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Choice-based stimulus preference assessment for children with or at-risk for emotional disturbance in educational settings.

Abstract

Students with or at-risk for emotional disturbance (ED) frequently receive interventions that include a direct manipulation of consequences. The ability of educators to identify reinforcing stimuli that may function as powerful consequences determines the success of reinforcement-based strategies. Choice-based stimulus preference assessments provide a systematic means of identifying potential reinforcers that have been well researched with children and adults with severe disabilities. However, research concerning the effectiveness of choice-based stimulus preference assessments for students with ED remains limited. Therefore, the current literature review examines the experimental context and effectiveness of choice-based stimulus preference assessments in identifying reinforcers for students with ED in educational settings and the advantages of these procedures over preference surveys. While reinforcers identified through choice-stimulus preference assessment increased the target behaviors of the participants, choice-based preference assessment methods did not unequivocally improve upon preference surveys. Implications for practitioners and future research directions are discussed.

KEYWORDS: Emotional Disturbance, Preference Assessment, Reinforcer

Students with or at-risk for emotional disturbance (ED) have poor outcomes compared to many other groups of students with high incidence disabilities (Bradley, Doolittle, & Bartolotta, 2008; US Department of Education, 2008; Wagner et al., 2006) and remain more likely than their peers to receive services in restrictive settings (Achilles, McLaughlin, & Croninger, 2007; US Department of Education, 2008; Whorton, Siders, Fowler, & Naylor, 2000). Consequently, there is a great need to adopt evidence-based practices that reduce problem behaviors for students with ED, as problem behavior is the primary barrier to access to less restrictive settings (Hurley et al., 2010). Rein-forcement (i.e., a change in consequence that increases the future frequency, intensity, or duration of a response) is a component of many commonly used evidence-based interventions for building appropriate alternative behaviors (e.g., token economies, differential reinforcement) (Alberto & Troutman, 2009; LaRue, Weiss, & Ferraioli, 2008; Petscher, Rey, & Bailey, 2009; Walker, Shea, & Bauer, 2007).

Many effective interventions for students with or at-risk for ED target both social and academic repertoires with a reinforcement-based intervention. For example, Christensen, Young, and Marchant (2007) increased the frequency of socially appropriate behaviors emitted by a student with a history of internalizing behaviors using a variable interval schedule of reinforcement. Ingvarsson, Hanley, and Welter (2009) drastically reduced escape-motivated disruption (e.g., spitting, aggression) in three disruptive students by differentially reinforcing the completion of academic tasks. The success of reinforcement interventions, however, largely depends on the identification of preferred stimuli that function effectively as reinforcers (Walker et al., 2007).

Practitioners often attempt to identify potential reinforcers using interviews, preference surveys, or questionnaires that require individuals or their caretakers (e.g., parents, teachers) to identify desirable stimuli (Ivancic, 2000). Structured interviews, such as the Reinforcer Assessment for Individuals with Severe Disabilities (RAISD; Fisher, Piazza, Bowman, & Amari, 1996) prompt caretakers to identify a list of potential reinforcers, or preferred items, for an individual (e.g., edibles, activities). Indirect methods of reinforcer identification (i.e., survey based preference assessment), however, often fail to identify effective reinforcers for students with severe disabilities (e.g., Parsons & Reid, 1990). In addition, the results of interviews do not always correspond with the results of direct observation based assessments of preference, though they typically increase the likelihood of finding effective reinforcers when the results are incorporated into subsequent direct observation based preference assessments (Fisher et al., 1996).

Preference assessment for typically developing students with emotional disorders often includes direct survey with the student in addition to caretaker interviews, reflecting the assumption that students without severe disabilities will accurately identify their own reinforcers (Northup, 2000). For example, the Child Reinforcement Survey (CRS; Fantuzzo, Rohrbeck, Hightower, & Work, 1991) prompts students to express preferences (e.g., "I like candy a lot") for 36 items that correspond to four stimulus classes (e.g., edibles, activities). However, two problems exist. Northup noted that preference surveys provide limited predictive accuracy. That is, children endorse items as preferred that will not actually produce change in their behavior when provided contingently (i.e., false positive endorsement), and they fail to identify items that actually would produce change in their behavior when provided contingently (i.e., false negative). This finding of lack of correspondence between verbal report and actual past or future behavior is common with children (Baer, 1990; Lloyd, 2002).

Choice-Based Stimulus Preference Assessment

Several researchers have developed preference assessment procedures that involve direct observation of choices between concurrently available stimuli as an index of preference (DeLeon & Iwata, 1996; Fisher et al., 1992; Mason, McGee, Farmer-Dougan, & Risley, 1989). These choice-based stimulus preference assessments have been studied extensively with individuals with severe disabilities with several notable findings. First, these procedures tend to be more accurate in identifying powerful reinforcers than survey methods or presenting potential items in isolation (Fisher et al., 1992; Roscoe, Iwata, & Kahng, 1999). These choice-based procedures also (a) directly expose students to stimuli or representations such as note cards, pictures, or verbal prompts and (b) require students to discriminate between the presented stimuli (Cannella, O'Reilly, & Lancioni, 2005; Hagopian, Long, & Rush, 2004; Northup, Jones, Broussard, & George, 1995), which does not occur in survey procedures. Studies suggest that choice-based procedures are an effective method of identifying reinforcers for children with limited verbal abilities, including those with profound, multiple, and developmental disabilities (e.g., Fisher, Thompson, Piazza, Crosland, & Gotjen, 1997; Graff, Gibson, & Cali-atsatos, 2006).

