Applied Behavior Analysis of Skin-Picking Behavior

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Table of Contents

Introduction
Participants and Setting
Procedure
Data Collection
Interobserver Agreement
Conclusion
References

Introduction

Self-injurious skin picking, also known as excoriation disorder in DSM-5, or dermatillomania, is characterized by repetitive and impulsive scratching, pulling, lancing, squeezing, picking, and gouging of one’s skin. Skin picking can be operationally defined as an individual that impulsively breaks their skin in one or more ways just mentioned despite not having a dermatological condition.

Self-injurious skin picking occurs in both non-disabled individuals and people with developmental disabilities. However, it is more common in individuals with developmental disabilities and seems to be related to the female gender, obsessive-compulsive behaviors, anxiety, and depression (Lang et al., 2009). Skin picking can be detrimental to an individual’s life.

Chronic skin picking can result in scars, tissue damage, skin lesions, ulcerations, and infections. Individuals who engage in skin picking also report significant psychological distress and impaired social functioning, as well as guilt, shame, and embarrassment of open sores, wounds, and scars (Deckersbach et al., 2002).

Applied Behavior Analysis is an evidence-based practice that would be greatly beneficial to individuals who engage in skin picking. Coping skills and replacement behavior can be taught so that this behavior can be diminished if not completely stopped. This would allow these individuals to live healthier and happier lives.

An example of skin picking is when Alice picks the skin around her nails until they bleed. When her skin begins to scar, Alice cannot stop herself and begins to pick around her nails again, not allowing her skin to recover fully. A scenario that does not depict skin picking is Amy got a pimple on her forehead and she squeezed it. Eventually, the area where the pimple was healed, and Amy did not pick her forehead again.

Participants and Setting

John is a 12-year-old male diagnosed with Autism Spectrum Disorder (ASD) who engages in chronic skin-picking. The participant is observed at his home and school for 3 hours at a time for 5 weeks. John was referred by his neurologist for treatment for his skin-picking. John’s parents reported that skin-picking began when he was 4 years old, but for the last 2 years, it has become chronic. Around this time, the family moved to a new house, and John began to go to a new school. John’s parents report that the transition has been very hard for their son.

Procedure

The intervention used in the hypothetical behavior analytic research study is Applied Behavior Analysis (ABA). ABA is an evidence-based practice used to modify behavior by understanding the effects of environmental events on behavior. ABA is effective in treating a variety of behaviors, including skin-picking in individuals with ASD (Ong et al., 2021). The intervention was implemented through a systematic process. First, John’s parents and teachers were trained on the ABA procedures and how to provide the necessary support for John. John was then assessed to identify the antecedents, behaviors, and consequences of his skin-picking (Lang et al., 2009). This information was used to develop a treatment plan for John. The treatment plan involved teaching John replacement behaviors to replace the skin-picking behavior.

To teach the replacement behaviors, John was introduced to recognizing the situations that triggered his skin-picking and using coping strategies to prevent it from occurring. John was also taught new behaviors to replace skin-picking. These behaviors included deep breathing, counting to 10, squeezing a stress ball, and using a fidget toy. John was given praise and rewards to reinforce these behaviors when he successfully used the replacement behaviors. John was also taught how to self-monitor his skin-picking behavior. He was prepared to keep a log of when and why he picked his skin. This information was then used to identify any patterns or triggers of his skin-picking behavior (Ong et al., 2021). John was further enlightened on identifying the consequences of his skin-picking behavior. He was taught to recognize that skin-picking could lead to pain, infection, and social embarrassment.

To maintain the effects of the intervention, John was taught how to generalize the replacement behaviors to new environments. To do this, John was asked to practice the replacement behaviors in different settings, such as at home, school, and in the community. This was done to ensure that John could use the replacement behaviors in different situations and contexts (Lang et al., 2009). In addition, John’s parents and teachers were trained on how to provide support for John in new environments.

John’s parents and teachers were asked to provide consistent feedback and reinforcement to ensure that the replacement behaviors were successful. They were asked to praise and reward John when he successfully used the replacement behaviors. They were also asked to provide corrective feedback when John was not using the replacement behaviors. To evaluate the effectiveness of the intervention, John’s skin-picking behavior was monitored for five weeks. During this time, data was collected to measure the frequency and duration of John’s skin-picking behavior (Lang et al., 2009). In addition, John’s parents and teachers were asked to complete surveys to measure the effectiveness of the intervention.

Data Collection

The data collection method used in the hypothetical behavior analytic research study was frequency recording. This method was chosen because it is an accurate and reliable way of measuring behavior. Frequency recording is a method of data collection used to measure the number of times a behavior occurs over time. Frequency recording allows the researcher to measure the exact number of times a behavior happens over time (Bull et al., 2020). This is important because it enables the researcher to measure the intervention’s effects accurately. The researcher also chose to use frequency recording because it allows the data to be collected in real time. This is important because it enables the researcher to measure the behavior while it occurs (Lang et al., 2009). This is important because it allows the researcher to collect data on the behavior in a real-world setting and accurately measure the intervention’s effects.

