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Sexual jokes at school and psychological complaints: Student- and class-level associations.

Sara Brolin LåftmanYlva BjereldBitte ModinPetra Löfstedt
Published in: Scandinavian journal of public health (2020)
Background: Students who are subjected to sexual harassment at school report lower psychological well-being than those who are not exposed. Yet, it is possible that the occurrence of sexual harassment in the school class is also stressful for those who are not directly targeted, with potential negative effects on well-being for all students. Aim: The aim was to examine whether exposure to sexual jokes at the student level and at the class level was associated with students' psychological complaints, and if these associations differed by gender. Method: Data from the Swedish Health Behaviour in School-aged Children (HBSC) of 2017/18 was used, with information from students aged 11, 13 and 15 years (N=3720 distributed across 209 classes). Psychological health complaints were constructed as an index based on four items. Exposure to sexual jokes at the student level was measured by one item, and at the class level as the class proportion of students exposed to sexual jokes, in per cent. Two-level linear regression analyses were performed.Results: Students who had been exposed to sexual jokes at school reported higher levels of psychological complaints, especially boys. Furthermore, the class proportion of students who had been exposed to sexual jokes was also associated with psychological complaints, even when adjusting for student-level exposure to sexual jokes, gender, grade and class size. Conclusions: Sexual jokes seem to be harmful for those who are directly exposed, but may also affect indirectly exposed students negatively. Thus, a school climate free from sexual jokes may profit all students.
Keyphrases
  • high school
  • mental health
  • physical activity
  • healthcare
  • public health
  • risk assessment
  • social media
  • health information
  • wastewater treatment
  • electronic health record
  • deep learning
  • neural network