-Most + Transfer Trial Fade 1 Fade Terminal 2!" #" $!" $#" %!" %#" &!" &#" '!" '#" #!" ##" Fade 2 Terminal Color Percentatge of Correct Trials Color and Shape!" #" $!" $#" %!" %#" &!" &#" '!" '#" #!" ##" Sessions Color, Shape, and Size Figure 12. Complex reinforcer assessment for Roy. The solid line represents the second MSWO. 67

79 Chapter 5: Discussion In this chapter, the results of the study presented in chapters 3 and 4 will be discussed in relation to contributions to the current literature, as well as limitations. Future directions for research will be outlined as well as implications for practice. The current data partially replicates previous research on the MSWO preference assessment using a basic reinforcer assessment (i.e., Carr, Nicolson, & Higbee, 2000; DeLeon & Iwata, 1996). For both Percy and Ike, HP items identified in the first MSWO preference assessment functioned as reinforcers in a subsequent basic reinforcer assessment. For Roy, HP and LP items were identified in the MSWO, but these stimuli failed to function as potent reinforcers in the basic preference assessment. These data may indicate that the MSWO was appropriate for both Ike and Percy, but not for Roy. A second explanation is that the items selected for inclusion in the preference assessments were not appropriate for Roy. In the current investigation, items were selected for inclusion in the MSWO based on responses from the classroom staff to questions on the RAISD. Roy s parents did not receive a copy of the RAISD. Although prior investigations have demonstrated positive results using staff report and a structured questionnaire (Green et al., 1988, Piazza et al., 1996), further information may have been required to obtain an adequate pool of items for Roy s assessment. 68

80 A second finding was that preference for HP items was not as stable as past research has indicated (e.g., Ciccone, Ahearn, & Graff, 2005). For both Percy and Roy, the first and second administrations of the MSWO preference assessment did not correspond. Of particular interest is the lack of stability in the HP item for both participants. Ciccone et al. (2005) assessed the food preferences of eight individuals with a developmental disability across 6 and 12 month time periods. A preference assessment was administered at two points. For example, in the 6-month phase, the assessment was administered and then administered again 6 months later. In the 12-month phase, the same procedures were implemented. In both phases, the data indicated HP and LP edible stimuli remained stable across 6- and 12-month periods. In the current investigation, stability of preference was only demonstrated for Ike. Data for Percy and Roy indicated that their preferences shifted markedly over the course of a few weeks. For example, Goldfish Crackers were initially the HP item for Percy. At the second MSWO administration, Goldfish Crackers were ranked last. Ciccone et al. (2005) and Zhou et al. (2001) provide a description of preference over time, but do not indicate conditions under which those preferences may shift or if a potential shift is possible. In the basic reinforcer assessments for Ike and Percy a marked decrease in responding to the HP item was observed in the second reinforcer assessment phase. Although brief, this temporary switch may have indicated both a switch in reinforcer value and in preference rank. One possible reason for this switch is the continued pairing with a response requirement that was novel or more difficult. The pairing may have decreased the reinforcing value of the item being delivered as a consequence for correct responding. In the complex reinforcer assessment, the data 69

81 indicated that Percy engaged in higher levels of correct responding after a new reinforcer was introduced. These data resemble data presented by Hanley, Iwata, Roscoe, Thompson, & Lindberg (2003). Hanley and colleagues investigated the alteration of activity preferences by pairing HP and LP activities with two adults with developmental disabilities. During baseline an HP and a LP activity were available concurrently. The experimenter indicated that the participant could interact with the items if they wanted. Once a clear preference for one item was demonstrated in baseline, conditioning (pairing) sessions were initiated. During conditioning sessions a previously established reinforcer was delivered on a fixed-time 30 s schedule. During the HP sessions (i.e., no conditioning), no additional reinforcement was delivered. After three conditioning and three HP sessions, a test session was conducted to determine if preference for the HP and LP activities had shifted. For both participants, preference shifted from the HP to the LP stimulus after pairing sessions. In the current study, the opposite effect may have occurred. During Percy s complex reinforcer assessment, responding decreased after a relatively small number of sessions. These data may indicate that pairing work with the HP item decreased the reinforcing effectiveness of the HP stimulus. Lastly, these data provide a demonstration of the effectiveness of reinforcers identified by a typical reinforcer assessment and a common preference assessment (i.e., MSWO) to complex tasks that may be analogous to tasks found in the natural context. As stated previously and in past literature, most demonstrations of reinforcer testing measure a simple operant response (Piazza et al., 1996), and efforts to quantify reinforcer potency may only yield information about one dimension of reinforcer effectiveness (Poling, 70

