Jeanne Miranda, PhD

Professor, Department of Psychiatry and Biobehavioral Sciences, UCLA
Disparities; Depression Treatment; Policy

mirandaJeanne Miranda, PhD, is a Professor in the Department of Psychiatry and Biobehavioral Sciences at UCLA.  She has focused her research on providing mental health care to low-income and minority communities. She holds a Ph.D. in Clinical Psychology from University of Kansas and completed post-doctoral training at University of California, San Francisco. Dr. Miranda's major research contributions have been in evaluating the impact of mental health care for ethnic minority communities. She is currently working to evaluate an intervention her team developed to provide care for families adopting older children from foster care. She is adapting depression interventions for young women in Uganda and evaluating a government micro-finance program in Uganda. She is recently funded to develop and test a resilience intervention for low-income and minority LGBT populations. She was the Senior Scientific Editor of Mental Health: Culture, Race and Ethnicity, A Supplement to Mental Health: A Report of the Surgeon General, published August 2001. She became a member of the Institute of Medicine in 2005. Dr. Miranda is the 2008 recipient of the Emily Mumford Award for Contributions to Social Medicine from Columbia University.

Outside of work, Dr. Miranda enjoys photography and cooking.

Selected Publications:

Miranda J, Duan N, Sherbourne C, Schoenbaum M, Lagomasino I, Jackson-Triche M, Wells KB. Can Quality Improvements Interventions Improve Care and Outcomes for Depressed Minorities? Results of a Randomized Controlled Trial. Health Services Research, 38(2):613-630, 2003.

Miranda J, Chung JY, Green BL, Krupnick J, Siddique J, Revicki DA, Belin T. Treating Depression in Predominantly Low-Income Young Minority Women: A Randomized Controlled Trial. Journal of American Medical Association, 290(1):57-65, 2003.

Miranda, J., Schoenbaum, M., Sherbourne, C., Duan, N., & Wells, K. The effects of primary care depression treatment on minority patients’ clinical status and employment. Archives of General Psychiatry, 61(8):827-34, 2004.

Miranda J, Azocar F, Organista K, Dwyer E, Arean P. Treatment of Depression among Impoverished Primary Care Patients from Ethnic Minority Groups Disadvantaged Medical Patients. Psychiatric Services, 54(2):219-25, 2003.

Miranda, J. & Persons, J. Dysfunctional thoughts are mood-state dependent. Journal of Abnormal Psychology, 97, 76-79, 1988.

Miranda, J., Persons, J. & Byers, C. Endorsement of dysfunctional beliefs depends on current mood state. Journal of Abnormal Psychology, 99, 237-241, 1990.

Miranda, J. Dysfunctional thinking is activated by stressful life events. Cognitive Therapy and Research, 16, 473-483, 1992.

Miranda J, Duan N, Sherbourne C, Schoenbaum M, Lagomasino I, Jackson-Triche M, Wells KB. Can Quality Improvements Interventions Improve Care and Outcomes for Depressed Minorities? Results of a Randomized Controlled Trial. Health Services Research, 38(2):613-630, 2003.

Miranda J, Duan N, Sherbourne C, Schoenbaum M, Lagomasino I, Jackson-Triche M, Wells KB. Can Quality Improvements Interventions Improve Care and Outcomes for Depressed Minorities? Results of a Randomized Controlled Trial. Health Services Research, 38(2):613-630, 2003.

Jaycox L, Miranda J, Meredith L, Duan N, Benjamin B, Wells K. Impact of a Primary Care Quality Improvement Intervention On Use of Psychotherapy for Depression. Mental Health Services Research, 5(2):109-121, 2003.

Asarnow JR, Miranda J. Improving care for depression and suicide risk in adolescents: innovative strategies for bringing treatments to community settings. Annual Review of Clinical Psychology, 10: 275-303, 2014.

