JOURNAL OF APPLIED BEHAVIOR ANALYSIS
2015, 48, 221–226
NUMBER
1 (SPRING)
INCREASING THE EFFICIENCY OF PAIRED-STIMULUS PREFERENCE ASSESSMENTS BY IDENTIFYING CATEGORIES OF PREFERENCE FRANCIS J. CICCONE, RICHARD B. GRAFF,
AND
WILLIAM H. AHEARN
NEW ENGLAND CENTER FOR CHILDREN AND NORTHEASTERN UNIVERSITY
A paired-stimulus preference assessment was conducted for 6 individuals with developmental disabilities. We selected stimuli that were representatives of 4 categories: chocolate, salty and crunchy, gummy, and fruit and vegetable. For all 6 participants, at least 3 of the 5 most preferred items came from the same category. On subsequent reinforcer assessments, items from the highest ranked preference category, some of which were included in the preference assessments and some of which were not, functioned as reinforcers. These findings suggest that after categories of preferred items are identified, clinicians may be able to identify reinforcers for some individuals without conducting additional assessments. Key words: autism, preference, reinforcer, developmental disabilities
The identification and effective use of reinforcers are crucial to increase skill acquisition and reduce problem behavior for individuals who have been diagnosed with developmental disabilities (e.g., Fisher et al., 1992; Karsten & Carr, 2009). In applied settings, high-preference items that have been specifically identified through a preference assessment may be unavailable for a period of time (e.g., because of depleted supplies); however, the need for an effective reinforcer remains. If categories of preferred items could be identified with minimal additional effort, it may provide clinicians with a mechanism to identify an alternative reinforcer without the need for additional preference assessments when a specific high-preference item is no longer available. Few studies have analyzed preferences for categories of stimuli. DeLeon, Iwata, and Roscoe (1997) conducted preference assessments using two categories of items: edible items and leisure items. When edible and leisure items were both used in the assessments, the most preferred item Richard B. Graff and William H. Ahearn are now associated with Western New England University, Springfield, Massachusetts. Address correspondence to Francis J. Ciccone, New England Center for Children, 33 Turnpike Rd., Southborough, Massachusetts 01772 (e-mail: fciccone@necc. org). doi: 10.1002/jaba.190
was an edible item for 12 of 14 participants; for 11 participants, the top two preferred items were edible items, and for nine participants, the top three preferred items were edible items. Bojak and Carr (1999) found that when leisure and edible items were combined on an eight-item preference assessment, for all participants, edible items ranked first through fourth, and leisure items ranked fifth through eighth. Although edible items may displace preference for leisure items for some individuals, to date no research has systematically evaluated preference for and reinforcer efficacy of various categories of edible items. The purpose of our study was to evaluate whether a researcher could identify a stimulus that would function as a reinforcer based on a previously identified high-preference category without conducting additional preference assessments. Although the multiple-stimulus-without-replacement assessment (MSWO; DeLeon & Iwata, 1996) and the free-operant (FO; Roane, Vollmer, Ringdahl, & Marcus, 1998) preference assessment have been demonstrated to be efficient methods to identify reinforcers, there are disadvantages to both which precluded their use for this study. Fewer stimuli can be simultaneously assessed on the tabletop with the MSWO compared to the paired-stimulus (PS; DeLeon, Graff, FrankCrawford, Rooker, & Bullock, 2014) preference
221
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assessment, and the FO assessment may not yield a distinct preference hierarchy. Given that we assessed preferences for 16 stimuli and required a distinct preference hierarchy, the PS assessment was used. METHOD Participants, Settings, and Materials Six boys between the ages of 14 and 19 years, who had been diagnosed with autism spectrum disorder, participated. All participants attended a residential school for individuals with autism and developmental disabilities. An independent clinician and the residential school made all diagnoses. PS preference assessments (Fisher et al., 1992) and reinforcer assessments were conducted with edible items in the students’ classrooms. Items were grouped into categories according to flavor and texture as follows: chocolate (M&Ms, chocolate bars, white chocolate bars, Kit Kats), salty and crunchy (peanuts, potato chips, Doritos, pretzels), gummy (Gummy Bears, Starburst, Twizzlers, Swedish Fish), and fruit and vegetable (celery, carrots, apples, and grapes). Response Measurement and Interobserver Agreement During preference assessments, approach responses (defined as making physical contact with one of the edible items) were recorded. Preference hierarchies were established based on the percentage of approach responses to each stimulus. In addition to determining the relative preference for individual stimuli, preferences for categories of edible items was determined by adding the mean percentage of approach responses for all four members of each category and dividing by four. Category preference hierarchies were established based on mean category scores. During the preference assessments, a second observer independently recorded data on approach and integrity in a mean of 43% of trials