Experimental evaluations of the efficacy of choice-based stimulus preference assessments incorporate reinforcer assessments in which the effects of contingent stimulus presentation are observed on student behavior (Cannella et al., 2005). Research has repeatedly confirmed the predictive validity of choice-based stimulus preference assessments, as students provided with a highly preferred stimulus exhibit a higher rate of target behaviors than when provided with a less preferred stimulus. For example, Gwinn et al. (2005) found that, when presented with a choice, a student with ADHD most often selected tasks that resulted in 30 seconds of access to items identified as highly preferred. Common forms of choice-based stimulus preference assessments include the paired-stimulus and multiple stimulus with/ without replacement.

Fisher et al. (1992) initially described the paired-stimulus (PS) preference assessment, or forced-choice approach, and many researchers have used this procedure subsequently (Hagopian et al., 2004). After presenting students with all possible pairs of stimuli, educators determine preferences based on the proportion of times an item was selected from all presentations. Successfully employed with many consumer populations (e.g., students with intellectual disabilities and autism) and settings (e.g., residential settings, schools), the PS procedures appear to be less time-consuming and more highly predictive than assessment procedures that involve presentation of each stimulus in isolation (i.e., non-choice based procedures [Hagopian et al., 2004]).

The multiple-stimulus (MS) and multiple-stimulus without replacement (MSWO) assessment procedures require students to select one of many stimuli presented in an array (Hagopian et al., 2004). In the MS approach described by Windsor, Fiche, and Locke (1994), every presentation array includes every stimulus, which can lead to the student repeatedly selecting only their most preferred item. In contrast, experimenters remove the selected stimulus from subsequent trials during an MSWO procedure allowing the student to select from the remaining stimuli (DeLeon & Iwata, 1996). In both cases, practitioners establish preference rankings based on a ratio of stimulus selection to the total number of trials. Researchers developed MS/MSWO procedures for individuals with profound disabilities in residential settings (e.g., Windsor et al., 1994). Although the MSWO preference assessment produces a more delineated and accurate hierarchy of individual preferences than the MS procedure (DeLeon & Iwata, 1996), both the MS and MSWO procedures represent significantly shorter alternatives to the PS preference assessment when there are more than 8 items in the array (Cannella et al., 2005).

Despite the abundance of research on preference assessments with individuals with disabilities, several questions remain regarding the application of choice-based stimulus preference assessment for students with ED. In both the PS and MS/MSWO preference assessments, the student generally interacts with the stimulus for a brief period of time in order for the results to prove predictive of subsequent reinforcement effects (Groskreutz & Graff, 2009). It is unclear whether the stimuli would always need to be provided during the assessment when the procedures are used with students with ED who have intact language and intellectual capabilities. Researchers also have yet to reach a consensus regarding the effect of the format of stimulus presentations during preference assessments (e.g., pictures, tangible stimuli) on the results (see Groskreuiz & Graff, 2009; c.f. Higbee, Carr, & Harrison, 1999). Additionally, Kahng and colleagues (2013) suggest that the results of choice-based stimulus preference assessments remain consistent across repeated administrations but findings with individuals with substantial intellectual disabilities remain mixed (Hanley, Iwata, & Roscoe, 2006). It is unclear how the stability findings or any of the other well-documented findings with individuals with intellectual disabilities might translate when choice-based procedures are used with students with ED.

Research Questions

The substantial literature base concerning the efficacy of choice-based stimulus preference assessments in identifying reinforcers for students with severe disabilities does not directly support the use of choice-stimulus methods for students with or at-risk for ED (Northup et al., 1995). Much of the research concerning the use of choice-stimulus preference assessment for students with ED has occurred within clinical settings (e.g., Gwinn et al., 2005). Given the emphasis placed on effective behavior management and skill development M educational settings (e.g., Lannie & McCurdy, 2007), practitioners require an efficient means of identifying effective reinforcers. The current review attempts to delineate the characteristics of choice-based stimulus preference assessment used with students with ED in educational settings. The review also attempts, when possible, to compare the results of choice-stimulus preference assessment for students with ED with alternative methods of reinforcer identification. Specifically, we examined the educational settings, assessment techniques and methodology, and outcomes featured in previous studies.

Methods

A review of the literature was conducted to identify articles investigating the use of choice-based stimulus preference assessments with students without intellectual or developmental disabilities formally identified as having ED, emotional behavioral disorder (EBD), attention deficit disorder (ADD), attention deficit hyperactivity disorder (ADHD), or being at-risk for EBD. The steps in the review included (a) a search of relevant computerized databases, (b) an ancestral search, and (c) a hand search of the Journal of Applied Behavior Analysis (JABA) and Education and Treatment of Children (ETC). All possible truncations of the following phrases were entered into PsycINFO, PsycARTICLES, and ERIC computer databases: preference assessment, reinforcer assessment, reinforcer survey and emotional disorder, emotional disturbance, behavior disorder, behavior disturbance, emotional-behavioral disorder, ebd, or attention deficit disorder, attention deficit hyperactivity disorder, adhd, add, or general education. The search generated 211 peer-reviewed articles. Eligibility for inclusion in the review was determined based on the following criteria:

1. Studies must have appeared in peer-reviewed journal articles published after the introduction of choice-stimulus preference assessment in 1992 (Fisher et al., 1992).

2. Participants must have been described as within the age range of 6-17 years or identified as attending the first grade at the time of the study. Therefore, studies that focused on toddlers (e.g., Rush, Mortenson & Birch, 2010), young children (e.g., Cote, Thompson, Hanley, & McKerchar, 2007), or adults (e.g., Grace, Thompson, & Fisher, 1996) were excluded from the review.

