Effects of a School-Based Intervention for Preventing Substance Use among Adolescents at Risk of Academic Failure: A Pilot Study of the Reasoning and Rehabilitation V2 Program.

Tobacco, alcohol and cannabis use are important health problems that contribute greatly to causes of death in worldwide. Early onset of substance use increases rapidly during adolescence and it has been associated with a wide range of adverse events. Because substance use is associated with dramatic consequences, delaying the initiation of substance use among adolescents remains a major public priority. This study examined the effectiveness of a school-based intervention program based on the application of the Reasoning and Rehabilitation V2 (R&R2) program for preventing substance use among adolescents at risk of academic failure. A sample of 142 participants (aged 13-17 years old) who were studying alternative education provision in Spain were randomly allocated to two conditions (68 experimental group, 74 control group). A pre-test survey assessing past and current substance use was conducted prior the implementation of the program, while a post-test survey was conducted about 12 months after the pre-test. The results showed a significant effect of the R&R program in the reduction of cigarette smoking, episodes of drunkenness, alcohol consumption and cannabis use. However, for daily smoking and episodes of drunkenness such benefits showed a reduction over time. These findings offer additional evidence of the effectiveness of the Reasoning and Rehabilitation V2 program in Spanish adolescent students who are exposed to substance use and suggest areas of future research.

Psychometric Properties and Confirmatory Factor Analysis of the Spanish Version of the Maudsley Violence Questionnaire among Adolescent Students.

The Maudsley Violence Questionnaire (MVQ) is an instrument specifically developed to evaluate violent thinking through two subscales examining macho attitudes and the acceptance of violence. This study analyzed the psychometric properties and factor structure of the Spanish version of the MVQ questionnaire in a large sample of 1933 Spanish adolescents. An online questionnaire was used to collect variables, such as sociodemographic and sexism data. The factor structure showed good fit indices in Spanish adolescents, which were similar to the original scale. The exploratory analysis yielded a first factor that explained 11.3% of the total variance and a second factor that explained 10.8% of the total variance. The Goodness of Fit Index (GFI) (0.902), Adjusted Goodness of Fit Index (AGFI) (0.90), Normed Fit Index (NNFI) (0.85), and the Comparative Fit Index (CFI) (0.86) suggested that the model fit the data adequately (with values ≥ 0.90) and the Root Mean Square Error of Approximation (RMSEA) (≤0.10) values indicative of an adequate fit. This study contributes a Spanish-language validated tool to measure machismo and the acceptance of violence among adolescents.

Dynamic measures for transportation networks.

Most complex network analyses of transportation systems use simplified static representations obtained from existing connections in a time horizon. In static representations, travel times, waiting times and compatibility of schedules are neglected, thus losing relevant information. To obtain a more accurate description of transportation networks, we use a dynamic representation that considers synced paths and that includes waiting times to compute shortest paths. We use the shortest paths to define dynamic network, node and edge measures to analyse the topology of transportation networks, comparable with measures obtained from static representations. We illustrate the application of these measures with a toy model and a real transportation network built from schedules of a low-cost carrier. Results show remarkable differences between measures of static and dynamic representations, demonstrating the limitations of the static representation to obtain accurate information of transportation networks.

Effectiveness of the TEI Program for Bullying and Cyberbullying Reduction and School Climate Improvement.

The increase in the prevalence of bullying and cyberbullying in recent years worldwide is undeniable. Although several intervention programs oriented towards the reduction of bullying and cyberbullying have been developed and implemented, significant disparities have been found regarding their efficacy. In most of the cases, the lack of the implementation of interventions involving all of the school community could be on the basis of this limited efficacy. The present study aimed to evaluate the effectiveness of the TEI Program, an intervention based on peer tutoring, in the reduction of bullying and cyberbullying, and in the improvement of school climate. The design of the study was quasi-experimental, in which 2057 Spanish students (aged 11 to 16 years) participated from 22 schools, and were randomly assigned to the experimental group (10 schools, 987 students) or the control group (12 schools, 1070 students). The obtained results showed a significant reduction in bullying behavior, peer victimization, fighting, cyberbullying and cybervictimization in the experimental group after the intervention implementation. Similarly, a significant improvement in factors of school climate was found only in this group. The obtained results demonstrated that the TEI program is effective in reducing bully and cyberbully behavior, and at the same time, improving the school climate.

Optimal Allocation of Node Capacity in Cascade-Robustness Networks.

The robustness of large scale critical infrastructures, which can be modeled as complex networks, is of great significance. One of the most important means to enhance robustness is to optimize the allocation of resources. Traditional allocation of resources is mainly based on the topology information, which is neither realistic nor systematic. In this paper, we try to build a framework for searching for the most favorable pattern of node capacity allocation to reduce the vulnerability to cascading failures at a low cost. A nonlinear and multi-objective optimization model is proposed and tackled using a particle swarm optimization algorithm (PSO). It is found that the network becomes more robust and economical when less capacity is left on the heavily loaded nodes and the optimized network performs better resisting noise. Our work is helpful in designing a robust economical network.