Mobile Health Technology for Pediatric Symptom Monitoring: A Feasibility Study

Jacqueline Vaughn, Siddharth Gollarahalli, Ryan J Shaw, Sharron Docherty, Qing Yang, Chandni Malhotra, Erika Summers-Goeckerman, Nirmish Shah, Jacqueline Vaughn, Siddharth Gollarahalli, Ryan J Shaw, Sharron Docherty, Qing Yang, Chandni Malhotra, Erika Summers-Goeckerman, Nirmish Shah

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.

Trial registration: ClinicalTrials.gov NCT02895841.

Conflict of interest statement

The authors have no conflicts of interest to report.

Figures

Figure 1.
Figure 1.
Empirical Summary Plots Figure 1.1. The empirical summary plot illustrates the trend of children’s weekly proportion of missing heart rate (wearable) data. Figure 1.2. The empirical summary plot illustrates the trend of children’s weekly proportion of missing chart (app) data.
Figure 1.
Figure 1.
Empirical Summary Plots Figure 1.1. The empirical summary plot illustrates the trend of children’s weekly proportion of missing heart rate (wearable) data. Figure 1.2. The empirical summary plot illustrates the trend of children’s weekly proportion of missing chart (app) data.
Figure 2.
Figure 2.
Heat Map Visualization Figure 2.1. The heat map allows visualization of complex longitudinal data. The seven patients are listed at the right of each row. Dark gray represents a day the child engaged with the app. Symptom occurrence and intensity are depicted by bright colors ranging from blue (low intensity) to red (high intensity) correlating to a numeric scale from 0–10. Figure 2.2. A zoom view of two segments of the heat map depicting symptom intensities with color.
Figure 2.
Figure 2.
Heat Map Visualization Figure 2.1. The heat map allows visualization of complex longitudinal data. The seven patients are listed at the right of each row. Dark gray represents a day the child engaged with the app. Symptom occurrence and intensity are depicted by bright colors ranging from blue (low intensity) to red (high intensity) correlating to a numeric scale from 0–10. Figure 2.2. A zoom view of two segments of the heat map depicting symptom intensities with color.

Source: PubMed

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