3. Studies must have featured participants identified as having a formal diagnosis of ED, EBD, or as exhibiting behavior problem through teacher nomination (e.g., at-risk, performance deficit; see Reddy, De Thomas, Newman, & Chun, 2009; Reddy & Richardson, 2006). In addition, the review included children with ADHD or ADD as these psychological disorders (Fabiano, et al., 2009) frequently coincide with ED (Dietz & Montague, 2006). Studies in which the authors explicitly indicated that participants possessed a diagnosis of profound disabilities, multiple disabilities, or developmental disabilities including autism and mental retardation (e.g., Kenzer & Bishop, 2011; Mech.ling & Bishop, 2011) were excluded.

4. Studies must have measured the predictive validity of specific forms of stimulus-choice preference assessment (e.g., PS,MSWO) to identify reinforcers using an experimental design. Exclusion criteria included (a) the application of a preference Assessment without a reinforcement trial (e.g., Cohen-Almeida, Graff, & Ahearn, 2000; Rapp, Rojas, Colby-Dirksen, Swanson, & Marvin, 2010), (b) the use of an unidentified preference assessment (e.g., Kern, Ringdahl, Hilt, & Sterling-Turner, (2001), (c) group designs that did not disaggregate data for students identified with ED (e.g., Heering & Wilder, 2006).

5.Given the research questions, the studies had to occur in environments in which students with problem behaviors often receive education services, including public schools, private schools, residential treatment facilities, or treatment schools (US Department of Education, 2008; Whorton et al., 2000). Excluded studies included those that occurred in outpatient settings or laboratory settings (e.g., Gwinn et al., 2005; Haynes, Derby, McLaughlin, & Weber, 2002).

Of the articles identified in the search, seven met the inclusion criteria. An ancestral search of these articles and relevant literature reviews (Cannella, et al., 2005; Hagopian et al., 2004; Ivancic, 2000) yielded one additional article. A final step involved a hand search of JABA and ETC, resulting in no additional articles. Ultimately, eight studies met the search criteria (Berkowitz & Martens, 2001; Daly et al., 2009; Damon, Riley-Tillman, & Fiorello, 2008; Kuhn, Deleon, Terlonge, & Goysovich, 2006; Northup, George, Jones, Broussard, & Vollmer, 1996; Paramore & Higbee, 2005; Resetar & Noell, 2008; Schanding, Tingstrom, & Sterling-Turner, 2009). The identified studies originated from five journals, including: JABA, Journal of Developmental and Physical Disabilities, Journal of Educational and Psychological Consultation, Psychology in the Schools, and Research in Developmental Disabilities.

We summarized the studies concerning choice-stimulus preference assessment for children with ED using an adapted form of the classification system created by Cannella et al. (2005). Articles were divided into two general categories (see Table 1). Noncom parative studies (e.g., Berkowitz & Martens, 2001; Daly et al., 2009; Kuhn et al., 2006; Paramore & Higbee, 2005) reported the effectiveness of choice-stimulus preference assessment in identifying reinforcers for students with ED. Comparative studies (e.g., Damon et al., 2008; Northup et al., 1996; Resetar & Noell, 2008; Schanding et al., 2009) evaluated the performance of choice-based stimulus preference assessments in comparison to alternative assessments. Studies in which authors compared multiple stimuli identified in stimulus-based choice preference assessments (e.g., Kuhn et al., 2006) rather than different types of assessments (e.g., survey, choice-based) were not considered comparative studies in the context of this analysis.

See Table 1 for a summary and general overview of the participants, settings, and research designs featured in each of the studies, along with a description of the stimulus presentation format (e.g., pictures, tangible stimuli) used in previous assessments. Inasmuch as edibles tend to displace nonedible items when presented concurrently (e.g., Bojack & Carr, 1999; DeLeon, Iwata, & Roscoe, 1997), we coded articles based on whether the assessments featured either uniform stimuli (e.g., only food, only tangibles, note cards) or diverse stimuli (e.g., food and tangible objects in the same assessment). In addition, we indicated whether or not researchers allowed students access to each selected stimulus during the assessment (i.e., access contingent upon selection). In light of the uncertainty surrounding the stability of preference assessments, we also indicated whether researchers administered the preference assessments on an ongoing basis (a) throughout the course of the experimental reinforcer assessment or (b) following the experimental evaluation.
Table 1 Summary of Articles Concerning Choice-Stimulus Preference
Assessment for Students with or At-Risk for Emotional Disturbance

Study       Category  n   Age   Classification   Design

Berkowitz      NC     2  11-12  EBD             Concurrent
& Martens                                       operants
(2001)

Daly et        NC     4      9  EBD             Concurrent
al.                                             operants
(2009)

Damon et       C      4  6-12c  At-risk         Reversal,
al.                                             multiple
(2008)                                          baseline

Kuhii et       NC     1     10  EBD             Concurrent
al.                                             operants
(2006)

Northup et     C      4    6-9  ADHD            Alternating
al.                                             treatments
(1996)

Pa ram ore     NC     3   9-11  EBD             Alternating
& Higbee                                        treatments
(2005)

Resetar &      C      4   6-8f  At-risk         Alternating
Noell                                           treatments
(2008)

Schanding      C      4   6-12  At-risk, ADHD   Alternating
et al.                                          treatments
(2009)

Study       Choice Format     Stimuli  Access  Ongoing   Findings
                                                Admin.