Miranda J, Chung JY, Green BL, Krupnick J, Siddique J, Revicki DA, Belin T. Treating Depression in Predominantly Low-Income Young Minority Women: A Randomized Controlled Trial. Journal of American Medical Association, 290(1):57-65, 2003

Miranda J, Azocar F, Organista K, Dwyer E, Arean P. Treatment of Depression among Impoverished Primary Care Patients from Ethnic Minority Groups Disadvantaged Medical Patients.  Psychiatric Services, 54(2):219-25, 2003

Miranda J, Green BL, Krupnick JL, Chung J, Siddique J, Belin T, Revicki D.  One-year Outcomes of a Randomized Clinical Trial Treating Depression in Low-Income Minority Women. Journal of Consulting and Clinical Psychology. Vol. 62(7), 815–835, 2006.

Ngo, V., Asarnow, J.R., Lange, J., Jaycox, L., Rea, M., Landon, C., Tang, L., & Miranda, J.  (2009). Do quality improvement interventions for depressed youth result in differential outcomes for ethnic minorities:  A randomized trial?  Psychiatric Services, 166(9), 1002-10, 2009.

McGuire, T., Miranda, J., Racial and Ethnic Disparities in Mental Health Care: Evidence and Policy Implications. Health Affairs 27, no. 2: 393-403, 2008.

Miranda, J., McGuire, T., Williams, DR., Wang, P., Mental Health in the Context of Health Disparities. American Journal of Psychiatry. 165:1102-1118, 2008.

Revicki DA, Siddique J, Frank L, Chung JY, Green BL, Krupnick J, Prasad M, Miranda J.  Cost-Effectiveness of Evidence-Based Antidepressant or Cognitive Behavioral Therapy Compared to Community Referral for Major Depression in Predominantly Low-Income Young Minority Women. Archives of General Psychiatry. Aug;62(8):868-75, 2005.


Inbal (Billie) Nahum-Shani

Research Assistant Professor, Institute for Social Research, University of Michigan
Adaptive Interventions; Just in Time Adaptive Interventions; Stress; Support

nahum shaniInbal (Billie) Nahum-Shani is a Research Assistant Professor at the University of Michigan's Institute for Social Research. Her research focuses on developing and employing behavioral theory and novel methodology to construct adaptive interventions, namely interventions that modify the type, timing, dose, or delivery mode of support in order to address the unique and changing needs of individuals. Nahum-Shani's scholarly and grant related work is highly multidisciplinary, spanning behavioral, health, and applied psychology, while also being tightly integrated with advanced research methodology. A more recent focus is on the use of mobile technologies to facilitate the timely delivery and adaptation of interventions, known as Just-In-Time Adaptive Interventions (JITAIs). 


 

Selected Publications:

Nahum-Shani, I., Smith, S.N. Spring, B.J., Collins, L.M., Witkiewitz, K., Tewari, A., & Murphy, S.A. (in press). Just-in-Time Adaptive Interventions (JITAIs) in Mobile Health: Key Components and Design Principles for Ongoing Health Behavior Support. Annals of Behavioral Medicine.

Nahum-Shani, I., Hekler, E. B., & Spruijt-Metz, D. (2015). Building health behavior models to guide the development of just-in-time adaptive interventions: A pragmatic framework. Health Psychology,34, 1209-1219.

Ertefaie, A., Wu, T., Lynch, K., & Nahum-Shani, I (Senior Author). (2015). Identifying a set that contains the best dynamic treatment regimes.Biostatistics, (in press).

Nahum-Shani, I., Qian, M., Almirall, D., Pelham, W.E., Gnagy, B., Fabiano, G., Waxmonsky, J., Yu, J., & Murphy, S. (2012). Q-Learning: A Secondary Data Analysis Method for Developing Adaptive Interventions. Psychological Methods, 17(4), 478.

Nahum-Shani, I., Qian, M., Almirall, D., Pelham, W.E., Gnagy, B., Fabiano, G., Waxmonsky, J., Yu, J., & Murphy, S. (2012). Experimental Design and Primary Data Analysis for Developing Adaptive Interventions. Psychological Methods, 17(4), 457.


