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.