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have implications for supported work environments. As students grow older, a greater emphasis may be placed on vocational opportunities and independence in these settings. In the current review, seven studies were conducted in vocational settings or focused on vocational tasks (Cobigo et al., 2009; Graff et al., 2006; Horrocks & Morgan, 2009; Lattimore et al., 2003; Reid et al., 2007; Spevack et al., 2008; Tasky et al., 2008). For example, Lattimore et al. implemented multiple stimuli with replacement (MSW) preference assessments outside of the work context with five individuals to determine preference for specific work tasks. After preferences were identified, participants were given the choice of tasks to complete during their daily work routine. Data indicated that the MSW assessment was effective in identifying preferred work preferences for the participants. Increases in choice making were observed in participants who did not display stable work preferences, and stable choice making was observed in participants who displayed stable preferences during the MSW. These data suggest that including a choice component may enhance the vocational planning process for adults with severe to profound disabilities. Although a large number of investigations reported positive results, these results should be viewed with a degree of caution. Of the studies cited, 11 reported mixed findings overall or findings that were negative or mixed for at least one experiment in the investigation. For example, Sigafoos et al. (2009) reported positive findings in the final two phases, but negative findings in the first phase of the investigation. These findings are important to consider when replicating procedures for future research as well as in clinical practice. First, the findings may indicate further areas of research into the implementation of choice and preference assessment methodology. The failure of an assessment methodology to yield positive results may be an indicator of the need for procedural refinement. Second, mixed results may be an indication that specific procedures are not appropriate for use with certain populations of individuals or under specific environmental conditions. Accessibility of Preference Assessments and Choice Interventions All four studies focusing on staff training reported clearly positive results, indicating the potential to successfully teach direct-care staff members to implement choice interventions (Reid et al., 2003) and preference assessments (Roscoe & Fisher, 2008; Roscoe et al., 2006; Machalicek et al., 2009). Although these studies reported positive results, a potential limitation in the training literature is the degree that these procedures may be effective in training parents or other care providers in more naturalistic environments. Participants in all four studies were employed at the facility where the research was conducted or were supervised by the first author of the study, and training for two studies (Roscoe & Fisher, 2008; Roscoe et al.) was conducted outside of the natural context. Both the population (i.e., therapists, job coaches) and the settings have the potential to limit the accessibility of choice and preference procedures to specific environments and individuals for three studies (Reid et al.; Roscoe & Fisher, 2008; Roscoe et al.). In contrast Machalicek et al. demonstrated a method of providing supervision and training in implementing preference assessment methodology via teleconference. The use of technology allowed the researchers to assess skill acquisition of the participants (preservice teachers) in the natural context with their students. Although it is important for professionals to know how to implement choice and preference methodologies, it may be even more useful to parents or other caregivers. Three articles that implemented choice interventions (Carlson et al., 2008; Harding et al., 2009; Humenik et al., 2008) and one preference assessment study (O’Reilly et al., 2004) included a parent, teacher, or other care provider as the interventionist. Carlson et al. implemented a choice intervention to decrease urinary incontinence and public disrobing for two individuals. Teachers were trained to implement the intervention, but data on their skill acquisition and treatment fidelity were not presented. Data indicated that the choice intervention decreased the occurrence of incontinence and disrobing for both participants. Additionally, the teachers did not re- Review of Choice and Preference Assessment / 589
port difficulty implementing the intervention nor did the experimenters observe difficulties. These data—along with those discussed previously—are promising for implementing preference assessments and choice interventions across a wide range of caregivers and practitioners in varied settings. Comments on Complexity of 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 high preference stimuli under PR schedules than low preference stimuli, regardless of the presentation format. During single stimulus arrangements, low preference stimuli functioned as reinforcers for two participants. These results suggest that responding for high preference stimuli was not disrupted by the concurrent availability of a low preference stimulus and that a 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 inappropriate 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. Concluding Comments and Future Research In this paper, studies focusing on preference assessment methodologies and choice interventions for individuals with severe to profound disabilities were summarized and discussed. Based on the results of these studies, research on choice is strengthening the evidence of its efficacy, and research on preference seems to be progressing toward a more complete description of the mechanisms and processes that underlie preference. The answers to the research questions posed at the beginning of this review are relatively clear, but should be further clarified. First, choice interventions continue to be effective for reducing challenging behavior and increasing appropriate behavior. Overall procedures have changed little. These procedures continue to have implications for enhancing programming in special education and noneducational settings (e.g., vocational settings, community, home, etc.). Second, preference assessments continue to be effective in identifying items that function as reinforcers. The most common methods for assessing preference in the studies reviewed were the PC and MSWO. Twenty studies used a PC preference assessment and six included an MSWO. The type of stimuli used in these assessments has expanded