Strengths and limitations
LCA
The data utilized in this study was drawn from a treatment-seeking sample recruited to an alcohol treatment trial; data collection was rigorous and standardized, and the dataset was reviewed and cleaned prior to analysis. LCA is a rigorous model-based approach that provides several fit statistics to assess model fit, and is appropriate for studying and classifying heterogeneity within a population. However, the cross-sectional nature of the data precludes the temporal ordering of variables, and it is recognized that class membership could change over alcohol consumption and help-seeking trajectories. Data on participants’ perceived treatment barriers were collected using binary indicator variables belonging to five pre-defined domains used in previous research (