J Autism Dev Disord (2015) 45:1146–1155 DOI 10.1007/s10803-014-2272-x
ORIGINAL PAPER
Use of a Self-monitoring Application to Reduce Stereotypic Behavior in Adolescents with Autism: A Preliminary Investigation of I-Connect Stephen A. Crutchfield • Rose A. Mason Angela Chambers • Howard P. Wills • Benjamin A. Mason
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Published online: 18 October 2014 Springer Science+Business Media New York 2014
Abstract Many students with autism engage in a variety of complex stereotypic behaviors, impacting task completion and interfering with social opportunities. Self-monitoring is an intervention with empirical support for individuals with ASD to increase behavioral repertoires and decrease behaviors that are incompatible with successful outcomes. However, there is limited evidence for its utility for decreasing stereotypy, particularly for adolescents in school settings. This study evaluated the functional relationship between I-Connect, a technology-delivered self-monitoring program, and decreases in the level of stereotypy for two students with ASD in the school setting utilizing a withdrawal design with an embedded multiple baseline across participants. Both students demonstrated a marked decrease in stereotypy with the introduction of the self-monitoring application. Results and implications for practice and future research will be discussed. Keywords Autism Self-monitoring Stereotypic behavior Technology-based application
S. A. Crutchfield (&) R. A. Mason H. P. Wills B. A. Mason Juniper Gardens Children’s Project, University of Kansas, 444 Minnesota Avenue, Kansas City, KS 66101, USA e-mail:
[email protected] R. A. Mason e-mail:
[email protected] A. Chambers Department of Special Education, School of Education, University of Kansas, 1122 West Campus Rd., Lawrence, KS 66045-3101, USA
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Introduction Along with qualitative impairments in communication and social interactions, restrictive and repetitive patterns of behavior are considered a defining characteristic of individuals on the autism spectrum (American Psychiatric Association 2012). This encompasses a wide variety of behavior, including preference for sameness and routine, narrow interests, stereotypic behavior, and self-injurious behavior (Bregman and Higdon 2012). Stereotypic behavior is often associated with individuals on the autism spectrum, and there is some evidence that higher rates of stereotypy occur in individuals who demonstrate more severe symptoms of autism (Reed et al. 2014). Stereotypy is heterogeneous, and encompasses a variety of motor and vocal behavior including: brisk arm movements, rigid or odd walking postures, toe-walking, body rocking, noncommunicative vocal repetitions, and head shaking (Bregman and Higdon 2012; Lanovaz et al. 2014; Lee et al. 2007). These complex behaviors, though not fully understood, are thought to serve a variety of sensory, stimulatory, and communication functions (Kennedy et al. 2000; Reed et al. 2014). However, they often present barriers to task completion, instructional routines, and social interactions while also contributing to the stigmatization surrounding ASD and disability in general (Kennedy et al. 2000; Koegel and Koegel 1990; Koegel et al. 1992; Lanovaz et al. 2014). Consequently, learning to manage these behaviors may lead to improved learning opportunities (Cervantes et al. 2014) and increases in social interactions (Lee et al. 2007). Self-monitoring (SM) is a plausible candidate for addressing this need. While other interventions have demonstrated effectiveness in reducing stereotypy (see Boyd et al. 2012; DiGennaro Reed et al. 2012), SM can be
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maintained without the direct supervision and implementation of an instructor and can be adapted and adjusted to the needs of the student and the environment (Koegel and Koegel 1990). SM, a component of self-management, involves performance assessment and recording of target behaviors (Ganz and Sigafoos 2005; Lee et al. 2007). SM has been implemented to address a variety of target behaviors for individuals with ASD including social skills such as reciprocal conversation (Koegel et al. 2014) and initiations (Reynolds et al. 2013); daily living skills like preparing meals and completing the laundry (Pierce and Schreibman 1994); on-task behaviors such as listening to the teacher and completing assigned tasks (Stasolla et al. 2014); and decreasing disruptive 5 (e.g. physical aggression, tantrumming, talking out) and noncompliant behaviors (e.g. wandering from assigned location, not following adult directives) (Koegel et al. 1992; Shogren et al. 2011). Additionally, limited evidence has indicated that SM systems may be successful in decreasing stereotypy (Ganz et al. 2013; Koegel and Koegel 1990; Mancina et al. 2000; and Shabani et al. 2001) while promoting generalization and independence. Koegel and Koegel (1990) implemented SM to reduce the level of stereotypic behavior