across participants and assessments (range, 37% to 50%). An agreement was scored if both observers recorded the same stimulus approached on a trial. A disagreement was scored if the observers recorded different stimuli being approached on a trial. Interobserver agreement was calculated on a trial-by-trial basis by dividing the number of agreements by the number of agreements plus disagreements and converting the result to a percentage. Integrity data were recorded on whether the correct stimuli were presented on a trial and whether the positions of the stimuli were correct. Mean agreement and integrity were 99% (range, 97% to 100%) and 99.7% (range, 98% to 100%), respectively. The dependent variable in the reinforcer assessment was the number of pieces of silverware sorted, defined as picking up a piece of silverware and placing it in a corresponding sorting bin. During each 5-min session, observers recorded the amount of silverware sorted. A second observer was present and independently recorded agreement and integrity data in a mean of 42% of reinforcer assessment sessions across participants and assessments (range, 39% to 47%). Interobserver agreement was calculated by dividing the smaller number of items sorted by the larger number and converting the result to a percentage. Integrity data were taken on whether or not sample stimuli were placed in the correct bins before each trial and if the bins were placed in the correct positions. Mean agreement and integrity were 99.6% and 100%, respectively. Preference Assessments PS preference assessments based on the procedures described by Fisher et al. (1992) were used to establish preference hierarchies for each individual. Each PS assessment consisted of 120 trials. On each trial, two items were placed on the table approximately 0.2 m apart and 0.3 m in front of the participant. The experimenter verbally cued the participant by saying “choose one.” A stimulus selection was recorded if the participant approached a stimulus.
CATEGORY PREFERENCE Although consumption was not part of the criteria, across participants, the majority of edible items were consumed. If the participant did not approach either item within 5 s, the stimuli were removed briefly and the trial was represented. If the participant did not approach either item on the repeated trial, the stimuli were removed, no response was recorded, and the next trial was presented. Attempts to approach both stimuli were blocked. Reinforcer Assessments After the preference assessments, reinforcer assessments were conducted using concurrentoperants procedures similar to those described by Piazza et al. (1999). Based on participants’ vocational learning objectives, silverware sorting was chosen as the assessment task. Reinforcer effects were evaluated using a multielement design embedded within a reversal; all sessions lasted 5 min. During all sessions, two sets of silverware, identical with the exception of color (red and white), were present. Each participant started each session with a set of mixed silverware (red and white forks, spoons, and knives) in front of him on the table. In addition, six sorting bins were placed on the table directly behind the silverware. The positions of the bins varied across sessions. Each of the sorting bins contained two sample stimuli. The task was to sort the silverware into the appropriate bins by matching to the sample. Placing one piece of silverware into its corresponding bin was considered a sorting response. Baseline. During baseline sessions, the materials were placed in front of the participant, and the participant was told that he could sort the silverware but that there were no arranged consequences for responding. Concurrent operants, tested stimuli. Before the start of each session, the experimenters randomly selected one edible item from the high-preference category and one from the low-preference category. The items were then randomly assigned to the colored silverware (red and white). The
223
