AddictionScience2023.pdf

Data capture and statistical approach All study data were collected and managed using REDCap (Research Electronic Data Capture) hosted at the University of Pennsylvania [15]. Descriptive statistics were calculated to characterize the sample at study entry and to generate prevalence rates for lifetime suicidal ideation and attempts. Next, a series of bivariate correlations were calculated between each of the binary suicide-related response variables (i.e., lifetime ideation, lifetime attempts) and clinical and demographic factors that may be associated with suicidality (age, education completed [years], gender identity [male/female with additional responses added for non-binary, etc.], race [White, Black, Other], ethnicity, years of heroin use and other opioid use, lifetime history of depression or anxiety [yes/no], physical and/or sexual abuse [yes/no], presence of a chronic pain-related condition [yes/no], parole/ probation [yes/no], days worked [past 30 days], and lifetime years of daily use of more than one substance [including alcohol]). Finally, a series of logistic regression analyses were performed to predict each of the suicide related binary response variables.