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Estimating the Effects of a Complex, Multidimensional Moderator: An Example of Latent Class Moderation to Examine
Bethany C Bray1, Eric K Layland2, Samuel W Stull3,4
1Institute for Health Research and Policy, University of Illinois Chicago, 1747 W Roosevelt Rd., IL, 60608, Chicago, USA. bcbray@uic.edu.
Abstract:
Improvements in substance use disorder recovery may be achieved by recognizing that effective interventions do not work equally well for all individuals. Heterogeneity of intervention effects is traditionally examined as a function of a single variable, such as gender or baseline severity. However, responsiveness to an intervention is likely a result of multiple, intersecting factors. Latent class moderation enables the examination of heterogeneity in intervention effects across subgroups characterized by profiles of characteristics. This study analyzed data from adolescents (aged 13 to 18 years old) who needed treatment for cannabis use (n = 14,854) and participated in the Global Appraisal of Individual Needs to evaluate differential effects of substance use services on cannabis use outcomes. We demonstrate an adjusted three-step approach using weights that account for measurement error; sample codes in Mplus and Latent Gold are provided and data are publicly available. Indicators of the latent class moderator comprised six contextual (e.g., recovery environment risk) and individual (e.g., internal mental distress) risk factors. The latent class moderator comprised four subgroups: low risk (21.1%), social risk (21.1%), environmental risk (12.5%), and mixed risk (45.2%). Limited moderation of associations between level of care and any past 90-day cannabis use were observed. In predicting number of cannabis use-days, compared to individuals with low risk, those with environmental risk showed improved outcomes from intensive outpatient care whereas individuals with social risk and mixed risk showed improved outcomes from residential care (all compared to early intervention/outpatient care). Latent class moderation holds potential to elucidate heterogeneity in intervention effectiveness that otherwise may go undetected.
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