Stephanie P. Goldstein, PhD, is an Assistant Professor (Research) at the Weight Control and Diabetes Research Center (WCDRC) of The Miriam Hospital and Alpert Medical School of Brown University. She earned her PhD in Clinical Psychology, with an emphasis on behavioral medicine, from Drexel University in 2018. Dr. Goldstein received training in obesity clinical research and cardiovascular behavioral medicine during her NHLBI-funded postdoctoral fellowship at the WCDRC & Alpert Medical School of Brown University. Her research focuses on digital health approaches (e.g., ecological momentary assessment [EMA], sensor technology, just-in-time adaptive intervention [JITAI]) to assess and intervene on weight-related behaviors implicated in cardiovascular disease (CVD) risk, particularly eating.
She specializes in using EMA administered via mobile phone to study dietary lapses (i.e., discrete instances of dietary non-adherence) and using JITAI to intervene on them. Specifically, she developed a smartphone-based JITAI that uses EMA to predict lapses before they occur and then deliver intervention “just-in-time” when risk for lapse is high. The JITAI is now being optimized via a micro-randomized trial to examine the immediate effect of theory-driven interventions on risk for lapsing (R01 HL153543; PI: Goldstein). Her postdoctoral work focused on combining EMA and a wrist-worn sensor to inform objective assessment of dietary lapses via real-time passive detection and characterization of eating (F32 HL143954).
In total, Dr. Goldstein has conducted and/or been substantially involved in 7 EMA studies (4 of which have been NIH-funded) and has coordinated the development and pilot testing of 3 JITAIs that use EMA to collect information about behavior and deliver personalized intervention. Two of her studies focus on delivering behavioral obesity treatment to individuals with CVD risk factors such as hypertension and diabetes (R01 HL153543; F32 HL143954). Dr. Goldstein has extensive experience in managing, analyzing, and disseminating results from large datasets produced by technology-based systems, and has provided logistical support and consultation to other researchers who are using technology-based methods.