Feasibility of Obtaining Measures of Lifestyle From a Smartphone App

McConnell, Michael V.; Shcherbina, Anna; Pavlović, Aleksandra; Homburger, Julian R.; Goldfeder, Rachel L.; Waggot, Daryl; Cho, Mildred K.; Rosenberger, Mary E.; Haskell, William L.; Myers, Jonathan; Champagne, Mary Ann; Mignot, Emmanuel; Landray, Martin J; Tarassenko, Lionel; Harrington, Robert A.; Yeung, Alan C.; Ashley, Euan A.

doi:10.1001/jamacardio.2016.4395

Cited by 227 publications

(162 citation statements)

References 44 publications

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“…Relative to other ResearchKit studies, we have seen less attrition and a higher percentage or participants filling out the surveys. [13][14][15][16] Additionally, 73% of participants in our study were willing to share data with outside researchers which is similar to other ResearchKit studies (67-78%). 13,15,16 Higher engagement and willingness to share data may be a result of our unique study population of expectant mothers bringing their baby into the world, during a limited, circumscribed temporal window.…”

Section: Commentsupporting

confidence: 79%

The Healthy Pregnancy Research Program: Transforming Pregnancy Research Through a ResearchKit App

Radin

Steinhubl

et al. 2018

Preprint

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Short Title: Pregnancy ResearchKit App 2 Background. Although maternal morbidity and mortality in the United States is among the worst of developed countries, pregnant women have been under-represented in research studies, resulting in deficiencies in evidence-based guidance for treatment. There are over two billion smartphone users worldwide, enabling researchers to easily and cheaply conduct extremely large-scale research studies through smartphone apps, especially among pregnant women in whom app use is exceptionally high, predominantly as an information conduit Objective: We aim to improve our understanding of factors that promote a healthy pregnancy for both the mother and developing fetus through the large-scale and simplified collection of participant-generated data.Study Design. We developed the first pregnancy research app that is embedded within an existing, popular pregnancy app for self-management and education of expectant mothers. Our research app is used to collect a combination of survey and sensor generated data from pregnant women living in the U.S. Results. From the study's launch onMarch 16, 2017 through December 17, 2017, we have enrolled 2,058 participants from all 50 states. Our study population is diverse geographically and demographically, and fairly representative of U.S. population averages. We have collected 14,045 individual surveys and 11,669 days of sleep, activity, blood pressure and heart rate measurements during this time. On average, women stayed engaged in the study for 64 days and 48 percent who reached their due date filled out the final outcome survey. Conclusion. During the first nine months of the deployment of this unique program of ongoing research in pregnancy, we demonstrated the potential for a smartphone-based research platform to capture an ever-expanding array of longitudinal, objective and subjective participantgenerated data from a continuously growing and diverse population of pregnant women. Clinical Trials Registration: ClinicalTrials.gov Identifier: NCT03085875

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Section: Commentsupporting

confidence: 79%

The Healthy Pregnancy Research Program: Transforming Pregnancy Research Through a ResearchKit App

Radin

Steinhubl

et al. 2018

Preprint

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“…Movement can be accurately calculated via GPS by simply summing travelled distance, or via algorithms that consider speed and patterns of motion to summarize type or quantity of motion. Movement patterns have been used in a number of large-scale longitudinal studies (Brocklebank, Falconer, Page, Perry, & Cooper, 2015;McConnell et al, 2017).…”

Section: Embodied Activitymentioning

confidence: 99%

Automated sensing of daily activity: A new lens into development

Barbaro

2019

Developmental Psychobiology

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Rapidly maturing technologies for sensing and activity recognition can provide unprecedented access to the complex structure daily activity and interaction, promising new insight into the mechanisms by which experience shapes developmental outcomes. Motion data, autonomic activity, and “snippets” of audio and video recordings can be conveniently logged by wearable sensors (Lazer et al., 2009). Machine learning algorithms can process these signals into meaningful markers, from child and parent behavior to outcomes such as depression or teenage drinking. Theoretically motivated aspects of daily activity can be combined and synchronized to examine reciprocal effects between children’s behaviors and their environments or internal processes. Captured over longitudinal time, such data provide a new opportunity to study the processes by which individual differences emerge and stabilize. This paper introduces the reader to developments in sensing and activity recognition with implications for developmental phenomena across the lifespan, sketching a framework for leveraging mobile sensors for transactional analyses that bridge micro‐ and longitudinal‐ timescales of development. It finishes by detailing resources and best practices to facilitate the next generation of developmentalists to contribute to this emerging area.

