EXPLORING THE INCREDIBLE 5-POINT SCALE: IMPACT ON TARGET BEHAVIORS IN PRESCHOOL

In the following experimental study, a multiple-probe, single subject design (SSD) was used to evaluate the effectiveness of the Incredible 5-Point Scale (Buron & Curtis, 2012) as an intervention tool for a preschool aged child with developmental delays (DD). The scale, originally designed for individuals with Autism Spectrum Disorder (ASD) but found through noted experiences to have positive effects for individuals with other disabilities as well, is a teaching tool that aids teachers, therapists, and families in encouraging positive social and behavioral development in individuals (Buron & Curtis, 2012). While not an identified evidence-based practice (EBP) itself, the Incredible 5Point Scale does utilize many EBP in its implementation and development. Therefore, the purpose of this study was to determine the effectiveness of the scale in modifying the target behavior of a four-year-old male with DD by using visual analysis, percentage of nonoverlapping data points (PND), and percentage of data exceeding the median (PEM) to indicate whether or not the scale was effective. After the implementation of the intervention, the participant’s target behavior (inappropriate play with peers) decreased between baseline and intervention phases across all three activities. Practice and research implications as well as study limitations are discussed.

iii ACKNOWLEDGMENTS I would like to take the opportunity to thank Paul LaCava, my major professor, for his guidance and support. I appreciate the time he spent talking through different research ideas and making suggestions throughout the study. His commitment and expertise were invaluable to my work. I appreciate the encouragement he offered along the way.
Dr. Susan Zoll's kind words and encouragement motivated me along the way and helped me to see the vast opportunities this world and field have to offer. Thank you.
Thank you, Dr. Kathy Peno. I appreciated your honesty and willingness to spend time talking me through my work and providing your recommendations from a lens very different than my own.
Dr. Sue Adams has been an amazing support throughout the dissertation process, she offered wonderful advice and encouragement. Thank you.
Dr. Mark Medwid, thank you for taking the time to serve on my committee. I appreciated your questions and thoughtfulness as you considered my work.
Thank you to the professors of the URI/RIC PhD. program. Each course provided me the opportunity to expand my thinking about education, the world around me, and myself as an individual. I appreciate the insightful conversations we had during our class times and the thoughtful feedback on my work as I progressed through the courses.
To the 2015 cohort, I send them love. Each member of the cohort has forever changed me and I am eternally grateful for the friendships and family we have developed along the way. I look forward to seeing each individual's successes through the years and am quite positive that they all are going to shape and change the world in some way whether iv it be big or small. They each have the heart, tenacity, and grit to be the movers of our generation.
Thank you to my colleagues at Rhode Island College. Throughout my journey the members of my department have checked in and offered support and guidance along the way. Having such a lovely group of individuals to work with has truly been a blessing.
To my family I want to thank my mom, Luann McBride for teaching me that it is okay to be who you are meant to be and to never feel like a goal is impossible, rather a journey and a path that you choose to overcome and achieve. My dad, Dave McBride, I thank him for teaching me to always look at things through as many lenses possible; that I may encounter a problem but there is always a solution for overcoming it. My dad, Bob Herringshaw, I thank him, because he taught me that even the big choices, we make in life can be rewritten and that when you dare to change your mind and try again, the possibilities from the choices and changes we make are endless. My mom, Tammy Herringshaw, I thank her for teaching me acceptance and what it means to truly embrace and love the changes that shape our everyday lives.

The Use of Evidence-Based Practices and Interventions in Early Childhood Settings
Since the signing of the No Child Left Behind Act (NCLB) in 2001 there has been a strong emphasis on the use of evidence-based practices (EBP) in schools. Eighteen years later, researchers continue to collaborate with teachers in order to add to the literature and provide evidence for teaching techniques and interventions to be used in the classroom for children with and without disabilities. One specific intervention designed as a tool to modify target behavior and teach social competence is The Incredible 5-Point Scale (Buron & Curtis, 2012; see Figure 1).  Originally the scale was developed to aid in modifying target behaviors of children with Autism Spectrum Disorder (ASD). However, as the developers of the scale implemented it, they found that the scale also worked for children with other disabilities.

Selection of the Problem
One of the primary responsibilities of preschool teachers is to facilitate the development of social and emotional skills within a group of young children who have a wide range of developmental strengths and needs (Exforsys, 2006). This includes children that may have never been to school before, have disabilities, have unidentified disabilities, or are still naturally developing self-regulation and behavior skills (Dodge et al., 2008).  (Barnett et al., 2017).
Preschool aged children with and without disabilities are developing at different rates, therefore, in order to meet the wide range of student abilities teachers frequently implement behavior management techniques in their classrooms (Aspy & Grossman, 2007, Buron, & Curtis, 2012. This includes techniques that have been thoroughly researched, vetted, and used on a wide scale such as video-modeling and prompting as well as trying new behavior management tools and techniques such as the Incredible 5-Point Scale, that have not gone through the rigor of multiple research studies. Moreover, current legislation (Individuals with Disabilities Education Improvement Act [IDEIA;2004] and the Every Student Succeeds Act [ESSA;) continue to require the use of EBP in classrooms.
Each study utilized to provide evidence for an intervention as an EBP must meet rigorous guidelines to ensure that data is valid and reliable in order to provide support for the effectiveness of the intervention (IDEA'04 Research in Inclusive Settings [IRIS] Center, 2018). Many professional organizations such as the Council for Exceptional 4 Children (CEC) set forth specific quality indicators for the rigor of studies to determine whether or not they qualify as a study to support the literature on the specific practice or intervention (CEC, 2014). The CEC has further developed specific guidelines that are used to determine whether an intervention meets the threshold of the number of quality studies to determine whether or not it can be considered an EBP (CEC, 2014).
Through the use of task analysis, the Incredible 5-Point Scale is a tool designed to be utilized by teachers, parents, and other professionals to address issues of social competence. The scale is developed by determining a target behavior and breaking it into five points (or tasks) in order to modify the identified target behaviors (Buron & Curtis, 2012;Coffin & Smith, 2009). Although the Incredible 5-Point Scale includes evidencebased techniques the scale itself has not been documented in published, empirical studies nor has it been accepted as an EBP. Therefore, per current educational policies (IDEIA [2004] and ESSA [2015]), the Incredible 5-Point Scale cannot be utilized as an official EBP listed on students' individualized education programs (IEP). The intent of the present study is to contribute evidence to begin to enable stakeholders to determine their confidence in the Incredible 5-Point Scale as an EBP.

Statement of the Purpose of the Study
The purpose of this single-subject, multiple-probe design study was to explore the extent of the effectiveness of the Incredible 5-Point Scale as it relates to addressing target behaviors in preschool children with Developmental Delays (DD). With the current emphasis on EBP another study purpose is to begin the empirical study of this tool.

Introduction
What follows are the theoretical and conceptual frameworks that drive the study and elements that attribute to the behaviors of preschool-aged children with and without disabilities. Also included will be discussion surrounding current behavior interventions used in preschool classrooms that are relevant to the Incredible 5-Point Scale, information regarding the scale, and a description of SSD research and its importance to determining EBP.

Theoretical Framework
In the Special Education field, several theories have been developed to help understand the behaviors of individuals from different disability categories.
Unfortunately, many of these theories approach disability from a deficit model of thinking. For example, the Child Saving (CS) Theory was devised under the premise that children with disabilities needed to receive therapy in order to participate in society and lead normal lives. From this theory, the concept of moral therapy was introduced to the field of special education. Due to the delivery method of moral therapy the development and increased use of institutions for individuals with disabilities was encouraged.
According to Trent, Artiles, and Englert (1998), there is evidence of practices surrounding CS as far back as the early 1800's into the early 1970's. Trent et al. mention several theories regarding disability (psychological process model, cognitive strategy model, and the behavioral model; p. 283). In their argument against these models Trent et al. state that they were deficit models designed to focus on the etiology and symptoms of 8 the disabilities, rather than focusing on the strengths individuals with disabilities have (Trent et al., 1998).
As the present study was developed and the linkages between the typical development of preschool-aged children and the common characteristics of individuals with ASD became clearer, the researcher began to consider theories specific to individuals with ASD. Multiple explanatory theories regarding individuals with ASD exist today. Unfortunately, many of the theories (mind-blindness theory/theory of mind developed by Baron-Cohen in1999, executive dysfunction theory developed by Pennington & Ozonoff in 1996, and weak central coherence theory developed by Frith in 1989 to name a few [Baron-Cohen, 2009]) like the original disability theories, utilize a deficit model approach to explaining the behaviors of individuals with ASD. The following is a review of several theories that were considered for the theoretical framework of this study.
The first theory that will be discussed is the Weak Central Coherence (WCC) Theory. Frith (1989) postulated that central coherence is one's ability to understand the big picture of the world around them; individuals with weak central coherence have a difficult time understanding the larger schema surrounding them and tend to focus on one aspect of the whole (Frith, 1989;Interactive Autism Network, n.d.). Preschool aged children are in the preoperational stage of Piaget's theory of cognitive development. Like individuals with WCC, preschoolers in the preoperational stage focus on the small parts of the big picture or one thing at a time in order to navigate the world around them (Dodge et al., 2008).
Similar to Piaget's preoperational stage of cognitive development, the context of WCC is that individuals with ASD have great attention to detail (Baron-Cohen, 2009).
While Baron-Cohen views this attention to detail as a strength in individuals with ASD he states that according to supporters of WCC, individuals with ASD are seen as being "forever lost in the detail..." (Baron-Cohen, 2009, p.74) while never achieving "...an understanding of the system as a whole" (Baron-Cohen, 2009, p. 74). This deficit model of thinking limits the development of interventions and practices for children with ASD and emphasizes what they are unable to do rather than focusing on any strengths that may provide insight to appropriate ways of providing services and supports to children with ASD. Therefore, WCC was not selected as the theoretical framework for this study.
The second theory, Executive Dysfunction (ED), stresses the lack of executive functioning skills individuals with ASD present. Executive function (EF) is defined by Rao, Mysore, and Raman (2016) as "an umbrella term for functions such as planning, working memory, impulse control, inhibition and shifting sets, as well as the initiation and monitoring of action" (p. 171). Cooper-Kahn and Dietzel (n.d.) similarly define EF as "a set of processes that all have to do with managing oneself and one's resources in order to achieve a goal. It is an umbrella term for the neurologically-based skills involving mental control and self-regulation" (Cooper-Kahn & Dietzel, n.d., A formal definition of executive functioning, para. 1).
According to the work of the Center for Development of the Child at Harvard University, EF is necessary for controlling behaviors, remembering information, and focusing (as cited in Jackman et al., 2015). Due to the pervasiveness of behaviors such as decreased ability to plan and organize, self-regulation, and working memory in individuals with ASD, some researchers believe that ED is a primary feature of ASD (Kriete & Noelle, 2015;Wong, 2004), and there is a common belief between some theorists that abnormalities of the prefrontal cortex may be the cause of some prevalent behaviors attributed to EF in individuals with ASD (Kriete & Noelle, 2015;Wong, 2004).
Authors identify three specific areas of executive functioning; 1) attention control, 2) goal setting, and 3) cognitive flexibility (Dichter et al., 2010;Kriete & Noelle, 2015;Rao et al., 2016;Wong, 2004). Attention control is one's ability to sustain attention and to selectively focus attention on an individual or situation. Cognitive flexibility considers an individual's working memory and the ability to self-regulate as well as shift attention and focus or the ability to transfer concepts from one context to another. Goal setting is the ability to plan and organize ideas, actions, and behaviors (Rao et al., 2016, p. 171).
According to the developmental continuum for preschoolers as presented by Dodge et al. (2008), there is significant evidence of the development of EF in preschool aged children. During preschool, young children are developing the ability to sustain attention to tasks for longer periods of time and show flexibility and persistence in activities and tasks. Additionally, there is a developmental focus on self-regulation skills (Dodge et al., 2008). Rao et al. (2016) note that "impairments in EF abilities have been widely reported in children with autism and appear to account for many of the features including the varied adaptive behaviour profile and restricted, repetitive behaviours" (p. 175). While ED theory aims to explain why individuals with ASD tend to perseverate on specific behaviors or a lack of working memory, it does not encompass the strengths of individuals with ASD and is narrowly focused, therefore, ED theory was not selected as the theoretical framework for this study.

