Dataset Information

The asthma mobile health study, smartphone data collected using ResearchKit.

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.

SUBMITTER: Chan YY

PROVIDER: S-EPMC5963336 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature

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The asthma mobile health study, smartphone data collected using ResearchKit.

Chan Yu-Feng Yvonne YY Bot Brian M BM Zweig Micol M Tignor Nicole N Ma Weiping W Suver Christine C Cedeno Rafhael R Scott Erick R ER Gregory Hershman Steven S Schadt Eric E EE Wang Pei P

Scientific data 20180522

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 ...[more]

PMID: 29786695

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Project description:Using smartphones to enroll, obtain consent, and gather self-reported data from patients has the potential to enhance our understanding of disease burden and quantify physiological impact in the real world. It may also be possible to harness integral smartphone sensors to facilitate remote collection of clinically relevant data.We conducted the Patient Rheumatoid Arthritis Data From the Real World (PARADE) observational study using a customized ResearchKit app with a bring-your-own-device approach. Our objective was to assess the feasibility of using an entirely digital approach (social media and smartphone app) to conduct a real-world observational study of patients with rheumatoid arthritis.We conducted this observational study using a customized ResearchKit app with a bring-your-own-device approach. To recruit patients, the PARADE app, designed to guide patients through a series of tasks, was publicized via social media platforms and made available for patients in the United States to download from the Apple App Store. We collected patient-reported data, such as medical history, rheumatoid arthritis-related medications (past and present), and a range of patient-reported outcome measures. We included in the assessment a joint-pain map and a novel objective assessment of wrist range of movement, measured by the smartphone-embedded gyroscope and accelerometer.Within 1 month of recruitment via social media campaigns, 399 participants self-enrolled, self-consented, and provided complete demographic data. Joint pain was the most frequently reported rheumatoid arthritis symptom to bother study participants (344/393, 87.5%). Severe patient-reported wrist pain appeared to be inversely linked with the range of wrist movement measured objectively by the app. At study entry, 292 of 399 participants (73.2%) indicated a preference for participating in a mobile app-based study. The number of participants in the study declined to 45 of 399 (11.3%) at week 12.Despite the declining number of participants over time, the combination of social media and smartphone app with sensor integration was a feasible and cost-effective approach for the collection of patient-reported data in rheumatoid arthritis. Integral sensors within smartphones can be harnessed to provide novel end points, and the novel wrist range of movement test warrants further clinical validation.

Project description:BackgroundInappropriate asthma control reduces quality of life and causes increased exacerbations. Mobile health (mHealth) employs information and communication technology for surveying health-related issues.ObjectiveThis noninterventional, observational study assessed current real-world asthma control levels among Japanese patients with asthma and cough variant asthma (CVA) using the Zensoku-Log app.MethodsWe developed the app using the ResearchKit platform and conducted a mobile-based, self-reporting, observational survey among patients with asthma and CVA. The app was downloaded 7855 times between February 2016 and February 2018, and enabled collection of data on symptoms, comorbidities, quality of life, medications, asthma control, and adherence.ResultsOf the 1744 eligible participants (median age 33 years; range 20-74 years; male-to-female ratio 38.7:61.3), 50.97% (889/1744) reported unscheduled visits, 62.84% (1096/1744) reported regularly scheduled visits, 23.14% (402/1737) smoked, and 40.75% (705/1730) had pets. In addition, 91.89% (1598/1739) of participants had atopic predisposition, including allergic rhinitis and atopic dermatitis. Daily inhaled corticosteroid and oral corticosteroid treatment had been prescribed for 89.45% (1552/1735) and 22.07% (383/1735) of participants, respectively. Although an asthma control questionnaire demonstrated poor asthma control in 58.48% (1010/1727), a leukotriene receptor antagonist, theophylline, and a long-acting muscarinic antagonist had been prescribed for only 30.66% (532/1735), 15.91% (276/1735), and 4.38% (76/1735), respectively. The Adherence Starts with Knowledge 12 total score was 29. In the 421 participants who repeated the questionnaire, asthma control increased significantly between the initial and last rounds (P=.002).ConclusionsUsers of this mHealth app in Japan had poorly controlled asthma and may need more treatment for asthma and their comorbidities. Repeated app users demonstrated improved asthma control.Trial registrationUMIN Clinical Trial Registry UMIN000021043; https://upload.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000023913.

Project description:BACKGROUND:Each year, millions of older adults fall, with more than 1 out of 4 older people experiencing a fall annually, thereby causing a major social and economic impact. Falling once doubles one’s chances of falling again, making fall prediction an important aspect of preventative strategies. In this study, 22 older adults aged between 65 and 85 years were trained in the use of a smartphone-based fall prediction system. The system is designed to continuously assess fall risk by measuring various gait and balance parameters using a smart insole and smartphone, and is also designed to detect falls. The use case of the fall prediction system in question required the users to interact with the smartphone via an app for device syncing, data uploads, and checking system status. OBJECTIVE:The objective of this study was to observe the effect that basic smartphone training could have on the user experience of a group that is not technically proficient with smartphones when using a new connected health system. It was expected that even short rudimentary training could have a large effect on user experience and therefore increase the chances of the group accepting the new technology. METHODS:All participants received training on how to use the system smartphone app; half of the participants (training group) also received extra training on how to use basic functions of the smartphone, such as making calls and sending text messages, whereas the other half did not receive this extra training (no extra training group). Comparison of training group and no extra training group was carried out using metrics such as satisfaction rating, time taken to complete tasks, cues required to complete tasks, and errors made during tasks. RESULTS:The training group fared better in the first 3 days of using the system. There were significant recorded differences in number of cues required and errors committed between the two groups. By the fourth and fifth day of use, both groups were performing at the same level when using the system. CONCLUSIONS:Supplementary basic smartphone training may be critical in trials where a smartphone app–based system for health intervention purposes is being introduced to a population that is not proficient with technology. This training could prevent early technology rejection and increase the engagement of older participants and their overall user experience with the system.

Dataset Information

The asthma mobile health study, smartphone data collected using ResearchKit.

Publications

The asthma mobile health study, smartphone data collected using ResearchKit.

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