for four children, ages 9–14, with ASD and significant cognitive delays in clinical and community settings utilizing a paper and pencil self-monitoring system. Similarly, paper–pencil based self-monitoring system with a watch to provide prompts was also implemented to successfully decrease stereotypic behavior across classroom settings for a 12 year old with ASD and cognitive impairments (Mancina et al. 2000). As both studies included reinforcement as part of the intervention, a functional relationship between self-monitoring alone and decreases in stereotypic behavior was not demonstrated. SM systems are generally a component in a package intervention including other components such as discrimination training (Agran et al. 2005; Koegel and Koegel 1990; Mancina et al. 2000) and reinforcement (Koegel and Koegel 1990; Mancina et al. 2000), isolating the specific intervention variables that contribute to the positive outcomes is challenging. More research is needed to further examine the functional relationship of selfmonitoring implemented alone and decreases in stereotypy. Additionally, the evidence for utilizing SM to decrease stereotypy is generally limited to elementary aged participants with ASD (e.g. Koegel and Koegel 1990; Loftin et al. 2008; Pierce and Schreibman 1994). Only a few studies have included adolescents (e.g. Ganz et al. 2013; Koegel and Koegel 1990; Mancina et al. 2000) and only two of those studies (Ganz et al. 2013; Mancina et al. 2000) were conducted in a school setting. However, as Ganz et al. (2013) only included two
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demonstrations of change a functional relationship between implementation of SM and decreases in stereotypy was not established according to the design standards established by the What Works Clearinghouse (Kratochwill et al. 2010). Thus, SM to decrease stereotypy for adolescents, particularly within a school setting, does not have a sufficient evidence base. Given the promise of SM, more research is needed to extend the evidence base of SM to decrease stereotypy for adolescents with ASD in a school setting. Additionally, typical implementation of SM does pose some challenges in terms of level of independence. For instance, the typical mechanism for monitoring can be somewhat cumbersome and socially distracting. Paper and pencil (Koegel and Koegel 1990; Stahmer and Schreibman 1992), tokens (Shogren et al. 2011), checklists (Mancina et al. 2000), and wrist watches/timers (Mancina et al. 2000; Stahmer and Schreibman 1992), not only require the individual to monitor his/her behavior but inadvertently require the user to remember and care for the monitoring system. This is significant in that one of the key features of SM systems is the ability to implement them without the direct supervision of teachers (Koegel and Koegel 1990). However, multi-component systems need to be organized and managed in order for them to be implemented effectively, and researchers are noticeably vague on how materials are managed within these systems. A single component system that automatically delivers interval reminders to students as well as recording and tracking their responses appears to be a unique and a relatively untested system within the SM literature for adolescents with ASD. Use of mobile technology as a delivery agent for prompting and monitoring would likely provide an efficient level of support that promotes independence and increases the social validity of the intervention. I-Connect (Wills and Mason 2014) is a SM application, delivered via a mobile device (see Fig. 1), which was initially developed by Wills and colleagues to improve academic engagement and decrease inappropriate behavior for high school students with disabilities. The virtually supported application allows for customizable prompts including type (i.e. tone, vibration, or flash), frequency (e.g. 30 s, 60 s), and wording (e.g. ‘‘Are you on task?’’, ‘‘Did you have quiet hands and mouth?’’). Additionally, participant responses are automatically uploaded to an online database that allows the teacher to monitor responses and progress. The use of modern handheld devices and webbased technology allows for a more efficient and socially acceptable platform for implementing SM. The efficacy of I-Connect to change behaviors for individuals with ASD, including reduction of stereotypy has not been evaluated.
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Fig. 1 Screenshot of I-CONNECT individualized self-monitoring question
Purpose and Research Questions This study seeks to extend the evidence base regarding the effectiveness of self-monitoring to decrease stereotypic behavior for individuals with ASD by investigating I-Connect, a school based, technology delivered, selfmonitoring intervention. Specifically, this study will address the following research question: Is there a functional relationship between implementation of I-Connect self-monitoring application and decreases in the level of stereotypy for adolescents with autism?