Berkowitz   Verbal MS            U        N        N     Negativea
& Martens
(2001)

Daly et     Pictorial MSWO       U        N        N     Posit
al.                                                      iveb
(2009)

Damon et    Teacher survey,      D        Y        N     Positived
al.         pictorial PS
(2008)

Kuhii et    Verbal/tangible      D/U      Y/N      N     Positivee
al.         PS
(2006)

Northup et  Student survey,      U        N        Y     Positived
al.         Verbal/pictorial
(1996)      PS

Pa ram ore  Tangible MSWO        U        Y        N     Positiveb
& Higbee
(2005)

Resetar &   Teacher survey,      D        N        N     Mixedg
Noell       Tangible MSWO
(2008)

Schanding   Teacher/student      U        N        Y     Mixedg
et al.      survey, Verbal
(2009)      PS

Note. MS = multiple-stimulus with replacement; EBD =emotional
behavioral disorder; MSWO = multiple-stimulus without
replacement; PS - paired-stimulus; ADHD = attention
deficit hyperactivity disorder; NC = noncomparative;
C = comparative; U - uniform; D - diverse. (a) Findings
indicated that choice-stimulus preference assessment did
not identify effective reinforcers. b Findings indicated that
choice-stimulus preference assessment identified effective
reinforcers. (c) Age of participants is approximate; study
involved students in grades 1-5. (b) Findings indicated that
choice-stimulus preference assessment identified effective
reinforcers more accurately than a survey or other testimonial
method. ' Findings in?dicated that a tangible and verbal choice
stimulus-preference assessment identified reinforcers; however,
tangible preference assessment yielded more accurate results.(f)
Age of participants is approximate; study involved students in
grades 1-2. (g) Findings indicated that choice-stimulus assess ment
identified effective reinforcers; however, results were not more
accurate than those of a survey or other testimonial method.


Table 1 also provides a classification of the reported outcomes. Positive findings refer to (a) noncomparative studies that reported choice-based stimulus preference assessments identified effective reinforcers or (b) comparative studies in which the reinforcers identified by choice-based stimulus preference assessment evoked higher levels of the target response than reinforcers identified through an alternate method (e.g., survey). Mixed findings referred to the outcomes of comparative studies in which the reinforcers identified by choice-based stimulus preference assessments, though they increased the target behavior, did not appear to be more effective than rein forcers identified through alternate assessments. Studies with negative findings were noncomparative studies in which the choice-stimulus preference assessment failed to identify an effective reinforcer.

Results

The eight reviewed studies describe (a) the administration settings and participants who received a choice-stimulus preference assessment, (b) the preference assessments employed by the researchers, and (c) the outcomes related to the use of direct preference assessments among students with problem behaviors (see Table 1). The studies featured single-subject designs in which the researchers identified the preferences of participating students using either choice-stimulus preference assessment or a combination of choice-stimulus preference assessment and preference surveys. Researchers in the identified articles then evaluated the effect of a preferred stimulus on the students' target behaviors (i.e., time on task).

Participants and Settings

All studies evaluated the efficacy of choice-stimulus preference assessment among young children (6-12) using no more than four participants. Two studies (Kuhn et al., 2006; Northup et al., 1996) involved children with ED in restrictive educational settings. Northup et al. (1996) conducted the first study of choice-stimulus preference assessment that featured children with ADHD outside of a purely clinical setting. In a similar study, Kuhn et al. (2006) examined the effectiveness of preference assessments for a student with severe EBD (self-injurious behavior) in a residential facility. Studies conducted in general education settings involved children with documented EBD (Berkowitz & Martens, 2001; Daly et al., 2009; Paramore & Higbee, 2005) or at-risk students (Damon et al., 2008; Resetar & Noell, 2008; Schanding et al., 2009) exhibiting relatively mild noncompliant behaviors (e.g., failure to complete work, inattentiveness, itinerancy).

Preference Assessment Implementation

Choice-based stimulus preference assessment requires the direct comparison of potential reinforcers (Vollmer & Iwata, 1992) with selection as the measure of relative preference. As a result, the time required for administration increases with the addition of each stimulus. Practical use of the choice-stimulus assessment typically requires the administrator to eliminate various stimuli from consideration prior to the assessment (Higbee, 2009). In each of the studies, implementation of the choice-stimulus preference assessment involved two separate phases: pre-assessment, in which the researchers narrowed the range of potential stimuli through indirect questions regarding preference (e.g., parent interview) or surveys and the choice-stimulus assessment, where the researchers presented the student with stimuli in accordance with an established assessment format (e.g., PS, MSWO).

Pre-assessment. In noncomparative studies, the range of stimuli featured in the choice-stimulus preference assessment was restricted to items considered appropriate for a school context (Berkowitz & Martens, 2001; Daly et al., 2009) or through pre-assessment interviews (Kuhn et al., 2006; Paramore & Higbee, 2005). As in earlier research involving nonverbal students, Kuhn et al. (2006) solicited possible preferences from the caretakers of the students using the RAISD (Fisher et al., 1996), which is a structured interview covering a range of stimulus classes (e.g., activities, tangibles). In light of the verbal skills of the participants, Paramore and Higbee (2005) identified edible preferences through a less formal interview process that included responses from participating students and caretakers.