category and color association varied across sessions, with the stipulation that an edible item could not be associated with the same color for more than two consecutive sessions. During each session, the item from the highpreference category was visible near a set of unsorted silverware and the item from the lowpreference category was visible near a second set of unsorted silverware. The participant could respond to either set of silverware. Experimenters delivered a small piece of the edible item on a fixed-ratio (FR) 1 schedule for responding at the start of the first session. For some participants, the reinforcement schedule was thinned during this session. The schedule in place at the end of the first session was used for all subsequent sessions. Across participants, schedules ranged from an FR 1 to a variable-ratio 12. Errors (e.g., placing white silverware in bins designated for red silverware) were blocked. Concurrent operants, untested stimuli. Procedures in this phase were identical to those described in the previous phase except that the edible items used were not items that had been evaluated in the preference assessment. Rather, the researchers identified one presumed highpreference and one presumed low-preference item based on the highest and the lowest ranked categories for each participant. For example, if a participant’s highest ranked category on the preference assessment was chocolate, the researcher identified a novel chocolate item to present contingent on sorting. The same procedure was used for the participant’s lowest ranked category. For each participant, this phase was conducted twice, and a different set of untested stimuli was assessed in each phase. RESULTS AND DISCUSSION Table 1 summarizes the results of each participant’s preference assessment. Across participants, items from within each category tended to group together in the preference hierarchies. This can most clearly be seen in
224
FRANCIS J. CICCONE et al. Table 1 Individual and Category Preference Assessment Rankings Participant
Rank
Mike
Individual item 1 Pretzel 2 Chips 3 Doritos 4 Peanuts 5 Kit Kat 6 Chocolate bar 7 White chocolate 8 M&M 9 Apple 10 Grape 11 Starburst 12 Carrot 13 Twizzler 14 Celery 15 Swedish Fish 16 Gummy Bear Category 1 Salty and crunchy 2 Chocolate 3 Fruit and vegetable 4 Gummy
Sam
Andy
Nick
Louis
Simon
Chocolate bar Kit Kat M&M Pretzel White chocolate Swedish Fish Grape Starburst Peanut Gummy Bear Doritos Apple Chips Celery Carrots Twizzler
White chocolate Pretzel Chocolate bar M&M Swedish Fish Kit Kat Grape Peanut Carrots Doritos Starburst Gummy Bear Apple Twizzler Chips Celery
Pretzel White chocolate M&M Chocolate bar Kit Kat Doritos Peanuts Swedish Fish Starburst Chips Gummy Bear Twizzler Celery Carrots Apple Grape
Chocolate bar Swedish Fish M&M Twizzler Gummy Bear Kit Kat Starburst Pretzel Peanut Grape Chips Doritos Apple Celery Carrots White chocolate
White chocolate Starburst Pretzel Choc Bar Kit Kat Doritos Chips Peanut M&M Swedish Fish Gummy Bear Twizzler Celery Apple Carrots Grape
Chocolate Salty and crunchy Gummy Fruit and vegetable
Chocolate Fruit and vegetable Salty and crunchy Gummy
Chocolate Salty and crunchy Gummy Fruit and vegetable
Gummy Chocolate Salty and crunchy Fruit and vegetable
Chocolate Salty and crunchy Gummy Fruit and vegetable
Mike’s data. Stimuli from the salty and crunchy category (pretzels, chips, Doritos, and peanuts) were ranked 1, 2, 3, and 4, respectively. The chocolate category items were ranked 5, 6, 7, and 8. The fruit and vegetable items and the gummy items occupied the remaining eight positions. For all six participants, at least three of the top five-ranked items were from the same category. Similarly, for five of six participants, three of the five lowest ranked items were from the same category. A sample of the results of the reinforcer assessments is presented in Figure 1. In general, responding was at zero or low levels during all baseline sessions (Condition A). During phases when reinforcement was available, all participants responded almost exclusively for the task associated with the item from the high-preference category regardless of whether that stimulus had been assessed in the preference assessment (tested stimuli; Condition B) or identified by the researchers (untested stimuli; Condition C).
Responding on the task associated with the lowpreference item occurred at low to zero levels across all participants for both tested and untested stimuli. The results were similar across the remaining three participants whose results are not depicted here (data available from the authors). For these participants, effective reinforcers were identified on the basis of the category information without the explicit assessment of the item. These results suggest that identification of a high-preference stimulus category may allow a clinician to infer the likely reinforcing efficacy of an untested stimulus from the same category. There may be some practical utility to this finding. In many applied settings in which individuals with developmental disabilities are served, preference assessments with edible items are often conducted to identify preferred stimuli that can be used in skill-acquisition or behaviorreduction programs. If a recent category assessment had been completed and staff do not have immediate access to one specific high-preference
CATEGORY PREFERENCE
225
Figure 1. Number of silverware sorted across baseline (A) and reinforcement conditions using items that were (B) and were not (C) included in the preference assessment for Mike, Nick, and Andy (top, middle, and bottom panels, respectively).
