This P50 application represents a novel interdisciplinary center at the intersection of behavioral economics and implementation science in pursuit of improving mental health service delivery. The Methods Core will provide support to the projects proposed in this application and to future pilot projects. The Methods Core also will develop new methodological approaches that support the center objectives of bringing together behavioral economics and implementation science to improve the use of evidence-based practice in mental health care. The Methods Core will be led by Drs. Buttenheim, Marcus, and Williams. The Methods Core will address three major challenges to advancing implementation science: lack of rigor in implementation strategy design, lack of specificity in the measurement of mechanisms, and inadequate statistical sophistication in testing mediation and moderation in multi-level models. The Methods Core will host three incubators ?design, measurement, and statistics ? to address these challenges. We propose the following aims for our Methods Core: (1) optimize the rigor of implementation strategy design; (2) strengthen measurement of mechanisms; (3) and develop novel approaches to testing mediating and moderating effects in multi-level models. The Methods Core also will provide operational support, disseminate methodological advances and center resources, and evaluate center research productivity and impact. The methodological advances to come out of the Methods Core will have a significant public health impact, consistent with NIMH priorities, by improving evidence-based practice mental health service delivery in community settings.
Williams, Nathaniel J; Beidas, Rinad S (2018) Annual Research Review: The state of implementation science in child psychology and psychiatry: a review and suggestions to advance the field. J Child Psychol Psychiatry : |
Lane-Fall, Meghan B; Cobb, Benjamin T; Cené, Crystal Wiley et al. (2018) Implementation Science in Perioperative Care. Anesthesiol Clin 36:1-15 |
Hong, Chuan; Ning, Yang; Wang, Shuang et al. (2017) PLEMT: A NOVEL PSEUDOLIKELIHOOD BASED EM TEST FOR HOMOGENEITY IN GENERALIZED EXPONENTIAL TILT MIXTURE MODELS. J Am Stat Assoc 112:1393-1404 |