Demographic and Clinical Variables Associated With Transcranial Magnetic Stimulation Response in Depression: A Growth Mixture Modeling Study
Depression is a growing public health crisis impacting millions around the world. Transcranial Magnetic Stimulation (TMS) is a non-invasive treatment for depression which has been FDA approved but the factors related to how well patients respond are still under investigation. The current study aimed to identify different treatment response patterns based on Patient Health Questionnaire (PHQ-9) scores over the course of transcranial magnetic stimulation (TMS) treatment for depression and to identify the differences between these response classes on demographic and clinical variables. A total of 285 patients from a psychiatric clinic were included with a sizable number of Hispanics and Military Families. Growth mixture modeling (GMM) was used to classify participants according to their response during TMS treatment. Three classes were identified: Responsive (56.5%), Excellent Response (56.6%), and Non-Response (13.3%). Various demographic and clinical variables were compared across these classes using chi-square tests of independence and analysis of variance (ANOVA) revealing 12 significant differences/associates (p<.01). Notably, higher depression severity at treatment initiation and comorbid chronic pain diagnosis was associated with poorer response. The results contribute to the literature confirming factors associated with TMS treatment response in a sample with underrepresented populations. Future research should include a follow-up at various timepoints to better understand the longevity of TMS treatment for depression. Likewise, brain biomarkers such as EEG could aid in better quantifying depression subtypes to further enhance treatment outcomes.
Psychology|Quantitative psychology|Hispanic American studies|Public health
Capps, John William, "Demographic and Clinical Variables Associated With Transcranial Magnetic Stimulation Response in Depression: A Growth Mixture Modeling Study" (2023). ETD Collection for University of Texas, El Paso. AAI30494155.