Factors Associated With Ruminative Thinking in Individuals With Gender Dysphoria
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abstract
This study aimed to examine psychosocial factors and medical history as well as symptoms of depression, anxiety, and stress associated with ruminative thinking in transgender people with gender dysphoria (GD) before undergoing gender affirmation surgery (GAS). This study evaluated 189 participants with GD (111 trans women and 78 trans men) from a specialized service for GAS in southern Brazil. Semi-structured interviews were conducted, and participants were asked to complete self-report questionnaires. We recovered participants' sociodemographic and psychosocial data (e.g., history of sexual abuse, expulsion from home, and history of drug use) and data regarding their clinical history (e.g., medication, history of suicidal ideation and attempted suicide, and HIV status). Further, we implemented the Depression, Anxiety and Stress Scale (DASS-21) to examine participants' psychological state, as well as the Ruminative Response Scale (RRS) to assess ruminative thinking, which includes brooding and reflection. The predictor variables were those that exhibited a minimum level of significance of p ≤ 0.05 in multivariate linear regression. The ruminative thinking scores for trans women were higher than those of trans men (Brooding p = 0.014; Reflection p = 0.052).In the multivariate model, suicidal ideation, moderate depression, and severe/very severe anxiety were associated with both brooding and reflection. Feminine gender identity and stress symptoms moderated only brooding, while anxiety symptoms moderated only reflection. Our findings show that trans women had the highest ruminative thinking scores, and that depression, anxiety, stress, and suicidal ideation were associated with ruminative thinking in total sample. Psychological symptoms should be examined in the context of gender affirmation surgery to minimize the possibility of adverse mental health outcomes. Follow-up studies are required to measure ruminative thinking levels more accurately and to identify its predictors.