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The third theory that will be discussed is Mindblindness Theory. Mindblindness Theory was developed by Baron-Cohen in 1990 and is based on the premise that individuals with ASD lack or have an impaired Theory of Mind (ToM; Baron-Cohen, 2009). According to Smuckler (2005), ToM is "a person's awareness and understanding that he or she, and other people, have thoughts, beliefs, desires, intentions, feelings-the full range of mental states" (p. 12). This aligns with Piaget's preoperational phase in that children in the preschool years are very egocentric. They have difficulty seeing things from the point of view of others. This is a skill that develops as children mature (Dodge et al., 2008). Similarly, mindblindness operates on the notion that individuals with ASD "lack this awareness and understanding and, therefore, cannot "mindread," or easily and automatically interpret the mental states of others, a talent that is presumed to come naturally to non-autistic people" (Smuckler, 2005, p. 12). Baron-Cohen (2009) conceptualizes ToM as being delayed in individuals with ASD and limiting an individual's ability to interact appropriately in social situations because he/she does not understand the nuances of others' behaviors.
Mindblindness Theory is beneficial because it considers the individuals social aptitude separately from his or her IQ and it provides one explanation as to why individuals with ASD have delayed social development ( Baron-Cohen. 2009 ToM and EF specific to inhibitory control in children with ASD between the ages of three to five (Wong, 2004). While Mindblindness and ToM are able to explain some behavioral characteristics of individuals with ASD, important concepts such as the need for consistency and rules are missing within the theory as it relates to preschool-aged children and individuals with ASD or DD. ToM looks at ASD through a deficit lens, therefore, it was not selected as the theoretical framework for this study.
The fourth and final theory that will be discussed is the Empathizing-Systemizing  Baron-Cohen (2009) labeled two brain types, the female brain as empathizing and the male brain as systemizing. He believed males tended to be more systematic while females were more empathetic (Baron-Cohen, 2009;Interactive Autism Network, n.d.). He argues that while in the typically developing population individuals have a shared brain type, they do tend to align with the identified gendered characteristics, and individuals with ASD tend to be stronger at systemizing (i.e., the male brain type; Baron-Cohen, 2009).
Although ES theory has some focus on the strengths of individuals with ASD and attempts to provide an explanation for the difficulty individuals with Autism have in empathizing with others there is some pushback surrounding the theory. After evaluating the theory, one individual with ASD considered the continuum Baron-Cohen developed to determine the level of empathizing (E) and/or systemizing (S) in a person. On the continuum, if you have E tendencies you will be further away from S and vice versa (Eartharcher, 2017). According to Eartharcher (2017), as an individual with ASD, she sees a flaw in this, as she does not believe that one is exclusive of the other and that the two can be separate and function well separately. However, ES is unique in that it addresses both the social (empathy) and nonsocial (systemizing) context of ASD (Baron-  (Buron & Curtis, 2012). Furthermore, due to the development occurring in children ages three to five, the preschool curriculum emphasizes social and emotional development (including the development of empathy), self-regulation, and the ability to follow multiple step directions and rules (Dodge et al., 2008;RIDE, 2013

Conceptual Framework:
The conceptual framework for this study, behavior therapy (BT), also known as behavioral psychotherapy, focuses on changing the behavior of an individual through the utilization of learning techniques (Bothamley, 2002). BT was selected as the conceptual framework for this study as it provided a guide for how to implement the intervention with the participant. Spiegler (2016) proposes four themes defining behavior therapy; scientific, active, present focus, and learning focus. The first theme is scientific which considers the importance of empirical studies and precision in the development and delivery of interventions. There is also a strong focus on data collection throughout the therapy.
The second theme is the active theme. This theme emphasizes doing as opposed to solely speaking about the issues that one is encountering. For example, having the child slowly encounter situations where he is separated for short periods of time from his parents if he has issues of separation anxiety. There are several EBP utilized in order to do this and they include reinforcement-based approaches, problem-solving training, operant and classical conditioning, and behavioral rehearsal (Antony & Roemer, 2011).
In the present study, several EBP will be used including operant conditioning through direct instruction, prompting, behavioral rehearsal, and visual cues.  Figure 2).
Spiegler (2016) discusses the importance of the therapist-client relationship. It is necessary for the person delivering the intervention (the teacher) and the individual participating in the intervention (the student) to collaborate with one another as the therapist facilitates the procedures (Spiegler, 2016). Antony and Roemer (2011) identify seven characteristics that behavior therapists adhere to as they consider their work in BT, and each characteristic plays a critical role in ensuring the success of the method. Figure   3 provides Antony and Romer's (2011) seven characteristics of BT as well as how the researcher maintained the integrity of BT in the present study.

Evidence-Based Practices (EBP)
Over the last two decades there has been an increased interest in the use of EBPs (a) Must be supported by at least two methodologically sound group comparison studies with random assignment to groups, positive effects, and at least 60 total participants across studies; four methodologically sound group comparison studies with non-random assignment to groups, positive effects, and at least 120 total participants across studies; or five methodologically sound single-subject studies with positive effects and at least 20 total participants across studies; OR (b) Meet at least 50% of criteria for two or more of the study designs described in (a). For example, the practice is supported by one methodologically sound group comparison study with random assignment, positive effects, and at least 30 total participants, as well as three methodologically sound single subject research studies with positive effects and at least 10 total participants; or three methodologically sound single-subject studies with positive effects and at least 10 total participants, as well as two methodologically sound group comparison studies with nonrandom assignment, positive effects, and at least 60 total participants; AND

