Identifying the Causes of Social Isolation and Designing a Relevant Model for Female High School First-Year Students

Purpose: The aim of the present study was to identify the causes of social isolation and design a relevant model for high school students. Methodology: This was an applied study in terms of its aim and mixed-method study in terms of its implementation method (qualitative and quantitative). The study population in the qualitative section included documents and resources and educational management experts and, in the quantitative section, 180 female high-school first-year students in Gorgan during the academic year 2019-2020. According to the data saturation principle, the research population in the qualitative part included documents and resources related to social isolation and 10 educational management experts who were selected by purposive sampling. According to Cochran's formula, the study population in the quantitative section included 180 female high-school first-year students who were selected by cluster sampling method. Data were collected by note taking, interviews and a researcher- made questionnaire (39 items), the construct and convergent validity of which were confirmed and its reliability was obtained α=0.96 by Cronbach's alpha method. Data were analyzed by open and axial coding methods, factor analysis and structural equation modeling in MAXQDA software. Findings: The findings of the qualitative section showed that social isolation consists of six components and 40 indicators, including socio-economic anomalies (7 indicators), individual variables (9 indicators), parental role (5 indicators), strengthening social relations (6 indicators), psychological interactions (10 indicators), and family level (3 indicators). The findings of the quantitative section showed that the social isolation model had a good fit and all six components, i.e. socio-economic anomalies, individual variables, parental role, strengthening social relations, psychological interactions and family level had a significant effect on social isolation (P<0.05). Conclusion: According to the results, sociologists can use the social isolation model designed in the present study to reduce social isolation; therefore, it is necessary to pay attention to the role of effective components.