Abstract: Intersection of Disability, School Climate, and School Violence in Inclusive Settings (Society for Social Work and Research 27th Annual Conference - Social Work Science and Complex Problems: Battling Inequities + Building Solutions)

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323P Intersection of Disability, School Climate, and School Violence in Inclusive Settings

Schedule:
Friday, January 13, 2023
Phoenix C, 3rd Level (Sheraton Phoenix Downtown)
* noted as presenting author
Saahoon Hong, PhD, Assistant Research Professor, Indiana University, IN
Background. School violence, including bullying and other forms of aggression, has been a common topic of national concern throughout the last decades across countries. Literature on school violence highlighted the importance of school climate in reducing violence and fostering a safe school environment (Espelage & Hong, 2019). In South Korea, nearly 55 percent of students reported that their friends became victims of school violence at least once during the previous month of the survey (Seoul Education Longitudinal Study, 2016). However, little is known about school violence and its school climate in inclusive settings that students with disabilities experience. This study examined the intersection of disability, psychosocial characteristics, school violence, friendship, and teacher roles in examining the effect of school violence and school climate on self-efficacy among students with disabilities.

Methods. The study utilized the third year of data collected from the Seoul Education Longitudinal Study (SELS, 2016). The student sample was of interest and comprised students with/without disabilities who were 9th graders in middle schools (total n=4,056; n of students with disabilities=171). In addition, demographic information and psycho-social characteristics were included to identify intersections of disability, gender, self-efficacy, school violence, friendship, and teacher effectiveness.

Analysis. This study focused on two groups (Disability vs. Non-Disability): the SELS’s six domains (i.e., school climate, school violence, attitudes toward friends/teachers/parents, self-efficacy), gender, and household income. The balance node in IBM SPSS Modeler was administered to create a better distribution of the participants. Then, the intersection of disability and school violence was examined by a machine learning decision tree model, chi-square automatic interaction detection (CHAID) (Milanović & Stamenković, 2016). In addition, hierarchical linear regression models were implemented to confirm the findings from the CHAID analysis.

Results. Findings presented that students with disabilities were more likely to experience school violence, and their self-efficacy was negatively associated with school violence. The CHAID indicated that the most significant predictor of a disability was income, followed by parents, school climate, school violence, friends, teachers, and gender. The overall model accuracy was .82, indicating that the model distinguished well between disability and non-disability.

Conclusion and Implications: The findings present well-posed variables to build the prediction model of students with disabilities in inclusive settings. The prediction model describes, in reverse, what areas of need and support we should consider for students with disabilities in inclusive settings. It could eventually be a foundation for another in-depth analysis of the best practice model for successful inclusion, such as effective programs to divert students with disabilities from exclusion, isolation, and school violence.