The role of family and school-level factors in bullying and cyberbullying: a cross sectional study

Background: Bullying and cyberbullying are common phenomena in schools. These negative behaviours can have a significant impact on the health and particularly mental health of those involved in such behaviours, both as victims and as bullies. This UK study aims to investigate student-level and school-level characteristics of those who become involved in bullying and cyberbullying behaviours as victims or perpetrators. Methods: We used data from 6667 Year 7 students from the baseline survey of a cluster randomized trial in 40 English schools to investigate the associations between individual-level and school-level variables with bullying victimization, cyberbullying perpetration, and cyberbullying victimization. We ran multilevel models to examine associations of bullying outcomes with individual-level variables and school-level variables. Results: In multilevel models, at the school level, school type and school quality measures were associated with bullying risk: students in voluntary-aided schools were less likely to report bullying victimization (0.6 (0.4, 0.9) p = 0.008), and those in community (3.9 (1.5, 10.5) p = 0.007) and foundation (4.0 (1.6, 9.9) p = 0.003) schools were more likely to report being perpetrators of cyberbullying than students in mainstream academies. A school quality rating of “Good” was associated with greater reported bullying victimization (1.3 (1.02, 1.5) p = 0.03) compared to ratings of “Outstanding.” Conclusions: Bullying victimization and cyberbullying prevalence vary across school type and school quality, supporting the hypothesis that organisational/management factors within the school may have an impact on students’ behaviour. These findings will inform future longitudinal research investigating which school factors and processes promote or prevent bullying and cyberbullying behaviours. Trial registration: Trial ID: ISRCTN10751359 Registered: 11/03/2014 (retrospectively registered)

If you build it, they still may not come: outcomes and process of implementing a community-based integrated knowledge translation mapping innovation

<p>Abstract</p> <p>Background</p> <p>Maps and mapping tools through geographic information systems (GIS) are highly valuable for turning data into useful information that can help inform decision-making and knowledge translation (KT) activities. However, there are several challenges involved in incorporating GIS applications into the decision-making process. We highlight the challenges and opportunities encountered in implementing a mapping innovation as a KT strategy within the non-profit (public) health sector, reflecting on the processes and outcomes related to our KT innovations.</p> <p>Methods</p> <p>A case study design, whereby the case is defined as the data analyst and manager dyad (a two-person team) in selected Ontario Early Year Centres (OEYCs), was used. Working with these paired individuals, we provided a series of interventions followed by one-on-one visits to ensure that our interventions were individually tailored to personal and local decision-making needs. Data analysis was conducted through a variety of qualitative assessments, including field notes, interview data, and maps created by participants. Data collection and data analysis have been guided by the Ottawa Model of Research Use (OMRU) conceptual framework.</p> <p>Results</p> <p>Despite our efforts to remove all barriers associated with our KT innovation (maps), our results demonstrate that both individual level and systemic barriers pose significant challenges for participants. While we cannot claim a causal association between our project and increased mapping by participants, participants did report a moderate increase in the use of maps in their organization. Specifically, maps were being used in decision-making forums as a way to allocate resources, confirm tacit knowledge about community needs, make financially-sensitive decisions more transparent, evaluate programs, and work with community partners.</p> <p>Conclusions</p> <p>This project highlights the role that maps can play and the importance of communicating the importance of maps as a decision support tool. Further, it represents an integrated knowledge project in the community setting, calling to question the applicability of traditional KT approaches when community values, minimal resources, and partners play a large role in decision making. The study also takes a unique perspective--where research producers and users work as dyad-pairs in the same organization--that has been under-explored to date in KT studies.</p

Roads from Rio+20. Pathways towards global sustainable development targets for 2050

In 1992, governments worldwide agreed to work towards a more sustainable development that would eradicate poverty, halt climate change and conserve ecosystems. Although progress has been made in some areas, actions have not been able to bend the trend in other, critical areas of sustainable development – areas such as those providing access to sufficient food and modern forms of energy, preventing dangerous climate change, conserving biodiversity and controlling air pollution. Without additional effort, these sustainability objectives also will not be achieved by 2050. This report analyses how combinations of technological measures and changes in consumption patterns could contribute to achieving a set of sustainability objectives, taking into account the interlinkages between them. The potential exists for achieving all of the objectives. The fundamental question here relates to the type of governance structures that could bring about the transformative changes required to meet the sustainable development objectives. We suggest a pragmatic governance approach that consists of a shared vision for 2050, strengthened short-term targets, and strong policy actions by governments, building on the strength of civil society and business

Bankruptcy Prediction During the IMF Crisis: Evidence from Malaysian Listed Industrial Companies

This paper develops bankruptcy prediction model of considerable efficiency for firms listed and traded in a small developing economy. New findings reported in this paper help extend bankruptcy prediction literature to a different market setting. We find there are three relevant variables: total liabilities; current asset turnover; and cash ratios. The model correctly classified about nine-tenth of failed and non-failed firms in the original and holdout samples. The model predicts failure four years ahead. We also introduce a further sample comprising of those firms that had experienced financial distress between 1997-1998 (during the Asian Financial Crisis period) to assess model superiority. The predictive accuracy of the model reveals that it was significantly better than chance. Thus, these findings are somewhat different from those in the literature