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Profiles of Adolescent Relationship Abuse and Sexual Harassment: a Latent Class Analysis

Abstract

This study aims to identify homogeneous groups of individuals based on self-reported victimization and perpetration of three subtypes of adolescent relationship abuse (ARA; physical, psychological, and sexual) and sexual harassment (SH). Study sample consists of 645 current or past-year daters aged 12–21, drawn from the National Survey on Teen Relationships and Intimate Violence (STRiV). Latent class analysis was used to classify individuals, and a three-class model was selected (Low ARA-Low SH, High ARA-High SH, and Psychological ARA-Medium SH). Results provide evidence for three latent classes with varying patterns of ARA and SH. A number of exogenous variables were significantly associated with these patterns, e.g., youth who were previously exposed to any general violence were three times as likely to be in the High ARA-High SH class as those not previously exposed to violence. Adolescent relationship abuse prevention efforts should include activities to address sexual harassment, and vice versa. Results call for universal preventive intervention programs targeting adolescent relationship abuse and sexual harassment to start as early as adolescence, and the existence of the High ARA-High SH group supports the need for more targeted effort to interrupt such patterns.

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Funding

This research was funded by National Institute of Justice (2011-WG-BX-0020).

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Correspondence to Weiwei Liu.

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All procedures performed were in accordance with the ethical standards of the NORC IRB and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Informed consent was confirmed from respondents at the time of interview.

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Liu, W., Taylor, B.G. & Mumford, E.A. Profiles of Adolescent Relationship Abuse and Sexual Harassment: a Latent Class Analysis. Prev Sci 21, 377–387 (2020). https://doi.org/10.1007/s11121-019-01075-5

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Keywords

  • Adolescent relationship abuse
  • Sexual harassment
  • Latent class analysis
  • STRiV