The relationship between objective app engagement and medication adherence in asthma and COPD: a retrospective analysis

1.Centers for Disease Control and Prevention (CDC), Most Recent National Asthma Data|CDC. 2020. https://www.cdc.gov/asthma/most_recent_national_asthma_data.htm. Accessed 06 Jul 2020.2.CDC-Basics About COPD-Chronic Obstructive Pulmonary Disease (COPD). 2019. https://www.cdc.gov/copd/basics-about.html. Accessed 06 Jul 2020.3.Chronic Obstructive Pulmonary Disease | AAAAI. The American Academy of Allergy, Asthma & Immunology. https://www.aaaai.org/conditions-and-treatments/related-conditions/chronic-obstructive-pulmonary-disease. Accessed 06 Jul 2020.4.Engelkes, M., Janssens, H. M., de Jongste, J. C., Sturkenboom, M. C. J. M. & Verhamme, K. M. C. Medication adherence and the risk of severe asthma exacerbations: A systematic review. Eur. Respir. J. 45(2), 396–407. https://doi.org/10.1183/09031936.00075614 (2015).Article  PubMed  Google Scholar  5.Bourbeau, J. & Bartlett, S. J. Patient adherence in COPD. Thorax 63(9), 831–838. https://doi.org/10.1136/thx.2007.086041 (2008).CAS  Article  PubMed  Google Scholar  6.Gillespie, C. W., Morin, P. E., Tucker, J. M. & Purvis, L. Medication adherence, health care utilization, and spending among privately insured adults with chronic conditions in the United States, 2010–2016. Am. J. Med. 133(6), 690-704.e19. https://doi.org/10.1016/j.amjmed.2019.12.021 (2020).Article  PubMed  Google Scholar  7.Mäkelä, M. J., Backer, V., Hedegaard, M. & Larsson, K. Adherence to inhaled therapies, health outcomes and costs in patients with asthma and COPD. Respir. Med. 107(10), 1481–1490. https://doi.org/10.1016/j.rmed.2013.04.005 (2013).Article  PubMed  Google Scholar  8.Otsuki-Clutter, M., Sutter, M. & Ewig, J. Promoting adherence to inhaled corticosteroid therapy in patients with asthma. Former USFSP Sch. 2011, [Online]. http://digital.usfsp.edu/former-pub/43.9.George, M. Adherence in asthma and COPD: New strategies for an old problem. Respir. Care 63(6), 818–831. https://doi.org/10.4187/respcare.05905 (2018).Article  PubMed  Google Scholar  10.Van Sickle, D., Barrett, M., Humblet, O., Henderson, K. & Hogg, C. Randomized, controlled study of the impact of a mobile health tool on asthma SABA use, control and adherence. Eur. Respir. J. 48, suppl 60. https://doi.org/10.1183/13993003.congress-2016.PA1018 (2016).Article  Google Scholar  11.Mosnaim, G. S. et al. The impact of patient self-monitoring via electronic medication monitor and mobile app plus remote clinician feedback on adherence to inhaled corticosteroids: A randomized controlled trial. J. Allergy Clin. Immunol. Pract. https://doi.org/10.1016/j.jaip.2020.10.064 (2020).Article  PubMed  PubMed Central  Google Scholar  12.Moore, A. et al. A randomised controlled trial of the effect of a connected inhaler system on medication adherence in uncontrolled asthmatic patients. Eur. Respir. J. https://doi.org/10.1183/13993003.03103-2020 (2020).Article  PubMed  Google Scholar  13.Unni, E., Gabriel, S. & Ariely, R. A review of the use and effectiveness of digital health technologies in patients with asthma. Ann. Allergy. Asthma. Immunol. 121(6), 680-691.e1. https://doi.org/10.1016/j.anai.2018.10.016 (2018).Article  PubMed  Google Scholar  14.Ramsey, R. R. et al. Systematic review of digital interventions for pediatric asthma management. J. Allergy Clin. Immunol. Pract. 8(4), 1284–1293. https://doi.org/10.1016/j.jaip.2019.12.013 (2020).Article  PubMed  Google Scholar  15.Yang, F., Wang, Y., Yang, C., Hu, H. & Xiong, Z. Mobile health applications in self-management of patients with chronic obstructive pulmonary disease: A systematic review and meta-analysis of their efficacy. BMC Pulm. Med. https://doi.org/10.1186/s12890-018-0671-z (2018).Article  PubMed  PubMed Central  Google Scholar  16.Lycett, H. J. et al. Theory-based digital interventions to improve asthma self-management outcomes: Systematic review. J. Med. Internet Res. 20(12), e293. https://doi.org/10.2196/jmir.9666 (2018).Article  PubMed  PubMed Central  Google Scholar  17.Serrano, K. J., Coa, K. I., Yu, M., Wolff-Hughes, D. L. & Atienza, A. A. Characterizing user engagement with health app data: A data mining approach. Transl. Behav. Med. 7(2), 277–285. https://doi.org/10.1007/s13142-017-0508-y (2017).Article  