Open AccessMobile Health-Collected Biophysical Markers in Children with Serious Illness-Related Pain
Author(s) -
Tolúwalàsé Ajayi,
Leia Salongo,
Yunyue Zang,
Nathan E. Wineinger,
Steven R. Steinhubl
Publication year - 2021
Publication title -
journal of palliative medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.986
H-Index - 90
eISSN - 1096-6218
pISSN - 1557-7740
DOI - 10.1089/jpm.2020.0234
Subject(s) - medicine , context (archaeology) , observational study , medical diagnosis , chronic pain , disease , population , physical therapy , health care , medical emergency , intensive care medicine , emergency medicine , paleontology , environmental health , pathology , economic growth , economics , biology
Context: There is an ongoing established need to develop engaging pain assessment strategies to provide more effective individualized care to pediatric patients with serious illnesses. This study explores the acceptability of wireless devices as one option. Objective: To evaluate the ability of wrist-wearable technology to collect physiological data from children with serious illnesses. Methods: Single-site prospective observational study conducted between September 2017 and September 2018 at Rady Children's Hospital, San Diego, California, inpatient wards. Pediatric patients with diagnoses of cancer and sickle cell disease admitted to the hospital for acute-on-chronic pain and taking opioid pain medications were asked to complete two 24-hour continuous monitoring periods with the Empatica E4 wristband. Results: Data collected from the device correlated with manually obtained vital signs. Children responded favorably to wearing the device. Participants with reported subjective pain versus no pain had average heart rate increased by 16.4 bpm, skin temperature decreased by 3.5°C, and electrodermal activity decreased by 0.27. Conclusions: This study shows the possibility of collecting continuous biophysical data in a nonobtrusive manner in seriously ill children experiencing acute-on-chronic pain using wearable devices. It provides the framework for larger studies to explore the utility of such data in relation to metrics of pain and suffering in this patient population.