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In addition to determining the classifications and guidelines for an intervention or teaching technique/tool to become an EBP the CEC also provides quality indicators for individual studies. The quality indicators determine whether or not an individual study meets the appropriate rigor for consideration in a literature review to determine the efficacy of the intervention or teaching technique/tool. The type of study performed is critical to determining whether or not it will be used when determining the efficacy of a specific intervention. All studies must be experimental in nature and can be group or single subject designs (CEC, 2014). As a rigorous, experimental design, single-subject research has provided a great deal of insight to the field of education regarding EBP (Horner et al., 2005). According to the CEC (2014), in order for a study utilizing a SSD including multiple-probe design to meet the appropriate rigor and provide support for an intervention as an EBP it must meet specific indicators within eight areas (context and setting, participants, intervention agent, description of practice, implementation fidelity, internal validity, outcome measures/dependent variable, and data analysis) addressed in In their comprehensive review of the literature on EBP utilized when working with individuals with ASD, Wong et al. (2015) identified two primary types of practices considered in the research regarding EBP, comprehensive treatment models (CTM) and focused interventions. CTMs are identified as being organized around a conceptual framework and designed to impact broad learning or development (Wong et al., 2015), whereas according to Odom, Collet-Klingenberg, Rogers, and Hatton (2010), focused interventions are designed to impact a "specific skill or goal of a student..." (as cited in Wong et al., 2015). CTMs are generally used to address multiple outcomes and therefore 23 are implemented over a longer span of time while the primary purpose of focused interventions rests on one skill/goal and therefore are implemented for a shorter time (Wong et al., 2015).
During their review of focused interventions, Wong et al. (2015) determined 27 interventions for working with individuals with ASD that met the rigor necessary to be considered EBPs (Wong et al. 2015). The article further divided the interventions by the ASD, studies solely focused on children with DD are limited at this time (Mattern, 2015).
Therefore, the overall lack of research for interventions for children with DD and the continued interest and importance of the use of EBP in educational settings further necessitates this study.
Young children develop rapidly and professionals working with preschool aged children need to be knowledgeable of typical preschool development. The curriculum for children birth to five is designed using a developmental continuum (Beaty, 2014;Dodge et al., 2008;RIDE, 2013). During the preschool years (ages three to five) there are four primary developmental domains that professionals plan for; 1) social/emotional (SE), 2) physical, 3) cognitive, and 4) language (Dodge et al., 2008;NAEYC, 2009). When educators are aware of typical development, they are able to utilize observations to identify what is happening when a child exhibits a behavior that may be challenging and draw conclusions as to whether or not the behavior is typical behavior expressed by three to five-year-olds. Professionals then use EBP such as a functional behavioral analysis (FBA) to identify the purpose of the behavior in order to develop and implement an intervention that is appropriate to the child's needs (Dodge et al., 2008;Jackman et al., 2015;NPDC, 2018). Two domains, SE and cognitive development, are discussed as they relate to behavior development in preschool aged children (Dodge et al., 2008).
Development occurs in the SE domain through the "child's sense of self… taking responsibility for self and others…(and) behaving in a prosocial way" (Dodge et al., 2008 p.19). Some items seen on the preschool developmental continuum include, learning how to regulate behaviors, following rules and routines, expressing empathy, and solving conflicts (Dodge et al., 2008;RIDE, 2013) which are developmental milestones that we also see within the theories relevant to ASD. Some specific characteristics we see in preschool aged children as it relates to SE development are the following: at three children enjoy receiving praise and attention for the behaviors and skills they are exhibiting (Dodge et al., 2008, p. 23). Four-year-old children become more social and enjoy making friends. They want to know you are paying attention to them and seek out reinforcement for their behaviors (Dodge et al., 2008 p.24). Five-year-old children tend to be very social and are generally able to have close friendships with other children (Dodge et al., 2008;Jackman et al., 2015).
Self-regulation and social skills rapidly develop during the preschool years.
Prompting (PP) is implemented by providing a prompt for a desired behavior and the prompt can be verbal, physical, visual, or gestural and can be provided by an adult or peer (Biederman, Fairhall, Raven, & Davey, 1998;Brown & Conroy, 2011;NPDC, 2018;Snodgrass, Meadan, Otrosky, & Cheung, 2017;Wong et al., 2015). After the prompt is given the child receiving the prompt is expected to exhibit the desired behavior (Biederman et al., 1998;Brown & Conroy, 2011;Snodgrass et al., 2017;Wong et al., 28 2015). For example, a teacher may say to a student, "What do we say when a friend helps us?" and the child should respond by saying "thank you".
Social narratives (SN) often called Social Stories™, are brief stories describing a situation one may encounter with other individuals. The story details an interaction and the appropriate behavior that should follow (Bayat, Mindes, & Covitt, 2010;Jones & Keiper, n.d.;NPDC, 2018;Wong et al., 2015). Through the use of techniques like role playing and play, social skills training (SST) educators teach children with ASD how to appropriately interact with other individuals (NPDC, 2018;Wong et al., 2015). Video modeling (VM) is similar to a social narrative in that a scenario is provided to a child demonstrating the desired target behavior, however, rather than a story being read aloud to the child a video of the scenario is played for the child to watch (Wong et al., 2015; NPDC, 2018; Center on the Social and Emotional Foundations for Early Learning [CSEFEL], n.d.). It's important to note that many of these interventions are also used in modifying behaviors through the other developmental domains.
Cognitive development also has a critical impact on a child's behavior development. As children begin to develop cognitive processes, they can start taking the perspectives of others, have stronger problem-solving abilities, and are able to create solutions in new contexts using prior information and experiences (Dodge et al., 2008;RIDE, 2013). When considering preschool-aged children, typical characteristics of cognitive development include egocentrism in three-year-olds however, they can show empathy to others (Dodge et al., 2008, p. 24). Four-year-old children often have a difficult time differentiating between fact and fiction (Dodge et al., 2008, p. 24). Due to this we may notice children begin to 'lie', however, often children at this age do not 29 understand or realize that they are lying (Dodge et al., 2008, p. 25). Five-year-old children are making connections between their experiences and generally have better problem-solving skills (Dodge et al., 2008, p. 26).
According to information reported by CDCHU (2011), the preschool years see extreme development in executive functioning (as cited in Jackman et al., 2015). As we consider the typical development of preschool aged children, it is also pertinent, at this point to think back to the information presented on ToM and EF. In a review of the literature Wong (2004) discussed that research generally shows an improvement in ToM and EF specific to inhibitory control in children with ASD between the ages of 3 to 5 (p. 54). Further emphasizing this point, Kriete and Noelle (2015) share that "in young children with autism, executive abilities appear developmentally appropriate when compared with controls matched for age and verbal ability" (p. 2).
Executive functioning and the ability to regulate one's behaviors are an essential developmental component in the preschool years. Often, children with DD demonstrate difficulty in these areas and EBPs are utilized to encourage development of these skills.
EBPs commonly used in preschool to aid in cognitive development include but are not limited to discrete trial training, pivotal response training, self-management, and task analysis (NPDC, 2018;Wong et al., 2015). Discrete trial training (DTT) requires a service provider (be it teacher or other specialist) to work with a child on a series of trials consisting of instruction for appropriate target behavior, evaluation of the child's response, implementation of a consequence dependent upon the child's response, and a break between the end of the trial and presentation of the next trial (Wong et al., 2015).
Pivotal response training (PRT) relies on the use of learner motivation.
Delivered in a play therapy environment, interventionists incorporate the interests of the child into the therapy in order to motivate him/her to perform specific tasks. PRT is often an intensive intervention for children with ASD, provided 25 hours a week (Autism Speaks, 2018;Wong et al., 2015). Self-management (SM) is an EBP utilized to encourage the child to discriminate between desirable and undesirable behaviors.
Children are taught to monitor and reward themselves for their behavior (Wong et al., 2015).
During preschool children learn how to follow a series of instructions. In order to do so directions are broken down into smaller tasks. Task analysis (TA) is another EBP utilized in preschool settings for children with a variety of disabilities (NPDC, 2018;Snodgrass, et al., 2017;Wong et al., 2015). TA is beneficial as it is developmentally appropriate for preschool aged children and it aligns with Baron-Cohen's ES theory in that individuals with ASD perform better by creating systems in their environments. Wong et al. (2015) define TA as "a process in which an activity or behavior is divided into small, manageable steps in order to assess and teach the skill" (p. 1960). Like the EBPs mentioned previously these four interventions can be utilized across the developmental domains in preschool and are not solely limited to the cognitive domain.
As preschool children with and without disabilities develop their ability to understand rules and regulate their own behaviors, they need time to adjust to change (Jackman et al., 2015, p.88). They benefit from the use of visual aids to help form understanding (Beaty, 2014) and from schedules and routines as it provides them with security and helps to build trust (Beaty, 2014;Connors-Burrow, Patrick, Kyzer, & McKelvey, 2017;Dodge et al., 2008;Jackman et al., 2015;NAEYC, 2009). Moreover, it is well known that the earlier interventions begin for children with exceptionalities such as ASD or DD the better the overall outcomes (Gillis & Butler, 2007;Menzies & Lane, 2011;Reynolds et al., 2017;Ritblatt et al., 2017).

Developmental Delay
In order for most individuals to receive educational services and supports through IDEIA they must qualify under one of the thirteen eligibility categories (deaf-blindness, ASD, emotional disturbance, intellectual disability, hearing impairment, deafness, visual impairment, traumatic brain injury, multiple disabilities, speech or language impairment, specific learning disability, other health impairments, or orthopedic impairment).
However, in the late 1980s early 1990s, parents and professionals began to become concerned about the overall developmental impact and stigma associated with labeling children at such a young age. Taking that into consideration, during the 1991 reauthorization of IDEA (the law became IDEIA in 2004) states were granted a special provision that allowed them to utilize more generic terms for identifying and providing eligibility to young children (three through nine years old) (Allen and Cowdery, 2015;Deiner, 2013;Gargiulo, 2015;Gargiulo & Kilgo, 2014). Then, during the 1997 reauthorization of IDEA, the common term, developmental delay (DD) was established (Deiner, 2013). One of the stipulations of the new adoption was that states could choose whether or not they wanted to include DD as an eligibility category; forty-two of the fifty states currently recognize the term (Gargiulo & Kilgo, 2014).
Upon authorization, the federal government required states that chose to use the more generic terms develop their own definitions and eligibility criteria to qualify for 32 services and supports under IDEIA for DD (Gargiulo & Kilgo, 2014). Moreover, once a state decided to use DD as a form of eligibility for services, an additional provision was that school districts were able to choose whether or not they too would accept the term (Learning Disabilities Association of America [LDA], n.d.). Early childhood education licensure in which the study took place, covers the span of preschool through eight years old and therefore has limited eligibility for DD to children three through eight. [Masked] Department of Education's (n.d.) eligibility criteria for DD follows: twenty-five percent (25 percent) delay and/or score equal to or greater than two standard deviations below the mean in one of these areas of development listed below; or a score equal to or greater than 1.5 standard deviation below the mean in two or more of the following areas: physical development, cognitive development, communication development, social or emotional development, and/or adaptive development. (p.6).
In order to diagnose a child as having DD specialists utilize norm-referenced tests such as the Bayley Scales of Infant and Toddler Development (Currie et al., 2012). Due to the broad definition and purpose of the label developmental delay, characteristics of individuals with DD vary greatly. According to Singh and Umakant (2018) when a child has a developmental delay, we see a significant lag involving developmental "domains such as physical, communication, problem solving and personal and social areas…" (p. 234). Often children with DD experience issues with social competency (Lewallen & Neece, 2015) and present with behavioral disorders. Brown and Conroy (2011) assert children with developmental delays "display chronic problem behaviors that affect their performance" (p. 313). As children age developmental delays are often relabeled as an 33 intellectual disability (Deiner, 2013). However, as a child grows and develops, natural development and maturation or the interventions provided to the child may have a significant enough impact that the child no longer needs nor qualifies for special education services.
The educational research supporting EBP for DD is growing, however, at this time is fairly limited (Mattern, 2015). Information we have indicates a strong positive correlation between early intervention services and developmental outcomes for children labeled as having a DD (Mattern, 2015;Singh & Umakant, 2018). During the early childhood years development is tracked through a developmental continuum. Atypical development in children does not follow the continuum therefore, early intervention services are recommended in order to reduce the impacts of any possible delays (Mattern, 2015). Furthermore, Gillberg (2010) states "early disorders such as DD, whether global or specific, requires that care should be given to the composite of deficits rather than to any well-defined developmental domain, at least until the specific nature of the deficit becomes dominant" (as cited in Levy, 2011, p. 182 (2018) is that there should be strong coordination between the school and home. Singh and Umakant (2018) state that this connection "demands designing an intervention program that includes as many facets of the child's life as possible" (p. 236).
Research identifies reinforcers, prompting, modeling, video modeling, specific verbal cues, and task analysis as common interventions utilized for children with DD (Biederman et al., 1998;Brown & Conroy, 2011;Cihak, Smith, Cornett, & Coleman, 2012; CSEFEL, n.d. ;Snodgrass, et al., 2017). The aforementioned practices align with the work of Wong et al. (2015) and the EBP utilized in the development and implementation of each individual Incredible 5-Point Scale, which also align with DEC recommended practices.
Overall, the research regarding DD is fairly new in the field of education. While there is limited research available (Mattern, 2015), evidence does point to the efficacy of common interventions such as social stories/narratives, prompting, visual cues, and video modeling (Biederman et al.,1998;Brown & Conroy, 2011;Cihak et al., 2012;CSEFEL, n.d.;NPDC, 2018). The limited research in the field surrounding DD is an additional indication of the importance of the present study and its possible implications to the field of early childhood special education.