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edible item, our findings suggest that staff may be more likely to find another effective reinforcer by selecting a new stimulus from the same category. However, future research should evaluate whether varying reinforcers within a category helps to avoid satiation on any one particular stimulus or whether individuals may satiate on all members of that category. One limitation of our study was the use of the concurrent-operants design for the reinforcer assessment. During reinforcement phases, two items were simultaneously presented, and participants could respond to access the highpreference or the low-preference item. Although participants allocated responding to the highpreference item, it was not clear if low-preference items may have functioned as reinforcers in the absence of a competing high-preference item (e.g., Roscoe, Iwata, & Kahng, 1999). Although untested items chosen by the researchers functioned as reinforcers, it is possible that had we chosen different items from that category, we would not have seen a similar reinforcing effect. Several studies have identified texture as a potentially important characteristic of food for persons with autism (Munk & Repp, 1994; Patel, Piazza, Santana, & Volkert, 2002; Sharp & Jaquess, 2009). Although we attempted to group items by flavor and texture, our categories were subjective, and care should be taken not to assume that an item is a reinforcer solely on the basis that the item is identified as being from a high-preference category. When attempting to develop categories of stimuli for both edible and leisure items, future research could examine more closely what aspects of a stimulus are most salient. This information may help future researchers to identify stimuli more effectively as members of certain categories. REFERENCES Bojak, S. L., & Carr, J. E. (1999). On the displacement of leisure items by food during multiple-stimulus preference assessments. Journal of Applied Behavior Analysis, 32, 515–518. doi: 10.1901/jaba.1999.32-515
DeLeon, I. G., Graff, R. B., Frank-Crawford, M. A., Rooker, G. W., & Bullock, C. E. (2014). Reinforcement arrangements for learners with autism spectrum disorder. In J. Tarbox, D. R. Dixon, P. Sturmey, & J. L. Matson (Eds.), Handbook of early intervention for autism spectrum disorders: Research, policy, and practice (pp. 205–228). New York, NY: Springer. DeLeon, I. G., & Iwata, B. A. (1996). Evaluation of a multiple-stimulus presentation format for assessing reinforcer preferences. Journal of Applied Behavior Analysis, 29, 519–533. doi: 10.1901/jaba.1996.29-519 DeLeon, I. G., Iwata, B. A., & Roscoe, E. M. (1997). Displacement of leisure reinforcers by food during preference assessments. Journal of Applied Behavior Analysis, 30, 475–484. doi: 10.1901/jaba.1997.30-475 Fisher, W., Piazza, C. C., Bowman, L. G., Hagopian, L. P., Owens, J. C., & Slevin, I. (1992). A comparison of two approaches for identifying reinforcers for persons with severe and profound disabilities. Journal of Applied Behavior Analysis, 25, 491–498. doi: 10.1901/ jaba.1992.25-491 Karsten, A. M., & Carr, J. E. (2009). The effects of differential reinforcement of unprompted responding on the skill acquisition of children with autism. Journal of Applied Behavior Analysis, 42, 327–334. doi: 10.1901/jaba.2009.42-327 Munk, D. D., & Repp, A. C. (1994). Behavioral assessment of feeding problems of individuals with severe disabilities. Journal of Applied Behavior Analysis, 27, 241–250. doi: 10.1901/jaba.1994.27-241 Patel, M. R., Piazza, C. C., Santana, C. M., & Volkert, V. M. (2002). An evaluation of food type and texture in the treatment of a feeding problem. Journal of Applied Behavior Analysis, 35, 183–186. doi: 10.1901/ jaba.2002.35-183 Piazza, C. C., Bowman, L. G., Contrucci, S. A., Delia, M. D., Adelinis, J. D., & Goh, H. L. (1999). An evaluation of the properties of attention as reinforcement for destructive and appropriate behavior. Journal of Applied Behavior Analysis, 32, 437–449. doi: 10.1901/jaba.1999.32-437 Roane, H. S., Vollmer, T. R., Ringdahl, J. E., & Marcus, B. A. (1998). Evaluation of a brief stimulus preference assessment. Journal of Applied Behavior Analysis, 31, 605–620. doi: 10.1901/jaba.1998.31-605 Roscoe, E. M., Iwata, B. A., & Kahng, S. (1999). Relative versus absolute reinforcement effects: Implications for preference assessments. Journal of Applied Behavior Analysis, 32, 479–493. doi: 10.1901/jaba.1999.32-479 Sharp, W. G., & Jaquess, D. L. (2009). Bite size and texture assessments to prescribe treatment for severe food selectivity in autism. Behavioral Interventions, 24, 157– 170. doi: 10.1002/bin.282 Received September 5, 2013 Final acceptance September 15, 2014 Action Editor, John Borrero
