A systematic literature review on preventing violent extremism

Disentangling Support for Violent and Non-violent Radicalization among Adolescents: A Latent Profile Analysis

Although support for violent and non-violent radicalization can co-occur, only a few adolescents who support non-violent radicalization also support or engage in violent acts. Yet, little is known about what factors are associated with adolescents' paths towards or away from violent and/or non-violent radicalization. Within a socio-ecological and positive youth development framework, this study investigates profiles of support for violent and non-violent radicalization among adolescents attending high schools in Quebec (Canada) and whether such profiles are differently associated with experiences of social adversity, school-, family- and peer-related factors and psychological distress. Adolescents (N = 1911; Mage = 15.7; SDage = 0.98; 48.7% girls) completed an online survey during school hours. A Latent Profile Analysis on scores of support for violent and non-violent radicalization was conducted. A multinomial logistic regression was used to explore the associations between profiles and variables of interest. We identified six profiles of adolescents. The heterogeneity of profiles suggested multiple and complex combinations of support for violent and non-violent radicalization as well as their co-existence in some but not all profiles. Adolescents who reported less discrimination, more positive school experiences and more family support were less likely to belong to profiles that supported violence. Primary prevention efforts in the field of support for violent radicalization must adopt a socio-ecological and social justice approach and consider the diversity of adolescents' profiles, attitudes and experiences.

Digital media use, depressive symptoms and support for violent radicalization among young Canadians: a latent profile analysis

BACKGROUND

Despite the prominent role that digital media play in the lives and mental health of young people as well as in violent radicalization (VR) processes, empirical research aimed to investigate the association between Internet use, depressive symptoms and support for VR among young people is scant. We adopt a person-centered approach to investigate patterns of digital media use and their association with depressive symptoms and support for VR.

METHODS

A sample of 2,324 Canadian young people (Mage = 30.10; SDage = 5.44 ; 59% women) responded to an online questionnaire. We used latent profile analysis to identify patterns of digital media use and linear regression to estimate the associations between class membership, depressive symptoms and support for VR.

RESULTS

We identified four classes of individuals with regards to digital media use, named Average Internet Use/Institutional trust, Average internet use/Undifferentiated Trust, Limited Internet Use/Low Trust and Online Relational and Political Engagement/Social Media Trust. Linear regression indicated that individuals in the Online Relational and Political Engagement/Social Media Trust and Average Internet Use/Institutional trust profiles reported the highest and lowest scores of both depression and support for VR, respectively.

CONCLUSIONS

It is essential to tailor prevention and intervention efforts to mitigate risks of VR to the specific needs and experiences of different groups in society, within a socio-ecological perspective. Prevention should consider both strengths and risks of digital media use and simulteaneously target both online and offline experiences and networks, with a focus on the sociopolitical and relational/emotional components of Internet use.

Estimating solid waste generation and suitability analysis of landfill sites using regression, geospatial, and remote sensing techniques in Rangpur, Bangladesh

Municipal solid waste (MSW) management has been a growing problem in fast-developing cities. A considerable amount of solid waste is generated daily and disposed anywhere, which creates an unhealthy environment. This study aims to develop a model to determine household solid waste (HSW) generation using multiple linear regression and identify suitable landfill sites to ensure proper MSW disposal in Rangpur City, Bangladesh. Socioeconomic variables data like average monthly income, educational level, family size, age of family head, and average HSW generation per day were collected from 381 respondents through stratified random sampling with a 95% confidence level. Multi-criteria decision analysis (MCDA) was performed using variables like surface water, slope, road network, and land use through GIS and remote sensing to find suitable landfill sites. Results of the model show no multicollinearity as the variance inflation factor was estimated to be less than 2 for each independent variable. Furthermore, the model provides a moderate overall fit because of the coefficient of determination (R² = 0.661), which denotes the independent variables' predictive capability. The results also demonstrate that family size and education are the most critical variables in predicting waste generation because of the values of coefficients 122.39 and - 184.72, respectively. This study also illustrated suitable landfill sites through MCDA, which can be a useful resource for the city authority to ensure environmental sustainability by implementing effective strategies for proper MSW management.