The Incredible 5-Point Scale
One quick search for the Incredible 5-Point Scale on Twitter will show a person that 1) the Incredible 5-Point Scale is widely used both domestically and internationally, and 2) that individuals using the scale love the results they are getting (Twitter, 2019). it is beneficial to the social emotional development and learning of young children as it provides a sense of security and control as it enables children to predict what will occur next in their environment (Dodge et al., 2008;NAEYC, 2009).
In order to make rules for a system an individual must take one activity and break it into manageable tasks. The Incredible 5-Point Scale takes advantage of this strength and provides a visual representation of a target behavior to define rules for interacting with others or the environment, or resolving issues concerning the behavior (Buron & Curtis, 2012). For example, if there is a child in the classroom who is unable to control his or her voice volume, a teacher may implement the scale demonstrating that a one is no talking, a two is whispering, a three is a conversational voice and so on.
For the scale to be successful it is important for the interventionist (whether it be a teacher, family member, or other professional) to know how to use it with fidelity. To start, the interventionist needs to determine the target behavior. That means figuring out what the person is currently doing and what it is that the interventionist feels he/she should be doing (Buron & Curtis, 2012). Once the problem has been identified it is critical to figure out what the individual needs to be taught to be successful. After the interventionist has determined what the problem is and what needs to be taught it is time to systemize the behavior by breaking it down into five manageable and understandable levels (Buron & Curtis, 2012).
The scale can be created by the interventionist but there is some evidence that cocreating the scale with the individual who it is being created for is beneficial (Buron & Curtis, 2012). A modified Incredible 5-Point Scale designed for a preschool aged child with three points. (Buron & Curtis, 2012). The interventionist will work one-on-one with the student and use direct teaching to describe, explain, and check for understanding of the scale.
As the interventionist is teaching the scale, he/she as access to a variety of methods to further understanding of the scale. First, creating the scale with the student helps him/her to have a stronger understanding because his/her words are being used for each component (Buron & Curtis, 2012). Another method to deepen understanding of the scale is through the use of a story (Buron & Curtis, 2012). Like any intervention, once the scale has been implemented it is important that it is used consistently (Buron & Curtis, 2012). A benefit of the Incredible 5-Point Scale is its flexibility of use. It can be adapted to meet the developmental needs of preschool-39 aged children. Preschool children with and without disabilities are developing the ability to follow multiple step directions and tasks. A developmentally appropriate expectation at this age is to follow two to three step directions (RIDE, 2013). While some preschool children would understand, and perform well with a 5-point scale, the Incredible 5-Point Scale can be modified to have three tasks to meet varying developmental needs (Buron & Curtis, 2012). Consider the voice volume scale example previously provided (See Figure   1); if the scale were adapted to have three points it would be appropriate for level one to be no voice or whispering, level two to be normal conversational voice, and level 3 an outside voice. The scale would still have five lines but only three would be utilized ( Figure 7 is an example of a comparison between the two options).
Buron and Curtis make the argument that if a three-point scale is utilized, but five levels are still visible, it makes the transition to a five-point scale easier as the child develops the ability to follow more directions and tasks (Buron & Curtis, 2012). An additional modification for preschool aged children is replacing the numbers with pictures of favorite characters or focus on the colors of the scale. Developmentally preschoolers are learning number recognition, so the use of numbers may or may not be beneficial depending on the child's level of development (Buron & Curtis, 2012, RIDE, 2013).
An additional benefit of the Incredible 5-Point Scale is its ease of use. The scale is often found in classrooms, however, with proper training it can easily be utilized at home and during sessions with specialists (Buron & Curtis, 2012). Again, consider the noise volume example, if families, teachers, and therapists work together to determine appropriate noise volumes and levels on the scale they can all implement the scale in their settings. The teacher, therapists, family members, and the child are both able to utilize the scale as a means of consistently communicating expectations and/or how the child may be feeling (Buron & Curtis, 2012). This provides consistency between settings and aligns with preschool aged children's developmental need for rules and routines (NAEYC, 2009).

Single-Subject Design
For over a century, single subject design (SSD) studies (also known as single case) have been conducted as an experimental design method that provides researchers with evidence for causal relationships between an intervention and its effectiveness (Kazdin, 2011). They are commonly utilized in applied research in the fields of psychology and education (Kazdin, 2011;Wong et al., 2015) in order to either "reduce behaviors associated with impairment" (Kazdin, 2011. p. 3) or "increase behaviors that improve functioning" (Kazdin, 2011. p. 3). They provide "A flexible alternative to traditional group designs in the development and identification of evidence-based practice…" (Byiers, Reichle, & Symons, 2012, p. 397) and can "lead to causal knowledge about the impact of the intervention" (Kazdin, 2011, p. vii). SSD relies on the observation of specific target behaviors before and after an intervention is implemented.
There are five general requirements that all SSD types follow; 1) continuous assessment: the researcher observes the participant(s) multiple times over time, 2) baseline assessment: this information is gathered prior to intervention to determine the behavior and to predict future behavior, 3) stability of performance: the baseline should be stable prior to the implementation of intervention, 4) trend in the data: once the intervention has been implemented there should be a trend in the target behavior, it could stay the same, improve, or get worse with the intervention, and 5) variability in the data: in SSD too much variability may show that the intervention was ineffective, it is preferable to see a stable trend (Kazdin, 1982, pp.104-109).
There are five designs primarily utilized in SSD: pre-experimental, withdrawal, changing-criterion, multiple-treatment (alternating treatments or adapted alternating treatments), and multiple-baseline (Byiers et al., 2012;Kazdin, 2011). Prior to implementing a SSD study the researcher needs to determine the research question, participants, behavior, and intervention in order to select the appropriate design for the study. Therefore, it's especially important to have an understanding of the purpose and pros/cons of each design type.
The first design type, the pre-experimental type follows an AB model. This means that the model is designed for the researcher to gather baseline data (A) and then treatment data (B). While this method can provide a researcher with preliminary information regarding an intervention it does not provide experimental control and is therefore considered pre-experimental (Byiers et al., 2012). AB designs are frequently used in schools because they are easy to implement and can provide some data for educators as they incorporate interventions into their classrooms. The remaining SSD types implement a variety of experimental methods which provide researchers options in the design of their studies based on the needs and purpose of the particular research question(s), setting(s), and/or participant(s) being observed. The SSD types will be discussed below.
The second SSD type, withdrawal design or ABA/ABAB, allows for experimental control in that an initial baseline (A) is gathered, intervention (B) is implemented, intervention is removed and new baseline (A) data is gathered, and in some studies intervention is re-implemented (B) to gather an additional data set. This provides experimental control in that after achieving a trend with the intervention it is removed and the participant is observed to determine if the behavior has changed with the removal of the intervention (Byiers, et al., 2012;Kazdin, 1982;Krishef, 1991). In order to meet the WCC standard without reservations, there should be a minimum of five data points in each phase (Byiers, et al., 2012;Kratochwill, et al., 2010).

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There are generally two methods to implement ABA/ABAB designs, and these are withdrawal design and reversal design. Withdrawal design is simply removing the intervention and gathering data over a certain time. If the behavior does not return to baseline then it is determined that either the intervention was not effective because the individual does not need the intervention to continue appropriate behaviors or, in some cases it may be determined that the behavior addressed in the intervention cannot be unlearned and therefore the intervention was effective. The general premise is that if the behavior returns to baseline without the intervention it can be determined that the intervention was effective (Byiers, et al., 2012;Kazdin,1982;Krishef, 1991).
Reversal designs require the researcher to attempt to reverse the effects of the intervention (Byiers, et al., 2012). When studies re-introduce the intervention and behaviors once again change after returning to baseline there is further evidence to support the effectiveness of the intervention (Byiers, et al., 2012;Kazdin,1982;Krishef, 1991). While ABAB designs are generally very strong experimental studies one thing researchers need to consider is whether or not the behavior being taught is reversible. If it is not reversible than the study functions more like an AB design because during the 3rd phase of the study (ABA) behavior will not return to baseline (Byiers, et al., 2012).
One final consideration of an ABAB design is that there is some ethical consideration and hesitancy in removing an intervention that has been effective for an individual. In some cases, such as an intervention that has shown efficacy in decreasing self-injurious harm or harm to others, the removal of the intervention would be unethical, therefore, the research team should consider an alternative single-subject design type that does not rely on the 44 removal of the intervention (Byiers et al. 2012). Due to ethical considerations regarding the removal of intervention, an ABAB design method was not selected for this study.
The third design type is the changing-criterion design. The changing criterion design does not require withdrawal from the intervention rather the intervention is designed to change behavior in increments (Kazdin, 2011). For example, if a teacher is trying to increase the amount of time a child spends actively engaged in an activity the teacher will gather baseline data to determine a stable baseline for the amount of time engaged. Next, the teacher will determine an intervention, generally a reward of some sort, for meeting the specific criterion (Byiers, et al. 2012;Kazdin, 2011). The teacher will set a specific time, let's say three minutes, for engaging in the activity, and once the participant has at least three stable data points (five are better) for three minutes of engagement the teacher will change the time to seven minutes, and so on. The increments of intervention serve as subphases of the intervention and the control for the study (Kazdin, 2011). At least two subphases should occur, however, three or more provides for a more rigorous study (Kazdin, 2011).
While most changing criterion designs utilize specific points (such as three minutes engagement for criterion one, and seven minutes engagement for criterion two) one variation to the design called the range-bound changing criterion design allows researchers to focus on a range to meet criteria (Kazdin, 2011). For example, in intervention subphase one, the child may need to show they are engaged for three to five minutes at a time, and if the child falls within that range he/she receives the intervention (reinforcer); once the child shows stability with the range in phase one it is then increased to a new range for subphase two and so on. According to Kazdin (2011), a limitation to 45 the changing criterion design is in the level of change. If the change occurs too quickly or too slowly there may be difficulty in drawing inferences from the data, rather the ideal model shows a step-like change in the data (p. 186). Due to the nature of the participant's behavior a changing criterion design would not have been feasible for this study.
The fourth SSD model is the multiple-treatment design. The multiple treatment design allows the researcher to change the intervention after one phase of intervention has been completed. This change can be simply modifying the treatment being used in some way or it can be implementing an all new treatment with the participant. In the literature we see the multiple treatment design written as ABACAC (Byiers, et al., 2012). This design is implemented similarly to an ABAB design, however the baseline (A) directly following the intervention is a withdrawal period from the first intervention.
Once a stable baseline has been met then the new intervention (C) is introduced. A CAC model then follows. For example, in a preschool classroom a teacher may be having a difficult time getting a student to clean-up after center time. The researcher would take baseline data and then implement an intervention, such as modeling. After adequate intervention data is collected the intervention would be withdrawn until the participant went back to a stable baseline. Then, a different intervention would be implemented, such as prompting. A baseline and intervention phase would follow (Byiers, et al., 2012).
There are several variations of this SSD model. One of the variations is the alternating treatments or adapted alternating treatments. In this model researchers implement more than one intervention; however, the implementation is started on the same day but at different times. For example, if a child has a difficult time cleaning up 46 his/her mess in all settings within the classroom the teacher may implement the first intervention (modeling) during centers and the second intervention (prompting) during snack time. The next day prompting may occur during centers while modeling occurs during snack.
One advantage of using a multiple-treatment design is that in some cases, the intervention does not have to be withdrawn. A limitation to the multiple-treatment design is the possibility for multiple-treatment interference. When multiple treatment interference occurs, it is because on treatment had an impact on the other, this makes it difficult to make conclusions about the data (Byiers, et al., 2012). A multiple-treatment design was not selected for this study because the study was only incorporating one intervention, the Incredible 5-Point Scale.
The fifth SSD model is the multiple-baseline or multiple-probe design. These two designs are very similar, with the main difference between the two designs being the number of data points that are collected and if the data is collected concurrently or not across phases. Data for both designs can be collected 1) across behaviors, 2) across settings (activities), or 3) across individuals. The across behaviors and across settings designs consider one individual and looks at developing an intervention for an individual across either different target behaviors or a singular behavior across settings (Byiers, et al., 2012;Kazdin, 2011). An across individuals design considers the same or similar behaviors perpetuated by two or more individuals (Horner et al., 2005;Kazdin, 2011;Krishef, 1991).
In all designs a baseline is gathered for the target behavior until it is stabilized and then the intervention is implemented with the first behavior, setting, or participant.

