Participants were drawn from FAB400, an ongoing cohort study of 488 female-assigned-at-birth sexual and gender minority (FAB SGM) youth, which includes sexual minority women, transgender men, and non-binary FAB youth. FAB400 employs a merged cohort accelerated longitudinal design (Galbraith, Bowden, & Mander, 2017 (link)), and includes two cohorts: (1) a late adolescent cohort recruited for FAB400 in 2016–2017 (N =400; 16–20 years old at baseline); and (2) a young adult cohort comprised of FAB SGM participants from Project Q2 (Mustanski, Garofalo, & Emerson, 2010 (link)), a longitudinal study of SGM youth that began in 2007 (N = 88; 23–32 years old at the FAB400 baseline assessment). Inclusion criteria for FAB400 and Project Q2 were virtually identical, requiring participants to be 16–20 years old at enrollment, speak English, and either identify with a sexual or gender minority label, report same-sex attractions, or report same-sex sexual behavior. (The age range of the FAB 400 young adult cohort is wider than expected because three participants were younger than16 years old and three were older than 20 years old at Q2 enrollment, which was not discovered until age verification became possible through identification checks during follow-up. Because this paper is not a developmental analysis and we only use data from FAB400 baseline, we retained these participants in the analytic sample.) To enroll in FAB400, participants were also required to have been assigned female at birth.
Each cohort was recruited using used an incentivized snowball sampling approach. Participants were recruited directly from various venues (i.e., SGM community organizations, health fairs, high school/college groups) and online social media advertisements (45% of the sample); enrolled participants could refer up to five peers to the study (55% of the sample). Participants were paid $10 for each peer they successfully recruited into the cohort. To determine if it were necessary to account for clustering due to recruitment chain, we calculated design effects, which quantify the extent to which the sampling error deviates from what would be expected if individuals were randomly assigned to clusters. The design effect for each IPV variable was less than the recommended cutoff of 2.0 (Muthen & Satorra, 1995 (link)), indicating that the small amount of non-independence present within recruitment chains would have a negligible effect on the Type I error rate. Therefore, we did not account for clustering in analyses.
In 2016–2017, all 488 participants completed the FAB400 baseline assessment, followed by additional assessments at 6-month intervals. Participants were paid $50 for each assessment. The study protocol was approved by the Institutional Review Board (IRB) at a midwestern university with a waiver of parental permission for participants under 18 years of age under 45 CFR 46, 408(c) (Mustanski, 2011 (link)). Participants provided written informed consent, and a federal certificate of confidentiality was obtained to safeguard participant confidentiality.
For the present study, we used data from the baseline assessment. At that interview, participants were asked to report on up to three sexual and/or romantic partnerships occurring in the last 6 months, one of which they designated as the most significant (i.e., “… the person that you spent the most time with, were most serious about, or who had the biggest effect on you”). For this paper, we selected the 352 participants who indicated having a romantic relationship with their most significant partner in the last 6 months, to be consistent with procedures used in most studies of IPV (see Capaldi et al., 2012 (link)). Demographic information for the full (N = 488) and analytic (N = 352) samples is presented in Table 1. Of note, this sample is diverse in race/ethnicity, gender identity, sexual orientation identity, and household income.