Methods Participants, Setting, and Materials Participants Two eighth grade middle-school students (pseudo named Barry and Carl) participated in this study. Participants were selected based on the following criteria: (a) receiving special education services as a student with autism, (b) stereotypic behavior impacting independent task completion, and (c) parental permission. Barry, a 14-year-old Caucasian, met special education eligibility under the category of autism. In addition, Barry was medically diagnosed with Down Syndrome and attention deficit hyperactivity disorder (ADHD), for which he was currently prescribed medication. According to school records he also received services in the areas of speech and language. Barry’s most recent IQ test,
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Universal Nonverbal Intelligence Test (Bracken and McCallum 1998), was administered one year prior to the study and reported results indicated a Full Scale IQ standard score of 54, falling into the very delayed category. The Vineland Adaptive Behavior Scales, Second Edition (VABS-II; Sparrow et al. 2005) was also administered 1 year prior to the study and teacher ratings indicated an Adaptive Behavior Composite of 54, which indicates adaptive skills in the moderately deficient range. Carl was also 14-year-old Caucasian who was receiving special education services as student with autism and ADHD. At the time of the study, Carl was not taking any medication for attention. He received services in the areas of speech and language. The most recent assessment of Carl’s cognitive functioning was from 5 years prior to the current study when he was administered the Stanford-Binet Intelligence Scales, Fifth Edition, (Roid 2003), which indicated a Nonverbal IQ composite standard score of 53 (classified as moderately delayed). Although this score should be interpreted with caution given its lack of recency, the assessment was consistent with the assessment of adaptive functioning which was administered a year prior to the current study. Both parent and teacher ratings on the VABS-II (Sparrow et al. 2005), yielded Adaptive Behavior Composite Scores, 58 and 43, in the mildly to moderately deficient range. Setting The study was conducted in an urban middle school in a Midwestern city. At the time of the study, the school’s enrollment consisted of 77 % minority populations and was
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economically disadvantaged, with 85 % of students, including both participants receiving free or reduced lunch. All data were collected in the special education environment with a 1:1 student ratio. All five students who received services in this setting had an educational classification of autism with similar levels of academic, social, and adaptive functioning. Students completed work in both individual workspaces and group work centers. Data was collected during independent work activities when the participant was seated and working in their assigned workspace. Independent activities consisted of a variety of language and academic tasks, such as writing numbers, writing personal information (e.g. name, address, etc.), and doing simple math, for which students had previously demonstrated mastery with 1:1 assistance and were working towards independent mastery. Materials The handheld device used in the study was a Samsung Galaxy 5.0 smartphone with a five-in. screen. I-Connect (Wills and Mason 2014) is an Android application designed to provide scheduled prompts for participants to selfevaluate and self-monitor targeted behaviors. The application provides a variety of prompts (e.g. tactile, chimes, flash only) and fixed intervals ranging from 30 s to 15 min as selected by the user (Fig. 1). The I-Connect application was loaded onto the Samsung device, connected to school wireless networks to assess for compatibility with school firewalls, and tested to insure it was functioning as intended prior to intervention. Experimental Design and Measurement Design The effect of the intervention was evaluated through the implementation of an ABAB reversal design with an embedded multiple baseline across two participants. Although an ABAB reversal design, in and of itself, is considered a strong design according to the standards established by the What Works Clearinghouse (WWC: Kratochwill et al. 2010), the inclusion of an additional multiple baseline strengthens the internal validity of the study. The design demonstrates experimental control and strong internal validity with the methodical introduction of the intervention at six separate instances. Six demonstrations of effect exceed the ‘‘Meet Standards’’ criterion of three demonstrations of change as established by the WWC (Kratochwill et al. 2010). The study was carried out over the course of 7 weeks with three to four, 5-min observation sessions per week. Observations and data collection occurred in the same
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setting across phases for both participants. The first author collected data on the occurrence of stereotypic behavior during the 5-min independent work sessions. Dependent Variable The percentage of intervals in which stereotypic behavior occurred was the dependent variable. Stereotypic behavior was individually defined for each participant. Operational definitions of stereotypic behaviors for Barry included: (1) non-functional hand gestures (i.e. hand flapping, waving hands in front of face); (2) placing hands in mouth; and (3) vocalizations not directed at another individual (i.e. grunts, repetitive laughing, and repeating words and phrases). The operational definitions for Carl’s stereotypic behaviors included: (1) vocal language not directed to a communication partner and (2) placing hands or objects in mouth. Measurement A 10-s partial interval recording was used to measure the frequency of the target behavior. Partial interval recording is a data collection method in which the observer indicates the occurrence or nonoccurrence of the target behavior during the interval irrespective of frequency and/or duration (Cooper et al. 2007). The observation recording form included a grid with columns labeled by minutes (i.e. 1–5) and rows labeled by seconds (i.e. 10, 20…60) resulting in a total of 30 recording boxes. The observer marked a ‘‘?’’ if the behavior occurred at all during the 10-s interval and a ‘‘-’’ if the behavior did not occur during the 10-s interval. The percentage of stereotypic behavior was calculated by dividing the number of intervals in which the behavior occurred by the total number of intervals. Reliability Two investigators, the first and third author trained in the data collection procedure, and concurrently, but independently, collected data for a minimum of 20 % of session across phases. Agreement was coded if both observers agreed on the occurrence or nonoccurrence of the target behavior during a given 10-s interval. Percent of agreement was calculated by dividing the number of intervals in which there was agreement by the total number of intervals. The overall mean percent of agreement was 87.5 % (range 57–97 %). The extremely low rate of agreement of 57 % occurred when Barry had a cold and wiping his nose with his hand was interpreted by the secondary observer as meeting the operationalized definition of his target behavior. The disagreement was discussed and corrected for future sessions. Had this outlier not been included
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(57 %) the rate of agreement across participants would have been 88.4 %. Fidelity of Implementation Fidelity of implementation was assessed on 25 % of treatment sessions. The fidelity measure consisted of the following ‘‘yes/no’’ questions: (1) Teacher said, ‘‘Start your timer’’? (2) Teacher provided no reinforcement during session? (3) Teacher interacted only if the child needed help on the assignment? (4) Was any student/teacher interaction limited only to discussion of assignment not self-monitoring? and (5) Were prompting procedures followed? Percent of treatment fidelity was assessed as the number of ‘‘yes’’ responses, divided by total responses. Fidelity of implementation was assessed at 100 % for each participant.
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instructional setting for more than 30 s or if the students asked a question or asked for assistance. The classroom teacher or support staff would place the work items on the students desk and give them the prompt ‘‘remember to work with quiet hands and mouth’’ before the student began. Following the collection of a minimum of five data points and baseline data that was stable without a decreasing trend, the intervention was systematically introduced for the first participant. Likewise, the intervention was introduced to the second participant with the additional criteria that the first participant’s intervention data indicated improvement from baseline. I-Connect Training
A ten-item teacher satisfaction survey was given to the participant’s classroom teacher. The survey was divided into two sections; the first section assessed the teacher’s opinion on the direct impact of the intervention on the student’s productivity, assignment completion, assignment accuracy, and the student’s grade. The teacher rated each area on a scale of 1–5 or ‘‘not applicable’’, with 1 indicating ‘‘no improvement’’ and 5 indicating ‘‘great improvement’’. The second section of the survey asked the teacher to compare the I-Connect intervention to other interventions that had been utilized to address the same behaviors. The specific comparisons included: desired change in the behavior, efficiency-time, efficiency-ease of implementation, efficiency-use of resources, participant enjoyment of intervention, and continued use of the intervention in the future. The teacher was asked to rate these items on a scale of 1–5, with 1 indicating, ‘‘a lot less than other interventions’’ and 5 indicating ‘‘a lot more than other interventions’’. Finally, the survey asked the teacher to provide comments about the features of the intervention they liked the most or thought the most beneficial.
Once the criteria for introducing the independent variable were met, training on the I-Connect application occurred. Training sessions, which lasted 15 min, were conducted by the classroom teacher at the desk where the participant’s independent work occurred. Before the training session the device was configured to use the flashing prompt, as chosen by the teacher, and written question ‘‘Quiet hands and mouth?’’ on 30-s intervals. Students began their independent work session in the same manner as in baseline but with the classroom teacher seated next to them. The classroom teacher waited until the device displayed the question and then prompted the student to ‘‘answer your question’’. Each interval, the classroom teacher would give the student 3 s to respond independently before providing the prompt. Once the student answered the questions independently, irrespective of accuracy, for 80 % of intervals during a training session, the training phase was complete. Barry needed only one session to demonstrate independence in referencing and responding to the device. After two 15-min training sessions, Carl was still not referencing and responding to the device independently, so a third session was conducted with the work tasks removed and only the device present. During this session, Carl responded to the device for 100 % of intervals. Independent responding with work tasks reintroduced was not assessed prior to beginning intervention for Carl.