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After the behaviors stabilize the intervention is applied to the next behavior, setting, or participant and so on. The staggering of the intervention should show that the target behavior is not changing without the implementation of the intervention within a phase (i.e., intervention is implemented in snack time, meanwhile baseline continues to be gathered in center time, the behavior changes in snack time, but center time behaviors remain consistent); the importance here is that it is important that a therapeutic trend is occurring only within the phase receiving the intervention. This helps to prevent threats to internal validity (Horner et al., 2005;Kazdin, 1982;Krishef, 1991). Finally, data collection ends for all behaviors, settings, or participants at the same time (Horner et al., 2005;Kazdin, 1982;Krishef, 1991). To be valid, multiple probe designs require: 1) three or more behaviors, settings/activities, or participants, 2) that the baseline data collection begins at the same time across contexts, 3) the intervention is incorporated at different times, and 4) the data collection process ends at the same time for each context (Fraenkel et al., 2012;Horner et al., 2005;Kazdin, 1982;Krishef, 1991).
The benefits of multiple baseline or probe SSD studies include no need for withdrawal of the intervention and it's generally easy to implement the intervention because the intervention is applied to one behavior, setting, or individual at a time (Kazdin, 1982). According to Kazdin (1982), "the underlying rationale of single-case experimental designs is similar to traditional between-group experimentation. All experiments compare the effects of different conditions (independent variables) on performance" (p. 103) and "the goal is to convey the underlying rationale, the logic in relation to the goals of the scientific research, and strength and limitations" (Kazdin, 1982, p. 103). This design is appropriate to respond to the current research question because it enables the researcher to individualize the intervention while maintaining experimental control throughout the study. Moreover, this design was selected because it addressed the ethical issue of removing an intervention that had the potential of having a positive effect on the participant's social and emotional development and behavior management skills.

Chapter Summary
The literature review discussed the theoretical and conceptual frameworks that have guided the present study. Furthermore, information regarding evidence-based practices and preschool development and behavior management strategies were provided to give a reference to practices that are currently available and what educators know about preschool aged children with and without disabilities. While limited information is available regarding the Incredible 5-Point Scale it was important to discuss its development and current use in educational settings. Finally, the chapter was concluded with information regarding single-subject designs including their efficacy and different models specifically multiple-probe designs. The following chapter will discuss the methodology used in the present study.

Introduction
For the present study, the researcher utilized a multiple probe, single-subject design with one participant (Mason) across three activities (activity one-snack time, activity two- McBride signed a consent form. Due to the nature of the present study, a single-stage, purposive (non-randomized) sampling procedure (Creswell, 2014;Fraenkel et al., 2012) was utilized to determine which participants to recruit. Therefore, prior to providing recruitment fliers to families the researcher informed the teacher of the eligibility criteria for participants. To meet the criteria as a participant in the study the participant(s) had to 1) exhibit a target behavior  Table 1 were initially selected for the study. (In order to protect their anonymity, all participants and teachers were given a pseudonym).
After the study began and baseline data were collected it was determined that Ivan was exhibiting behaviors (loud voice) that mimicked the voice volume of classroom teachers and other students. Therefore, the study ended at baseline for him. Leo, Thiago,

Setting for the Study
The present study was completed during the 2018-2019 school year, in an inclusive preschool classroom at an urban, public school in southern New England. The school in which the study took place provides educational services to children from preschool through 5 th grade. There are approximately 480 students in the school and 33 teachers.
Of the 33 teachers there is one preschool classroom with one teacher and one paraprofessional. None of the teachers in the school are emergency certified and 96% of the teachers in the school are considered to be highly qualified (Infoworks, 2018). The preschool teacher, Ms. McBride, self-identified as a Hispanic/White, female. At the time of the study she was 31 years-old and had 10 years of early childhood teaching experience, and five of the 10 years were in early childhood special education programs.
She held a bachelor's degree in early childhood education, a master's degree in early childhood special education, and was considered highly qualified by the licensing state (McBride, personal communication, February 6, 2019).
Demographic information collected on families in this district showed that 72% of the student population was eligible for free and reduced lunch which indicated that many children come from low-income families. The students and families within the school were diverse. Approximately 49% of the students at the school were Hispanic, while 20% were African American, 17% were White, 9% were Multiracial, and 5% were Asian. The students in the preschool classroom were representative of the school's overall racial/ethnic population. Additional information indicated that 13% of the student population within the school received ESL/bilingual services and 9% of the student population received special education services (Inforworks, 2018). Two students in the preschool classroom were bilingual, however they were not receiving ESL/bilingual services. Due to the nature and purpose of an inclusive preschool classroom, there was a higher rate of children receiving special education services (50%) in the preschool classroom setting than the overall school demographics for special education services.
The classroom in which the study took place was a large room, on the first floor of the building. It had two entrances on the same wall. Directly opposite of the doors was a full wall of windows that stretched the entire length of the room and allowed for natural light when not covered by student artwork or other items on the radiator. To the right of the door used as the primary entrance and exit of the classroom, was a sink and small

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The dependent variable in this study was the frequency of the target behavior, inappropriate play with peers which was calculated into rate per minute (RPM) of the behavior occurrence and was collected utilizing a researcher developed tool (See Figure   8). After a discussion with Ms. McBride, inappropriate play with peers was defined as Mason behaving in either a physically or emotionally aggressive manner towards other children. This looked like hitting, spitting, and kicking others or taking things from other children whether it be toys, tools, and/or other objects, or taunting other children.
Taunting was described as Mason taking an item and running away with it and then watching the other child until the child reacted to the situation; as the other child reacted Mason would run away with the item again. Another example of taunting included Mason pretending to take an item, watching for a reaction from the other child and then taking the item or continued instances of pretending to take the item.

Interobserver Agreement
Interobserver agreement (IOA) is the extent of agreement between observers' scoring of a behavior (Kazdin, 2011). According to Kazdin (2011) there are three primary reasons to assess IOA which are 1) consistency in scoring, 2) the avoidance of researcher bias and prevention of the definition of the behavior from changing, and 3) In order to assess IOA the researchers utilized frequency ratio. During the observations each researcher used frequency counts for the target behavior. At the end of the observation the frequencies were added by each researcher. In order to compute agreement using frequency ratio the smaller number was then divided by the larger number then multiplied by 100 (See Table 2). There are limitations to using frequency ratios in that although two observers may have high agreement in frequency, they may not have observed the same behaviors at the same time. For example, one observer may have identified five frequencies of a behavior while the other observer also identified five frequencies of the behavior, but they were five different instances of the behavior from the first observer. When a behavior is discrete and clearly defined the likelihood of this occurring is small (Kazdin, 2011).
Prior to the present study the researchers practiced IOA before beginning data collection and checked in with each other several times during the observations. These opportunities were utilized to discuss any discrepancies in the recording of observed behaviors. observations. Correlation ranges from -1.00 to +1.00. The closer to +1.00, the higher the agreement. A r score of 0 would mean that the scores are unrelated and a -1.00 means that the observers reported conflicting data, which means that they did not collect data that was similar and therefore the data collection method was not reliable (Kazdin, 2011).

The data from the two researchers in this study was input into Excel and the Pearson
Product-Moment Correlation function was used to calculate r for the IOA across observations for the entire study. The r scores reported for this study indicate that there is a positive correlation between the two researchers' data and that their observations tended to be in agreement (See Table 3).
As a general rule IOA of .80 or 80% or higher has been considered to be acceptable (Kazdin, 2011). The overall IOA for each phase of this study was 97.8% or higher and therefore showed high agreement. It can be assumed that the results of both IOA methods support the assumption that the observers were consistent in recording the target behaviors and that the target behavior was well defined (Kazdin, 2011).

Independent Variable
The Incredible 5-Point Scale (Buron & Curtis, 2012) was used as the independent variable in this study. The scale was designed by Buron and Curtis to be an individualized intervention that can be implemented by families and/or professionals.
Moreover, the tool was developed to be used as either a long-term or short-term intervention for an individual with ASD for addressing target behaviors related to social competency. As they continued their work with the scale Buron and Curtis found that it was also effective for individuals with other disabilities such as anxiety disorders and obsessive-compulsive disorders as well (Buron & Curtis, 2012

Treatment Fidelity
Treatment fidelity is an essential component to ensure an intervention is delivered correctly throughout a study. If the intervention is not implemented properly than it can impact the efficacy of said intervention (Kazdin, 2011) and have significant implications to the study. According to Kazdin (2011), treatment fidelity is defined as the "extent to which the intervention is delivered as intended" (p. 194). To ensure treatment fidelity in this study 1) the classroom teacher underwent an hour long training session with the researcher to learn and understand the use and implementation of the scale as well as determine agreement on the targeted behaviors of the participant; 2) The researcher collected data for procedural fidelity during 100% of the intervention observations across all activities; and 3) IOA of procedural fidelity was conducted randomly throughout the study.

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Once the scale was developed the researcher met with Ms. McBride to discuss the implementation schedule for activity one. The researcher provided documents to the teacher and walked her through the intervention and implementation processes and schedule. Ms. McBride was given the opportunity to ask any questions that she had regarding the intervention process. Once the training was completed a date was set to begin intervention.  The final change to the implementation of the intervention came on day seven throughout the end of the intervention phase across all activities. The intervention implementation steps dropped from seven to two (See Figure 11). On day 10 of the intervention for activity one, the fidelity check indicated that all steps were followed.
The following day activity one intervention continued, and activity two intervention began. During this observation an IOA for treatment fidelity was recorded and the researchers were in 100% agreement that both steps were followed. During all subsequent interventions for all activities the two implementation steps were followed by the teacher. Additionally, there were three more observations in which IOA was she asked for clarification via email, text, or face-to-face when the researcher was in the classroom. Treatment fidelity was maintained throughout the study and IOA was gathered for fidelity on five of 13 intervention days or 38.4% of the data collection days during the intervention phase across activities.

Research Design
This study utilized a multiple-probe SSD across activities for a single participant.
Intervention was implemented across three separate activities using a staggered implementation schedule. The three activities were snack time (activity one), table time (activity two), and circle time (activity three).
Multiple-probe SSD are experimental studies that are intended to determine the effectiveness of an intervention for one or more participants. Multiple probe designs are utilized in instances where the use of "extended baselines (1) may prove reactive, (2) is impractical, and/or (3) a strong priori assumption of stability can be made" (Horner & Baer, 1978, pp. 193).
In this case, it was necessary to utilize a multiple probe design as opposed to a continuous, extended multiple-baseline design in order to avoid reactive behaviors for activities two and three over a long implementation and intervention period. Moreover, due to the aggressive nature of Mason's inappropriate behaviors it was determined that a multiple-probe design would be the most ethical choice for the circumstances and safety of all children in the classroom. Additionally, due to financial and time constraints a continuous baseline design would have been impractical.

Procedures
The procedures followed for the development and implementation of the study will be provided in the following sections.

IRB and District Approval
The RIC IRB process was completed in the spring of 2018. After one resubmission the study was approved. The school selected for this study had a districtwide research and accountability office that was responsible for collecting research proposals prior to any study implementation within the district. The process was similar 67 to the RIC IRB approval process and took a little over a month to receive final approval once submitted.

