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. Author manuscript; available in PMC: 2023 Dec 2.
Published in final edited form as: J Interpers Violence. 2022 Nov 11;38(9-10):6576–6600. doi: 10.1177/08862605221135166

Table 2.

Gender-specific estimates and linear regression coefficients for the association between 6th/7th/8th-grade sexual harassment victimization and concurrent psychological distress, as predicted by current-year sexual harassment victimization and potential confounders, among 4,718 middle school students in Kansas and Illinois

Gender-specific estimates b (95% CI) p
Association between above-mean sexual harassment victimization and concurrent psychological distress score, girls 2.12 (1.74, 2.50) <0.001
Association between above-mean sexual harassment victimization and concurrent psychological distress score, boys 1.57 (1.22, 1.92) <0.001
Linear regression coefficients for concurrent psychological distress b (95% CI) p

Sexual harassment victimization above mean, time t 2.12 (1.74, 2.50) <0.001
Male x sexual harassment victimization above mean, time t −0.55 (−1.04, −0.06) 0.032
Sexual harassment victimization, time t-1 (z score) −0.18 (−0.30, −0.05) 0.008
Time-varying potential confounders
Psychological distress, time t-1 (z score) 3.68 (3.51, 3.85) <0.001
Bullying victimization, time t (z score) 2.00 (1.83, 2.18) <0.001
Bullying victimization, time t-1 (z score) −0.76 (−0.93, −0.60) <0.001
Gender (ref=female)
  Male −2.03 (−2.27, −1.79) <0.001
Race/ethnicity (ref=White)
  Black or African American −0.30 (−0.59, −0.02) 0.046
  Hispanic or Latino/a/x 0.26 (0.04, 0.49) 0.023
  Asian or Asian American 0.24 (−0.71, 1.19) 0.636
  Biracial or multiracial 0.11 (−0.36, 0.58) 0.653
Baseline family context variables
Family functioning - moderate (ref=low) −0.12 (−0.25, 0.00) 0.066
Parental monitoring (z score) −0.04 (−0.16, 0.08) 0.501
Child abuse victimization index 0.04 (−0.14, 0.22) 0.681
Second Step implementation (ref=school did not implement Second Step)
  Attended school that implemented Second Step 0.06 (−0.15, 0.26) 0.586

Note. Estimates are based on a repeated-measures linear generalized estimating equations model. Gender-specific estimates were calculated using the main effect and interaction terms for sexual harassment victimization from the linear regression model.