Procedures
Intervention
Baseline and Withdrawal
Once the participant met the training criteria, the I-Connect intervention began. During treatment, independent work session proceeded in exactly the same fashion as baseline with the addition of the self-monitoring application. The smartphone was placed in the student’s workspace and was programmed to ask them the monitoring question ‘‘Quiet hands and Mouth?’’ every 30 s. To ensure the students were actually engaging in self-monitoring, they were not permitted to miss more than one electronic prompt in a
Social Validity
During baseline, students accessed independent work per their daily school routine. Data were collected on the percentage of intervals that they engaged in stereotypic behavior during independent work time. Students completed the work independently at a desk in their special education classroom. Students received prompts from teachers or support staff only if they got up from the
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row. If the student did not respond within 3 s to the device prompt, then for the proceeding device prompt a verbal prompt, ‘‘answer the question’’, was delivered by the teacher or first author. When monitoring, the intervention the observer was sitting at the teacher’s desk in an effort to be unobtrusive, yet still be able to hear the prompt and monitor the participant’s response. Fading The fading procedure was implemented once the participant demonstrated decreases in stereotypic behavior and had a clearly established pattern of responding to the second I-Connect intervention phase. For the fading phase of the study task, setting, and prompting procedures were identical to those in the intervention phase. For fading, the I-Connect device was placed in the student’s workspace and was programmed to ask them the monitoring question ‘‘Quiet hands and Mouth?’’ every 60 s, as opposed to the 30 s during the intervention phase. Data Analysis Visual and statistical analyses were employed to evaluate the functional relationship between use of the I-Connect self-monitoring application and decreases in stereotypic behavior. The graphical display of data was utilized to evaluate changes in data between concurrent baseline and intervention phases (i.e. Baseline vs. I-Connect 1 and Withdrawal vs. I-Connect 2) and between the final intervention phase and fading (I-Connect 2 vs. Fading) for both participants. Visual analysis between phases included evaluation of differences in variability, mean, and trend. Additionally, Tau effect sizes (Parker et al. 2011) were calculated to provide a quantitative measure of the degree of change that occurred between contrasted phases for each participant and then combined to obtain an overall Tau effect size for the study. Tau effect sizes \.5, .5–.69, and .70–1 are interpreted as minimal to no effect, moderate effect, and large effect respectively.
Results Intervention Results for all phases for both participants are graphically displayed in Fig. 2. The x-axis indicates the session and the y-axis indicates the percentage of intervals in which stereotypy occurred. Data for Barry is in the top panel and data for Carl is in the bottom panel. As is indicated by the phase change lines, introduction and withdrawal of the I-Connect intervention was systematically staggered across
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participants, with six demonstrations of change at different points in time. Additionally, as each phase includes a minimum of five data points, a consistent pattern of responding was established across phases within and between participants. Visual analysis of baseline data for both participants indicates a high rate of stereotypy. Although data are variable, percentage of stereotypy was typically above 60 % for both participants and demonstrated an increasing trend to nearly 100 % for Barry and over 80 % for Carl. Introduction of the I-Connect self-monitoring intervention resulted in an immediate reduction in levels of stereotypy for both participants, although Carl’s data demonstrated continued variability before stabilizing at 40 %. Withdrawal of the I-Connect intervention resulted in an ascending trend in rate of stereotypy for both participants, steadily returning to initial baseline levels. The second systematic introduction of I-Connect again resulted in an immediate decrease in the level of stereotypy for both participants, with Carl once again demonstrating more variability than Barry, again with a steadily descending trend in rate of stereotypy across treatment sessions. Statistical analysis indicates moderate to large magnitude of change with the introduction of I-Connect (see Table 1). Calculated effect size for Barry with the introduction of Tau indicated a moderate change (.60) between baseline and I-Connect 1 and a large magnitude of change (.83) with the contrast of the withdraw phase and I-Connect 2. Results for Barry yielded a combined large effect size of .71. Likewise, calculated effect size for Carl indicates a large magnitude of change (.82) with the initial introduction of I-Connect and a moderate magnitude of change (.60) with the second introduction. The combined calculated Tau for Carl of .72 again indicates a large magnitude of change. Fading In an effort to promote maintenance, the level of prompting was faded to 1 min rather than 30 s. As is evident by visual analysis of Fig. 2, Barry demonstrated an immediate decrease in levels of stereotypy, with variability until the last three data points, which indicate a steep, descending trend. Carl demonstrated a slight increase in level of stereotypy with the introduction of the 1 min prompt; however, rate of stereotypy remained consistent with observed rates during the 30 s prompt, the I-Connect 1 and I-Connect 2 phases. Social Validity Results of the social validity measure for both students indicated that the teacher saw improvements in