82 2010). The data from the current demonstration provide some information as to the actual effectiveness of reinforcers with more complex tasks. Overall, mixed results were observed when HP items were applied contingently to more complex responses. For Ike, items determined to be reinforcing in a basic reinforcer assessment did not function as reinforcers when applied to a more complex task. That is, they did not increase the target behavior to the same degree in both basic and complex reinforcer assessments. Additionally, when items were assessed again, the HP item remained stable but continued to remain ineffective as a reinforcer. The absence of an increase in the complex reinforcer assessment may have been the result of factors other than the HP item failing to function as a reinforcer. First, the probability of reinforcement may have continued to favor prompted responding. During teaching, Ike was given a second opportunity to engage in the correct response and gain access to reinforcement after a prompt. Adding a final opportunity to respond independently to gain access to reinforcement may not have been sufficient to encourage Ike to respond to the first S D. Second, some aspect of the prompting procedure functioned as reinforcement that may have competed with the item identified as HP during the MSWO. Anecdotally, Ike engaged in an elevated amount of behavior that may have been attention maintained (e.g., holding hand up for high fives). During prompting, a physical (i.e., hand-over-hand) prompt was implemented. If physical attention (e.g., high fives) was reinforcing, this type of prompting may have encouraged responding to remain low because of access to another preferred stimulus (i.e., physical attention). For Roy, a weak reinforcer may have been identified during the basic reinforcer assessment. Although sustained differentiation was not observed in the basic reinforcer 71

83 assessment, the HP item that was indentified in the MWSO resulted in a larger overall increase in card exchanges in relation to both baseline and the LP item. One source for the lack of clear responding may have been the occurrence of stereotypic behavior during sessions. Roy frequently spun in circles, waved his hands in front of his eyes, and rubbed the walls of the session room during sessions. Efforts were made to block stereotypic behavior (e.g., moving Roy away from the wall), but even low levels of stereotypic behavior may have continued to compete with responding to the HP and LP items. During the complex reinforcer assessment, similar results were observed, with the contingent application of the HP item failing to encourage elevated levels of responding for even single-feature discrimination. The failure of both the basic and complex reinforcer assessments to validate the HP item as a reinforcer may indicate that for Roy, the MSWO may not be predictive of item reinforcing effectiveness. A second confound may have also occurred in the basic reinforcer assessment. Anecdotally, Roy engaged in high levels of stereotypic behavior (e.g., spinning, rubbing walls) that may have competed with responding to the stimuli present in the room. A third source of the weak results may be the nature of the prompting procedure. Similar to Ike, Roy may have waited to gain access to the reinforcer on the independent trial delivered immediately after a prompted response. More positive results were observed with Percy. During the basic reinforcer assessment, a clear reinforcing effect was observed, and the effect was also observed with one discrimination in the complex reinforcer assessment. Specifically, a significant, but slow and variable increase in responding was observed during the color discrimination 72

