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Using baseline target moderation to guide decisions on adapting prevention programs

  • George W. Howe (a1)


Tom Dishion, a pioneer in prevention science, was one of the first to recognize the importance of adapting interventions to the needs of individual families. Building towards this goal, we suggest that prevention trials be used to assess baseline target moderated mediation (BTMM), where preventive intervention effects are mediated through change in specific targets, and the resulting effect varies across baseline levels of the target. Four forms of BTMM found in recent trials are discussed including compensatory, rich-get-richer, crossover, and differential iatrogenic effects. A strategy for evaluating meaningful preventive effects is presented based on preventive thresholds for diagnostic conditions, midpoint targets and proximal risk or protective mechanisms. Methods are described for using the results from BTMM analyses of these thresholds to estimate indices of intervention risk reduction or increase as they vary over baseline target levels, and potential cut points are presented for identifying subgroups that would benefit from program adaptation because of weak or potentially iatrogenic program effects. Simulated data are used to illustrate curves for the four forms of BTMM effects and how implications for adaptation change when untreated control group outcomes also vary over baseline target levels.


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Author for Correspondence: George W. Howe, Department of Psychology, George Washington University, 2125 G Street NW, Washington, DC 20052. Email to


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August, G. J., Piehler, T. F., & Bloomquist, M. L. (2016). Being ‘SMART’ about adolescent conduct problems prevention: Executing a SMART pilot study in a juvenile diversion agency. Journal of Clinical Child and Adolescent Psychology, 45, 495509. doi:10.1080/15374416.2014.945212
Coie, J. D., Watt, N. F., West, S. G., Hawkins, J. D., Asarnow, J. R., Markman, H. J., … Long, B. (1993). The science of prevention: A conceptual framework and some directions for a national research program. American Psychologist, 48, 10131022. doi:10.1037/0003-066X.48.10.1013
Crowley, D. M., Dodge, K. A., Barnett, W. S., Corso, P., Duffy, S., Graham, P., … Plotnick, R. (2018). Standards of evidence for conducting and reporting economic evaluations in prevention science. Prevention Science, 19, 366390. doi:10.1007/s11121-017-0858-1
D'Amico, E., Tucker, J., Miles, J., Zhou, A., Shih, R., & Green, H. (2012). Preventing alcohol use with a voluntary after-school program for middle school students: Results from a cluster randomized controlled trial of CHOICE. Prevention Science, 13, 415425. doi:10.1007/s11121-011-0269-7
Dishion, T. J., & Kavanagh, K. (2003). Intervening with adolescent problem behavior: A family-centered approach. New York, NY: Guilford Press.
Dishion, T. J., McCord, J., & Poulin, F. (1999). When interventions harm: Peer groups and problem behavior. American Psychologist, 54, 755764. doi:10.1037/0003-066X.54.9.755
Dishion, T. J., Poulin, F., & Burraston, B. (2001). Peer goup dynamics associated with iatrogenic effect in group interventions with high-risk young adolescents. New Directions for Child & Adolescent Development, 2001, 7992. doi:10.1002/cd.6
Dishion, T. J., & Stormshak, E. A. (2007). Intervening in children's lives: An ecological, family-centered approach to mental health care. Washington, DC: American Psychological Association.
Fishbein, D. H., Hyde, C., Eldreth, D., Paschall, M. J., Hubal, R., Das, A., … Yung, B. (2006). Neurocognitive skills moderate urban male adolescents' responses to preventive intervention materials. Drug and Alcohol Dependence, 82, 4760.10.1016/j.drugalcdep.2005.08.008
