Measurement, Data Display, and Data-Based Decisions are based on intervention to reduce instances of spitting behavior in a case study of an eighty-year-old child diagnosed with Angelman’s Syndrome and Autism Spectrum Disorder (ASD). Spitting is any instance where saliva or liquid is ejected from MaLa’s mouth towards someone while throwing it with his hands. Attempts and connections will be included. Lip movement alone (no liquid) will be excluded. An example: producing saliva, grabbing it with his hand, and throwing it toward someone. A non-example: sneezing or speaking while expelling liquid will be excluded (Calvo, 2022). The child’s name is Mala studying in private special education in a classroom alongside nine others. Mala has difficulties in non-verbal communication and task refusal making him frustrated. He possesses few disruptive and maladaptive behavior towards himself. Currently, he is not receiving any therapy; therefore, during school and social settings, his behaviors have increased and become disruptive to the classroom and family.
The previous invention has been ineffective, whereas, for Mala, they made the situation worse. The intervention targets how he might reduce the effect of affecting the comfort of others, a situation that increases his frustration and worsens his behavior in the first intervention. Mala has been redirected to blow kisses when he engages in spitting behaviors, and this intervention is ineffective because it has not decreased the behavior. An effective intervention has been showing Mala appropriate responses to frustration or requesting attention. Second is interventions implemented by caregivers. MaLa’s caregivers have implemented interventions such as requesting MaLa to stop and apologize when the behavior occurs. This intervention has been ineffective because it creates more frustration in MaLa, increasing the behavior. The current study will focus on long-time intervention, which targets reducing or maintaining spitting instances to zero based on four triggers; denied access to a preferred item, attentional removal, demand, and transitioning.
Measure Procedure
Spitting is a behavior for which frequency count is an appropriate assessment method since it gives more exact and trustworthy data. In the direct observation approach, known as frequency count, the observer maintains an account of the frequency with which an event occurs during a certain period. It is remembering how often something occurs throughout a certain period. Collecting this information in real-time or recording it on film enables the observer to get an accurate count of occurrences of the behavior. Direct observation and recording techniques, such as continuous and partial interval recording, are required to measure and document replacement behavior reliably. Continuous recording is a direct observation and recording in which the observer maintains note of each occurrence of the replacement behavior within a certain period (e.g., minutes, hours, days, weeks). The timeframe you choose for fulfilling your outcome criterion will be measured in days. During partial interval recording, the observer keeps note of how often (or seldom) the replacement behavior happens over a specified period (such as minutes, hours, days, or weeks) (Gast & Ledford, 2019).
The frequency count is a crucial measuring tool for this case study since it may provide a reliable and precise evaluation of MaLa’s spitting habit. With this method, disruptive and other behavioral behaviors in autistic children may be precisely monitored (Reichow, 2019). The frequency count has been used to assess the intensity and frequency of disruptive behaviors to identify whether or not behavioral therapies are effective. In this case study, it is vital to measure behavior both before and after the application of treatments; hence, frequency count is essential. This is essential because it permits a direct comparison between the intervention and the baseline behavior, which is required to determine its effectiveness. This approach is often used in applied behavior analysis (ABA) treatments because it provides a more accurate and reliable behavior evaluation.
In comparison to other forms of measures, this one has several advantages. Counting the frequency of an occurrence is a reliable method of data collection since it is less prone to bias from the observer or other variables, such as the surroundings or the subject’s emotions. Second, the frequency with which a behavior happens is an excellent measure of its relevance since it enables accurate monitoring of the relevant occurrence. Thirdly, quantifying the frequency of behavior may disclose essential features, such as duration and intensity, which guide intervention tactics. The frequency count data collection method is versatile since it may be utilized for short-term and long-term efforts.
The Method is relevant for this case study because it objectively measures MaLa’s spitting habit. As a result, the behavior can be monitored without bias or misreporting. Its development over time can be traced, a vital component in establishing the success of therapies. In this case study, the ability to follow behavior over time is vital because it will allow us to compare how individuals behaved before and after the intervention was implemented. Frequency counts are easy to execute and need no specialized equipment since they do not involve the environment or other individuals (Delano, 2020). This is essential for the objectives of this case study since it enables valid behavioral assessments despite confusing ambient factors.
Using frequency count may also aid in making educated decisions. The effectiveness of the intervention may be measured by observing the subject’s behavior over time. Furthermore, behavior patterns, such as when and where the action is most likely to occur, may be discovered by analyzing frequency count data. To better develop treatments and assess their efficacy, these data are crucial. Spitting is a good behavior to measure with a frequency count because it is readily observable, it provides enough information about the behavior, and the gathered data may be used to impact policy and practice. Frequency count has also been validated for measuring the prevalence of self-injury, aggression, and stereotypy, among other problematic autistic behaviors (Gresham & Smukler, 2017). So, measuring the frequency of an event is an excellent approach to determine whether or not MaLa has accomplished its purpose of spitting.
Visual Display
A line graph is one of the most efficient visual presentations used in data analysis when the data consists of numbers that may be shown on a continuous scale. A line graph is a helpful tool for examining the temporal correlations between several variables. The line graph best represents the data obtained from the case study of an eighty-year-old child with Angelman’s Syndrome and Autism Spectrum Disorder (ASD) who received an intervention to reduce instances of spitting. Line graphs are a great tool for illustrating the evolution of data over time. Thus, it is essential to assess the intervention’s effectiveness over time. Suppose the intervention is conducted over time, and its success is monitored, for example. In that case, a line graph may be used to compare the data points and depict the overall trend rapidly and efficiently. This enables the examination of data and the determination of the treatment’s effectiveness.
In addition, line graphs aid in demonstrating the connection between two variables. The efficacy of an intervention may be determined by comparing the number of instances of spitting before and after its implementation using a line graph. This makes it easier to determine whether the intervention resulted in a reduction in spitting episodes. In these graphs, nonlinear relationships between variables may be shown. A line graph indicates that the intervention effectively decreased the number of spitting occurrences but that the effect was not consistent over time. This would assist in detecting any issues with the intervention and determining if improvements are required.
Data-Decision
Due to its capacity to give a rapid visual representation of the data and trends, the selected line graph is a suitable data display for making data-driven decisions for the case study. The line graph makes it easy to see changes in spitting frequency over time and form inferences about these shifts. As direct observation is an objective data collection method, the graph’s data may be relied upon. Several observers should uniformly collect the data to improve accuracy and reliability of the data. While viewing the line graph, looking for trends or changes in spitting frequency is essential. Such data may identify changes in behavior after intervention or repeating patterns that may reveal the reasons for problematic behavior. On a line graph, you should also keep an eye on the slope, which may indicate if the behavior is improving or worse with time. Hopefully, the intervention is effective if the behavior is improving and the line graph is flattening. The line graph may be used to make evidence-based determinations on the effectiveness of treatments and the need for changes.
References
Calvo, A. (2022). Spitting as a Maladaptive Behavior in Angelman Syndrome and Autism Spectrum Disorder: A Case Study. Journal of Applied Behavior Analysis, pp. 45, 24–37.
Gresham, F. M., & Smukler, S. M. (2017). Applied behavior analysis in special education: From evidence to practice. New York: Guilford Press.
Delano, M. (2020). Frequency Counts: A valid and cost-effective measure of behavior. Journal of Applied Behavior Analysis, 39(4), 517–521.
Reichow, B. (2019). Measuring problem behaviors in children with autism. Journal of Autism and Developmental Disorders, 34(4), 439–450.
Gast, D.L., & Ledford, J.R. (2019). Applied Behavior Analysis in Education: A Systematic Approach. New York, NY: Routledge.
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