Comparative studies featured surveys that identified an initial set of preferred stimuli and evaluated the accuracy of the preference hierarchies created by choice-stimulus preference assessments. Resetar and Noe11 (2008) required teachers to assign ranks based on perceptions of student preferences to 20 edible and tangible stimuli using an informal survey. The remaining comparative studies (Damon et al., 2008; Northup et al., 1996; Schanding et al., 2009) featured variations of the Child Reinforcement Survey (CRS; Fantuzzo et al., 1991), a standard preference survey. As originally designed, the CRS identifies preferred and nonpreferred stimuli without establishing a hierarchy of the respondent's preferences. Respondents rate (e.g., respondent likes item a lot, somewhat, not at all) stimuli that commonly appear in schools (e.g., chocolate). Each stimulus corresponds to a general stimulus category (e.g., edibles, tangibles). Northup and colleagues (1996) modified the CRS by assigning an ordinal rank to each rating and converting the sum of the ranks for each category into a percentage score. The scoring method identified several categories as highly preferred, producing an indistinct hierarchy of preferences in which no single stimulus category emerged as the optimal preference. Schanding et al. (2009) created a more definitive preference hierarchy by requiring teachers and students to rank their top choices using the Ranked Reinforcer Survey (RRS), a modified form of the CRS. Damon et al. (2008) compared a ranked list of teacher-nominated preferences from a single stimulus category (i.e., activities) to the results of a PS preference assessment. The wider range of stimuli presented in the PS assessment was initially identified using a CRS.

CI The results of the comparative and noncomparative studies suggest that choice-based stimulus preference assessment procedures successfully identify reinforcers when coupled with interview, checklist, and survey pre-assessments. Although the influence of various pre-assessments on the efficacy of choice-stimulus assessment has yet to be experimentally evaluated for students with ED, the current literature provides some insight into factors that enhance or lessen the effectiveness of choice-stimulus preference assessment. Studies in which teachers preselected stimuli did not result in better results with choice-based stimulus preference assessments than survey methods (Berkowitz & Martens, 2001; Resetar & Noe11, 2008, respectively). Likewise, Schanding et al. (2009) found that requiring the students to rank responses via the RRS eliminated advantages associated with choice-stimulus preference assessment (see below for more information regarding study outcomes).

Choice-based stimulus preference assessment. Each of the studies featured variations of PS and MS/MSWO preference assessment (Cannella et al., 2005; Hagopian et at, 2004). Studies that included the PS procedure offered students a chance to select stimuli based on verbal (Kuhn et at, 2006; Northup et al., 1996), tangible (Kuhn et al., 2006), pictorial (Damon et al., 2008; Northup et al., 1996), or written (Schand-ing et at, 2009) item presentation. Students received access to selected reinforcers during the preference assessment sessions in two of the studies (Damon et al., 2008; Kuhn et al., 2006). The authors presented uniform stimuli (i.e., either verbal or pictorial prompts) in three of the four studies involving PS preference assessment (see Table 1).

Studies conducted by Northup et al. (1996) and Kuhn et al. (2006) directly addressed the potential influence of the format of stimulus-choice preference assessment on student responses. Northup and colleagues (1996) administered a verbal and a pictorial choice-stimulus preference assessment. The verbal PS procedure created by Northup et al. (1996) assessed preference for classes of stimuli (e.g., edibles, attention) derived from the CRS rather than for specific stimuli and consequently required three minutes to administer. The pictorial assessment, which required approximately 5 min to administer, prompted students to select tokens associated with a class of reinforcers. In addition to conducting a verbal choice-stimulus preference assessment, Kuhn et all. (2006) presented participants with individual stimuli (e.g., comic book, tickling) due to concerns regarding the potential of preferences for specific stimuli within a class to skew the perception of an entire class.

Researchers using tangible, pictorial, and written PS procedures employed similar methods as Fisher et al. (1992) with notable differences, including the use of concurrent verbal prompts. Damon et al. (2008) presented subjects with pictures designed to depict individual stimuli. Although the authors did not report the duration of the assessment administration, they described the process as "time and labor intensive" (p. 51). The pictorial assessment employed by Northup et al. (1996), which presented students with coupons representing classes of stimuli, required approximately five minutes to administer. Similarly, the written assessment used by Schanding et al. (2009) did not exceed five minutes.

Researchers who administered the MS/MSWO assessments allowed children to make selections from an array of tangible objects (Paramore & Higbee, 2005; Resetar & Noe11, 2008) or written prompts representing tangible stimuli and activities (Daly et al., 2009, Berkowitz & Martens, 2001). The MSWO assessments, though similar to work initially conducted by Deleon and Iwata (1996), featured a smaller number of assessment sessions (i.e., decreased from five to three array presentations) and a smaller number of items in the array to increase the efficiency of the assessment (see Carr, Nicolson, & Higbee, 2000). Leaving aside Paramore and Higbee (2005), studies featuring the MS/MSWO assessment did not allow students access to selected stimuli. The majority of studies presented students with a uniform array of verbal or pictorial stimuli. However, Resetar and Noe11 (2008) included edibles and nonedible objects in the stimulus array. Neither Daly et al. (2009) nor Resetar and Noe11 (2008) reported the length of each session. Paramore and Higbee (2005) reported their MSWO procedure required 10 minutes of administration time. The MS procedure performed by Berkowitz and Martens (2001) differed from previous procedures (e.g., Windsor et al., 1994) in several respects. Rather than requiring participants to select items from an array, students in one 20 minute assessment session arranged note cards featuring 10 potential reinforcers in order of preference. In addition, the researchers permitted students to select the academic assignments (i.e., reading, math, or arithmetic) required to attain the stimuli.

Given the variation in procedures, the current literature provides little insight into the role of choice format, access to stimuli, or the use of uniform stimuli in outcomes of choice-stimulus preference assessment for students with ED. However, all studies involving PS preference assessment found that choice-based stimulus preference assessments identified effective reinforcers. Of the studies that featured multiple stimulus methods (i.e., MS or MSWO), only Berkowitz and Martens (2001) found that choice-stimulus preference assessment did not identify effective reinforcers. Studies with negative or mixed findings (Berkowitz & Martens, 2001; Resetar & Noe11, 2008; Schand-ing et al., 2009) featured verbal stimuli and did not allow students to access stimuli during the assessment. However, studies with positive findings using similar methodology found that choice-based stimulus preference assessments identified effective reinforcers (Kuhn et al., 2006) or identified reinforcers more effectively than survey/self-report methods (Northup et at, 1996).