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2015, 48, 221–226
NUMBER
1 (SPRING)
INCREASING THE EFFICIENCY OF PAIRED-STIMULUS PREFERENCE ASSESSMENTS BY IDENTIFYING CATEGORIES OF PREFERENCE FRANCIS J. CICCONE, RICHARD B. GRAFF,
AND
WILLIAM H. AHEARN
NEW ENGLAND CENTER FOR CHILDREN AND NORTHEASTERN UNIVERSITY
A paired-stimulus preference assessment was conducted for 6 individuals with developmental disabilities. We selected stimuli that were representatives of 4 categories: chocolate, salty and crunchy, gummy, and fruit and vegetable. For all 6 participants, at least 3 of the 5 most preferred items came from the same category. On subsequent reinforcer assessments, items from the highest ranked preference category, some of which were included in the preference assessments and some of which were not, functioned as reinforcers. These findings suggest that after categories of preferred items are identified, clinicians may be able to identify reinforcers for some individuals without conducting additional assessments. Key words: autism, preference, reinforcer, developmental disabilities
The identification and effective use of reinforcers are crucial to increase skill acquisition and reduce problem behavior for individuals who have been diagnosed with developmental disabilities (e.g., Fisher et al., 1992; Karsten & Carr, 2009). In applied settings, high-preference items that have been specifically identified through a preference assessment may be unavailable for a period of time (e.g., because of depleted supplies); however, the need for an effective reinforcer remains. If categories of preferred items could be identified with minimal additional effort, it may provide clinicians with a mechanism to identify an alternative reinforcer without the need for additional preference assessments when a specific high-preference item is no longer available. Few studies have analyzed preferences for categories of stimuli. DeLeon, Iwata, and Roscoe (1997) conducted preference assessments using two categories of items: edible items and leisure items. When edible and leisure items were both used in the assessments, the most preferred item Richard B. Graff and William H. Ahearn are now associated with Western New England University, Springfield, Massachusetts. Address correspondence to Francis J. Ciccone, New England Center for Children, 33 Turnpike Rd., Southborough, Massachusetts 01772 (e-mail: fciccone@necc. org). doi: 10.1002/jaba.190
was an edible item for 12 of 14 participants; for 11 participants, the top two preferred items were edible items, and for nine participants, the top three preferred items were edible items. Bojak and Carr (1999) found that when leisure and edible items were combined on an eight-item preference assessment, for all participants, edible items ranked first through fourth, and leisure items ranked fifth through eighth. Although edible items may displace preference for leisure items for some individuals, to date no research has systematically evaluated preference for and reinforcer efficacy of various categories of edible items. The purpose of our study was to evaluate whether a researcher could identify a stimulus that would function as a reinforcer based on a previously identified high-preference category without conducting additional preference assessments. Although the multiple-stimulus-without-replacement assessment (MSWO; DeLeon & Iwata, 1996) and the free-operant (FO; Roane, Vollmer, Ringdahl, & Marcus, 1998) preference assessment have been demonstrated to be efficient methods to identify reinforcers, there are disadvantages to both which precluded their use for this study. Fewer stimuli can be simultaneously assessed on the tabletop with the MSWO compared to the paired-stimulus (PS; DeLeon, Graff, FrankCrawford, Rooker, & Bullock, 2014) preference
221
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FRANCIS J. CICCONE et al.