The instrument used for data collection in the hypothetical behavior analytic research study was a tally counter. A tally counter is a device used to count the number of times a behavior occurs. This device was chosen because it is an accurate and reliable way of measuring behavior. The tally counter allows the researcher to accurately measure the number of times a behavior occurs over time. This is important because it enables the researcher to accurately measure the effects of the intervention (Bull et al., 2020). The tally counter was also chosen because it is easy to use and efficient. The device is easy to use because it requires minimal training and can be used in various settings. This is important because it allows the researcher to collect data in multiple locations and accurately measure the intervention’s effects (Lang et al., 2009). Additionally, the tally counter is efficient because it requires no additional equipment or materials.

The data collection schedule used in the hypothetical behavior analytic research study was a multiple-baseline design. A multiple-baseline design is a type of data collection schedule used to measure an intervention’s effects. This design involves collecting data on behavior before an intervention is implemented and then collecting data after the intervention is implemented to measure the intervention’s effects (Bull et al., 2020). Baseline data was collected once a week for five weeks. Data was collected at John’s home and school for three hours. John’s parents and teachers collected data. John’s parents and teachers were trained on the data collection procedures before data collection. They were instructed to observe John and to record the number of times he engaged in skin-picking behavior each week (Bull et al., 2020). The data was then collected and analyzed to measure the effects of the intervention. Data collection was conducted confidentially. John’s parents and teachers were asked not to discuss the data collection with John (Lang et al., 2009). This was done to ensure that John did not become aware of the data collection process and that the data collected was accurate and reliable.

Interobserver Agreement

The interobserver agreement (IOA) method used in the hypothetical behavior analytic research study was the Kappa coefficient. The Kappa coefficient is a measure of interobserver agreement used to assess the reliability of data collected by two or more observers (Xavier et al., 2019). This method is used to measure the degree of agreement between two or more observers who are collecting data on the same behavior. The Kappa coefficient is a measure of understanding expressed as a number between 0 and 1 (Xavier et al., 2019). A Kappa coefficient of 0 indicates that the agreement between the observers is no better than chance. A Kappa coefficient of 1 indicates perfect agreement between the observers.

The Kappa coefficient was chosen as the IOA method because it is an accurate and reliable way of measuring agreement between observers. The Kappa coefficient allows the researcher to measure the exact degree of agreement between observers. For instance, the difference in the results achieved by the data collected by the parents and the teachers (Lang et al., 2009). This is important because it will enable the researcher to measure the reliability of the data collected accurately. Additionally, the Kappa coefficient allows the researcher to determine if the data collected is reliable enough to be used in the intervention analysis. The Kappa coefficient was also chosen as the IOA method because it is easy to use and interpret (Xavier et al., 2019). The Kappa coefficient is easy to use because it requires minimal training and can be used in various settings. This is important because it allows the researcher to collect data from a variety of backgrounds and to measure the agreement between observers accurately. Additionally, the Kappa coefficient is easily interpreted because it is expressed as a number between 0 and 1. This is important because it allows the researcher to quickly and easily analyze the degree of agreement between the observers.

Conclusion

The Kappa coefficient was calculated by dividing the number of times the observers agreed on behavior by the total number of observations. The percentage of sessions IOA was collected was determined by dividing the total number of sessions in the study-managed IOA. The percent agreement was determined by dividing the number of times the observers agreed on behavior by the total number of observations (Xavier et al., 2019). IOA was collected for 50% of the sessions in the hypothetical behavior analytic research study. This was done to ensure that the data collected was reliable and accurate. The Kappa coefficient for the IOA data was 0.76, which indicates that the agreement between the observers was higher than the chance. The percent agreement between the observers was 87%, showing that the observers agreed on most of the observations. These results suggest that the data collected by the observers was reliable and accurate.

References

Bull, L. E., Oliver, C., & Woodcock, K. A. (2020). Skin picking in people with Prader–Willi syndrome: Phenomenology and management. Journal of Autism and Developmental Disorders, 51(1), 286–297. Web.

Deckersbach, T., Wilhelm, S., Keuthen, N., Baer, L., & Jenike, M. (2002). Cognitive-behavior therapy for self-injurious skin picking. Behavior Modifications, 26, 361-377.

Lang, R., Didden, R., Sigafoos, J., Rispoli, M., Regester, A., & Lancioni, G. E. (2009). Treatment of chronic skin-picking in an adolescent with Asperger syndrome and borderline intellectual disability. Clinical Case Studies, 8(4), 317-325. Web.

Ong, K. M., Sun, M. D., & Rieder, E. A. (2021). Behavioral modification for acne excoriée and skin picking. Essential Psychiatry for the Aesthetic Practitioner, 216–222. Web.

Xavier, A. C., Souza, C. M., Flores, L. H., Prati, C., Cassal, C., & Dreher, C. B. (2019). Improving skin picking diagnosis among Brazilians: Validation of the skin picking impact scale and development of a photographic instrument. Anais Brasileiros De Dermatologia, 94(5), 553–560. Web.

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