Repeated measures latent class analysis identifies unique daily cocaine-use patterns and associated clinical...

Cocaine use poses significant health risks and treatment challenges. Individual patterns of multi-daily use and their association with clinical characteristics remain poorly understood. Novel approaches that differentiate cocaine-use patterns may improve clinical understanding and guide treatments. This study aimed to identify distinct patterns of cocaine use with a timeline follow-back (TLFB) approach and to evaluate relationships with demographics, cocaine-use severity, and negative emotionality.

Data were collected from 109 (88 male) non-treatment seeking people who use cocaine (mean + SD age 45.6+7.1 years) through past 15-day TLFB interviews tracking daily cocaine use and amounts. Bias-adjusted 3-step repeated-measures latent class analysis identified distinct patterns of daily binary (yes/no) cocaine use. Predictors of class membership including age, income, negative emotionality (depression and anxiety symptoms), and cocaine-use severity were evaluated via regression models as part of the last step of the 3-step RM-LCA approach.

Three cocaine-use patterns emerged: high variability across days (Class 1, n = 36), infrequent use (Class 2, n = 52), and consistent use across days (Class 3, n = 21). Consistent use class reported higher daily cocaine-use amounts and cocaine craving than high-variability and infrequent use classes; consistent use class also reported higher income than infrequent use. Infrequent use class reported lower income compared to high variability use.

This study identifies distinct patterns of cocaine use associated with different behavioral and demographic characteristics, providing a foundation for tailored treatment development and stratification. Future work should expand these methods and findings to explore the broader context of polysubstance use.