Publications & Abstracts

Behavioral Engagement and Activation Model Study (BEAMS)

Evidation and Sanofi partnered to look at Type 2 Diabetes patients with and without digital health technology (DHT) use to understand who might require more tailored support to adopt DHTs.

John D Piette, Keni C S Lee, Hayden B Bosworth, Diana Isaacs, Christian J Cerrada, Raghu Kainkaryam, Jan Liska, Felix Lee, Adee Kennedy, David Kerr

Patient and physician perspectives on the use of a connected ecosystem for diabetes management: International cross-sectional observational study

Evidation and Sanofi partnered to understand which type 2 diabetes patients are more likely to participate in and benefit from connected ecosystem programs.

Elizabeth Benito-Garcia; Julio Vega; Eric J Daza; Wei-Nchih Lee; Adee Kennedy; Jean-Marc Chantelot

Association of digital measures and self-reported fatigue

Evidation contributed to research that looked at whether or not multimodal digital data can be used to quantify fatigue in both healthy individuals and individuals with chronic inflammatory rheumatic disease.

Characterization of influenza-like Illness burden using commercial wearable sensor data and patient-reported outcomes: Mixed methods cohort study

Evidation research aimed to characterize the burden of influenza-like illness using commercial wearable sensor data and investigate the extent to which these data correlate with self-reported illness severity and duration.

Victoria Hunter, Allison Shapiro, Devika Chawla, Faye Drawnel, Ernesto Ramirez, Elizabeth Phillips, Sara Tadesse-Bell, Luca Foschini, Vincent Ukachukwu

Machine learning COVID-19 detection from wearables

Evidation research looks into which criteria must be met before a study can claim reasonable COVID-19 detection performance using data from wearable devices.

Bret Nestor, Jaryd Hunter, Raghu Kainkaryam, Erik Drysdale, Jeffrey B Inglis, Allison Shapiro, Sujay Nagaraj, Marzyeh Ghassemi, Luca Foschini, Anna Goldenberg

Precision recruitment for high-risk participants in a COVID-19 cohort study

Evidation describes an approach for reducing recruiting time and resources in a COVID-19 study by targeting recruitment to high-risk individuals.

Mezlini A, Caddigan E, Shapiro A, Ramirez E, Kondow-McConaghy H, Yang J, DeMarco K, Naraghi-Arani P, Foschini L

American Life in Realtime: A benchmark registry of health data for equitable precision health

ALiR, funded by a grant from the NIH, is a first-of-its-kind, publicly available benchmark registry and research infrastructure for person-generated health data collected from smartphones and wearables, made possible by Evidation.

Ritika R. Chaturvedi, Marco Angrisani, Wendy M. Troxel, Tania Gutsche, Eva Ortega, Monika Jain, Adrien Boch & Arie Kapteyn

Predictors of seeking care for influenza-like illness in a novel digital study

Evidation conducted a study that used person-generated health data (PGHD) to identify factors associated with seeking care for ILI.

Devika Chawla, Alejandra Benitez, Hao Xu, Victoria Whitehill, Sara Tadesse-Bell, Allison Shapiro, Ernesto Ramirez, Kelly Scherer, Luca Foschini, Faye Drawnel, Barry Clinch, Marco Prunotto, Vincent Ukachukwu

COVID-19 real-world evidence primer

Evidation contributed to this online resource consisting of seven chapters that cover types of RWD, methods in RWE generation, examples of RWE studies, and more.

Amy Cavet; Claire Cravero, MPH; Aaron Galaznik, MD; Bray Patrick-Lake, MFS; Aniketh Talwai