Abstract
This chapter starts with the premise that an investigator has completed an optimization trial and analyzed the data. Now what? How does an investigator take these experimental results and use them to create an optimized intervention ? In other words, how does an investigator use empirical data from an optimization trial to make decisions about which components and component levels will constitute the optimized intervention? This chapter describes one approach to making the decisions needed to complete the optimization phase of the multiphase optimization strategy (MOST). Familiarity with the material in Chaps. 1, 2, 3, 4, 5, and 6 is assumed throughout the present chapter.
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References
Collins, L. M., & Kugler, K. C. (Eds.). (2018). Optimization of multicomponent behavioral, biobehavioral, and biomedical interventions: Advanced topics. New York, NY: Springer.
Collins, L., Trail, J., Kugler, K., Baker, T., Piper, M., & Mermelstein, R. (2014). Evaluating individual intervention components: Making decisions based on the results of a factorial screening experiment. Translational Behavioral Medicine, 4, 238–251.
Cook, J. W., Collins, L. M., Fiore, M. C., Smith, S. S., Fraser, D., Bolt, D. M., et al. (2016). Comparative effectiveness of motivation phase intervention components for use with smokers unwilling to quit: A factorial screening experiment. Addiction, 111, 117–128.
Dziak, J. (2018). Optimizing the cost-effectiveness of a multicomponent intervention using data from a factorial experiment: Considerations, open questions, and tradeoffs among multiple outcomes. In L. M. Collins & K. C. Kugler (Eds.), Optimization of behavioral, biobehavioral, and biomedical interventions: Advanced topics. (forthcoming) New York, NY: Springer.
Kraemer, H. C. (2011). Another point of view: Superiority, noninferiority, and the role of active comparators. The Journal of Clinical Psychiatry, 72, 1350–1352.
Kugler, K. C., Dziak, J. J., & Trail, J. (2018). Coding and interpretation of effects in analysis of data from a factorial experiment. In L. M. Collins & K. C. Kugler (Eds.), Optimization of multicomponent behavioral, biobehavioral, and biomedical interventions: Advanced topics (forthcoming). New York, NY: Springer.
MacKinnon, D. P. (2008). Introduction to statistical mediation analysis. New York: Lawrence Erlbaum Associates.
Piper, M. E., Cook, J. W., Schlam, T. R., Jorenby, D. E., Smith, S. S., Collins, L. M., ... Baker, T. B. (in press). A randomized controlled trial of an optimized smoking treatment delivered in primary care. Annals of Behavioral Medicine.
Piper, M. E., Fiore, M. C., Smith, S. S., Fraser, D., Bolt, D. M., Collins, L. M., et al. (2016). Identifying effective intervention components for smoking cessation: A factorial screening experiment. Addiction, 111, 129–141.
Schlam, T. R., Fiore, M. C., Smith, S. S., Fraser, S., Bolt, D. M., Collins, L. M., et al. (2016). Comparative effectiveness of intervention components for producing long-term abstinence from smoking: A factorial screening experiment. Addiction, 111, 142–155.
Smith, R. A., Coffman, D. L., & Zhu, X. (2018). Investigating an intervention’s causal story: Mediation analysis using a factorial experiment and multiple mediators. In L. M. Collins & K. C. Kugler (Eds.), Optimization of multicomponent behavioral, biobehavioral, and biomedical interventions: Advanced topics (forthcoming). New York, NY: Springer.
Walker, E., & Nowacki, A. S. (2011). Understanding equivalence and noninferiority testing. Journal of General Internal Medicine, 26, 192–196.
Wu, C. F. J., & Hamada, M. S. (2009). Experiments: Planning, analysis, and optimization (2nd ed.). Hoboken, NJ: Wiley.
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Collins, L.M. (2018). The Completion of the Optimization Phase. In: Optimization of Behavioral, Biobehavioral, and Biomedical Interventions. Statistics for Social and Behavioral Sciences. Springer, Cham. https://doi.org/10.1007/978-3-319-72206-1_7
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DOI: https://doi.org/10.1007/978-3-319-72206-1_7
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