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. 2022 Jun 10;24(6):e34191.
doi: 10.2196/34191.

Electronic Health Record-Based Recruitment and Retention and Mobile Health App Usage: Multisite Cohort Study

Janelle W Coughlin  1   2 , Lindsay M Martin  3 , Di Zhao  2   4 , Attia Goheer  4 , Thomas B Woolf  5 , Katherine Holzhauer  3 , Harold P Lehmann  3 , Michelle R Lent  6 , Kathleen M McTigue  7 , Jeanne M Clark  2   3 , Wendy L Bennett  2   3
Affiliations

Electronic Health Record-Based Recruitment and Retention and Mobile Health App Usage: Multisite Cohort Study

Janelle W Coughlin et al. J Med Internet Res. .

Abstract

Background: To address the obesity epidemic, there is a need for novel paradigms, including those that address the timing of eating and sleep in relation to circadian rhythms. Electronic health records (EHRs) are an efficient way to identify potentially eligible participants for health research studies. Mobile health (mHealth) apps offer available and convenient data collection of health behaviors, such as timing of eating and sleep.

Objective: The aim of this descriptive analysis was to report on recruitment, retention, and app use from a 6-month cohort study using a mobile app called Daily24.

Methods: Using an EHR query, adult patients from three health care systems in the PaTH clinical research network were identified as potentially eligible, invited electronically to participate, and instructed to download and use the Daily24 mobile app, which focuses on eating and sleep timing. Online surveys were completed at baseline and 4 months. We described app use and identified predictors of app use, defined as 1 or more days of use, versus nonuse and usage categories (ie, immediate, consistent, and sustained) using multivariate regression analyses.

Results: Of 70,661 patients who were sent research invitations, 1021 (1.44%) completed electronic consent forms and online baseline surveys; 4 withdrew, leaving a total of 1017 participants in the analytic sample. A total of 53.79% (n=547) of the participants were app users and, of those, 75.3% (n=412), 50.1% (n=274), and 25.4% (n=139) were immediate, consistent, and sustained users, respectively. Median app use was 28 (IQR 7-75) days over 6 months. Younger age, White race, higher educational level, higher income, having no children younger than 18 years, and having used 1 to 5 health apps significantly predicted app use (vs nonuse) in adjusted models. Older age and lower BMI predicted early, consistent, and sustained use. About half (532/1017, 52.31%) of the participants completed the 4-month online surveys. A total of 33.5% (183/547), 29.3% (157/536), and 27.1% (143/527) of app users were still using the app for at least 2 days per month during months 4, 5, and 6 of the study, respectively.

Conclusions: EHR recruitment offers an efficient (ie, high reach, low touch, and minimal participant burden) approach to recruiting participants from health care settings into mHealth research. Efforts to recruit and retain less engaged subgroups are needed to collect more generalizable data. Additionally, future app iterations should include more evidence-based features to increase participant use.

Keywords: EHR; engagement; mHealth; mobile apps; obesity; recruitment; retention; timing of eating; timing of sleep.

PubMed Disclaimer

Conflict of interest statement

Conflicts of Interest: TBW founded DaiWare, but has no current commercial projects associated with DaiWare. JMC has served on a Scientific Advisory Board for Novo Nordisk and Boehringer Ingelheim.

Figures

Figure 1
Figure 1
Screenshots of web-based electronic recruitment and onboarding: electronic consent (top left), baseline surveys (top right), and POWER 28 and POWER week information (bottom).
Figure 2
Figure 2
Screenshots of the Daily24 app: empty sleep ring (top left), complete sleep ring (top middle), empty food ring (top right), meal size selection (bottom left), complete food ring (bottom middle), and complete day (bottom right).
Figure 3
Figure 3
Screenshots of the badges earned to encourage usage in the Daily24 app.
Figure 4
Figure 4
Recruitment and retention flow. REDCap: Research Electronic Data Capture.
See this image and copyright information in PMC