assessment, and the FO assessment may not yield a distinct preference hierarchy. Given that we assessed preferences for 16 stimuli and required a distinct preference hierarchy, the PS assessment was used. METHOD Participants, Settings, and Materials Six boys between the ages of 14 and 19 years, who had been diagnosed with autism spectrum disorder, participated. All participants attended a residential school for individuals with autism and developmental disabilities. An independent clinician and the residential school made all diagnoses. PS preference assessments (Fisher et al., 1992) and reinforcer assessments were conducted with edible items in the students’ classrooms. Items were grouped into categories according to flavor and texture as follows: chocolate (M&Ms, chocolate bars, white chocolate bars, Kit Kats), salty and crunchy (peanuts, potato chips, Doritos, pretzels), gummy (Gummy Bears, Starburst, Twizzlers, Swedish Fish), and fruit and vegetable (celery, carrots, apples, and grapes). Response Measurement and Interobserver Agreement During preference assessments, approach responses (defined as making physical contact with one of the edible items) were recorded. Preference hierarchies were established based on the percentage of approach responses to each stimulus. In addition to determining the relative preference for individual stimuli, preferences for categories of edible items was determined by adding the mean percentage of approach responses for all four members of each category and dividing by four. Category preference hierarchies were established based on mean category scores. During the preference assessments, a second observer independently recorded data on approach and integrity in a mean of 43% of trials
across participants and assessments (range, 37% to 50%). An agreement was scored if both observers recorded the same stimulus approached on a trial. A disagreement was scored if the observers recorded different stimuli being approached on a trial. Interobserver agreement was calculated on a trial-by-trial basis by dividing the number of agreements by the number of agreements plus disagreements and converting the result to a percentage. Integrity data were recorded on whether the correct stimuli were presented on a trial and whether the positions of the stimuli were correct. Mean agreement and integrity were 99% (range, 97% to 100%) and 99.7% (range, 98% to 100%), respectively. The dependent variable in the reinforcer assessment was the number of pieces of silverware sorted, defined as picking up a piece of silverware and placing it in a corresponding sorting bin. During each 5-min session, observers recorded the amount of silverware sorted. A second observer was present and independently recorded agreement and integrity data in a mean of 42% of reinforcer assessment sessions across participants and assessments (range, 39% to 47%). Interobserver agreement was calculated by dividing the smaller number of items sorted by the larger number and converting the result to a percentage. Integrity data were taken on whether or not sample stimuli were placed in the correct bins before each trial and if the bins were placed in the correct positions. Mean agreement and integrity were 99.6% and 100%, respectively. Preference Assessments PS preference assessments based on the procedures described by Fisher et al. (1992) were used to establish preference hierarchies for each individual. Each PS assessment consisted of 120 trials. On each trial, two items were placed on the table approximately 0.2 m apart and 0.3 m in front of the participant. The experimenter verbally cued the participant by saying “choose one.” A stimulus selection was recorded if the participant approached a stimulus.
CATEGORY PREFERENCE Although consumption was not part of the criteria, across participants, the majority of edible items were consumed. If the participant did not approach either item within 5 s, the stimuli were removed briefly and the trial was represented. If the participant did not approach either item on the repeated trial, the stimuli were removed, no response was recorded, and the next trial was presented. Attempts to approach both stimuli were blocked. Reinforcer Assessments After the preference assessments, reinforcer assessments were conducted using concurrentoperants procedures similar to those described by Piazza et al. (1999). Based on participants’ vocational learning objectives, silverware sorting was chosen as the assessment task. Reinforcer effects were evaluated using a multielement design embedded within a reversal; all sessions lasted 5 min. During all sessions, two sets of silverware, identical with the exception of color (red and white), were present. Each participant started each session with a set of mixed silverware (red and white forks, spoons, and knives) in front of him on the table. In addition, six sorting bins were placed on the table directly behind the silverware. The positions of the bins varied across sessions. Each of the sorting bins contained two sample stimuli. The task was to sort the silverware into the appropriate bins by matching to the sample. Placing one piece of silverware into its corresponding bin was considered a sorting response. Baseline. During baseline sessions, the materials were placed in front of the participant, and the participant was told that he could sort the silverware but that there were no arranged consequences for responding. Concurrent operants, tested stimuli. Before the start of each session, the experimenters randomly selected one edible item from the high-preference category and one from the low-preference category. The items were then randomly assigned to the colored silverware (red and white). The