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“…The MyHeart Counts smartphone app 12 provides a platform for clinical research using smartphones. 13 The app allows researchers to obtain informed consent for study participation using fully automated methods 14 and enables the monitoring of an individual's physical activity via the integrated HealthKit platform. 15 The MyHeart Counts app also surveys selfreported happiness and physical wellbeing and sleep quality.…”

Section: Introductionmentioning

confidence: 99%

The effect of digital physical activity interventions on daily step count: a randomised controlled crossover substudy of the MyHeart Counts Cardiovascular Health Study

Shcherbina

Hershman

Lazzeroni

et al. 2019

The Lancet Digital Health

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Background Smartphone apps might enable interventions to increase physical activity, but few randomised trials testing this hypothesis have been done. The MyHeart Counts Cardiovascular Health Study is a longitudinal smartphone-based study with the aim of elucidating the determinants of cardiovascular health. We aimed to investigate the effect of four different physical activity coaching interventions on daily step count in a substudy of the MyHeart Counts Study. Methods In this randomised, controlled crossover trial, we recruited adults (aged ≥18 years) in the USA with access to an iPhone smartphone (Apple, Cupertino, CA, USA; version 5S or newer) who had downloaded the MyHeart Counts app (version 2.0). After completion of a 1 week baseline period of interaction with the MyHeart Counts app, participants were randomly assigned to receive one of 24 permutations (four combinations of four 7 day interventions) in a crossover design using a random number generator built into the app. Interventions consisted of either daily prompts to complete 10 000 steps, hourly prompts to stand following 1 h of sitting, instructions to read the guidelines from the American Heart Association website, or e-coaching based upon the individual's personal activity patterns from the baseline week of data collection. Participants completed the trial in a free-living setting. Due to the nature of the interventions, participants could not be masked from the intervention. Investigators were not masked to intervention allocation. The primary outcome was change in mean daily step count from baseline for each of the four interventions, assessed in the modified intention-to-treat analysis set, which included all participants who had completed 7 days of baseline monitoring and at least 1 day of one of the four interventions. This trial is registered with ClinicalTrials.gov, NCT03090321. Findings Between Dec 12, 2016, and June 6, 2018, 2783 participants consented to enrol in the coaching study, of whom 1075 completed 7 days of baseline monitoring and at least 1 day of one of the four interventions and thus were included in the modified intention-to-treat analysis set. 493 individuals completed the full set of assigned interventions. All four interventions significantly increased mean daily step count from baseline (mean daily step count 2914 [SE 74]): mean step count increased by 319 steps (75) for participants in the American Heart Association website prompt group (p<0·0001), 267 steps (74) for participants in the hourly stand prompt group (p=0·0003), 254 steps (74) for participants in the clusterspecific prompts group (p=0·0006), and by 226 steps (75) for participants in the 10 000 daily step prompt group (p=0·0026 vs baseline).Interpretation Four smartphone-based physical activity coaching interventions significantly increased daily physical activity. These findings suggests that digital interventions delivered via a mobile app have the ability to increase shortterm physical activity levels in a free-living cohort.

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Feasibility of Obtaining Measures of Lifestyle From a Smartphone App

Cited by 227 publications

References 44 publications

The Healthy Pregnancy Research Program: Transforming Pregnancy Research Through a ResearchKit App

The Healthy Pregnancy Research Program: Transforming Pregnancy Research Through a ResearchKit App

Automated sensing of daily activity: A new lens into development

The effect of digital physical activity interventions on daily step count: a randomised controlled crossover substudy of the MyHeart Counts Cardiovascular Health Study

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