84 task. When the same item was applied to the second task, a less apparent increase occurred. Although a reinforcing effect was demonstrated with Percy, a high degree of variability was observed in both acquisition phases for color discrimination. The variability observed during both skill acquisition phases may have been the result of a decrease in reinforcing effectiveness of the HP item over time. In the first acquisition phase for the color discrimination task, a clear increase was observed with the original HP item, but then responding decreased. After a second MSWO, responding again increased. In the second MSWO, a different HP item was found. The decreases in responding followed by an increase with a new HP item may indicate that for Percy, both preference and reinforcing effectiveness of items identified via MSWO may be highly transient. Similar results were reported by DeLeon et al. (2001) with five individuals with intellectual and developmental disabilities. In their investigation, the reinforcing effects of items identified with a lengthy preference assessment (i.e., PC preference assessment) were compared to the reinforcing effects of items identified with a daily brief preference assessment (i.e., MSWO). An initial HP item was identified for all participants using a PC preference assessment and it was compared in a CO reinforcer assessment to the item identified each day by the MSWO. If a different item was not chosen during the daily MSWO, a reinforcer assessment session was not conducted. The data indicated that for four of the participants, the item identified via the daily MSWO was a more potent reinforcer than the item identified during the initial PC preference assessment. For one participant, the PC preference assessment yielded a more potent reinforcer, but only two 73

85 reinforcer assessment sessions were conducted, limiting conclusions that could be drawn from her data. In the second task (color and shape discrimination) for Percy, a small increase in responding was observed. Overall responding in this task did not increase significantly over baseline, which may indicate that the HP item did not function as a potent reinforcer for the task. The absence of a steep increase in responding may be analogous to a progressive ratio (PR) break point. Under PR schedule contingencies, reinforcer ratios change arithmetically from ratio to ratio within the session. The point where the participant ceases to respond is called the break point. In other words, the break point is where the reinforcer ceases to be potent enough to encourage responding. In an early applied example of the application of PR schedules to a clinical population, Roane et al. (2001) investigated a more clinical application of PR schedules with four individuals with moderate to intensive intellectual and developmental disabilities. In the first experiment, the reinforcing effectiveness of HP and LP items identified in a PC preference were tested in a SO reinforcer assessment. A PR schedule requirement was in place for both HP and LP testing sessions. The data for the first experiment indicated that HP items sustained responding at higher PR requirements (i.e., high break point). LP items also encouraged responding, but to a much smaller degree (i.e., low break point). In the second experiment, the HP and LP items tested in the previous phase were compared in three common interventions for challenging behavior. For one participant, a non-contingent reinforcement procedure was chosen and hypothesized to be a low response effort intervention. That is, the participant only had to engage with the LP or the HP item. For the remaining two participants, a differential reinforcement of other 74

86 procedure (DRO) and a differential reinforcement of alternative behavior (DRA) procedure were chosen. The differential reinforcement procedures were hypothesized to be higher response effort interventions. In the DRO procedure, the participant had to cease engaging in challenging behavior for a prespecified amount of time to gain access to reinforcement. The requirement of the DRA procedure was the emission of an alternative response, which was not specified by the authors. The data indicated that the HP item that was previously identified as a reinforcer was also a more potent reinforcer in all intervention conditions. Although Roane et al. (2001) reported positive outcomes when the HP item was applied to an intervention, the responses were still relatively simple (i.e., refraining from engaging in challenging behavior). The results for Percy may be a more applicable demonstration of reinforcer strength across higher response requirements. The data for color discrimination for Percy demonstrate a slight reinforcing effect, but when the response requirement was increased, sharp decreases in responding were observed. Sustained decreases may indicate that under that particular response requirement, the HP item functioned weakly as a reinforcer. This type of responding may be analogous to the PR break points illustrated in the Roane et al. (2001) study. A more complex response may be similar to increasing the PR schedule. For Percy, the increase in potential difficulty from a color discrimination to one that required discrimination of color and shape may have been similar to a large ratio requirement increase in a PR schedule. Limitations and Future Directions for Research The current data are a preliminary example of the effects of items identified via an MSWO preference assessment under more complex requirements. Overall, the data are 75