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References

    1. Ng M, Fleming T, Robinson M, Thomson B, Graetz N, Margono C, Mullany EC, Biryukov S, Abbafati C, Abera SF, Abraham JP, Abu-Rmeileh NME, Achoki T, AlBuhairan FS, Alemu ZA, Alfonso R, Ali MK, Ali R, Guzman NA, Ammar W, Anwari P, Banerjee A, Barquera S, Basu S, Bennett DA, Bhutta Z, Blore J, Cabral N, Nonato IC, Chang JC, Chowdhury R, Courville KJ, Criqui MH, Cundiff DK, Dabhadkar KC, Dandona L, Davis A, Dayama A, Dharmaratne SD, Ding EL, Durrani AM, Esteghamati A, Farzadfar F, Fay DFJ, Feigin VL, Flaxman A, Forouzanfar MH, Goto A, Green MA, Gupta R, Hafezi-Nejad N, Hankey G, Harewood H, Havmoeller R, Hay S, Hernandez L, Husseini A, Idrisov B, Ikeda N, Islami F, Jahangir E, Jassal S, Jee S, Jeffreys M, Jonas J, Kabagambe E, Khalifa S, Kengne A, Khader Y, Khang Y, Kim D, Kimokoti R, Kinge J, Kokubo Y, Kosen S, Kwan G, Lai T, Leinsalu M, Li Y, Liang X, Liu S, Logroscino G, Lotufo P, Lu Y, Ma J, Mainoo N, Mensah G, Merriman T, Mokdad A, Moschandreas J, Naghavi M, Naheed A, Nand D, Narayan K, Nelson E, Neuhouser M, Nisar M, Ohkubo T, Oti S, Pedroza A, Prabhakaran D, Roy N, Sampson U, Seo H, Sepanlou S, Shibuya K, Shiri R, Shiue I, Singh G, Singh J, Skirbekk V, Stapelberg N, Sturua L, Sykes B, Tobias M, Tran B, Trasande L, Toyoshima H, van de Vijver S, Vasankari T, Veerman J, Velasquez-Melendez G, Vlassov V, Vollset S, Vos T, Wang C, Wang X, Weiderpass E, Werdecker A, Wright J, Yang Y, Yatsuya H, Yoon J, Yoon S, Zhao Y, Zhou M, Zhu S, Lopez A, Murray C, Gakidou E. Global, regional, and national prevalence of overweight and obesity in children and adults during 1980-2013: A systematic analysis for the Global Burden of Disease Study 2013. Lancet. 2014 Aug 30;384(9945):766–781. doi: 10.1016/S0140-6736(14)60460-8. http://europepmc.org/abstract/MED/24880830 S0140-6736(14)60460-8 - DOI - PMC - PubMed
    1. Khan SS, Ning H, Wilkins JT, Allen N, Carnethon M, Berry JD, Sweis RN, Lloyd-Jones DM. Association of body mass index with lifetime risk of cardiovascular disease and compression of morbidity. JAMA Cardiol. 2018 Apr 01;3(4):280–287. doi: 10.1001/jamacardio.2018.0022. http://europepmc.org/abstract/MED/29490333 2673289 - DOI - PMC - PubMed
    1. Williams EP, Mesidor M, Winters K, Dubbert PM, Wyatt SB. Overweight and obesity: Prevalence, consequences, and causes of a growing public health problem. Curr Obes Rep. 2015 Sep;4(3):363–370. doi: 10.1007/s13679-015-0169-4.10.1007/s13679-015-0169-4 - DOI - PubMed
    1. Arroyo-Johnson C, Mincey KD. Obesity epidemiology worldwide. Gastroenterol Clin North Am. 2016 Dec;45(4):571–579. doi: 10.1016/j.gtc.2016.07.012. http://europepmc.org/abstract/MED/27837773 S0889-8553(16)30069-3 - DOI - PMC - PubMed
    1. Dwivedi AK, Dubey P, Cistola DP, Reddy SY. Association between obesity and cardiovascular outcomes: Updated evidence from meta-analysis studies. Curr Cardiol Rep. 2020 Mar 12;22(4):25. doi: 10.1007/s11886-020-1273-y.10.1007/s11886-020-1273-y - DOI - PubMed

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