Fisher, J., Rahman, A., Cabral de Mello, M., Chandra, P. S., & Herrman, H. (2010). Mental health of parents and infant health and development in resource-constrained settings: Evidence gaps and implications for facilitating ‘good-enough parenting’ in the twenty-first-century world. In Tyano, S., Keren, M., Herrman, H., & Cox, J. (Eds.), Parenthood and mental health: A bridge between infant and adult psychiatry (pp. 429442). Hoboken, NJ: Wiley-Blackwell.
George, M. R. W., Yang, N., Van Horn, M. L., Smith, J., Jaki, T., Feaster, D., … Howe, G. (2013). Using regression mixture models with non-normal data: Examining an ordered polytomous approach. Journal Of Statistical Computation And Simulation, 83, 757770.10.1080/00949655.2011.636363
Ginwright, S., & Cammarota, J. (2002). New terrain in youth development: The promise of a social justice approach. Social Justice, 29, 8295.
Gonzales, N. A., Dumka, L. E., Millsap, R. E., Gottschall, A., McClain, D. B., Wong, J. J., … Kim, S. Y. (2012). Randomized trial of a broad preventive intervention for Mexican American adolescents. Journal of Consulting and Clinical Psychology, 80, 116. doi:10.1037/a0026063
Gotlib, I. H., Lewinsohn, P. M., & Seeley, J. R. (1995). Symptoms versus a diagnosis of depression: Differences in psychosocial functioning. Journal of Consulting and Clinical Psychology, 63, 90100. doi:10.1037/0022-006X.63.1.90
Green, K. M., & Stuart, E. A. (2014). Examining moderation analyses in propensity score methods: Application to depression and substance use. Journal of Consulting and Clinical Psychology, 82, 773783. doi:10.1037/a0036515
Haack, S. (2003). Defending science—within reason. Between scientism and cynicism. Amherst, NY: Prometheus Books.
Howe, G. W. (2019 a). Heterogeneity in the effects of interventions to prevent depression in couples facing job loss: Studying baseline target moderation of effect. Paper presented at the Society for Prevention Research, San Francisco, CA.
Howe, G. W. (2019 b). Preventive effect heterogeneity: Causal inference in personalized prevention. Prevention Science, 20, 2129. doi:10.1007/s11121-017-0826-9
Howe, G. W., Beach, S., & Brody, G. (2010). Microtrial methods for translating gene-environment dynamics into preventive interventions. Prevention Science, 11, 343354. doi:10.1007/s11121-010-0177-2
Howe, G. W., Reiss, D., & Yuh, J. (2002). Can prevention trials test theories of etiology? Development and Psychopathology, 14, 673694. doi:10.1017/S0954579402004029
Howe, G. W., & Ridenour, T. A. (2019). Bridging the gap: Microtrials and idiographic designs for translating basic science into effective prevention of substance use. In Sloboda, Z., Petras, H., Hingson, R., & Robertson, E. B. (Eds.), Prevention of Substance Use. (pp. 349366). Cham, Switzerland: Springer.
Imai, K., Keele, L., & Tingley, D. (2010). A general approach to causal mediation analysis. Psychological Methods, 15, 309334. doi:10.1037/a0020761
Kim, M., Lamont, A. E., Jaki, T., Feaster, D., Howe, G., & Van Horn, M. L. (2016). Effect of an equality constraint on the class-specific residual variances in regression mixtures: A Monte Carlo simulation study. Behavior Research Methods, 48, 813826. doi:10.3758/s13428-015-0618-8
Knafl, G. J., Barakat, L. P., Hanlon, A. L., Hardie, T., Knafl, K. A., Li, Y., & Deatrick, J. A. (2017). Adaptive modeling: An approach for incorporating nonlinearity in regression analyses. Research in Nursing & Health, 40, 273282. doi:10.1002/nur.21786
Luyten, H., & ten Bruggencate, G. (2011). The presence of Matthew effects in Dutch primary education, development of language skills over a six-year period. Journal of Learning Disabilities, 44, 444458. doi:10.1177/0022219411410289
MacKinnon, D. P. (2008). Introduction to statistical mediation analysis. New York: Lawrence Erlbaum.
MacKinnon, D. P., Krull, J. L., & Lockwood, C. M. (2000). Equivalence of the mediation, confounding and suppression effect. Prevention Science, 1, 173181. doi:10.1023/A:1026595011371