Outcomes of Noncom parative Studies

Choice-based stimulus preference assessments identified functional reinforcers capable of increasing student task performance in the majority of noncomparative studies (Daly et al., 2009; Kuhn et al., 2006; Paramore & Higbee, 2005). Paramore and Higbee (2005) found that stimuli identified as preferred resulted in an increase of on-task behavior over a large number of treatment sessions (n>20). Initially the response level and trend increased sharply in comparison to baseline regardless of the preference rank of the reinforcer. However, a greater differentiation in response emerged over time, with the high-preference items producing the highest percentage of intervals on task. Kuhn et al. (2006) observed that the participant exhibited a higher rate of worksheet completion when receiving a stimulus identified using a tangible PS assessment relative to when receiving a stimulus identified via the verbal PS. Due to the nature of the concurrent operants design, it remains unclear if all stimuli identified by the verbal PS functioned as a reinforcer. The concurrent presentation of stimuli potentially permits students to exclusively select a highly preferred stimulus over alternatives that, in the absence of the highly preferred stimulus, would also evoke high levels of responding (i.e., function as a reinforcer; Higbee, 2009; Roscoe et al., 1999). Daly et al. (2009) observed similar findings, though the students received a potentially confounding form of reinforcement (e.g., escape from class) upon satisfying the criteria necessary to receive the proffered reinforcement (i.e., completion of math problems).

In contrast, Berkowitz and Martens (2001) identified a small average Spearman rank order correlation (.33) between the results of the MS assessment and a reinforcement assessment providing limited support for choice-based stimulus preference assessment. Furthermore, students proved less responsive to highly preferred stimuli as the demands of the task (i.e., number of required math problems) increased (Berkowitz & Martens, 2001). Although results presented by the authors may undermine the supposed predictive ability of choice-stimulus assessment, multiple factors (i.e., unusual preference assessment, lack of baseline, limited number of trials, etc.) should lead us to interpret the findings with caution.

Outcomes of Comparative Studies

Based on the increases observed in student responses, choice-based stimulus preference assessments identified functional reinforcers in each of the comparative studies. Nonetheless, studies that compared reinforcers identified by teachers to choice-stimulus preference assessment (Damon et al., 2008; Resetar & Noell, 2008) yielded mixed results. Damon et al. (2008) found that reinforcers selected through PS assessment produced the highest levels of responding in math-fact completion and on-task behavior (e.g., engagement with instructor or materials) in the classroom. Resetar and Noell (2008) observed that the number of math problems completed by students under reinforcement conditions surpassed average problem completion during baseline (13.25) and performance under a no reward condition (13), suggesting that the preference assessments identified functional reinforcers. However, the students exhibited similar rates of responding under both reinforcement conditions. That is, the reinforcer assessment revealed minimal average differences between the number of items students completed when students received reinforcers identified by MSWO assessment (24.15) and the teacher survey (21.22), suggesting that both procedures identified equally effective reinforcers for this context.

Additional studies (Northup et al., 1996; Schanding et al., 2009) revealed limited differences in the predictive accuracy of choice-stimulus preference assessments and surveys completed by students. Nor-thup et al. (1996) found that both the CRS and choice-stimulus preference assessments identified the reinforcer associated with the highest rates of responding on a contrived digit coding task (e.g., matching letters with numbers) for the majority of participants. However, the CRS also identified several items as highly preferred that failed to increase the response rate of participants. Identification accuracy associated with pictorial PS assessment (80%) and verbal PS assessment (70%) exceeded the accuracy of the CRS (55%). Although reinforcers identified by the PS preference assessment resulted in a slightly higher response on a digit coding task for three of the four participants, Schanding et al. (2009) reported similar increases in the frequency of task completion in response to reinforcers identified by the RRS.

In contrast to the noncomparative studies, in which the authors did not report data concerning the stability of the choice-stimulus preference assessment, two of the comparative studies conducted preference assessments over time (Northup et al., 1996; Schanding et al., 2009). Northup and colleagues' (1996) second administration of the preference assessments following the reinforcer assessment found the reliability of the pictorial PS assessment (80%) to be greater than either the verbal PS assessment (60%) or the CRS (65%). Schanding and colleagues conducted the MSWO procedure throughout the reinforcer assessment but did not report data concerning the reliability of the results.

Discussion

The current review evaluated the research on the use of choice-based stimulus preference assessments for students with or at-risk for ED in educational settings. Specific questions addressed (a) the instructional context, (b) implementation, and (c) efficacy of researcher administered choice-stimulus preference assessments for students with ED. Although some studies featured specialized and restrictive facilities, much of the research occurred in general education settings. Nonetheless, many of the studies assessed the effectiveness of the identified reinforcers by observing student performance on nonacademic tasks (e.g., digit coding) in isolated areas within the school (e.g., empty resource rooms) rather than in their natural ongoing instructional environments (e.g., inclusive classrooms). Study outcomes suggest that choice-based stimulus preference assessment identified stimuli that increased student task performance. However, differences in the predictive value among choice-based stimulus preference assessments and surveys remain unclear.

