Sexual exploitation of young men: Background characteristics and needs from a life-course perspective.

Background: Sexually exploited young men are prevalent, yet underrepresented in clinical practice, policy and research. There are multiple barriers that often prevent young men to disclose and to seek or receive support, such as gender norms, limited awareness of victimization and feelings of guilt and shame.

Objective: By gaining more insight into the background characteristics of young men who experienced sexual exploitation and their needs, this study aims to raise awareness and to better inform policymakers, care- and educational professionals on adequate prevention and intervention efforts.

Introducing a multi-variate classification method: Risky driving acceptance among different heterogeneous driver sub-cultures.

Introduction: Heterogeneous driving populations with many different origins are likely to have various sub-cultures that comprise of drivers with shared driver characteristics, most likely with dissimilar traffic safety cultures. An innovative methodology in traffic safety research is introduced which is beneficial for large datasets with multiple variables, making it useful for the multi-variate classification of drivers, driving attitudes and/or (risky) driving behaviours.

Method: With the application of multidimensional scaling analysis (MDS), this study explores traffic safety culture in the State of Qatar using a questionnaire and investigates the similarity patterns between the questionnaire items, aiming to classify attitudes towards risky driving behaviours into themes.

Analysis of road traffic crashes in the State of Qatar.

Road traffic crashes (RTCs) are globally acknowledged as increasing threat to society, because they can affect many lives when they result in severe injury or fatality. In the State of Qatar RTCs are getting more awareness and attention, aiming to improve the traffic safety in the country. This study is an exploratory research providing different analyses of the crash data for seven consecutive years, ranging from 2010 to 2016, which is obtained from the Traffic Department in the Ministry of Interior for the State of Qatar.