%0 Journal Article
%@ 2291-5222
%I JMIR Publications
%V 7
%N 12
%P e13305
%T Lessons Learned: Recommendations For Implementing a Longitudinal Study Using Wearable and Environmental Sensors in a Health Care Organization
%A L'Hommedieu,Michelle
%A L'Hommedieu,Justin
%A Begay,Cynthia
%A Schenone,Alison
%A Dimitropoulou,Lida
%A Margolin,Gayla
%A Falk,Tiago
%A Ferrara,Emilio
%A Lerman,Kristina
%A Narayanan,Shrikanth
%+ Information Sciences Institute, University of Southern California, 3740 McClintock Ave, EEB 413, Los Angeles, CA, 90089, United States, 1 2137402318, mhasan@isi.edu
%K research
%K research techniques
%K Ecological Momentary Assessment
%K wearable electronic devices
%D 2019
%7 10.12.2019
%9 Viewpoint
%J JMIR Mhealth Uhealth
%G English
%X Although traditional methods of data collection in naturalistic settings can shed light on constructs of interest to researchers, advances in sensor-based technology allow researchers to capture continuous physiological and behavioral data to provide a more comprehensive understanding of the constructs that are examined in a dynamic health care setting. This study gives examples for implementing technology-facilitated approaches and provides the following recommendations for conducting such longitudinal, sensor-based research, with both environmental and wearable sensors in a health care setting: pilot test sensors and software early and often; build trust with key stakeholders and with potential participants who may be wary of sensor-based data collection and concerned about privacy; generate excitement for novel, new technology during recruitment; monitor incoming sensor data to troubleshoot sensor issues; and consider the logistical constraints of sensor-based research. The study describes how these recommendations were successfully implemented by providing examples from a large-scale, longitudinal, sensor-based study of hospital employees at a large hospital in California. The knowledge gained from this study may be helpful to researchers interested in obtaining dynamic, longitudinal sensor data from both wearable and environmental sensors in a health care setting (eg, a hospital) to obtain a more comprehensive understanding of constructs of interest in an ecologically valid, secure, and efficient way.
%M 31821155
%R 10.2196/13305
%U https://mhealth.jmir.org/2019/12/e13305
%U https://doi.org/10.2196/13305
%U http://www.ncbi.nlm.nih.gov/pubmed/31821155