Recruitment and Consent
After district approval to conduct the study was received the researcher was permitted to begin recruiting teachers. Three teachers who were past students of the researcher were initially contacted via email by the researcher's major professor. The major professor sent the recruitment emails in order to avoid the possibility of coercion.
Two of the three teachers had switched jobs; one was now in a position that she would no longer be in a classroom setting and the other in a different teaching role. Therefore, they were not interested in participating in this study. However, Ms. McBride responded that she was interested in participating in the present study; at that point it was acceptable for the researcher to contact her.
Once Ms. McBride responded, the researcher emailed her to thank her for her interest in participating in the present study, to determine a date and time to have an initial meeting, and to provide her with the district study approval document. The document was also shared with her building principal who verbally approved the present study at the building level. The initial meeting was held the same week.
During the initial meeting, the researcher provided Ms. McBride with a folder of information regarding the study. The folder contained a teacher recruitment flier and consent form, parent recruitment fliers and consent forms (in both English and Spanish, developed by a native Spanish speaker), and samples of the Incredible 5-Point Scale.
During the meeting the purpose of the study was discussed and what that would mean for her as the classroom teacher. The researcher explained how the scale would work and asked if the teacher thought she had any students that could benefit from the study. Ms.
McBride responded that she did have students this study may benefit and that she would reach out to the appropriate families the following week. At the end of the meeting the researcher asked Ms. McBride to read the teacher consent form to ensure she was 69 interested in the study. The researcher planned to collect the form from the teacher at the next meeting.
The following week Ms. McBride sought out the families of children she selected for the study and provided them with recruitment fliers. She collected the signed recruitment fliers and when the researcher met with her next, they discussed getting signed consent from the families whom indicated an interest in participating in this study.
The teacher distributed and collected signed consent forms. The next time the researcher went to the school she gathered the signed consent forms and sat with Ms. McBride for about one hour and a half to clearly identify and define the target behaviors that would be addressed during the present study (See Figure 12). This information was used to clearly define the target behavior and was the premise of the observations and the development of the scale for Mason.
When the researcher went to the classroom to collect the signed consent forms, after her meeting with Ms. McBride, the researcher stayed and observed the participants.
She utilized this time to familiarize herself with three of the five participants (two of the participants [Ivan and Matheus)] were absent). She also used the time to ask clarifying questions regarding the specified target behaviors. During the next visit both researchers were present and data collection for this study began.

Data Collection
In order to record data for this study, the researcher developed a data collection document which included the observation date, start and end time, frequency of target behavior, and notes for each activity and participant. This format was utilized by both researchers for all consecutive observations. Data collection occurred during specified 70 activities within the classroom dependent upon the participants' identified target behaviors and the teacher identified activities in which the behaviors were occurring. Due to the dynamics of center time, the researchers had to navigate the classroom to maintain close proximity to the participants in order to observe any target behaviors while staying out of the way of the free flow of the classroom environment. The data collection instrument was used for each participant separately; the start and end time of the activity was recorded as well as the frequency of the target behavior for both Mason and Ivan. After data collection ceased during center time, the observation was completed, and the researcher(s) left for the day or spoke with the teacher. On days that both researchers were collecting data they spoke with one another about the observation, any next steps, and clarified any discrepancies in the reporting of the data. Again, it is important to mention that while five students were initially selected for the study and baseline data was gathered for all five individuals due to changes in the classroom and observations of the defined target behaviors the full study was solely conducted with Mason.
After the final day of data collection an email was sent to the teacher with an attached survey to determine her overall feelings regarding the implementation of the scale (social validity assessment). She returned the completed scale. Maintenance for this study will be performed at one and three months.

Baseline Data
In multiple-probe, SSD there are specific requirements for proper baseline data collection. According to Horner and Baer (1978), the following three requirements should be met when gathering baseline data in a multiple probe design (1) each baseline should have an initial probe; (2) each baseline should have a probe once stabilization has occurred in any phase receiving intervention; (3) a series of probes that increases by one session for each phase should be recorded before the independent variable is introduced to a phase (p. 190).
In the present study, baseline data for activity one was gathered for two days.
Typically, baseline data should be gathered for three days or probes, but an exception is made in instances such as the present study when the target behaviors are potentially harmful to others, in that case baseline data probes can be decreased. The target behaviors exhibited by Mason were potentially harmful to himself and others, therefore, only two baseline probes for activity one were collected.
Multiple probe SSD requires that baseline collection increases by one probe for each activity. Therefore, the researcher observed and recorded three baseline probes for activity two. The first probe was on the same day as the first probe for activity one, the second probe for activity two was collected when trend began for activity one, and then one additional baseline probe was gathered before intervention began for activity two.
There were seven baseline probes recorded for activity three. The first probe was collected at the same time that the first probes for activities one and two were recorded.
The second probe for activity three was recorded on the second observation day and final baseline day for activity one. The third probe was collected when activity one started trend. The fourth probe was recorded when intervention began for activity two. The fifth probe was recorded on the next visit and the sixth and seventh probes were collected once a stable trend occurred during activity two.

Creating the Intervention
In order to create the intervention, the researcher met with the teacher to develop a concrete definition of the target behavior (inappropriate play with peers). Once a definition was determined then the behavior was broken down into five separate levels by determining specific and observable behaviors and characteristics of each level for the scale. (See Table 4). Once the target behaviors were identified the researcher began to collect baseline data, this provided the opportunity to clarify any questions regarding the identified behaviors. After the second observation the scale was developed (See Figure 13)  behaviors (see Figure 14). According to Buron and Curtis (2012), using a small portable scale is beneficial because it can be with a person at all times. In this study the portable scale was not carried at all times, but it was easily accessible and could be placed in front of Mason while he worked. In short, the scale was developed and utilized in three separate formats, the full scale, a story, and a portable flip scale. Each format of the scale was developed for ease of use or to teach the scale to Mason. Furthermore, each format was a recommended practice from the authors of the Incredible 5-Point Scale (Buron & Curtis, 2012).

Implementation of the Staggered Intervention Over Time
From the beginning of the district proposal process until the end of the intervention data collection across all three activities the present study took 17 weeks.
The baseline and intervention data collection across all three activities took seven weeks (See Appendix E). Baseline data collection across all three activities began on the same day.
Two baseline probes were collected for activity one. Due to the safety risk of Mason's aggressive behaviors rather than waiting for three baseline probes the researcher determined that ethically the intervention should begin after two probes. After an interview with Ms. McBride regarding Mason's target behavior over the previous two years of preschool and once there was baseline evidence of the presence of the target behavior an a priori assumption was made that the target behavior was present, pervasive, and stable; therefore, intervention was implemented for activity one.
Due to scheduling conflicts and a holiday, neither researcher was able to gather data the first day of the intervention implementation for activity one. On the third day of intervention the first researcher went to the school to collect data however, Mason was absent, so the researcher interviewed Ms. McBride to check for fidelity of the first day of intervention. The following week, on the fifth day of activity one intervention, the second researcher was able to gather intervention data and conduct a procedural fidelity check. That same week, on the seventh day of intervention (activity one) both researchers attended the observation and recorded data on the intervention, completed procedural fidelity checks, gathered baseline probes for activities two and three, and recorded data for IOA.
Activity one intervention continued for 10 days. During that time there were three observations of activity one and two observations of activities two and three. In multiple-probe designs a staggered implementation for intervention is essential as it is the experimental control of the study (Horner & Baer, 1978;Kazdin, 2011;Murphy & Bryan, 2001). As the intervention is implemented during one activity and baseline data collection continues in the other activities it is anticipated that behaviors will stay the same in the two activities still in the baseline phase of the study; meanwhile, it is expected that the behaviors will change in the activity receiving the intervention. If the behavior changes across all activities or does not change in the activity receiving the intervention it can be assumed that the intervention is not having the intended effect or there is carryover of the intervention across the activities. Therefore, when the intervention for activity one began, baseline data continued to be collected for activities two and three. In order to begin intervention in subsequent activities target behaviors need to be stable in the activity(ies) which intervention is already implemented (Horner & Baer, 1978). A stable trend was identified during the second and third intervention observations and on the 11 th day of activity one intervention, activity two intervention was implemented.
When activity two intervention implementation occurred activity one intervention continued and procedural fidelity checks were made for activities one and two, baseline 79 data was gathered for activity three, and both researchers recorded IOA data. Activity one maintained a stable trend and on the 10 th day of the intervention phase of activity two a stable trend was met. Therefore, activity three intervention was implemented.
On the first day of intervention for activity three both researchers attended the observation in order to record IOA data. Data were also gathered for procedural fidelity during all three activities. A second observation was made during this week. Intervention data and procedural fidelity checks were collected across all three activities. Once activity three intervention was implemented data were collected across all three activities of intervention for six days. As required by SSD, data collection ended at the same time for all activities (Kazdin, 2011;Krishef, 1991).
In a multiple-probe design, intervention implementation is dependent upon a stable baseline being met prior to the implementation of the intervention (Horner & Baer, 1978;Kazdin, 2011;Murphy & Bryan, 2001). Additionally, baseline begins at the same time across activities of the study. Once intervention has been implemented for an activity each consecutive activity should have at least one additional baseline probe. For example, if activity one has one probe then activity two should have at minimum two probes, and so on. Activity one of this study has two recorded baseline probes, activity two has three, and activity three has seven recorded probes. After the intervention was implemented in activity one and a trend was established intervention began for activity two. In order to be valid as an experimental design the interventions had to be staggered as each activity acted as a control for the study and the efficacy of the intervention (Kazdin, 2011;Krishef, 1991;Murphy and Bryan, 2001).

80
The research question (To what extent does the implementation of the Incredible

5-Point Scale impact target behaviors of preschool children with Developmental Delays?)
was answered by gathering baseline data across three separate activities and utilizing a staggered implementation of the intervention across the three activities. The frequency of the target behavior was recorded during the observations and then calculated into a rate per minute (RPM) of observed target behavior. RPM was then input into Microsoft Excel and a line graph was developed to conduct a visual analysis.
In order to analyze the data, the researcher utilized three methods of analysis common to SSD. The first method of analysis was visual analysis, the second was indicates that an intervention is highly effective, whereas an effect size below .50 is considered to be ineffective (Lenz, 2013).
Visual analysis has historically been the primary data analysis method utilized in SSD research (Kazdin, 2011) and was utilized in this study. When incorporating visual analysis into a study, researchers consider the data patterns between phases and across activities then identify whether or not the target behavior changes once intervention has been implemented (Kazdin, 2011). While performing the visual analysis for the present study, the researcher considered the difference between the mean of each baseline and intervention phases across the three activities and then identified if there was a change in 81 level between the baseline and intervention phases of each activity. Level is identified by the researcher by looking at the final datum point of the baseline phase and the first datum point of the intervention phase and determining whether or not there was a visible shift between the baseline and intervention phases (Kazdin, 2011). Trend and latency were also considered in the visual inspection of the data. When determining trend, the researcher looked for an increase or decrease in behavior over time. Latency on the other hand was determined by how quickly changes occurred after the intervention was implemented (Kazdin, 2011).
The second method of data analysis used in this study was the percentage of nonoverlapping data (PND). PND considers the baseline datum closest to the anticipated trend and then the number of treatment phase data points either under or over the baseline datum point (dependent upon anticipated trend) is divided by the total number of data points in the treatment phase. Once computed, the researcher has an effect size calculation and is able to determine whether or not the intervention was effective.
However, using PND has a limitation in that if the baseline data set has an outlier relatively closer to the anticipated intervention trend compared to all other baseline data points the results may have a type II error, meaning the effect size may indicate no effect when there actually was an intervention effect (Lenz, 2013).
The third and final data analysis method utilized in this study was percentage of data exceeding the median (PEM). PEM calculates the median baseline datum point and then calculates how many data points in the intervention phase overlap with the median datum point. PEM provides the researcher with an effect size and is frequently used when there are outliers in the baseline data which could impact the results of the study (Lenz, 82 2013). In activity two of this study there is an outlier in the baseline data therefore, PEM was selected in order to avoid a type II error that may be present in the PND analysis. According to Lenz (2013) there are five specific steps that the researcher must follow in order to calculate PEM. The first step is to determine whether the intended change will increase or decrease data points between baseline and treatment. The second step is to find the median baseline phase datum point. The third step is to draw a line from the median datum point, and it extend it through the treatment phase. The fourth step is to count how many data points in the treatment phase are above or below the median (whether the data points counted are above or below the line is dependent upon intended change of behavior after intervention [i.e., if the anticipation was that behaviors would decrease the researcher would count any data points below baseline median datum point]). The fifth step is to divide the number found in step four by the total number of treatment phase data points (Lenz, 2013, p. 70). PEM is fairly easy to calculate however it is subject to Type I errors, meaning that the effect size could indicate that there was a change with intervention when there actually was not.

