Recommended Reading for Optimizing Behavioral Interventions


Collins, L. M., Kugler, K. C., & Gwadz, M. V. (2015). Optimization of multicomponent behavioral and biobehavioral interventions for the prevention and treatment of HIV/AIDS. Aids Behavior, Supp 1, 197-214.

Collins, L. M., Nahum-Shani, I., & Almirall, D.(2014). Optimization of behavioral dynamic treatment regimens based on the sequential, multiple assignment, randomized trial (SMART). Clinical Trials, 11, 426-434.


Implementations of MOST

These articles describe the thinking behind some implementations of MOST or related approaches in field settings.  They describe factorial experiments in varying stages of completion.

Baker, T. B., Collins, L. M., Mermelstein, R., Piper, M. E., Schlam, T. R., Cook, J. W., et al. (2016). Enhancing the effectiveness of smoking treatment research: conceptual bases and progress. Addiction, 111(1)., 107-16. doi:10.1111/add.13154

Caldwell, L. L., Smith, E. A., Collins, L. M., Graham, J. W., Lai, M., Wegner, L., Vergnani, T., Matthews, C., & Jacobs, J. (2012). Translational research in South Africa: Evaluating implementation quality using a factorial design. Child and Youth Care Forum, 41, 119-136. PMCID: PMC3375728

Collins, L. M., Baker, T. B., Mermelstein, R. J., Piper, M. E., Jorenby, D. E., Smith, S. S., Schlam, T. R., Cook, J. W., & Fiore, M. C. (2011). The multiphase optimization strategy for engineering effective tobacco use interventions. Annals of Behavioral Medicine, 41, 208-226. PMCID: PMC3053423

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(1)., 117-28. doi:10.1111/add.13161

McClure, J. B., Derry, H., Riggs, K. R., Westbrook, E. W., St. John, J., Shortreed, S. M., Bogart, A., & An, L. C. (2012). Questions about quitting (Q(2)): Design and methods of a Multiphase Optimization Strategy (MOST) randomized screening experiment for an online, motivational smoking cessation intervention. Contemporary Clinical Trials, 33(5), 1094-1102. PMCID: PMC3408878

Pellegrini, C.A., Hoffman, S.A., Collins, L.M., & Spring, B. (2014).  Optimization of remotely delivered intensive lifestyle treatment for obesity using the multiphase optimization strategy:  Opt-IN study protocol.  Contemporary Clinical Trials. NOTE: See important corrigendum {Pellegrini, C. A., Hoffman, S. A., Collins, L. M., & Spring, B. (2015). Corrigendum to “Optimization of remotely delivered intensive lifestyle treatment for obesity using the Multiphase Optimization Strategy: Opt-IN study protocol” [Contemp. Clin. Trials 38 (2014) 251–259]. Contemporary Clinical Trials, 45, 468 – 469. doi:10.1016/j.cct.2015.09.001}

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(1)., 129-41. doi:10.1111/add.13162

Schlam, T. R., Fiore, M. C., Smith, S. S., Fraser, D., 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(1)., 142-55. doi:10.1111/add.13153

Strecher, V. J., McClure, J. B., Alexander, G. W., Chakraborty, B., Nair, V. N., Konkel, J. M., Greene, S. M., Collins, L. M., Carlier, C. C., Wiese, C. J., Little, R. J., Pomerleau, C. S., & Pomerleau, O. F. (2008). Web-based smoking cessation programs: Results of a randomized trial. American Journal of Preventive Medicine, 34, 373-381. PMCID: PMC2697448


Rationale for factorial experiments

These articles review practical aspects of experimental design relevant to intervention science, and also attempt to correct some pervasively held misconceptions. These articles provide a rationale for considering a factorial experiment and may be useful citations.

Chakraborty, B., Collins, L. M., Strecher, V., & Murphy, S. A. (2009). Developing multicomponent interventions using fractional factorial designs. Statistics in Medicine28, 2687-2708. PMCID: PMC2746448

Collins, L.M., Dziak, J.J., Kugler, K.C., & Trail, J.B. (2014).  Factorial experiments: Efficient tools for evaluation of intervention components. American Journal of Preventive Medicine47, 498-504.

Collins, L. M., Dziak, J. J., & Li, R. (2009). Design of experiments with multiple independent variables: A resource management perspective on complete and reduced factorial designs. Psychological Methods,14(3), 202-224. PMCID: PMC2796056

Dziak, J. J., Nahum-Shani, I., & Collins, L. M. (2012). Multilevel factorial experiments for developing behavioral interventions:  Power, sample size, and resource considerations. Psychological Methods, 17, 153. PMCID: PMC3351535

Nair, V., Strecher, V., Fagerlin, A., Ubel, P., Resnicow, K., Murphy, S. A., Little, R., Chakraborty, B., & Zhang, A. (2008). Screening experiments and the use of fractional factorial designs in behavioral intervention research. American Journal of Public Health,98, 1354-1359. PMCID: PMC2446451


Enhancing effectiveness through MOST

This article addresses the question “Is MOST really likely to produce more potent behavioral interventions in practice?” by means of an extensive statistical simulation:

Collins, L. M., Chakraborty, B., Murphy, S. A., & Strecher, V. (2009). Comparison of a phased experimental approach and a single randomized clinical trial for developing multicomponent behavioral interventions. Clinical Trials6(1), 5-15. PMCID: PMC2711350


Practical considerations

Collins, L.M., Kugler, K., Trail, J.B., Baker, T., & Mermelstein, R. (2014). Evaluating individual intervention components: Making decisions based on the results of a factorial component screening experiment. Translational Behavioral Medicine, 4, 238-251.

Collins, L. M., Trail, J. B., Kugler, K. C., Baker, T. B., Piper, M. E., & Mermelstein, R. J. (2014). Evaluating individual intervention components: making decisions based on the results of a factorial screening experiment. Translational Behavioral Medicine, 4, 238-251. doi:10.1007/s13142-013-0239-7

Wyrick, D.L., Rulison, K.L., Fearnow-Kenney, M., Milroy, J.J., & Collins, L.M. (2014).  Moving beyond the treatment package approach to developing behavioral interventions: Addressing questions that arose during an application of the multiphase optimization strategy (MOST). Translational Behavioral Medicine, 4, 252-259.


Other approaches to optimization

Dong, Y., Rivera D.E., Downs, D.S., Savage, J.S., Thomas, D.M., & Collins, L.M. (2013). Hybrid model predictive control for optimizing gestational weight gain behavioral interventions. Procedings from the 2013 American Control Conference. 1970-1975. PMCID: PMC3856197.

Timms, K.P., Rivera, D.E., Collins, L.M., & Piper, M.E. (2014). Continuous-time system identification of a smoking cessation intervention. International Journal of Control, 87, 1423-1437.

Timms, K. P., Rivera, D. E., Collins, L. M., & Piper, M. E. (2013).  A dynamical systems approach to understand self-regulation in smoking cessation behavior change. Nicotine and Tobacco Research, 16, S159-168.

Timms, K. P., Rivera, D. E., Collins, L. M., & Piper, M. E. (2013).  Control systems engineering for understanding and optimizing smoking cessation interventions.Proceedings from the 2013 American Control Conference.

Trail, J. B., Collins, L. M., Rivera, D. E., Li, R., Piper, M., & Baker, T. (2013). Functional data analysis for the system identification of behavioral processes.  Psychological Methods, 19, 175-187.