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      PSH‐C: A measure of peer sexual harassment among children

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          Abstract

          Peer sexual harassment among adolescents is a widespread problem worldwide, associated with several adverse outcomes. Although retrospective reports indicate that people's first experience of peer sexual harassment occurs before puberty, research in younger ages is still scarce and measures of peer sexual harassment developed for children are lacking. This study explores the possibility of measuring peer sexual harassment in late childhood by evaluating a new scale of developmentally informed items, the Peer Sexual Harassment Scale—Child (PSH‐C), designed to capture peer sexual harassment (i.e., victimization, perpetration, and witnessing) in late childhood (ages 10–12 years) in the school context. Self‐report surveys were distributed to 1007 fourth‐grade students in Sweden ( M age = 10.0 years, SD = .3, n = 516 girls). The PSH‐C showed good psychometric properties, supporting the scale's ability to capture peer sexual harassment in late childhood. Exploratory structural equation analyses suggested a two‐factor structure which was confirmed by confirmatory factor analyses: 1) direct verbal sexual aggression, and 2) direct physical sexual harassment, verbal comments and jokes, and visual sexual harassment. The division of the structure contradicts previous studies of adolescents, possibly indicating a difference in the peer sexual harassment construct in relation to development and age.

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          G*Power is a free power analysis program for a variety of statistical tests. We present extensions and improvements of the version introduced by Faul, Erdfelder, Lang, and Buchner (2007) in the domain of correlation and regression analyses. In the new version, we have added procedures to analyze the power of tests based on (1) single-sample tetrachoric correlations, (2) comparisons of dependent correlations, (3) bivariate linear regression, (4) multiple linear regression based on the random predictor model, (5) logistic regression, and (6) Poisson regression. We describe these new features and provide a brief introduction to their scope and handling.
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            lavaan: AnRPackage for Structural Equation Modeling

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              Evaluating Goodness-of-Fit Indexes for Testing Measurement Invariance

                Author and article information

                Contributors
                Journal
                Journal of Social Issues
                Journal of Social Issues
                Wiley
                0022-4537
                1540-4560
                December 2023
                July 07 2022
                December 2023
                : 79
                : 4
                : 1123-1146
                Affiliations
                [1 ] Department of Psychology, University of Gothenburg Gothenburg Sweden
                Article
                10.1111/josi.12517
                369478b6-5352-4ec4-9920-e7c9d5844382
                © 2023

                http://creativecommons.org/licenses/by/4.0/

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