McAlister, F. A. (2008). The “number needed to treat” turns 20—and continues to be used and misused. CMAJ: Canadian Medical Association Journal = Journal De L'association Medicale Canadienne, 179, 549553. doi:10.1503/cmaj.080484
Merton, R. K. (1968). The Matthew Effect in science: The reward and communication systems of science are considered. Science (New York, N.Y.), 159, 5663.10.1126/science.159.3810.56
Muthén, L. K., & Muthén, B. O. (1998–2017). Mplus user's guide. Eighth edition. (6th ed.). Los Angeles, CA: Muthén & Muthén.
Pantin, H., Prado, G., Lopez, B., Huang, S., Tapia, M. I., Schwartz, S. J., … Branchini, J. (2009). A randomized controlled trial of Familias Unidas for Hispanic adolescents with behavior problems. Psychosomatic Medicine, 71, 987995. doi:10.1097/PSY.0b013e3181bb2913
Pearl, J. (2009). Causality: Models, reasoning, and inference (2nd ed.). New York, NY: Cambridge University Press.
Pearl, J. (2012). The causal mediation formula-A guide to the assessment of pathways and mechanisms. Prevention Science, 13, 426436. doi:10.1007/s11121-011-0270-1
Perrino, T., Brincks, A., Howe, G., Brown, C., Prado, G., Pantin, H., & Brown, C. H. (2016). Reducing internalizing symptoms among high-risk, hispanic adolescents: Mediators of a preventive family intervention. Prevention Science, 17, 595605. doi:10.1007/s11121-016-0655-2
Perrino, T., Pantin, H., Prado, G., Huang, S., Brincks, A., Howe, G., … Brown, C. H. (2014). Preventing internalizing symptoms among Hispanic adolescents: A synthesis across Familias Unidas trials. Prevention Science, 15, 917928. doi:10.1007/s11121-013-0448-9
Prado, G., & Pantin, H. (2011). Reducing Substance use and HIV health disparities among Hispanic youth in the USA: The Familias Unidas Program of Research. Reduciendo las desigualdades en salud por consumo de drogas y VIH en los jóvenes Hispanos de EEUU: El Programa de Investigación Familias Unidas., 20, 6373. doi:10.5093/in2011v20n1a6
Prado, G., Pantin, H., Briones, E., Schwartz, S. J., Feaster, D., Huang, S., … Szapocznik, J. (2007). A randomized controlled trial of a parent-centered intervention in preventing substance use and HIV risk behaviors in Hispanic adolescents. Journal of Consulting and Clinical Psychology, 75, 914926.
Rohde, P., Brière, F. N., & Stice, E. (2018). Major depression prevention effects for a cognitive-behavioral adolescent indicated prevention group intervention across four trials. Behaviour Research and Therapy, 100, 16. doi:10.1016/j.brat.2017.10.013
Rosenberg, B. D., & Siegel, J. T. (2018). A 50-year review of psychological reactance theory: Do not read this article. Motivation Science, 4, 281300. doi:10.1037/mot0000091
Rubin, D. B. (1974). Estimating causal effects of treatments in randomized and nonrandomized studies. Journal of Educational Psychology, 66, 688701. doi:10.1037/h0037350
Teisl, M., Wyman, P. A., Cross, W., West, J., & Sworts, L. (2012). Adaptive intervention to address the needs of children with language delays and behavior problems: Proximal effect on emotion-regulation skill knowledge. Paper presented at the Annual Meeting of the Society for Prevention Research, Washington, DC.
VanderWeele, T. J. (2015). Explanation in causal inference. Methods for mediation and interaction. Oxford: Oxford University Press.
Van Horn, M. L., Jaki, T., Masyn, K., Howe, G., Feaster, D. J., Lamont, A. E., … Kim, M. (2015). Evaluating differential effects using regression interactions and regression mixture models. Educational and Psychological Measurement, 75, 677714.10.1177/0013164414554931
Wagenmakers, E.–J., Morey, R. D., & Lee, M. D. (2016). Bayesian benefits for the pragmatic researcher. Current Directions in Psychological Science, 25, 169176. doi:10.1177/0963721416643289


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Using baseline target moderation to guide decisions on adapting prevention programs

  • George W. Howe (a1)


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