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Fig. 2 Graphical display of participants’ percentage of stereotypy
Table 1 Participants TauU effect size and relevant confidence intervals Tau effect size
p value
90 % CI Lower limit
Upper limit
Barry Baseline versus ICONNECT-1
.60
.09
.02
1
Withdraw versus ICONNECT-2
.83
\.00
.31
1
Combined
.71
\.00
.34
1
Baseline versus ICONNECT-1
.82
\.00
.44
1
Withdraw versus ICONNECT-2
.60
.02
.15
1
Combined
.72
\.00
.41
1
Carl
productivity and assignment completion when students were using the I-Connect application (both were rated ‘‘4’’ which indicated ‘‘improvements noted’’). The teacher saw no improvements in student accuracy as a result of the I-Connect intervention (rated ‘‘1, no improvements noted’’), and rated ‘‘grades’’ as ‘‘not applicable’’. The results of the second section of the survey indicated that when compared to other interventions used to address the same behaviors the I-Connect led to ‘‘a lot more changes’’
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in the target behavior (rated a 5), was more time efficient than other interventions (rated a 4), was just as easy to implement as other interventions (rated a 3), and used fewer resources than other interventions (rated a 4). The ratings indicated the participants enjoyed the intervention ‘‘much more’’ than other interventions (rated a 5), and she felt like she was ‘‘much more likely’’ to use the I-Connect in the future instead of other interventions (rated a 5). The teacher commented that she particularly liked the students’ motivation to use the device for self-monitoring and the adaptability of the I-Connect application. She also noted that I-Connect was ‘‘more socially acceptable than bulky paper/pencil self-monitoring checklists’’ and the students needed ‘‘less adult support’’ when using the application.
Conclusion This study demonstrates a functional relationship between implementation of I-Connect, a technology-delivered SM program, and decreases in the level and rate of stereotypy for two adolescents with autism and cognitive impairment in a school setting. Both participants demonstrated an immediate decrease in level of stereotypy with both introductions of the I-Connect intervention. Although the data to data session within and across participants indicated the stereotypy was variable, there is clear indication that use of the I-Connect self-monitoring system resulted in a
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steady decrease in the target behavior across time, whereas absence of I-Connect yielded a steady increase in the target behavior across time. Considering the advantages of a technology-delivered SM system such as I-Connect, the results of this study are promising. I-Connect incorporates a prompting system and recording method into one program, eliminating the need for multiple materials such as a timers, and paper/pencil checklists. Once the application is programmed for each individual including the interval for prompts, SM question, and type of electronic prompt (i.e. flash, vibrate, or ring), the teacher merely has to provide the student with the device during occasions when SM is warranted. The handheld mobile device utilized for this study was readily accepted by the participants and easy for both participants to manipulate with little interruption to their academic task. The subtlety of the prompt also ensured others in the class were not interrupted by the SM system. In addition, increasing the prompt interval in an attempt to fade the prompting level resulted in maintenance of intervention effects for both participants. The experimental control and strong internal validity of the study as established by six demonstrations of change at different points in time, systematic introduction and withdrawal of the intervention, and establishment of a pattern of results with a minimum of five data points per phase (Kratochwill et al. 2010), provides a high level of confidence in the interpretation of the results. This study extends the literature on the impact of SM for decreasing stereotypy for adolescents with autism. As previously mentioned, the evidence base for SM typically involves a multi-component package precluding the ability to make definitive statements on the impact of SM as the other components in the prescribed packages or the components together may actually be the change agent. I-Connect was delivered alone, without reinforcement for accurate SM or decreases in stereotypy, which to the knowledge of the authors has not previously been explored in the SM literature. Results indicated meaningful decreases in the target behavior, although a stable pattern of responding is not established. Despite this, the study is promising as the absence of additional discrimination training or planned reinforcement allowed the intervention to be delivered without the support of an outside agent. The ability to produce meaningful changes in behavior, particularly ones that are typically treatment resistant such as stereotypy (Ganz et al. 2013), with a highly efficient, socially valid intervention in a virtually independent manner is appealing. Although these results are encouraging, it is acknowledged that there are several theories of change connected to the SM literature and they generally center on a subject-driven model of behavioral evaluation (Spates and Kanfer 1977). However, some have posited