Participants and Setting

The settings featured in the studies depict the full range of locations in which young students with ED (ages 6-42) receive education services. Although Damon et al. (2008) suggested that reinforcement assessments conducted in contrived and classroom settings yield similar results, the majority of the studies (Berkowiiz & Martens, 2001; Daly et al., 2009; Kuhn et al., 2006; Northup et al., 1996; Resetar & Noell, 2008; Schanding et al., 2009) administered experimental procedures outside of the students' typical classroom (e.g., empty classroom, isolated treatment room). Given the role of classroom stimuli in maintaining inappropriate behavior, settings removed from the classroom may not represent the ideal milieu for establishing the effectiveness of reinforcers. Alberto and Troutman (2009) noted that stimuli administered in contrived settings have a different effect on student behaviors than stimuli administered in the classroom. Furthermore, the presence of experimenters and trained researchers, rather than classroom teachers, may have served as a confounding reinforcer of student behavior (Resetar & Noe11, 2008).

Implementation

Several studies implemented choice-stimulus preference assessment using methods established among other populations (e.g., Cannella et al., 2005; Hagopian et al., 2004), with exceptions related to the characteristics of students with ED and general education settings. Past research evaluating preference assessments with students with severe disabilities typically gathered information from caregivers and presented students with tangible stimuli (e.g., Piazza, Fisher, Hagopian, Bowman, & Toole, 1996). Although researchers continued to use teacher input and tangible stimuli during choice stimulus preference assessments (e.g., Kuhn et al., 2006), the verbal skills of students with ED enabled researchers to augment caretaker information with student input and present verbal (e.g., questions, note cards) representations of stimuli (e.g., Northup et al., 1996).

Previous studies concerning students with severe disabilities in residential settings offered participants a wide range of stimuli (e.g., Pace et al., 1985). A change from clinical to educational settings required researchers to limit the options available to students as a response to the requests of teachers. Several studies (Berkowii2 & Martens, 2001; Daly et al., 2009) included items in the assessment based on the established preferences of the teachers. Thus, researchers excluded stimuli (e.g., escape, edibles) from consideration based on objections from teachers (Berkowitz & Martens, 2001). The limitations placed on the stimuli presented in the choice-stimulus preference assessment potentially precluded highly preferred items from subsequent reinforcer assessments, possibly explaining the lack of response differentiation observed in some studies (e.g. Resetar & Noe11, 2008).

Many of the unresolved questions regarding choice-based stimulus preference assessment for students with profound disabilities continue to linger over the use of the procedures for students with ED. The use of pictorial or verbal stimuli in the majority of studies (see Table 1) appears to perpetuate the view that higher-functioning children do not require direct access to tangible stimuli in order to provide an accurate reflection of their preferences. Studies that directly addressed this issue (e.g., Kuhn et al., 2006, Northup et al., 1996) were not conclusive and the majority of studies conducted separate uniform array presentations, presumably based on the displacement effect findings observed with individuals with autism and intellectual disabilities. Access to selected stimuli was not provided in seven of the studies, with the majority (n = 6) indicating that students with ED do not require access to stimuli in order to identify reinforcers through choice-based stimulus preference assessment. Northup et al. (1996) further suggest that choice-based preference assessments in which students do not receive access to stimuli may be a preferable alternative to preference surveys. However, comparative studies in which students did not receive access to stimuli (Resetar & Noell, 2008; Schanding et al., 2009) did not find differences in the ability of choice-stimulus or survey-based assessments to identify reinforcers. Although the importance of access remains unsettled, choice-based stimulus assessments that present students with stimuli may produce different, potentially more accurate results than survey methods.

Outcomes

In general, the research suggests that choice-stimulus preference assessment successfully identifies reinforcers for students with or at-risk for ED (see Table 1). Educators often use reinforcement strategies to encourage students with ED to complete daunting or otherwise unappealing academic assignments (Alberto & Troutman, 2009). The negative relationship between reinforcer effectiveness and response effort (i.e., task difficulty) observed in research concerning reinforcement (e.g., Neef, Shade, & Miller, 1994) suggests that students may require high-quality reinforcement in order to complete challenging assignments. Nonetheless, the majority of the reviewed studies (Berkowitz & Martens, 2001; Daly et al., 2009; Kuhn et al., 2006, North-up et al., 1996; Resetar & Noe11, 2008; Schanding et at, 2009) appraised the predictive validity of the preference assessments using contrived activities (e.g., basal math problems, digit coding) unrelated to the needs of the participants. Studies assessing the efficacy of reinforcers through the use of facile tasks may provide limited insight into the capacity of choice-based stimulus preference assessments to identify useful stimuli for educational settings.

It remains unclear whether choice-based stimulus preference assessments offer a clear advantage over surveys with students with ED. Some comparative studies supported the additional predictive utility of choice-based stimulus preference studies over surveys (Damon et al, 2008; Northup et al., 1996) while others found that the choice-based procedure added little to the findings of a survey (Resetar & Noe11, 2008; Schanding et al., 2009). In all instances, the choice-based procedures were at least as effective, if not more effective, than a survey. Although Northup et al. (1996) suggests that the findings of choice-based stimulus preference assessments appear to be more consistent than those of preference surveys, the published studies do not permit definitive conclusions regarding stability, as no extended assessment studies have been done with students with ED to date.

The surveys featured in the studies potentially influenced the results. Northup and colleagues' (1996) findings, though supportive of choice-stimulus preference assessment, may have resulted from a comparison of dissimilar procedures. Unlike choice-based procedures, the CRS does not establish a hierarchy of preferences. Two studies in which preference surveys required respondents to assign ranks to stimuli (Resetar & Noell, 2008; Schanding et al., 2009) did not find reinforcers identified through choice-based stimulus preference assessment more effective than the survey-based ranks. Although Damon et al. (2008) suggest that reinforcers identified through choice-based stimulus preference assessments yielded higher rates of student responding compared to teacher rankings, the procedures permitted students to identify preferences from a much larger range of stimuli than the teachers ranked. The limitations on the nominations of the teachers may have eliminated alternate categories (e.g., edibles) that could have produced higher rates of responding. The results may also indicate that student input improves the identification of reinforcers regardless of how researchers obtain the information.