beyond edible and leisure items. For example, Wilder et al. (2008) assessed preference for olfactory stimuli with three adults diagnosed with autism and severe to profound mental retardation. A PC preference assessment was implemented to determine a hierarchy of preferred smells. In the subsequent reinforcer assessments, all participants engaged in increased levels of responding in relation to baseline, indicating that the highly preferred stimuli functioned as reinforcers. Third, preference and choice technologies—though very effective—may be inaccessible to individuals who are not systematically trained. The research-base supports the implementation of choice- and preference-based interventions to increase independence, decrease challenging behavior, and teach appropriate behavior, and that the available training protocols have been demonstrated to be effective (e.g., Roscoe & Fisher, 2008). One major limitation of this literature is the absence of training procedures that have been shown to be effective in teaching caregivers specific procedures. Without easily implemented procedures or training programs, research findings 590 / Education and Training in Autism and Developmental Disabilities-December 2011
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Education and Training in Autism an
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March 2012 Manuscripts Accepted for
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new line of research, the review ho
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TABLE 1—(Continued) Overview of H
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TABLE 1—(Continued) Overview of H
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Figure 1. MP3 Player (Model: SM-320
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Figure 3. Sony-Ericsson K800. Retri
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computer with three middle school s
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Figure 6. Video iPod. Apple, Inc. h
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example, in contrast to previous st
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using public transportation. Device
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accessible software to increase ind
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(14.3%), a unique curriculum (13.8%
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TABLE 1 Student Characteristics Stu
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eos” was highlighted. Students th
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ment was 100% for baseline and main
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Figure 3. Percentage of independent
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how to program and operate the equi
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Individuals with Disabilities Educa
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TABLE 1 Video Prompting Studies Con
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TABLE 1—(Continued) Video Prompti
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Length of video clips. Researchers
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to learn three cooking tasks. Resul
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Van Laarhoven and Van Laarhoven-Mye
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Dogoe, M., & Banda, D. R. (2009). R
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TABLE 1 Summary of Demographic and
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TABLE 2 Summary of Outcome Variable
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with students in preschool (Akmanog
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with MoID acquiring some of their p
Page 63 and 64: Vocational task. To date one study
Page 65 and 66: ed; thereby adding to the amount of
Page 67 and 68: Retardation and Developmental Disab
Page 69 and 70: Education and Training in Autism an
Page 71 and 72: TABLE 1 Student Demographic Informa
Page 73 and 74: Figure 1. Example of the mini-poste
Page 75 and 76: Experimental Design This study empl
Page 77 and 78: intervention sessions was 75.55% de
Page 79 and 80: help continue maximum skill profici
Page 83 and 84: at the same time, or did not respon
Page 85 and 86: Figure 1. Correct responses for Joe
Page 87 and 88: sponses for each skill. No trends w
Page 89 and 90: then be used as a template for quic
Page 91 and 92: 2007). Choice making initiates the
Page 93 and 94: making choices is clearly not in th
Page 95 and 96: epeated until stable choice pattern
Page 97 and 98: transportation, commitment) to prov
Page 99 and 100: can be made. Last, because consumer
Page 103 and 104: TABLE 1 Studies Listed According to
Page 105 and 106: TABLE 1—(Continued) Studies Liste
Page 111 and 112: (i.e., MSW) and duration-based (i.e
Page 113: 2008), and increasing adaptive beha
Page 117 and 118: of a preferred item while continuin
Page 119 and 120: Kreiner, J., & Flexer, R. (2009). A
Page 123 and 124: autism on the CARS. Regarding socia
Page 125 and 126: other effect size measures and with
Page 127 and 128: quests during baseline sessions. Du
Page 129 and 130: ulation was generally clear and he
Page 131 and 132: communication training as a treatme
Page 133 and 134: encing allergy symptoms (one partic
Page 135 and 136: Assessments Preference assessment.
Page 137 and 138: Interobserver agreement. A second o
Page 139 and 140: challenging behavior in the presess
Page 141 and 142: tion of the preferred item signaled
Page 143 and 144: ior: An analysis of the literature.
Page 145 and 146: moderate intellectual disabilities
Page 147 and 148: Effects of the STAR intervention pr
Page 149 and 150: Copeland, S. R. (2002). See citatio
Page 151 and 152: 126. Ezell, D., & Klein, C. (2003).
Page 153 and 154: computer-based instruction program.
Page 155 and 156: sight words to students with mental
Page 157 and 158: Mastropieri, M. A. (2009). See cita
Page 159 and 160: 262. Noyes, D. A., & Sax, C. L. (20
Page 161 and 162: Rispoli, M. (2009). See citation #1
Page 163 and 164: Sparks, S. (2010). See citation #87
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Vlaskamp, C. (2008). See citation #
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INDEX—VOLUME 46,
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Runes, Sandra. See Hausmann-Stabile
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Review of video prompting studies w
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Look! I'm in College! DVD Look, I
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13th International Conference on Au
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