Internal Validity
According to Horner et al. (2005), "Single-Subject research designs provide experimental control for most threats to internal validity and, thereby, allow confirmation of functional relationship between manipulation of the independent variable and change in the dependent variable" (p.168). Within SSD there are eight primary threats to internal validity. The threats and procedures implemented in this study to protect the internal threat to validity are included in Figure 15. The assessment of maintenance following the treatment protocol will be an added check to internal validity.

External Validity
In SSD, "External validity of results from single-subject research is enhanced through replication of the effects across different participants different conditions, and/or different measures of the dependent variable" (Horner et al., 2005, p. 171). In the present study the participant was a preschool-aged child with DD. Per multiple-probe design, effects across activities were documented. Due to the small sample size in SSD, attrition is a significant threat to external validity (Horner et al., 2005). In order to avoid attrition Figure 15. How the Present Study Avoided Threats to Internal Validity 84 in this study the researcher started gathering data for three separate but similarly designed studies. One study came to fruition. While a limitation can be seen in the sample size, to assist readers in determining if the sample is representative of and transferrable to their student population the researcher provided a description of the participant and his demographics, a detailed description of the school and classroom settings, and an observable, concrete, and specific definition of the target behavior and the levels of the target behavior exhibited by the participant.

Social Validity
According to Kazdin (2011) social validity is designed to ensure that interventions take into consideration the concerns of society. In order to do this social validity should answer three questions, (1) Are the goals of the interventions relevant; (2) Are the intervention procedures acceptable to consumers and to the community at large; (3) Are the outcomes of the intervention important, that is, do the changes make a difference in the everyday lives of individuals (Kazdin, 2011)? The method of social validation that was used in the present study was subjective evaluation. Subjective evaluation is a method of social validation used in single subject design which relies on the opinions of individuals who have expertise and/or familiarity of an individual, in this case the teacher, and are in a position which allows them to make a decision regarding the behaviors of an individual (Kazdin, 2011).
The first social validation occurred in the selection process of the five preschool aged participants whom exhibited identifiable, target behaviors. The participants were selected using the subjective evaluation method in that the target behaviors were determined by the teacher through her own observations per normal classroom 85 procedures. The target behaviors ranged from using a loud voice in the classroom, to taunting and teasing peers, or engaging in harmful behaviors such as hitting, pushing, or kicking. The identified target behaviors of each participant determined to which study they would be assigned. After the observations began two studies were discontinued.
The first study was discontinued after changes were made to the classroom routine and a discussion between the researcher and teacher determined that three participants (Leo, Matheus, and Thiago) were no longer eligible for the study as they no longer exhibited the identified target behavior. The second study was discontinued after it was determined that the voice volume of the participant (Ivan) mimicked that of the classroom norm. The third study continued from start to finish with the fifth participant (Mason).
The second social validation used was a short questionnaire which was provided to the teacher electronically at the end of the study to solicit her opinions on the process and impact of the study on Mason and herself as the individual implementing the scale.
The questionnaire included 8 Likert scale items ranging from strongly disagree to strongly agree and 4 short answer questions. The teacher's responses can be found in Appendix F.

Chapter Summary
Chapter Three addressed the many components of methodology for this study.

Introduction
Chapter Four will explore the results of the present study. Data regarding the visual analysis, PND, and PEM across all three activities will be provided. Additionally, the responses provided by Ms. McBride in the social validity questionnaire will be shared. The chapter will conclude with a summary of the results.

Research Question
This study utilized a multiple-probe single subject design with one participant,

Results of Visual Analysis
Activity one. Upon visual inspection of activity one data, the researcher was able to determine that the intervention had an immediate impact on the participant's behaviors. Although there was a decline in the dependent variable during the baseline phase of activity one and slight variability in target behaviors during the intervention phase (range= 0-0.4 RPM), there were no overlapping data points between baseline (range= 0.57-1.7 RPM) and intervention. Figure 16 provides a graphic representation of the data between baseline and intervention during activity one. The red arrow on Figure   16 indicates shows an increasing trend up prior to intervention indicating that the initial probe may have been an outlier. Figure 17 provides a graphic representation of the data between baseline and intervention during activity two. The red arrow on Figure  The range for activity two baseline data was 0.2-1.2 and the range for intervention was 0-0.5. All data points were analyzed to calculate m for activity two in each phase. Activity two baseline data was x ̅ = 0.78, this was higher than the largest Figure 17. Activity Two: Table Toys Observation Frequency: Rate per Minute 89 datum point during intervention (0.5) and the x ̅ for intervention (x ̅ =0.206). Given this, despite the outlier, this indicates that there was a decrease in target behavior between baseline and intervention phases. Finally, a regression line across baseline and intervention data with negative slope indicates that the dependent variable continued to decrease throughout the study. The visual analysis of activity two provides evidence that despite the outlier in the baseline phase the intervention had the intended effect of decreasing Mason's target behaviors (see Figure 17).

Activity 3.
After the visual inspection of activity three baseline and intervention data, the researcher was able to determine that the intervention had an immediate impact on Mason's target behavior. Baseline data indicated some variability (range= 0.38-1.217) however, once intervention started the dependent variable decreased immediately and shared zero overlap between phases. During the intervention phase the RPM for target behavior continued to decrease (range=0 .02-0.16). A regression line with negative slope across baseline and intervention data indicates that the target behavior continued to decrease throughout the intervention phase of the present study. Figure 18 provides a graphic representation of the data between baseline and intervention during activity three.

Summary of the Visual Analysis
A visual analysis across all three activities provides a strong indication of the intervention's effectiveness. There is no indication of intervention carry-over effects between activities as Mason's target behaviors continued to remain mostly stable across activities until intervention began. Analysis of Figure 19 indicates immediate negative shifts in level between baseline and intervention phases across activities. indicates that overall the scale was an effective intervention (Lenz, 2013; See Figure   20).

Results of Percentage of Data Exceeding the Median
The final method of analysis used in this study was PEM. PEM was computed to determine the effect size of the intervention on the target behavior across all activities of the study. After computing the median baseline datum point for each activity, the researcher then calculated each corresponding effect size. All activities reported an effect size of +1 (100%) which indicates that the independent variable was highly effective for each intervention phase across all three activities (See Figure 21). .57 13/13 1 2 (Table  Toys) .

Social Validity
The questionnaire provided to Ms. McBride included eight Likert scale items ranging from strongly disagree to strongly agree and four short answer questions.
Overall, her responses indicated that she agreed that her student's behavior improved; the intervention was effective; that she could accurately implement the scale in her classroom; and that the time required to implement the scale was reasonable. She strongly agreed that the changes she observed in her student were socially important; she understood the intervention steps for the Incredible 5-Point Scale; the scale was easily incorporated into her classroom; and that she had the necessary materials to implement the scale.  (Table  Toys) .93 10/10 1 3 (Center) .78 6/6 1 94 implementation of the scale in her classroom, including the impact on Mason's behaviors.
The first question asked about her thoughts and opinions regarding the purpose of the study. She replied that the study was helpful within her classroom and that it "not only helped change the behavior of one of our students but having the research team in the classroom helped us ensure we were using the scale correctly and with consistency" (Ms. McBride

Introduction
Chapter Five includes a discussion of the results of the study. Limitations will be discussed as well as implications for current professionals and future research.

What this Study Tells Us About the Incredible 5-Point Scale
Results of this experimental design suggest that the Incredible 5-Point Scale may be an effective tool for modifying target behaviors of preschool-aged children with DD.
Visual analysis determined that although there was some variability in Mason's behaviors throughout both baseline and intervention phases that the frequency as calculated by rate per minute decreased immediately following implementation of the intervention across all three activities. Furthermore, linear regression presented in the visual analysis was evidence of a negative slope which indicated a decrease in target behaviors. Mean scores across baseline and intervention across all three activities had zero overlapping data points. One concern in the visual analysis was an outlier identified in activity two that overlapped in six out of 10 data points in the intervention phase. However, change in mean, level, and linear regression supported the efficacy of the intervention despite the outlier in the baseline phase.
PND, a statistical analysis used in the present study, measures the effect size of an intervention by determining the baseline datum point closest to the intended effect of intervention and how many overlapping data points during the intervention phase are recorded. Activities one and three both indicated that the scale had a high level of effectiveness (+1 or 100%). However, when PND was calculated for activity two, the result was .40 or 40%. Anything below .5 or 50% is considered to be ineffective (Lenz, 97 2013). One concern in using PND is the possibility of a type II error occurring, meaning there was a failure to reject a false null (Field, 2014). The baseline datum point (0.20 RPM) utilized for PND during activity two was an outlier and likely resulted in a type II error.
PEM was the third and final method of statistical analysis used in this study. The calculation of PEM required the researcher to determine the median baseline datum point for each phase. After the median was calculated the number of overlapping data points in the intervention phase were counted. Then, the total number of overlapping scores were divided by the total number of observations. Through the use of the median baseline datum point, PEM prevents type II errors from occurring because while outliers are included in determining which datum point is the median point, they are not selected as the comparison point. PEM is subject to type I error, meaning the null was accepted when it should be rejected (Field, 2014). Based on the analysis of PEM each phase had an effect size of +1 (100%), which indicates that the intervention was highly effective. The outlier in the baseline phase of activity one was no longer an issue. Overall the data collected for this study in most instances indicated that the intervention was effective or highly effective as an intervention tool for preschool aged children with DD.
The data collection sheets provided space for the researchers to identify and write specific behaviors as they were observed.  Mason about the emotions and behaviors of his peers in response to his behaviors was the immediate and consistent prompting throughout the intervention phase across all three activities. Prompting occurred at the beginning of the activity and then as needed throughout the activity. This is important, because like individuals with ASD, during the preschool years, information must be broken down into steps or tasks as children are developing the ability to follow a series of instructions and see the broader picture within a variety of contexts (Dodge et al., 2008). Therefore, interventions that utilize systemizing such as task analysis are frequently utilized in preschool settings.
In order to ensure that both empathizing and systemizing were being addressed as Fidelity was maintained throughout the implementation of the scale and the intervention was implemented on a staggered schedule across activities. After each visit the data was analyzed and at the end of the intervention phase across all three activities final analysis was completed. Maintenance visits have been scheduled.

