Background: Studies published on gender-related differences in the gambling behavior of adolescents have focused mainly on psychological and social factors. The aim of this study was to develop separate risk factor models for male and female adolescents, considering the environmental, psychological, behavioral and socio-economic factors related to their gambling. Methods: A survey was conducted through a questionnaire developed on a dedicated web site in 2014 on a representative sample of the Italian 15–19-years-old population, including 34,922 students attending 438 secondary schools. The SOGS-RA questionnaire was used to measure gambling behavior. To verify the risk factors associated with gambling a logistic regression stratified by gender was performed. Results: In our representative sample of Italian adolescents nationwide, the prevalence of each level of gambling was higher in males than in females. The logistic regression stratified by gender found that for both genders, gambling was positively associated with internet surfing, playing sports, getting into a fight, having unprotected sex, pulling stunts, drinking alcohol at least once in the previous month, having not a satisfactory relationship with teachers, receiving pocket money from parents, spending each week much money and having someone in the family (father, sister/brother, other relatives) who gambles. On the other hand, having poor or average school marks, going to ED in the previous year, smoking at least once in the previous month, having dissatisfied with relationships with father and having a lower family income than their friends was only associated with gambling in boys. Having an accident or injury in the previous year and having a mother who gambled was associated only in girls with higher odd of at risk or problem gambling behavior. A low psychological distress is protective only in girls for risk of gambling. Conclusions: Understanding the gender-related differences, and how they emerge in younger people at the start of their gambling careers, can suggest how best to educate individuals, families and the community on the topic of gambling. Programs to prevent substance use and abuse should be multifaceted, and include efforts to prevent gambling with a gender perspective approach.

Vaccination against SARS-CoV-2 will likely be the most promising way to combat the pandemic. Even if mass vaccination is urgent, it should still always be supported by appropriate patient safety management. The aim of this study, based on failure mode, effects and criticality analysis (FMECA), was to identify possible failures and highlight measures that can be adopted to prevent their occurrence. A team of resident doctors in public health from the University of Padua and specialists in risk analysis in public health examined the mass vaccination process. A diagram was drafted to illustrate the various phases of mass vaccination, analyze the process, and identify all failure modes. Criticalities were ascertained by rating the severity, frequency and likelihood of failure detection on a scale of 1 to 10. We identified a total of 71 possible faults distributed over the various phases of the process, and 34 of them were classified as carrying a high risk. For the potentially high-risk failure modes, we identified 63 recommended actions to contain the cause of their occurrence or improve their detection. For the purpose of detecting potential failures, FMECA can be successfully applied to mass vaccination, which should be considered a high-risk process.

During the COVID-19 pandemic, many countries adopted various non-pharmacological interventions to contain the number of infections. The most often used policy was school closures. We describe the strategy adopted by the Veneto Regional Authority to contain transmission in school settings. This included a detailed school surveillance system, strict contact tracing, and maintaining school attendance with self-monitoring for symptoms whenever possible. All analyzed COVID-19 cases among children, adolescents (0–19 years old), and school staff were registered using a web-based application between 4 January 2021 and 13 June 2021. During the study period, 6272 episodes of infection in schools were identified; 87% were linked to a student index case and 13% to school staff; 69% generated no secondary cases; 24% generated one or two; and only 7% caused more than two. Our data may help to clarify the role of school closures, providing useful input for decisions in the months to come. Good practice in public health management needs tools that provide a real-time interpretation of phenomena like COVID-19 outbreaks. The proposed measures should be easy to adopt and accessible to policymakers.