Implications for Practice

The current studies hold some value for practitioners. Choice-based stimulus preference assessment successfully identifies reinforcers, which may prove useful to teachers who wish to provide rewards but remain largely unaware of their students' preferences (Fantuzzo et al., 1991). As preferences vary among individual students, educators can conduct a form of assessment to increase the efficacy of reinforcement strategies (Alberto & Troutman, 2009). Findings also demonstrate that response to reinforcement varies based on the level of student preference, underscoring the additional value of ranking, rather than merely identifying, preferences.

Nonetheless, the available literature provides only partial insight into the practical application of choice-based stimulus preference assessment. These studies suggest that choice-based stimulus-preference assessments may be administered quickly and in a manner similar to the individualized assessments commonly used in special education (e.g., Floyd, Phaneuf, & Wilcznski, 2005). Regardless, the research provides little information concerning the skills required to administer choice-stimulus preference assessments. The experimenters in Damon et al. (2008) received consultation training through a psychology program and claimed at least 10 years of classroom experience. Although the remaining studies provided limited information regarding the training or experience received by administrators of the assessments, numerous studies (e.g., Lavie & Sturmey, 2002; Roscoe & Fisher, 2008) suggest that the training requirements for choice-stimulus preference assessment may be minimal. Certain preference surveys (e.g., CRS) may provide educators with an equally effective form of reinforcer identification that presents fewer challenges in terms of time or resources. Should survey methods fail to identify effective reinforcers, however, choice-based assessments may provide practitioners with an easily acquired, supplementary means to improve reinforcement-based treatment (Damon et al., 2008; Volz & Cook, 2009).

Accurate identification of specific reinforcers may be more important when teaching students with severe disabilities or students that require immediate access to reinforcement. However, students with ED are more likely to have behavior intervention plans that include components such as consequence choice (e.g., Carr & Carlson, 1993) or token economies with a menu of available reinforcers (e.g., LePage et al., 2003), which may render the specific results from choice-based stimulus preference assessment less necessary (Cooper, Heron, & Heward, 2007). Educators may find it prudent to initially attempt to identify student preferences using the quicker and easier survey procedures and incorporate choice-based preference assessments only when the results of the survey are not proving useful or when resources prohibit providing a wide range of back-up reinforcers in a token economy (e.g., Montarello & Martens, 2005; Sran & Borrero, 2010).

Directions for Future Research

Researchers should continue to compare choice-stimulus preference assessment to preference surveys. The literature has yet to conclusively demonstrate the advantages of choice-based procedures over preference surveys. However, the majority of comparative studies featured formal preference surveys (i.e., CRS) that may not be available for use in all settings. Additional research should compare the results of choice-stimulus preference assessment to simpler alternatives, such as ranked student interviews, that practitioners may be more likely to employ. Additional examination of the relative stability of preferences identified through choice-stimulus assessments and surveys would extend the work of Northup et al. (1996) and potentially contribute to the literature on reinforcers for students with ED. Additional research with older adolescents with ED could also be useful. This population often has more significant and dangerous problem behavior and is more likely to have a variety of comorbid conditions (e.g., anxiety, depression) which might impact the accuracy of preference assessment procedures (Kauffman & Landrum, 2009; Reddy & Richardson, 2006).

At least some participants in each study identified different top preferred items through the survey and choice-based assessments; however, some children might identify the same reinforcers regardless of the assessment method. The current literature does not provide an explanation for the lack of correspondence observed in the comparative studies. However, the outcomes of the studies suggest that providing students with access to items selected during the assessment may improve outcomes of the assessment, possibly as a result of altered motivating operations or displacement (Vollmer & Iwata, 1992). Future studies should consider the extent to which the procedural factors create the lack of correspondence between choice-based stimulus preference assessments and surveys.

The literature currently emphasizes the completion of contrived tasks as a means of evaluating the effectiveness of reinforcers. Those who work with students with ED, however, identify and use reinforcers to encourage student engagement in a range of nonpreferred, challenging tasks with the potential to improve learning outcomes. Future comparative studies may determine if highly preferred stimuli can sustain higher rates of responding from students required to complete authentic academic activities in contexts where alternative social reinforcers are often available for inappropriate behavior. This type of study would provide valuable information about the broader contextual variables that are often in play in ED educational settings. Similarly, research should attempt to demonstrate that reinforcers identified through choice-stimulus preference assessment compete successfully with the classroom stimuli that frequently maintain inappropriate behavior.

It is ultimately unclear if choice-based stimulus preference assessments improve the identification of reinforcers for children with ED over preference survey assessments. However, choice-based assessments certainly appear to represent an effective method of identifying reinforcers for a variety of students with ED. Further research may determine if choice-based stimulus preference assessments constitute a necessary component of reinforcement procedures applied in educational settings that serve students with ED.

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Seth A. King

Vanderbilt University

Douglas E. Kostewicz

University of Pittsburgh

Address correspondence to Douglas Kostewicz, Department of Instruction & Learning, University of Pittsburgh, 5146 Posvar Hall, 230 S. Bouquet St., Pittsburgh, PA 15260, (o) 412.648.7113 (f) 412.648.3131; e-mail: dekostapitt.edu
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