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Observational Study
. 2018 May 22:5:180096.
doi: 10.1038/sdata.2018.96.

The asthma mobile health study, smartphone data collected using ResearchKit

Yu-Feng Yvonne Chan  1   2   3 , Brian M Bot  4 , Micol Zweig  1   3 , Nicole Tignor  1   3 , Weiping Ma  1   3 , Christine Suver  4 , Rafhael Cedeno  1   3 , Erick R Scott  1   5 , Steven Gregory Hershman  6   7 , Eric E Schadt  1   3   5 , Pei Wang  1   3
Affiliations
Observational Study

The asthma mobile health study, smartphone data collected using ResearchKit

Yu-Feng Yvonne Chan et al. Sci Data. .

Abstract

Widespread adoption of smart mobile platforms coupled with a growing ecosystem of sensors including passive location tracking and the ability to leverage external data sources create an opportunity to generate an unprecedented depth of data on individuals. Mobile health technologies could be utilized for chronic disease management as well as research to advance our understanding of common diseases, such as asthma. We conducted a prospective observational asthma study to assess the feasibility of this type of approach, clinical characteristics of cohorts recruited via a mobile platform, the validity of data collected, user retention patterns, and user data sharing preferences. We describe data and descriptive statistics from the Asthma Mobile Health Study, whereby participants engaged with an iPhone application built using Apple's ResearchKit framework. Data from 6346 U.S. participants, who agreed to share their data broadly, have been made available for further research. These resources have the potential to enable the research community to work collaboratively towards improving our understanding of asthma as well as mobile health research best practices.

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Conflict of interest statement

Eric Schadt (a Co-Investigator in this study and Chair of the Department of Genetics and Genomics Sciences, and Director of the Icahn Institute for Genomics and Multiscale Biology at the Icahn School of Medicine at Mount Sinai) holds equity in the form of stock options in LifeMap Solutions, a privately held company. In addition Schadt serves as an uncompensated advisory board member and is administratively responsible for the medical school’s collaboration with LifeMap Solutions.

Figures

Figure 1
Figure 1. User experience and study sample sizes.
(a)Diagram of user experience. (b) Flowchart describing sample sizes during onboarding process.
Figure 2
Figure 2. Longitudinal response counts to daily and weekly survey questions.
(a) 7 day rolling mean of daily survey question response counts across participants. (b) 4 week rolling mean of weekly survey question response counts across participants. The survey question labels used in the figure legends correspond to the column names of survey data matrices, and are annotated in Supplementary Table 1. Substantially overlapping curves were plotted with a single line and grouped in the legend. Y-axis is plotted on a log10 scale with y-axis ticks displaying back-transformed counts.
Figure 3
Figure 3. Individual response counts to daily and weekly surveys.
(a) Individual response counts of daily surveys. (b) Individual response counts of weekly surveys.
Figure 4
Figure 4. Distributions of enrollment lengths and individual response rates.
(a) Distributions of participants’ total enrollment lengths (blue) and active enrollment lengths (green). (b) Boxplots of individual response rates of daily survey questions, which are ratios of numbers of days with non-null responses of that question to either total enrollment lengths (top) or active enrollment length (bottom) of participants. (c) Boxplots of individual response rates of weekly survey questions, which are ratios of numbers of weeks with non-null responses to either number of weeks during total enrollment period (top) or active enrollment period (bottom) of participants. The survey question labels used in the figure legends correspond to the column names of survey data matrices, and are annotated in Supplementary Table 1.
Figure 5
Figure 5. Geographic distribution.
The map illustrates the geographic of 1959 participants who agreed to share their data broadly and supplied location data after May 5, 2015.
See this image and copyright information in PMC

Dataset use reported in

  • doi: 10.1038/nbt.3826

References

Data Citations

    1. Chan Y. F. Y. 2017. Synapse. http://dx.doi.org/10.7303/syn8466435.1 - DOI
    1. Chan Y. F. Y. 2017. Synapse. http://dx.doi.org/10.7303/syn8466429.1 - DOI
    1. Chan Y. F. Y. 2017. Synapse. http://dx.doi.org/10.7303/syn8466433.1 - DOI
    1. Chan Y. F. Y. 2017. Synapse. http://dx.doi.org/10.7303/syn8466442.1 - DOI
    1. Chan Y. F. Y. 2017. Synapse. http://dx.doi.org/10.7303/syn8466443.1 - DOI

References

    1. Lella Adam US Smartphone Penetration Surpassed 80% in 2016. Comscore https://www.comscore.com/Insights/Blog/US-Smartphone-Penetration-Surpass... (2017).
    1. Chan Y. F. Y. et al. The Asthma Mobile Health Study, a large-scale clinical observational study using ResearchKit. Nat Biotechnol. 35.4, 354–362 (2017). - PMC - PubMed
    1. Behavioral risk factor surveillance system: 2016 summary data quality report (Centers for Disease Control, 2017).
    1. Global strategy for asthma management and prevention. (Global Initiative for Asthma, (2017).
    1. Bot B. M. et al. The mPower study, Parkinson disease mobile data collected using ResearchKit. Sci Data 3, 160011 (2016). - PMC - PubMed

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