223
category and color association varied across sessions, with the stipulation that an edible item could not be associated with the same color for more than two consecutive sessions. During each session, the item from the highpreference category was visible near a set of unsorted silverware and the item from the lowpreference category was visible near a second set of unsorted silverware. The participant could respond to either set of silverware. Experimenters delivered a small piece of the edible item on a fixed-ratio (FR) 1 schedule for responding at the start of the first session. For some participants, the reinforcement schedule was thinned during this session. The schedule in place at the end of the first session was used for all subsequent sessions. Across participants, schedules ranged from an FR 1 to a variable-ratio 12. Errors (e.g., placing white silverware in bins designated for red silverware) were blocked. Concurrent operants, untested stimuli. Procedures in this phase were identical to those described in the previous phase except that the edible items used were not items that had been evaluated in the preference assessment. Rather, the researchers identified one presumed highpreference and one presumed low-preference item based on the highest and the lowest ranked categories for each participant. For example, if a participant’s highest ranked category on the preference assessment was chocolate, the researcher identified a novel chocolate item to present contingent on sorting. The same procedure was used for the participant’s lowest ranked category. For each participant, this phase was conducted twice, and a different set of untested stimuli was assessed in each phase. RESULTS AND DISCUSSION Table 1 summarizes the results of each participant’s preference assessment. Across participants, items from within each category tended to group together in the preference hierarchies. This can most clearly be seen in
224
FRANCIS J. CICCONE et al. Table 1 Individual and Category Preference Assessment Rankings Participant
Rank
Mike
Individual item 1 Pretzel 2 Chips 3 Doritos 4 Peanuts 5 Kit Kat 6 Chocolate bar 7 White chocolate 8 M&M 9 Apple 10 Grape 11 Starburst 12 Carrot 13 Twizzler 14 Celery 15 Swedish Fish 16 Gummy Bear Category 1 Salty and crunchy 2 Chocolate 3 Fruit and vegetable 4 Gummy
Sam
Andy
Nick
Louis
Simon
Chocolate bar Kit Kat M&M Pretzel White chocolate Swedish Fish Grape Starburst Peanut Gummy Bear Doritos Apple Chips Celery Carrots Twizzler
White chocolate Pretzel Chocolate bar M&M Swedish Fish Kit Kat Grape Peanut Carrots Doritos Starburst Gummy Bear Apple Twizzler Chips Celery
Pretzel White chocolate M&M Chocolate bar Kit Kat Doritos Peanuts Swedish Fish Starburst Chips Gummy Bear Twizzler Celery Carrots Apple Grape
Chocolate bar Swedish Fish M&M Twizzler Gummy Bear Kit Kat Starburst Pretzel Peanut Grape Chips Doritos Apple Celery Carrots White chocolate
White chocolate Starburst Pretzel Choc Bar Kit Kat Doritos Chips Peanut M&M Swedish Fish Gummy Bear Twizzler Celery Apple Carrots Grape
Chocolate Salty and crunchy Gummy Fruit and vegetable
Chocolate Fruit and vegetable Salty and crunchy Gummy
Chocolate Salty and crunchy Gummy Fruit and vegetable
Gummy Chocolate Salty and crunchy Fruit and vegetable
Chocolate Salty and crunchy Gummy Fruit and vegetable
Mike’s data. Stimuli from the salty and crunchy category (pretzels, chips, Doritos, and peanuts) were ranked 1, 2, 3, and 4, respectively. The chocolate category items were ranked 5, 6, 7, and 8. The fruit and vegetable items and the gummy items occupied the remaining eight positions. For all six participants, at least three of the top five-ranked items were from the same category. Similarly, for five of six participants, three of the five lowest ranked items were from the same category. A sample of the results of the reinforcer assessments is presented in Figure 1. In general, responding was at zero or low levels during all baseline sessions (Condition A). During phases when reinforcement was available, all participants responded almost exclusively for the task associated with the item from the high-preference category regardless of whether that stimulus had been assessed in the preference assessment (tested stimuli; Condition B) or identified by the researchers (untested stimuli; Condition C).
Responding on the task associated with the lowpreference item occurred at low to zero levels across all participants for both tested and untested stimuli. The results were similar across the remaining three participants whose results are not depicted here (data available from the authors). For these participants, effective reinforcers were identified on the basis of the category information without the explicit assessment of the item. These results suggest that identification of a high-preference stimulus category may allow a clinician to infer the likely reinforcing efficacy of an untested stimulus from the same category. There may be some practical utility to this finding. In many applied settings in which individuals with developmental disabilities are served, preference assessments with edible items are often conducted to identify preferred stimuli that can be used in skill-acquisition or behaviorreduction programs. If a recent category assessment had been completed and staff do not have immediate access to one specific high-preference
CATEGORY PREFERENCE
225
Figure 1. Number of silverware sorted across baseline (A) and reinforcement conditions using items that were (B) and were not (C) included in the preference assessment for Mike, Nick, and Andy (top, middle, and bottom panels, respectively).
