Development and validation of dependence and craving measures specific to athletes who use anabolic-androgenic steroids

Abstract

Anabolic-androgenic steroid (AAS) dependence affects approximately 30% of people who use AAS. Presently, measures to assess and diagnose AAS dependence are adapted from scales specific to other forms of drug misuse (e.g., alcohol), containing issues with internal consistency and breadth of construct capture. Additionally, there are no measures available to assess AAS craving, which represents a potentially important coeval factor to AAS dependence. Therefore, this study aimed to develop and provide evidence of validity for measures of AAS dependence and AAS craving.Data were collected from male and female strength athletes who use AAS across two samples (nsample 1 = 206; nsample 2 = 224). Sample 1 completed the new measures alongside instruments assessing theoretically related constructs (Doping Moral Disengagement, Doping Self-Regulatory Efficacy Scale, craving items from the Wisconsin Smoking Withdrawal Scale, AAS adapted Diagnostic and Statistical Manual for Mental Disorder 4th Edition), whereas Sample 2 completed the new instruments.Exploratory and Confirmatory Factor Analyses (CFA) with Sample 1 data were used to finalize the item sets for both measures and determine the factorial structures of the AAS Dependence Scale (AASDS) and AAS Craving Scale (AASCS). The AASDS consists of 15-items across five first-order factors that are represented by one second-order factor. The AASCS consists of 16-items across four first-order factors that are represented by one second-order factor. Evidence supporting the concurrent, convergent and discriminant validity of scores obtained with both scales was provided through their associations with the theoretically related variables. CFA with the data from Sample 2 confirmed the factor structures for both scales.The AASDS and AASCS represent valid and reliable measures of AAS dependence and AAS craving for use in research with strength athletes who use AAS.