PubMed  PubMed Central  Google Scholar  18.Kosse, R. C. et al. Effective engagement of adolescent asthma patients with mobile health–supporting medication adherence. JMIR mHealth uHealth 7(3), e12411 (2019).Article  Google Scholar  19.Osterberg, L. & Blaschke, T. Adherence to medication. N. Engl. J. Med. 353(5), 487–497. https://doi.org/10.1056/NEJMra050100 (2005).CAS  Article  PubMed  Google Scholar  20.Global Initiative for Asthma. Global Strategy for Asthma Management and Prevention, 2016. http://www.ginasthma.org.21.Global Initiative for Chronic Obstructive Lung Disease. Global strategy for the diagnosis, management, and prevention of chronic obstructive pulmonary disease. https://goldcopd.org/2021-gold-reports/.22.Nathan, R. A. et al. Development of the asthma control test: A survey for assessing asthma control. J. Allergy Clin. Immunol. 113(1), 59–65. https://doi.org/10.1016/j.jaci.2003.09.008 (2004).Article  PubMed  Google Scholar  23.Jones, P. W. et al. Development and first validation of the COPD assessment test. Eur. Respir. J. 34(3), 648–654. https://doi.org/10.1183/09031936.00102509 (2009).CAS  Article  PubMed  Google Scholar  24.Edney, S. et al. User engagement and attrition in an app-based physical activity intervention: Secondary analysis of a randomized controlled trial. J. Med. Internet Res. 21(11), e14645. https://doi.org/10.2196/14645 (2019).Article  PubMed  PubMed Central  Google Scholar  25.Kwasny, M. J., Schueller, S. M., Lattie, E., Gray, E. L. & Mohr, D. C. Exploring the use of multiple mental health apps within a platform: Secondary analysis of the intellicare field trial. JMIR Ment. Health 6(3), e11572. https://doi.org/10.2196/11572 (2019).Article  PubMed  PubMed Central  Google Scholar  26.Martos-Méndez, M. J. Self-efficacy and adherence to treatment: The mediating effects of social support. J. Behav. Health Soc. Issues 7(2), 19–29 (2015).Article  Google Scholar  27.Kahwati, L. et al. Identifying configurations of behavior change techniques in effective medication adherence interventions: A qualitative comparative analysis. Syst. Rev. https://doi.org/10.1186/s13643-016-0255-z (2016).Article  PubMed  PubMed Central  Google Scholar  28.Tanenbaum, M. L., Ross, K. M. & Wing, R. R. Overeat today, skip the scale tomorrow: An examination of caloric intake predicting nonadherence to daily self-weighing. Obesity 24(11), 2341–2343. https://doi.org/10.1002/oby.21650 (2016).Article  PubMed  Google Scholar  29.Carlo, A. D., HosseiniGhomi, R., Renn, B. N., Strong, M. A. & Areán, P. A. Assessment of real-world use of behavioral health mobile applications by a novel stickiness metric. JAMA Netw. Open 3, 8. https://doi.org/10.1001/jamanetworkopen.2020.11978 (2020).Article  Google Scholar  30.Carroll, J. K. et al. Who uses mobile phone health apps and does use matter? A secondary data analytics approach. J. Med. Internet Res. 19(4), e125. https://doi.org/10.2196/jmir.5604 (2017).Article  PubMed  PubMed Central  Google Scholar  31.Bidargaddi, N. et al. To prompt or not to prompt? A microrandomized trial of time-varying push notifications to increase proximal engagement with a mobile health app. JMIR MHealth UHealth 6(11), e10123. https://doi.org/10.2196/10123 (2018).Article  PubMed  PubMed Central  Google Scholar  32.Wilson, S. R. et al. Shared treatment decision making improves adherence and outcomes in poorly controlled asthma. Am. J. Respir. Crit. Care Med. 181(6), 566–577. https://doi.org/10.1164/rccm.200906-0907OC (2010).Article  PubMed  Google Scholar  Page 2  Asthma n = 1629 COPD n = 663 Age (mean (SD)); years 39.4 (12.6) 60.9 (8.3) Female, n (%) 1302 (80) 443 (67) Baseline CAT, mean (SD) – 23.8 (7.5) Baseline ACT, mean (SD) 13.3 (4.5) – Uncontrolled Asthma (ACT  20), n (%)   449 (67.7) Android, n (%) 860 (53) 437 (66) Rescue use (mean (SD)), puffs/day 1.0 (1.8) 1.74 (2.5) Daily medication adherence (mean (SD)), % 45 (32) 62 (32) Percent of days with 100% adherence (mean (SD)), % 31 (33) 50 (38) Percent of days with app opens (mean (SD)), % 16 (19) 28 (27) App opens/day (mean (SD)) 0.2 (0.4) 0.5 (0.8) Daily app session duration (mean (SD)), mina 4.4 (6.5) 4.3 (5.0) *90 days of participant data included e.g., mean rescue puffs/day was calculated over 90 days. aCapped at 60 min/day.
https://www.nature.com/articles/s41598-021-03827-2