87 promising, but several main limitations should be addressed with further investigations. First, the tasks that were selected for the participants were selected by the experimenter and based on teacher report of a skill deficit in discrimination skills. It is possible that the lack of responding by all participants was the result of a skill deficit in a prerequisite skill needed to engage in a complex discrimination. The arbitrarily selected discrimination task may have been too difficult a task to teach without these prerequisite skills, potentially leading to the lack of correspondence between basic and complex reinforcer assessments. Green (2001) outlined a number of considerations when teaching discrimination s skills to individuals with autism. Although only one of the participants (Ike) in the current study had a diagnosis of autism, the areas outlined by Green may still be applicable, based on the skill level of the participant. The current study contained several practices Green (2001) recommended, which will be omitted from this discussion. The two practices that were not used in the current study were requiring participants to make an observing response and repeating the S D at scheduled intervals during the teaching trial. Anecdotally, it seemed that Roy and Ike did not scan the entire stimulus array during all trials, making correct responding difficult. Additionally, the S D was only provided once for each trial (e.g., Touch red. ). Green noted that delivering the S D at the beginning of the trial instead of at specific intervals only allows the participant to observe the response a single time. Additionally, presenting the S D multiple times potentially curbs the risk of the participant not hearing the directive, not discriminating that directive from others in different trials, or failing to remember the directive throughout the trial. 76

88 A related issue may be the nature of the task selected. In the current investigation, the tasks selected for the complex reinforcer assessment may have been more abstract in nature. Complex behavior could be conceptualized as a behavior that is abstract in nature or behavior that involves more response effort (i.e., steps). For example, cooking a meal and adding digits without the benefit of a calculator may be considered a complex tasks. Where the two differ is one is more abstract (i.e., adding without a calculator) and one is more functional or concrete (i.e., cooking a meal). Given the limited skill sets of all three participants, a more functional skill may have been appropriate, and if used may have yielded different results. Future investigations may benefit from implementing more functional tasks (e.g., cooking, vocational skills etc.) when investigating the reinforcing effectiveness of items identified via preference assessments. For all participants, responding may have been due at least in part to a continued foundational skill deficit (e.g., lack of observing response). Because of that potential deficit, a more complex conditional discrimination may have been a skill that would not be readily learned. Further investigations in the application of preference assessment methodology to more complex behavior should identify assessments that may better identify skill areas for testing. For example, future investigations could use the Assessment of Basic Learning Abilities (ABLA; Vause, Yu, & Martin, 2007) as a preassessment tool to select discrimination tasks. In the current study, a preassessment was not included because many of the available assessments are either inappropriate for older learners (e.g., VB-MAPP; Sundberg, 2008) or are well researched, but have some flaws that have drawn into question their rigor (e.g., ABLA; Stewart, McElwee, & Ming, 2010). Despite these limitations, it may still be fruitful for further investigations to 77

89 include some objective measure of student skills prior to testing reinforcing effectiveness with a more complex task. Second, the procedures used for prompting were limited. Although the effects of prompting procedures were not the focus of the current investigation, effective prompting strategies were critical for examining reinforcement effects. For all three participants, the prompting procedures were based on sound empirical investigations (e.g., Steege, Wacker, & McMahon, 1987), but only two general strategies were used. The possibility exists that for all participants, the prompting strategies selected were ineffective. The data for Ike and Roy specifically may have reflected not a failure to identify a reinforcer, but a failure to identify an effective prompting strategy. For Percy, the additive nature of the decisions related to the prompting procedure may also account for some degree of responding. Some carryover from previous phases may have contributed to the responding seen in subsequent phases. For at least one participant (Ike), it seems that prompting may have functioned as a reinforcer. Because of the multiple sources of potential reinforcement, correct responding could not be adequately reinforced with the most potent stimulus available. Karsten and Carr (2009) demonstrated the effects of differential reinforcement and NCR on academic responding for two young boys diagnosed with autism. The data indicated that non-differential reinforcement (e.g., NCR) procedures were ineffective in encouraging correct responding for both participants. In contrast, a differential reinforcement procedure (i.e., withholding HP items for correct responses only) was the most effective in promoting skill acquisition. In other words, only delivering reinforcement for correct responses. For Ike, the complex reinforcer assessment sessions 78

