Mobile Health Technology for Pediatric Symptom Monitoring

Abstract

Background Pediatric blood and marrow transplant (PBMT) patients experience significant symptom distress. Mobile health (mHealth) technologies can be leveraged to improve understanding of the patient’s symptom experience by providing continuous, real-time, in situ, patient-generated symptom data. This rich data stream can subsequently enhance symptom management strategies. However, limited research has been conducted in this area. Objectives This pilot study seeks to (a) explore the feasibility of integrating mHealth technologies to monitor symptom data for PBMT patients and (b) evaluate the study design, measures, and procedures. Methods An exploratory longitudinal design was employed to assess the feasibility of monitoring 10 PBMT patients’ symptoms using data from two mHealth technologies: (a) a smartphone mHealth application (app) to collect symptom data and (b) a wearable tracking device (Apple watch) to collect physiological data. Feasibility was measured as usability and acceptability. Monthly patient interviews and an end-of-study feasibility survey were employed and analyzed to further understand reasons for sustained interest in and attrition from the study. Results Overall usability of the wearable was 51%, and app was 56%. Children reported devices were easy to use and acceptable. The study demonstrated acceptability with an enrollment rate of 83% and an attrition rate of 30%, with 70% of the children remaining in the study for at least 40 days. Discussion This pilot study is among the first to explore the feasibility of using mobile technologies to longitudinally obtain patient-generated symptom data to enhance understanding of the PBMT symptom experience. In addition, it will improve our understanding of how these data present, interact, and cluster together throughout the posttransplant period.

Acceleration of mobile health for monitoring post‐transplant in the COVID‐19 era: Applications for pediatric settings

“… 18 The TRU‐PBMT intervention is currently being studied for feasibility, acceptability, and usability. 23 , 24 Thus, the development of mHealth interventions for the pediatric transplant population is in its early stages.…”

“… 32 Other studies have reported similar findings. 14 , 24 , 33 Patients may, thus, be willing to use telehealth monitoring and interventions post‐transplant, but persistence in using such apps/devices or interventions, beyond the initial novelty, has yet to be established.…”

“…Studies have found high acceptability rates over the short run, but findings to date are drawn from a handful of studies that may not generalize well given design considerations and short follow‐up or, reliance on self‐report measures rather than actual use metrics. In both adult and pediatric trials, findings were reported in the context of small sample sizes 13 , 14 , 17 , 19 , 24 and a lack of long‐term outcomes. 12 , 13 , 14 , 16 , 17 , 24 Additionally, almost all trials were single‐center trials, which may result in patient homogeneity in terms of race and socioeconomic status and consequently a lack of generalizability.…”

“…In both adult and pediatric trials, findings were reported in the context of small sample sizes 13 , 14 , 17 , 19 , 24 and a lack of long‐term outcomes. 12 , 13 , 14 , 16 , 17 , 24 Additionally, almost all trials were single‐center trials, which may result in patient homogeneity in terms of race and socioeconomic status and consequently a lack of generalizability. Many of these studies, both adult and pediatric trials, made use of self‐report and collateral measures, 12 , 15 , 16 which tend to inflate adherence.…”

“…The literature surrounding pediatric trials specifically is sparse with all findings referencing interventions that are in early stages of development, ranging from field tests to small feasibility trials. The majority of these studies used cohort (uncontrolled) designs, 17 , 19 , 24 therefore lacking robust evidence for efficacy. Of note, there were a number of publications on proposed studies without the inclusion of data.…”