Tim DeLise

Programmer
Software Development; Applied Math; mHealth


delise largeTim DeLise is a computer programmer with a background in mobile devices, server infrastructure, databasing, robotics, web-based technologies, object-oriented programming languages, mathematics, statistics, and finance.  He is a full-stack developer who has built information systems, apps, and financial trading systems.  He has a bachelor's degree in mathematics from the University of Vermont and a master of science degree in applied mathematics and statistics from the Stony Brook University.  He is passionate about contributing to the addiction research agenda at the CTBH.


A. James O’Malley, PhD

Professor of Biostatistics, Department of Biomedical Data Science, The Dartmouth Institute for Health Policy and Clinical Practice

Bayesian Methods; Social Network Analysis; Causal Inference; Multivariate-Multilevel Models

omalley4 cropMy methodological research interests have center on social network analysis, causal inference (comparative effectiveness research), multivariate-hierarchical modeling, and previously the design and analysis of medical device clinical trials. In these I have developed novel statistical methods, often involving novel use of Bayesian statistical methods, to solve important methodological and applied problems in health policy and health services research, including the evaluation of treatments and outcomes of health care in multiple areas of medicine. This has led to advances in interventional cardiology, vascular surgery, measuring quality of health care, mental health and long-term care.

My primary teaching activities currently include teaching a statistics class to medical and health policy students, guest lectures in other courses, and presenting short courses at conferences and other forums. My educational also include a large number of invited seminars; mentoring colleagues, post-doctoral fellows and students; and service to the statistics profession. In addition, my service to the statistics profession includes eight-years at the forefront of the Health Policy Statistics Section of the ASA, associate editorships at both Statistics in Medicine and Health Services and Outcomes Research Methodology, and as reviewer for over 20 respected academic journals.

In recognition of many of the above contributions, I was elected fellow of the American Statistical Association (ASA) in 2012 and awarded the 2011 Mid-Career Award by the Health Policy Statistics Section of the ASA (a single award is given biannually).

For fun, I enjoy several sports and particularly tennis, swimming, road biking, and trail running. Since moving to the Upper Valley, I have enjoyed improving my downhill and cross-country skiing.


 

Selected Publications:

O’Malley AJ, Normand, S-LT. Likelihood methods for treatment noncompliance and subsequent nonresponse in clinical trials. Biometrics 2005, 61, 325-334.

O’Malley AJ, Zaslavsky AM. Variance-Covariance Functions for Domain Means of Ordinal Survey Items. Survey Methodology 2005, 31, 169-182.

O’Malley AJ, Zaslavsky AM. Domain-Level Covariance Analysis for Multi-Level Survey Data with Structured Nonresponse. Journal of the American Statistical Association, 2008, 103, 1405-1418.

O’Malley AJ, Marsden PV. The Analysis of Social Networks. Health Services and Outcomes Research Methodology 2008, 8, 222-269. PMID: 20046802

Neelon B, O’Malley AJ, Normand S-LT. A Bayesian two-part latent class model for longitudinal medical expenditure data: Assessing the impact of mental health and substance abuse parity. Biometrics, 2011, 67, 280-289.

O’Malley AJ, Christakis NA. Longitudinal Analysis of Large Social Networks: estimating the Effect of Health Traits on changes in Friendship Ties. Statistics in Medicine 2011, 30, 9, 950-964.

O’Malley AJ, Cotterill P, Schermerhorn ML, Landon BE. Optimal Referral Strategies Involving Treatment Selection and Volume-Outcome Relationships for AAA Repair. Medical Care 2011, 49, 1126-1132.

O’Malley AJ. Instrumental Variable Specifications and Assumptions for Longitudinal Analysis of Mental Health Cost Offsets. Health Services and Outcomes Research Methodology, 2012, 12, 254-272.