90 may have been similar to the Karsten and Carr non-differential reinforcement sessions. Future research should investigate the interaction between reinforcer potency and prompting procedures. For example, investigating skill interaction when an LP stimulus is used as a reinforcer in combination with a previously successful prompting procedure. A second area of future research may focus on identifying methods of assessing for stimuli that are potent enough to compete with concurrently available HP stimuli. Third, in the current study, an initial preference assessment was conducted at the beginning of the study. Subsequent assessments were conducted only if participant responding decreased. For two participants, the second administration of the MSWO resulted in preference shifts. That is, the HP item from the first and second MSWO assessments did not correspond. Previous research had demonstrated that preference for items that are HP remains stable over extended periods of time (Ciccone et al., 2005; Zhou et al., 2001). For Percy and Roy, preference outcomes did not remain stable. The preference assessment data from Percy and Roy may indicate that for some individuals preferences do not remain as stable as has previously been reported (e.g., Zhou et al., 2001). Percy s complex reinforcer assessment data may be indicative of not only variability in preference, but also variability in reinforcing effectiveness. Future research should further investigate the variability of reinforcing effects over time. For example, further investigation of the DeLeon et al. (2001) methodology may provide information related to the extent to which preference stability corresponds with stability of reinforcing effects. Additional research investigating the conditions under which preferences shift or methods of shifting preference (e.g., from LP to HP) may also be helpful. For example, future investigations could test the stability of brief MSWO preference assessments (e.g., 79

91 Tullis et al., in press) in comparison to more extensive preference assessments (e.g., DeLeon & Iwata, 1996). Fourth, only one type of preference assessment was tested (i.e., MSWO). Previous literature has demonstrated some level of correspondence between the MSWO and other preference assessments (e.g., PC; DeLeon & Iwata, 1996). The previous results supporting correspondence may allow for some preliminary conclusions to be made about the generality of other assessments. An MSWO was chosen for inclusion in this study based on the clinical experience of the experimenter in combination with solid support from the literature. Current literature supports very loose criterion for selecting preference assessments for specific individuals (Hagopian et al., 2001). A reliance on clinical experience may lead a clinician or experimenter to choose the methodology that is most comfortable, instead of the one that is the most effective and yields the most generalizable results. One method of adding additional rigor may be to compose treatment selection models (Geiger, Carr, & LeBlanc, 2010). In a study by Karsten et al. (2011), a selection model for the MSWO was investigated with 20 individuals with autism. Participants were initially exposed to a typical MSWO preference assessment. Modifications to the assessment were made systematically based on the occurrence of challenging behavior or the failure to compile a hierarchy of preferred items. For all participants, a hierarchy of preferred items was identified. Although the methods proposed by Karsten et al. are promising, only the MSWO was tested. Future research should focus on identifying a decision making process for choosing preference assessment methodologies and for 80

92 altering all available methodologies. For example, extending the Karsten et al. methodology to additional methodologies. Fifth, only one type of reinforcer assessment was implemented in the current study. Roscoe et al. (1999) demonstrated the differential effects of SO and CO reinforcer assessments, but they did not apply their findings to more complex responses. The results of their study were discussed in terms of more complex responses and more naturalistic contexts. A CO reinforcer assessment was chosen because it yields a measure of relative reinforcing effectiveness. Relative measures of reinforcing effectiveness have the potential to be more potent, because they compete with other available stimuli in the assessment context (Roscoe et al., 1999). Future studies should compare additional methods for assessing for reinforcing effectiveness (e.g., SO reinforcer assessment) to determine if one assessment identifies potent reinforcers more reliably. Sixth, in the current study a small number of assessment stimuli were indicated by classroom staff as being preferred. Specifically, classroom staff indicated a small number of leisure stimuli that were preferred and a number of them could not be easily delivered (e.g., community outings). Parents were not surveyed in the current study, but the addition of information from caregivers may have been helpful in constructing more varied pools of preferred items. Edible stimuli were chosen because of the ease of delivery and the range of stimuli recommended by classroom staff. For Ike, non-edible stimuli, specifically attention, may have been a more effective reinforcer. Anecdotally, Ike requested high-fives, handshakes, and general attention at high rates both in and outside of experimental sessions. 81

