Levels and sources of adolescents' sexual knowledge in traditional societies: A cross‐sectional study.

  • Published In: Nursing & Health Sciences, 2023, v. 25, n. 1. P. 120 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Jabareen, Raifa; Zlotnick, Cheryl 3 of 3

Abstract

Gender rules, patriarchy, and cultural taboos on sexual issues in traditional societies may compel adolescents to seek sexual information from informal and inadequate sources. The aim of this cross‐sectional study was to determine whether the level and sources of sexual knowledge differed by gender in the traditional community comprising Palestinian‐Israeli high school students. Guided by the Human Ecological Systems Model and informed by a community‐based participatory research approach, a convenience sample of high school students (n = 558) was recruited. Although findings indicated that both boys and girls had low levels of sexual knowledge, the areas of knowledge deficits varied by gender. The model demonstrated good fit for boys but not for girls. Post hoc analyses indicated that girls obtained sexual knowledge solely from close family members, while boys obtained sexual knowledge from multiple sources. Very few students of either gender obtained sexual knowledge from doctors or nurses, but with community input on cultural issues, nurses can play a pivotal role in creating comprehensive, school‐based sex education for adolescents living in traditional societies. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Nursing & Health Sciences. 2023/03, Vol. 25, Issue 1, p120
  • Document Type:Article
  • Subject Area:Ethnic and Cultural Studies
  • Publication Date:2023
  • ISSN:1441-0745
  • DOI:10.1111/nhs.12999
  • Accession Number:162730453
  • Copyright Statement:Copyright of Nursing & Health Sciences is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Looking to go deeper into this topic? Look for more articles on EBSCOhost.