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edible item, our findings suggest that staff may be more likely to find another effective reinforcer by selecting a new stimulus from the same category. However, future research should evaluate whether varying reinforcers within a category helps to avoid satiation on any one particular stimulus or whether individuals may satiate on all members of that category. One limitation of our study was the use of the concurrent-operants design for the reinforcer assessment. During reinforcement phases, two items were simultaneously presented, and participants could respond to access the highpreference or the low-preference item. Although participants allocated responding to the highpreference item, it was not clear if low-preference items may have functioned as reinforcers in the absence of a competing high-preference item (e.g., Roscoe, Iwata, & Kahng, 1999). Although untested items chosen by the researchers functioned as reinforcers, it is possible that had we chosen different items from that category, we would not have seen a similar reinforcing effect. Several studies have identified texture as a potentially important characteristic of food for persons with autism (Munk & Repp, 1994; Patel, Piazza, Santana, & Volkert, 2002; Sharp & Jaquess, 2009). Although we attempted to group items by flavor and texture, our categories were subjective, and care should be taken not to assume that an item is a reinforcer solely on the basis that the item is identified as being from a high-preference category. When attempting to develop categories of stimuli for both edible and leisure items, future research could examine more closely what aspects of a stimulus are most salient. This information may help future researchers to identify stimuli more effectively as members of certain categories. REFERENCES Bojak, S. L., & Carr, J. E. (1999). On the displacement of leisure items by food during multiple-stimulus preference assessments. Journal of Applied Behavior Analysis, 32, 515–518. doi: 10.1901/jaba.1999.32-515
DeLeon, I. G., Graff, R. B., Frank-Crawford, M. A., Rooker, G. W., & Bullock, C. E. (2014). Reinforcement arrangements for learners with autism spectrum disorder. In J. Tarbox, D. R. Dixon, P. Sturmey, & J. L. Matson (Eds.), Handbook of early intervention for autism spectrum disorders: Research, policy, and practice (pp. 205–228). New York, NY: Springer. DeLeon, I. G., & Iwata, B. A. (1996). Evaluation of a multiple-stimulus presentation format for assessing reinforcer preferences. Journal of Applied Behavior Analysis, 29, 519–533. doi: 10.1901/jaba.1996.29-519 DeLeon, I. G., Iwata, B. A., & Roscoe, E. M. (1997). Displacement of leisure reinforcers by food during preference assessments. Journal of Applied Behavior Analysis, 30, 475–484. doi: 10.1901/jaba.1997.30-475 Fisher, W., Piazza, C. C., Bowman, L. G., Hagopian, L. P., Owens, J. C., & Slevin, I. (1992). A comparison of two approaches for identifying reinforcers for persons with severe and profound disabilities. Journal of Applied Behavior Analysis, 25, 491–498. doi: 10.1901/ jaba.1992.25-491 Karsten, A. M., & Carr, J. E. (2009). The effects of differential reinforcement of unprompted responding on the skill acquisition of children with autism. Journal of Applied Behavior Analysis, 42, 327–334. doi: 10.1901/jaba.2009.42-327 Munk, D. D., & Repp, A. C. (1994). Behavioral assessment of feeding problems of individuals with severe disabilities. Journal of Applied Behavior Analysis, 27, 241–250. doi: 10.1901/jaba.1994.27-241 Patel, M. R., Piazza, C. C., Santana, C. M., & Volkert, V. M. (2002). An evaluation of food type and texture in the treatment of a feeding problem. Journal of Applied Behavior Analysis, 35, 183–186. doi: 10.1901/ jaba.2002.35-183 Piazza, C. C., Bowman, L. G., Contrucci, S. A., Delia, M. D., Adelinis, J. D., & Goh, H. L. (1999). An evaluation of the properties of attention as reinforcement for destructive and appropriate behavior. Journal of Applied Behavior Analysis, 32, 437–449. doi: 10.1901/jaba.1999.32-437 Roane, H. S., Vollmer, T. R., Ringdahl, J. E., & Marcus, B. A. (1998). Evaluation of a brief stimulus preference assessment. Journal of Applied Behavior Analysis, 31, 605–620. doi: 10.1901/jaba.1998.31-605 Roscoe, E. M., Iwata, B. A., & Kahng, S. (1999). Relative versus absolute reinforcement effects: Implications for preference assessments. Journal of Applied Behavior Analysis, 32, 479–493. doi: 10.1901/jaba.1999.32-479 Sharp, W. G., & Jaquess, D. L. (2009). Bite size and texture assessments to prescribe treatment for severe food selectivity in autism. Behavioral Interventions, 24, 157– 170. doi: 10.1002/bin.282 Received September 5, 2013 Final acceptance September 15, 2014 Action Editor, John Borrero
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