93 Previous literature has demonstrated the effectiveness of non-edible items to function as reinforcers for a variety of adaptive behavior (Daly et al., 2009), but most of the assessment procedures utilized graphic representations of activities (e.g., pictures). Daly et al. (2009) tested the effectiveness of the MSWO preference assessment in identifying activities that functioned as reinforcers for five participants with behavioral disorders. Eight activities were selected and presented to participants in an MSWO preference assessment. The data indicated that items identified as HP in the MSWO functioned as the most effective reinforcers for math problem completion in a subsequent reinforcer assessment. In the current investigation, the participants did not seem to have an equivalent level of picture correspondence in their repertoire. Future research should replicate the current investigation using conditioned stimuli (e.g., activities). Additional research may also be valuable to adapt procedures proposed by Daly et al. (2009) for use with individuals with more severe disabilities. In the current study, a switch was not made for Ike and Roy because of questions regarding their skill level and how best to include a relatively abstract concept as part of the stimulus array. Similar to the potential need for a preassessment before testing the effects of reinforcers identified via preference assessments, it may be beneficial to have additional information to construct stimulus arrays (e.g., pictures vs. physical items). Graff and Gibson (2003) investigated the use of pictures in PC preference assessments with four boys with autism, developmental disabilities, and behavior disorders. Two types of preference assessments were used, in one assessment physical items were used, and in the second pictures of stimuli were used. In both assessments, the same stimuli were assessed. For example, if a video game was included in the physical preference 82

94 assessment, a picture of the same video game was present in the pictorial preference assessment. The data indicated that similar preference hierarchies were identified for three out of the four participants and that reinforcers were identified more accurately with the pictorial assessment for one participant. It should be noted that all of the participants had object-to-picture and picture-to-object matching in their repertoire. The presence of this skill may have allowed the participants to more accurately perform using pictures. This skill did not seem to be present in Ike and Roy s current skill repertoire. Further research should be conducted in both teaching these abstract representations (e.g., stereotypy) and in assessing for the requisite skills needed to use pictures in preference assessments. Lastly, the definition of complex behavior may vary from participant to participant. Previous researchers have recommended that more complex behavior be measured in reinforcer assessments (e.g., Piazza et al., 1996). Although a measure of a more complex behavior would be beneficial, a definition of complex behavior has not been outlined in the literature. In the current study, complex behavior was conceptualized as a more abstract concept (i.e., discrimination). Defining complex behavior as a more abstract concept may be accurate for some participants, but not others. For all three participants, this may have been the case. In future investigations, it may be beneficial to use more functional target behaviors to measure the reinforcing effectiveness of items identified in preference assessments. For example, future researchers may choose multistep behaviors (e.g., taking out the trash, shoe-tying) that may be measured more systematically. Additionally, the choice of a multistep behavior may allow future 83

95 researchers to systematically vary the response requirement for each participant to further examine the interaction between reinforcer magnitude and work effort. Conclusion and Implications The application of preference assessment methodologies is a practice that is supported by ample research and a number of empirical literature reviews (Cannella et al., 2005; Lancioni et al., 1996, Lohrmann-O Rourke & Browder, 1998, Tullis et al., 2011). Previous literature has provided researchers and clinicians with a robust technology to objectively quantify preference for individuals with moderate to intensive intellectual and developmental disabilities. The current literature has provided information on reinforcer potency (e.g., Milo et al., 2010), preference stability (e.g., Zhou et al., 2001), and correspondence between and among various methodologies (e.g., Roane et al., 1998). Although a large amount of information is present about a number of parameters of preference assessment methodologies, the current literature relies heavily on the measurement of simple operant responses to determine reinforcing effectiveness. The current study provides preliminary data to demonstrate some of the effects of identifying a reinforcer using one type of preference assessment and then testing the effectiveness of that item on a more complex response. Overall, the results were mixed, with a reinforcing effect observed with one participant in the single feature discrimination. For one participant, a reinforcer was identified in the basic reinforcer assessment, but it was not potent enough to increase the responding with a more complex behavior. Results for the final participant indicated that at the very most, a weak reinforcer was identified in the basic reinforcer assessment. This item was also inadequate as a reinforcer when applied to a more complex behavior, which is not 84