Paul S, O’Malley AJ. Hierarchical longitudinal models of relationships in social networks. Journal of the Royal Statistical Society, Series C (Applied Statistics), 2013, 62 (5), 705-722.

O’Malley AJ. The Analysis of Social Network Data: An Exciting Frontier for Statisticians. Statistics in Medicine, 2013, 32, 539-555. PMID: 23023735

MacKenzie TA, Tosteson TD, Morden NE, Stukel TA, O'Malley AJ (2014). Using instrumental variables to estimate a Cox's proportional hazards regression subject to additive confounding. Health Services Outcomes Res Methodology 14(1-2):54-68.  PMCID: PMC 4261749

O'Malley AJ, Elwert F, Rosenquist JN, Zaslavsky AM, Christakis NA (2014). Estimating peer effects in longitudinal dyadic data using instrumental variables. Biometrics.  70(3):506-515 PMCID: PMC 4213357

O’Malley AJ and Paul S. Using Retrospective Sampling to Estimate Models of Relationship Status in Large Longitudinal Social Networks. Computational Statistics and Data Analysis, 2014, 82, 35–46. http://dx.doi.org/10.1016/j.csda.2014.08.001

Busch AB, He Y, Zelevinsky K, O’Malley AJ. Which Patients Participate in Clinical Trials? Psychiatric Services, Published online (March 31, 2015), http://ps.psychiatryonline.org/doi/pdfplus/10.1176/appi.ps.201300557. PMID: 25828873

O’Malley AJ, Zelevinsky K, He Y, and Busch AB. Do Patients at Sites with High RCT Enrollment Propensity have Better Outcomes? Medical Care, 2015, 53 (11), 989–995. doi: 10.1097/MLR.0000000000000429

O’Malley AJ, Zaslavsky AM. Optimal small-area estimation and design when nonrespondents are subsampled for followup. Journal of Survey Statistics and Methodology, 2016, 4 (1): 2-21. http://jssam.oxfordjournals.org/.

Moen EL, Fricano-Kugler CJ, Luikart BW, O’Malley AJ (2016). Analyzing Clustered Data: Why and How to Account for Multiple Observations Nested within a Study Participant? PLoS ONE 11(1): e0146721. doi:10.1371/journal.pone.0146721

Choi J, O’Malley AJ. Estimating the Causal Effect of Treatment in Observational Studies with Survival Time Endpoints and Unmeasured Confounding. In press: Journal of the Royal Statistical Society, Series C (Applied Statistics).

Moen EL, Austin AM, Bynum JP, Skinner JS, O’Malley AJ. An analysis of patient-sharing physician networks and implantable cardioverter defibrillator therapy. In Press: Health Services and Outcomes Research Methodology.

Neelon B, O’Malley AJ, Smith VA. Modeling Zero-Modified Count and Semicontinuous Data in Health Services Research, Part 1: Background and Overview. Accepted for Publication: Statistics in Medicine

Neelon B, O’Malley AJ, Smith VA. Modeling Zero-Modified Count and Semicontinuous Data in Health Services Research, Part 2: Case Studies. Accepted for Publication: Statistics in Medicine 


Emily Scherer, PhD

Assistant Professor of Biomedical Data Science, Geisel School of Medicine at Dartmouth; Assistant Professor of Community and Family Medicine, Geisel School of Medicine at Dartmouth

emily schererDr. (Blood) Scherer is an Assistant Professor of Biomedical Data Science and of Community and Family Medicine. She is a biostatistician and has worked in several clinical areas including cancer clinical trials, spine surgical studies, adolescent medicine, and psychiatry and has extensive experience with statistical collaboration in research studies. Her current methodologic research interest is in the analysis of intensively collected data such as those obtained through mobile technology-based assessments, particularly in the area of mental health and substance use. She has also worked in the area of longitudinal and correlated data modeling as well as structural equation modeling. She received her PhD in Biostatistics from Boston University in 2010.