Social Validity
The questionnaire provided to Ms. McBride indicated that she agreed that Mason's behavior improved, the intervention was effective, that she could accurately implement the scale in her classroom, and the time required to implement the scale was reasonable. She strongly agreed that the changes she observed in her student were socially important, she understood the intervention steps for the Incredible 5-Point Scale, the scale was easily incorporated into her classroom, and that she had the necessary materials to implement the scale.

Limitations
Clear definitions of the participant and setting, procedural fidelity checks, and social validity checks support the validity of the present study (See Figure 22). The use of IOA ensured the reliability of the data collected. However, all studies have limitations that should be addressed by the researcher. The limitations for the present study are related to the data collection, IOA, and researcher created intervention and will be discussed.
First, there were some limitations in the data collection. During activity one, only two baseline probes were gathered. WWC and CEC recommend that a minimum of three baseline probes be collected as one criterion for a study to be recommended without reservations (CEC, 2014;Kratochwill, 2010). However, if there is concern for the safety of the participant or other individuals in the environment both WWC and CEC permit less than three baseline probes to be collected (CEC, 2014;Kratochwill, 2010). In the current study, Mason's behaviors were potentially harmful to himself and his peers, therefore, the collection of two rather than three baseline data probes for the first activity was appropriate. Although, during activity one Mason's baseline data indicated a decreasing trend in the target behavior, prior conversations with the teacher provided evidence for an a priori assumption that the target behavior would have some variability 108 and would increase again. On days snacks were small such as goldfish crackers or animal crackers Mason's incidence of target behavior would be higher than days where the students were offered muffins. Due to the dangerous nature of his target behaviors during snack and the potential risk of injury (such as a child falling off of a chair or spilling a drink) it was determined to begin intervention after the second data probe.
There was some variability in the baseline data for activity two. According to Kazdin (2011), one source of data variability can come from uncontrolled changes in the setting (p. 41). The first baseline datum point was an outlier compared to the other two  Throughout the data collection when both researchers were present, they discussed the data they gathered and any possible discrepancies in between their data; for example, if one researcher or the other noticed when a behavior was identified that the other researcher did not see, the two researchers would discuss the discrepancy.
A third limitation in the present study was the use of researcher created intervention tools. After speaking with the teacher, the researcher developed the scale and story to be implemented throughout this study. While this provided the researcher with more control over how the information was presented, it limited the teacher's ability to learn and experience the process of the development of an  Buron and Curtis (2012), incorporating the child's interests encourages increased engagement and acceptance of the scale (Buron & Curtis, 2012).
Teachers considering the use of the Incredible 5-Point Scale in their classrooms need to first clearly define a target behavior by identifying observable characteristics of the behavior. Using a functional behavior assessment or some other type of anecdotal record over time to observe and document the behaviors is essential to the identification of the target behavior and determining the motivation behind the target behavior.
Teachers should then determine what behavior the student should be exhibiting and clearly define and identify observable behaviors of the desired behavior.
In the present study, the researcher determined that the success of the intervention was due in part to Mason's ability to relate to the scale as well as the consistency of the 112 implementation of the scale. With that being said, teachers need to either develop the scale with the student or fully consider the student's interests as the scale is created.
Whenever possible Buron and Curtis (2009)  After the teacher has identified the target behavior(s), desired behavior(s), and student interests, he or she should consider the classroom schedule, overall student needs and demands, as well as the learning style of the student receiving the intervention to determine which techniques and tools (i.e. social narratives, flipscale, large scale, prompting, etc.) are most feasible for the setting where the intervention will take place and which methods the child will respond to most positively. In the present study, Mason responded extremely well to the use of a social narrative both in print and electronic versions to help him process and learn the components of the scale and to define the specific behaviors addressed on the scale. The use of the small flipscale was also beneficial as it was easy to carry from one place in the classroom to another. There are many free online resources that can be used to aid in the development of the scale, videos, or social narratives. For the present study, the researcher used ClipArt characters and a free online program, Canva™ to develop the illustrations for the story. After the illustrations were completed the researcher used Adobe Spark™ (also a free online 113 resource) to create the story pages and voiceover. The story was then uploaded to YouTube™ so that it would be easily accessible to the teacher.
Once the scale has been created the teacher should teach the scale to any adults who will also be utilizing the scale with the student. This ensures consistency throughout the implementation of the intervention. After the adults have been trained on the scale's use and provided specific definitions and descriptions of the observable target and desired behaviors the teacher will be ready to implement the scale with the student. It is critical that the teacher takes the time to thoroughly teach the scale to the student receiving the intervention to ensure he or she has a full understanding of the target behaviors and the teacher's expectations of the student's behaviors. The scale must be implemented consistently, and the student should be prompted with the scale as often as needed.
Buron and Curtis (2012)  Finally, throughout the process (pre-intervention through intervention) the teacher should have some way to document the student's behaviors. The documentation will provide data to determine whether or not the intervention is working. Additionally, the teacher will see patterns in the student's behaviors across different activities or settings and times throughout the day, across activities, and across observations. The researcher developed a data collection tool that enabled her to identify the frequency of the behaviors during specific activities throughout Mason's day. She included a column to write the time of each observation across activities and a place to write anecdotal observations throughout the data collection period. The tool that was created was one page so that the researchers did not have to flip through pages during the observations.
This ensured that all of the data collected in a visit was maintained on one document and reduced the possibility of losing portions of the data. therapeutic, and home). Furthermore, to address the present study's limitations, and to increase the methodological rigor, it is recommended that future researchers improve IOA procedures, observe stable data across all baselines, and encourage teacher made intervention tools.
For individuals interested in early childhood education, specifically preschool, future research should focus on determining the tool's efficacy for preschool aged children who are typically developing and who have a wide range of disabilities. A natural progression would be to complete a series of multiple-baseline or multiple probe design studies across participants in which one study focuses on typically developing 115 students, one study focuses on students with DD, and one study focuses on children with ASD. These studies would be indicative of the efficacy of the scale for children with different exceptionalities. After the completion of these three separate studies an additional multiple-baseline or multiple probe design study across participants in which there is a participant whom is typically developing, a participant with DD, and a participant with ASD should be conducted. During this study the researcher(s) could determine the scale's efficacy across participants and exceptionalities as well as its effectiveness for different skills and behaviors. The present study focused on Mason's inappropriate play with peers, however a future study could focus on shyness or a child's indiscretion when speaking with strangers. Additional research in ECE environments could include whole group use of the scale. For example, a study could be completed to determine if the scale could be utilized to help groups of students regulate the classroom noise volume.
For individuals interested in elementary, middle, or high school students, studies could be completed with participants of varying disabilities. In their book, Buron and Curtis (2012) have indicated the use of the Incredible 5-Point Scale across a variety of classroom settings from elementary to high school. They have also found that students with disabilities other than ASD such as obsessive-compulsive disorder and anxiety disorders have reacted well to the interventions. If research can provide support for the scale's use across the lifespan its use could be limitless as it could provide a familiar support from early childhood through adulthood. This demonstrates the need for future research across ages.

116
This study was an initial empirical attempt to shed light on the effectiveness of the Incredible 5-Point Scale. Although, the scale uses several EBP throughout its development, implementation, and intervention, there is no published research on the scale and it has not been determined to be an EBP. Moreover, results from this study are promising and build the foundation for future research. The present study may enable stakeholders to make decisions regarding the effectiveness of the scale through the evidence it provides.
This study focused on a preschool aged child with DD. In almost all analysis the scale was considered to be effective or highly effective for decreasing the RPM of a well-defined target behavior across three separate activities. Although one activity, activity two, was considered ineffective when PND was calculated the same activity had an effect size of +1 when calculated using PEM. This discrepancy in data indicated that there may have been a type I or type II error in the data analysis. After conducting visual analysis and considering the baseline data, it was determined that a type II error was more likely due to the significant outlier recorded in the baseline data phase.
Results from this study have implications for future research on the tool as well as the use of the tool in preschool classrooms. Several research ideas have been proposed as follow-up studies to this work. The present study utilized the Incredible 5-Point Scale as an intervention, however, known EBPs were utilized to teach the scale to the participant and regular prompting of the scale was necessary for its success. As professionals continue to advance the literature regarding evidence-based practices it is important to take note of the relationship between old and new; new methods are important and provide more opportunities for individuals to learn and grow, meanwhile, old, tried and true methodologies have proven effective and should not be placed on the shelf for the sole purpose of only trying the new methodologies. There needs to be a balance and sometimes a marriage between what the old and new methodologies have to offer to students, teachers, and families alike. As professionals in the field it is necessary to embrace both 117 and incorporate them into the work done in the classroom. Lastly, educators reading this work will have an indication of the potential of the tool and be able to make a decision as to whether or not they could implement it in their classrooms and if they believe the tool will be effective.
have to share information from the study is if it is subpoenaed by a court, or if we think your child is being harmed by others then I would have to report it to the appropriate authorities. Also, if there are problems with the study, the records may be viewed by the Rhode Island College review board responsible for protecting the rights and safety of people who participate in research. The information will be kept for a minimum of three years after the study is over, after which it will be destroyed.

Contacts and Questions
You can ask any questions you have now. If you have any questions later, you may contact Beth Pinheiro at 401.456.8599 or bpinheiro@ric.edu. You may also contact Dr. Paul LaCava with any questions or concerns at placava@ric.edu.
If you think you were treated unfairly, have complaints, or would like to talk to someone other than the researcher about your rights or safety as a research participant, please contact Cindy Padula, Chair of the Rhode Island College Institutional Review Board at IRB@ric.edu, or by phone at 401-456-9720.
You will be given a copy of this form to keep.

Permission Statement
By signing below I/we are stating that I/we understand the information and give permission for my/our child to be in this study. Both parents/guardians must give their permission unless one parent is deceased, unknown, incompetent, or not reasonably available, or when only one parent has legal responsibility for the care and custody of the child. I/we are over 18 years of age, and either the parent or legal guardian of the child named below.

Would you like to be a part of this study?
If you say yes, what will you need to do?
• You will identify target behaviors you would like to see addressed in some of your students.
• You will send home a recruitment flier to the families of children you have identified.
• Once families indicate to you that they are interested in the study, you will send home a consent form to be signed.
• You will be trained on the development and implementation of the Incredible 5-Point Scale.
• Your classroom and students will be observed during the 2018-2019 school year.
• You will have a discussion at the end of the study regarding your opinions on the use of the scale.

Appendix E. Schedule and Activities for the Present Study
Week: Month Activity