96 surprising given the results of the basic reinforcer assessment. These data demonstrate the potential for results of the MSWO preference assessment to fail to apply to more complex behavior (Piazza et al., 1996). In practical application, teachers and clinicians should be systematic when identifying reinforcers and equally systematic in monitoring the effects on both simple and complex operant behavior. These data have several implications for researchers and clinicians. First, the over-reliance on simple operant responses may indicate that the preference technology that is available is not as robust as has been reported for some individuals (e.g., Tullis et al., 2011). Further research is needed to determine the parameters of preference assessment results, but for practitioners, preference assessments seem to be a sound place to start when attempting to identify reinforcers. The procedures available to objectively measure preference give practitioners a place to start when teaching a student with a moderate to intensive developmental or intellectual disability. If the items identified via a preference assessment are used for a wide array of adaptive behavior, practitioners should pay close attention to the effects to determine if a reinforcing effect is observed. Second, reinforcement alone is not sufficient to teach meaningful (i.e., complex) skill sets. In the current study, there may have been some interaction between prompting method and the potential reinforcer. Ineffective prompting may have decreased the potency of the items identified to function as reinforcers. For research, these results may indicate the need for a more fine-grained examination of the effects of prompting on reinforcement and vice versa. In practice, teachers and clinicians should continue to change prompting procedures and reinforcers systematically, based on student performance. Similar to the lack of clear guidelines on choosing preference assessments, 85

97 guidelines that indicate how to apply prompting procedures are absent from the literature. Many clinicians may resort to only the most familiar prompting procedure, which from the current results may negatively impact teaching procedures. Lastly, previous research supports some of the assumptions that preferences for stimuli with individuals with moderate to intensive intellectual and developmental disabilities remain stable (Ciccone et al., 2005; Zhou et al., 2001). The current data do not seem to support the conclusions that have been previously made regarding preference stability. In the case of Percy, stability of preference and reinforcing effectiveness seemed to be highly variable. The most stable preference assessment data (Ike) did not result in identification of a reinforcer for complex behavior. For Percy, these data would support the recommendations of Lohrmann-O Rourke and Browder (1998) who recommended assessing preference frequently to capture shifts in preference. A separate issue is how to handle stable preferences that do not yield a potent reinforcer (i.e., Ike). For clinicians, these data support frequent assessment of preferred items and surveying a large number of significant others to gather a large enough pool of potential reinforcers. When put into place, items that are used as reinforcers should be monitored closely to ensure the most effective stimulus remains in place for skill acquisition. In the current study, the generality of preference assessment outcomes was tested across basic and complex reinforcer assessments. Overall, the results of the current study are mixed, but may provide a framework for further investigation. Future research should focus on addressing methodological limitations (e.g., pre-assessment, stimulus selection) that may have hindered the identification of appropriate stimuli and tasks to test reinforcing effectiveness. Further methodological refinement and testing may yield more 86

98 positive results. Such results can help address some of the large limitations in the current literature base and provide a more robust description of preference and the utility of preference assessment information for more complex behavior. 87

