Publications & Abstracts

REVEAL, a prospective, observational study

Authors: Elizabeth A. Griffiths, Jae S. Min, Wei-Nchih Lee, Jeffrey C. Yu, Yogesh Patel, Karl-Johan Myren, & David Dingli
Source: BMC Part of Springer Nature
Date: August 9, 2024
Summary: Evidation and partners aimed to examine the impact of paroxysmal nocturnal hemoglobinuria (PNH) and its treatment on patients’ daily lives by combining patient-reported outcomes with wearable technology.

Behavioral Engagement and Activation Model Study (BEAMS)

Authors: 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
Source: Translational Behavioral Medicine
Date: July 2, 2024
Summary: 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.

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

Authors: Elizabeth Benito-Garcia, Julio Vega, Eric J Daza, Wei-Nchih Lee, Adee Kennedy, Jean-Marc Chantelot
Source: JMIR Formative Research
Date: November 30, 2023
Summary: Evidation and Sanofi partnered to understand which type 2 diabetes patients are more likely to participate in and benefit from connected ecosystem programs.

Association of digital measures and self-reported fatigue

Source: Frontiers in Digital Health
Date: June 22, 2023
Summary: 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

Authors: Victoria Hunter, Allison Shapiro, Devika Chawla, Faye Drawnel, Ernesto Ramirez, Elizabeth Phillips, Sara Tadesse-Bell, Luca Foschini, Vincent Ukachukwu
Source: JMIR Publications
Date: March 24, 2023
Summary: 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.

Machine learning COVID-19 detection from wearables

Authors: Bret Nestor, Jaryd Hunter, Raghu Kainkaryam, Erik Drysdale, Jeffrey B Inglis, Allison Shapiro, Sujay Nagaraj, Marzyeh Ghassemi, Luca Foschini, Anna Goldenberg
Source: The Lancet Digital Health
Date: March 24, 2023
Summary: Evidation research looks into which criteria must be met before a study can claim reasonable COVID-19 detection performance using data from wearable devices.

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

Authors: Mezlini A, Caddigan E, Shapiro A, Ramirez E, Kondow-McConaghy H, Yang J, DeMarco K, Naraghi-Arani P, Foschini L
Source: ScienceDirect
Date: March 14, 2023
Summary: Evidation describes an approach for reducing recruiting time and resources in a COVID-19 study by targeting recruitment to high-risk individuals.

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

Authors: Ritika R. Chaturvedi, Marco Angrisani, Wendy M. Troxel, Tania Gutsche, Eva Ortega, Monika Jain, Adrien Boch & Arie Kapteyn
Source: Nature Medicine
Date: February 3, 2023
Summary: 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.

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

Authors: 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
Source: Open Forum Infectious Diseases
Date: December 22, 2022
Summary: Evidation conducted a study that used person-generated health data (PGHD) to identify factors associated with seeking care for ILI.

COVID-19 real-world evidence primer

Authors: Amy Cavet, Claire Cravero, MPH, Aaron Galaznik, MD, Bray Patrick-Lake, MFS, Aniketh Talwai
Source: The Reagan-Udall Foundation for the FDA
Date: September 23, 2022
Summary: 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.