Describing the evolution of mobile technology usage for Latino patients and comparing findings to national mHealth estimates

Arora, Sanjay; Ford, Kelsey Lynett; Terp, Sophie; Abramson, Tiffany M.; Ruiz, Ryan; Camilon, Marissa; Coyne, Christopher J.; Lam, Chun Nok; Menchine, Michael; Burner, Elizabeth

doi:10.1093/jamia/ocv203

Cited by 32 publications

(22 citation statements)

References 25 publications

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“…Thus, we aimed, as best possible and while maintaining an ethical research approach, to simulate realworld conditions in this study. Second, because the Beiwe application runs on both Android and Apple smartphones, we did not exclude any subjects based on the type of phone they owned, which is important as phone may be a proxy for socioeconomic status [29,30], which is known to be associated with both overall health and the type of health care that is available to individuals [31,32]. Third, given that the Beiwe platform is open source, others will be able to conduct similar studies and can replicate or disprove our results.…”

Section: Discussionmentioning

confidence: 99%

Relapse prediction in schizophrenia through digital phenotyping: a pilot study

Barnett

Torous

Staples

et al. 2018

Neuropsychopharmacol

321

226

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Among individuals diagnosed, hospitalized, and treated for schizophrenia, up to 40% of those discharged may relapse within 1 year even with appropriate treatment. Passively collected smartphone behavioral data present a scalable and at present underutilized opportunity to monitor patients in order to identify possible warning signs of relapse. Seventeen patients with schizophrenia in active treatment at a state mental health clinic in Boston used the Beiwe app on their personal smartphone for up to 3 months. By testing for changes in mobility patterns and social behavior over time as measured through smartphone use, we were able to identify statistically significant anomalies in patient behavior in the days prior to relapse. We found that the rate of behavioral anomalies detected in the 2 weeks prior to relapse was 71% higher than the rate of anomalies during other time periods. Our findings show how passive smartphone data, data collected in the background during regular phone use without active input from the subjects, can provide an unprecedented and detailed view into patient behavior outside the clinic. Real-time detection of behavioral anomalies could signal the need for an intervention before an escalation of symptoms and relapse occur, therefore reducing patient suffering and reducing the cost of care.

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Section: Discussionmentioning

confidence: 99%

Relapse prediction in schizophrenia through digital phenotyping: a pilot study

Barnett

Torous

Staples

et al. 2018

Neuropsychopharmacol

321

226

View full text Add to dashboard Cite

show abstract

“…While most were positive to the idea of using an app to manage GDM, they were sometimes discouraged by the technical issues. A cross-sectional survey on mHealth use among Latino patients with diabetes found that the lack of operability between the smartphone app and other devices could serve as a barrier to using the app (Arora et al, 2016). In the same study, the perceived lack of additional benefits was also an important barrier (Arora et al, 2016).…”

Section: Discussionmentioning

confidence: 99%

“…A cross-sectional survey on mHealth use among Latino patients with diabetes found that the lack of operability between the smartphone app and other devices could serve as a barrier to using the app (Arora et al, 2016). In the same study, the perceived lack of additional benefits was also an important barrier (Arora et al, 2016). In our study, many women no longer seemed to see the benefits of using the app when the automatic transfer of the blood glucose values didn't work.…”

Section: Discussionmentioning

confidence: 99%

Women's experiences with using a smartphone app (the Pregnant+ app) to manage gestational diabetes mellitus in a randomised controlled trial

et al. 2018

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“…Use of the Android platform is more common in some racial and/or ethnic groups, thus the availability of an Android version of AHA (facilitated by the open source ResearchKit framework) could capture a more representative sampling of the general population. Other nuances, such as a propensity to text rather than use apps in low-income Hispanic communities should be considered in attaining diverse participation in mobile health research 13,14 .…”

Section: Discussionmentioning

confidence: 99%

The Asthma Mobile Health Study, a large-scale clinical observational study using ResearchKit

et al. 2017

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The feasibility of using mobile health applications to conduct observational clinical studies requires rigorous validation. Here, we report initial findings from the Asthma Mobile Health Study, a research study, including recruitment, consent, and enrollment, conducted entirely remotely by smartphone. We achieved secure bidirectional data flow between investigators and 7,593 participants from across the United States, including many with severe asthma. Our platform enabled prospective collection of longitudinal, multidimensional data (e.g., surveys, devices, geolocation, and air quality) in a subset of users over the 6-month study period. Consistent trending and correlation of interrelated variables support the quality of data obtained via this method. We detected increased reporting of asthma symptoms in regions affected by heat, pollen, and wildfires. Potential challenges with this technology include selection bias, low retention rates, reporting bias, and data security. These issues require attention to realize the full potential of mobile platforms in research and patient care.

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Describing the evolution of mobile technology usage for Latino patients and comparing findings to national mHealth estimates

Abstract: Published national estimates do not accurately reflect the mobile technology use of Latino patients served by our public safety-net facility. The difference is greater for older, less educated patients with chronic disease.

Cited by 32 publications

References 25 publications

Relapse prediction in schizophrenia through digital phenotyping: a pilot study

Relapse prediction in schizophrenia through digital phenotyping: a pilot study

Women's experiences with using a smartphone app (the Pregnant+ app) to manage gestational diabetes mellitus in a randomised controlled trial

The Asthma Mobile Health Study, a large-scale clinical observational study using ResearchKit

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