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Uncovering multiple pathways to substance use: a comparison of methods for identifying population subgroups
Lisa Dierker1, Jennifer Rose, Xianming Tan
1Psychology Department, Wesleyan University, 207 High Street, Middletown, CT 06459, USA. ldierker@wesleyan.edu
The Journal of Primary Prevention
|September 17, 2010
Summary
This study compares modeling techniques to find population subgroups for targeted substance use interventions. It reviews trajectory analysis, functional hierarchical linear modeling (FHLM), and decision trees to guide intervention strategies.
Area of Science:
- Public Health
- Biostatistics
- Behavioral Science
Background:
- Identifying homogeneous population subgroups is crucial for effective, targeted substance use interventions.
- Existing modeling techniques offer various approaches to subgroup identification, each with unique strengths and limitations.
Purpose of the Study:
- To describe and compare available modeling techniques for identifying homogeneous population subgroups.
- To inform the development of targeted substance use intervention programs by evaluating different analytical methods.
Main Methods:
- A nontechnical review of three common modeling techniques: trajectory analysis, functional hierarchical linear modeling (FHLM), and decision tree methods.
- Comparison of methods based on data requirements, modeling flexibility for outcomes and predictors, and applicability to intervention planning.
Main Results:
- Each method (trajectory analysis, FHLM, decision trees) possesses distinct features influencing its suitability for subgroup identification.
- Understanding the strengths and limitations of each technique is essential for selecting the most appropriate approach.
Conclusions:
- The choice of modeling technique impacts the ability to identify specific population subgroups for substance use interventions.
- These methods can guide the selection of targets and optimal timing for substance intervention programs.
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