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106 reinforcers on preference and resistance to change. Journal of the Experimental Analysis of Behavior, 93, Mithaug, D. E., & Hanawalt, D. A. (1978). The validation of procedures to assess prevocational task preferences in retarded adults. Journal of Applied Behavior Analysis, 11, O Reilly, M. F., Lancioni, G. E., & Sigafoos, J. (2004). Using paired-choice assessment to identify variables maintaining sleep problems in a child with severe disabilities. Journal of Applied Behavior Analysis, 37, Pace, G. M., Ivancic, M. T., Edwards, G. L., Iwata, B. A., & Page, T. J. (1985). Assessment of stimulus preference and reinforcer value with profoundly retarded individuals. Journal of Applied Behavior Analysis, 18, Paclawskyj, T. R., & Vollmer, T. R. (1995). Reinforcer assessment for children with developmental disabilities and visual impairments. Journal of Applied Behavior Analysis, 28, Parsons, M. B., & Reid, D. H. (1990). Assessing food preferences among persons with profound mental retardation: Providing opportunities to make choices. Journal of Applied Behavior Analysis, 23, Piazza, C. C., Fisher, W. W., Hagopian, L. P., Bowman, L. G., & Toole, L. (1996). Using a choice assessment to predict reinforcer effectiveness. Journal of Applied Behavior Analysis, 29, 1 9. Poling, A. (2010). Progressive-ratio schedules and applied behavior analysis. Journal of Applied Behavior Analysis, 43, Reed, D. K., Luiselli, J. K., Magnuson, S. F., Vieira, S., & Rue, H. C. (2009). A comparison between traditional economical and demand curve analyses of relative reinforcer efficacy in the validation of preference assessment predictions. Developmental Neurorehabilitation, 12, Reid, D. H., Parsons, M. B., Towery, D., Lattimore, L. P., Green, C. W., & Brackett, L. (2007). Identifying work preferences among supported workers with severe 95

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109 Appendix A: Literature Review Data Sheet 98

110 99

111 Appendix B: Study Recruitment Letter 100

112 Dear Parents, We would like to include your child in a study that will examine methods to assess your child s preferences. The purpose of this project is to determine whether items that increase a simple academic behavior can also increase more complex behaviors. If your child participates in this study, sessions will be conducted 4-5 times weekly for twenty to thirty minutes. Three assessments will be conducted with your child. First, we will conduct a preference assessment in which a group of items is presented and they will have the opportunity to choose from the group. A choice will be defined as your child point to or touching an item in the group. Once we have identified those items that are preferred based on the results of the first assessment, we will assess whether or not those items are reinforcing to your child. In other words, can we use those items to increase a skill that your child does not use consistently. This will be done by asking your child to do a task, such as asking for the preferred item. If that behavior increases, it would suggest that the items are 101

113 indeed preferred and reinforcing. In the third assessment, the same item identified previously will be used to teach discrimination skills of differing levels. For example, one level is teaching your child to identify objects using three features (e.g., color, shape, size). If this study is successful, your child s teacher will have a way to systematically determine what your child does and does not like. They can then use these items to reinforce and teach new skills. Additionally, they will also have information about what types of items reinforce harder tasks. I will be leading this project with the assistance of OSU graduate students. If you would like more information, please feel free to contact me at the phone number or address below. If you would like for your child to participate in this study, please sign the attached consent form and return it to your child s teacher. Please know that your consent for your child s participation is voluntary, you can refuse to answer questions that you do not wish to answer, and you can refuse your child s participation or withdraw your child at any time without penalty or repercussion. Thank you for your time and attention. Helen I. Malone, Ph.D. Associate Professor 102

114 Appendix C: Consent Form 103

115 104

116 105

117 106

118 107

119 Appendix D: Reinforcer Assessment for Individuals with Severe Disabilities 108

120 109

121 110

122 Appendix E: MSWO Preference Assessment Data Sheet 111

123 112

124 Appendix F: MSWO Preference Assessment Treatment Integrity Data Sheet 113

125 114

126 Appendix G: Basic Reinforcer Assessment Data Sheet 115

127 116

128 Appendix H: Basic Reinforcer Assessment Procedural Integrity Data Sheet 117

129 118

130 Appendix I: Complex Reinforcer Assessment Data Sheet 119

131 120

132 Appendix J: Complex Reinforcer Assessment Procedural Integrity Data Sheet 121

133 122