Tamar Krishnamurti, PhD, is an Assistant Professor of Medicine and Clinical and Translational Science. Her research interests include risk perception and communication, medical decision making, mHealth, and the design of effective communications, decision support tools, and behavioral interventions. She is particularly interested in research that focuses on vulnerable and high-risk social groups. Her work uses quantitative and qualitative methods to conduct both basic and applied research. She has applied her methods to diverse topic areas, including pregnancy, sexual and reproductive health, addiction, informed consent, and environmentally-conscious behavior. Her research has been supported by the National Institutes of Health, the Centers for Disease Control, the Pittsburgh Foundation, the Hillman Foundation, ICON, Plc., the Richard King Mellon Foundation, and USAID. Her work is disseminated broadly in peer-reviewed journals such as PNAS, Nature Climate Change, Medical Decision Making, JAMA Internal Medicine, and the Journal of Experimental Social Psychology. She won an Ideas of the Year Award from the New York Times in 2009 and her work has been featured by major news organizations, such as The New York Times, NPR, and MSNBC.
Dr. Krishnamurti enjoys traveling off the beaten path with her family and doesn’t leave town without a good mystery novel in her bag. She’s also the co-founder of Naima Health, a university spinout that develops health tools, using behavioral science and machine learning, to better engage patients in their clinical care.
Education & Training
- General Course (Cultural Anthropology), The London School of Economics and Political Science, 2002
- BS (Biological Anthropology), Carnegie Mellon University, 2003
- MS (Social Psychology & Behavioral Decision Research), Carnegie Mellon University, 2006
- PhD (Behavioral Decision Research), Carnegie Mellon University, 2010
Krishnamurti T, Davis AL, Simhan HN. Worrying yourself sick? association between pre-eclampsia onset and health-related worry in pregnancy. Pregnancy Hypertension. 2019;18:55-57
Applying a machine learning regularized regression to a prospective observational data set of 10,037 nulliparous U.S. women, this study found a significant relationship between psychosocial worry and later pre-eclampsia onset, even when controlling for medical history and other pre-eclampsia risk factors.
Krishnamurti T, Davis AL, Wong-Parodi G, Fischhoff B, Sadovsky Y, Simhan HN. Development and testing of the MyHealthyPregnancy app: a behavioral decision research-based tool for assessing and communicating pregnancy risk. JMIR Mhealth Uhealth. 2017;5(4):e42.
A longitudinal, prospective pilot study used behavioral decision research methods to develop a smartphone app that gathers risk data and communicates personalized pregnancy risk assessments, with the goal of decreasing preterm birth rates in a hard-to-engage patient population.
Krishnamurti T, Argo N. A patient-centered approach to informed consent: results from a survey and randomized trial. Medical Decision Making. 2016;36(6):726-740.
Two studies developed a new approach to creating patient-centered informed consent and found that concise informed consent documents, systematically developed from patients’ self-reported information needs, were more effective at engaging and informing clinical trial participants than the traditional consent approach, without detriment to trial comprehension, risk assessment, or enrollment.
Krishnamurti T, Woloshin S, Schwartz LM, Fischhoff B. A randomized trial testing US Food and Drug Administration "breakthrough" language. JAMA Internal Medicine. 2015;175(11):1856-1858.
A randomized trial identified that the use of terms “breakthrough” and “promising” in FDA press releases increased people’s beliefs in a drug’s effectiveness and strength of supporting evidence; using neutral terms might help consumers make more accurate judgements about these drugs.
- Judgment and decision making
- Risk perception and communication
- Behavioral interventions