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(see Nelson and Hayes 1981) that perhaps the primary change agent of SM is actually a response to environmental cues to self-monitor or self-record, either from the teacher or the cueing system (i.e. the I-Connect application). Limitations One limitation of this study is the absence of data regarding participants’ response accuracy. Such data would perhaps provide evidence on the participant’s discrimination ability, however, given the evidence in previous research indicating accuracy is not necessary for self-monitoring to be effective (Ganz 2008; Koegel and Koegel 1990), this omission does not limit the demonstration of a functional relationship with the use of SM and decreases in stereotypy. In addition, due to the nature of partial interval recording the percentage is likely an overestimate (Cooper et al. 2007) of the occurrence of stereotypy for both participants. Another limitation of this study is the minimal social validity data, as only one teacher completed the social validity measure. Such a limited sample lends itself to bias and should be viewed with caution. Including ratings from another teacher or support personnel would strengthen the confidence one could have in this measure. Additionally, having the participants rate, or at a minimum provide anecdotal information regarding their experience with the I-Connect intervention would provide further information as it relates to the acceptability and effectiveness of the intervention. The lack of generalization data is also a limitation of this study particularly given the challenges students with autism have with skill transfer and generalization of skills across environment (Simpson and Myles). Interventions that can demonstrate effects across multiple environments are uniquely positioned to offer maximum benefit for individuals with autism. Implications for Future Research Best practice suggests utilizing the least amount of prompting necessary to yield changes, however the evidence-base on self-monitoring lacks guidance on how to determine the length of the prompt interval. For this study, the small 30 s fixed prompt interval was determined to be appropriate due to the high levels of stereotypy exhibited during baseline for both participants. However, it is possible that longer prompt intervals would be less intrusive yet yield the same benefits. In addition, a variable prompt interval might further strengthen desired changes in the target behavior. Future research exploring differential effects of length of prompt intervals as well as fixed versus variable intervals is warranted. Along those same lines, the
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withdrawal of the I-Connect intervention did not result in an immediate return to baseline levels of stereotypy but rather yielded a steady acceleration towards baseline. This points toward residual effects of the I-Connect intervention yielding some short-term maintenance. In addition to exploring variable prompt intervals, future research that explores variable schedules of SM intervention delivery and impact on maintenance would be beneficial. For instance exploration of SM intervention that begins with continuous self-monitoring and then fading intervention to a variable schedule to evaluate the effect on skill maintenance would be practically informative. Both participants in this study were able to read thus the program would likely not produce the same results for students with lower cognitive functioning and absence of literacy skills. One plausible solution for this is modifications to the I-Connect program that allows for the use of picture and/or symbol prompts rather than words. Future research should explore the functional relationship between the use of I-Connect or a modified I-Connect and decreases in stereotypy for highly impacted students. The use of I-Connect to increase a variety of target behaviors such as social-communication, engagement, and academic responding for students with ASD should also be explored. Acknowledgments The authors disclosed receipt of the following financial support for the research, and/or publication of this article: This research was supported in part by grants from the U.S. Department of Education, Institute of Education Sciences (R324B100004), the National Institute on Disability and Rehabilitation Research (H133A130032), and the Office of Special Education Programs (H327A100082). The opinions expressed in this article are not necessarily reflective of the positions of the U.S. Department of Education. This research was supported in part by the Research Grant No. H133A130032, I-CONNECT PLUS: Enhancing Community Participation for Adolescents and Adults with ASD Using Online Instruction, Coaching, and Accessible Self-Management Technologies.
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