An mHealth App to Promote Adherence to Immunosuppressant Medication and Track Symptoms in Children After Hematopoietic Stem Cell Transplant: Protocol for a Mixed Methods Usability Study

Micah Skeens, Emre Sezgin, Jack Stevens, Wendy Landier, Ahna Pai, Cynthia Gerhardt, Micah Skeens, Emre Sezgin, Jack Stevens, Wendy Landier, Ahna Pai, Cynthia Gerhardt

Abstract

Background: In the United States, poor adherence accounts for up to 70% of all medication-related hospital admissions, resulting in $100 billion in health care costs annually. In pediatrics, adherence is largely dependent on caregivers. In a high-risk hematopoietic stem cell transplant (HSCT) population, caregivers are isolated with their child due to infection risk and must manage challenging treatment regimens at home, often with limited time and support. Complex behavioral interventions, typically employed to address adherence, are difficult to deliver and manage in the context of these daily tasks. The most successful adherence interventions, and thus improved clinical outcomes, have included mobile health (mHealth) reminder approaches and a direct measure of adherence.

Objective: This is a 3-phase project, with this protocol describing phase 2, to determine the usability and feasibility of an mHealth app (BMT4me) designed to promote adherence to immunosuppressant medication and to track symptoms among children who received HSCT.

Methods: This study uses an iterative convergent mixed methods design to develop and assess the usability and feasibility of an adherence digital health intervention. We will recruit 15 caregivers of pediatric patients receiving HSCT to complete user testing. Qualitative and quantitative data will be integrated to enhance and expand upon study findings.

Results: Enrollment began in September 2021 and is ongoing. A total of 7 caregivers have enrolled. We anticipate completion by fall 2022. We anticipate high usability scores and a better understanding of unique features within the app that are needed for HSCT families post transplant. To date, usability scores among enrolled participants are greater than 70%. Feedback from qualitative interviews is being used to further adapt the app by adding specific weekly logs, call provider options, and voice to text.

Conclusions: This protocol describes a mixed methods usability and feasibility study to develop and implement a smartphone app for caregivers of children receiving HSCT. The app was designed to improve immunosuppressant adherence and to track symptoms in the acute phase post discharge. Study findings will inform further refinement of the app and the feasibility of a pilot randomized controlled trial examining efficacy on clinical outcomes.

Trial registration: ClinicalTrials.gov NCT04976933; https://ichgcp.net/clinical-trials-registry/NCT04976933.

International registered report identifier (irrid): DERR1-10.2196/39098.

Keywords: HSCT; adherence; app; bone marrow transplant; caregivers; children; digital health; feasibility; hematopoietic stem cell transplant; mHealth; medication adherence; pediatrics; usability.

Conflict of interest statement

Conflicts of Interest: None declared.

©Micah Skeens, Emre Sezgin, Jack Stevens, Wendy Landier, Ahna Pai, Cynthia Gerhardt. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 21.07.2022.

Figures

Figure 1
Figure 1
BMT4me app wireframes.
Figure 2
Figure 2
Multiphase mixed methods app design of BMT4me. GVHD: graft vs host disease; HCP: health care practitioner; RCT: randomized controlled trial.
Figure 3
Figure 3
A stepped approach to usability testing with caregivers.

References

    1. Bissonnette Janice M. Adherence: a concept analysis. J Adv Nurs. 2008 Sep;63(6):634–43. doi: 10.1111/j.1365-2648.2008.04745.x.JAN4745
    1. Drotar DD, Crawford P, Bonner M. Collaborative decision-making and promoting treatment adherence in pediatric chronic illness. PI. 2010 Mar;2:1–7. doi: 10.2147/pi.s8820.
    1. Drotar D. Strategies of adherence promotion in the management of pediatric chronic conditions. J Dev Behav Pediatr. 2013;34(9):716–29. doi: 10.1097/DBP.0b013e31829f6781.00004703-201311000-00010
    1. McGrady M, Hommel Kevin A. Medication adherence and health care utilization in pediatric chronic illness: a systematic review. Pediatrics. 2013 Oct;132(4):730–40. doi: 10.1542/peds.2013-1451. peds.2013-1451
    1. Fiese B, Everhart Robin S. Medical adherence and childhood chronic illness: family daily management skills and emotional climate as emerging contributors. Curr Opin Pediatr. 2006 Oct;18(5):551–7. doi: 10.1097/01.mop.0000245357.68207.9b.00008480-200610000-00013
    1. Landier W. Age span challenges: adherence in pediatric oncology. Semin Oncol Nurs. 2011 May;27(2):142–53. doi: 10.1016/j.soncn.2011.02.006.S0749-2081(11)00009-X
    1. Shemesh Eyal, Shneider Benjamin L, Savitzky Jill K, Arnott Lindsay, Gondolesi Gabriel E, Krieger Nancy R, Kerkar Nanda, Magid Margret S, Stuber Margaret L, Schmeidler James, Yehuda Rachel, Emre Sukru. Medication adherence in pediatric and adolescent liver transplant recipients. Pediatrics. 2004 Apr;113(4):825–32. doi: 10.1542/peds.113.4.825.
    1. Quine L, Steadman L, Thompson S, Rutter Derek R. Adherence to anti-hypertensive medication: proposing and testing a conceptual model. Br J Health Psychol. 2012 Feb;17(1):202–19. doi: 10.1111/j.2044-8287.2011.02034.x.
    1. Varni JW, Wallander JL. Adherence to health-related regimens in pediatric chronic disorders. Clin Psych Rev. 1984 Jan;4(5):585–596. doi: 10.1016/0272-7358(84)90046-1.
    1. Hoodin F. Psychological and behavioral correlates of medical adherence among adult bone marrow transplant recipients (Dissertation) Detroit, MI: Wayne St. University; 1993.
    1. Phipps S, DeCuir-Whalley S. Adherence issues in pediatric bone marrow transplantation. J Pediatr Psychol. 1990 Aug;15(4):459–75. doi: 10.1093/jpepsy/15.4.459.
    1. Pai AL, Rausch J, Drake S, Morrison CF, Lee JL, Nelson A, Tackett A, Berger S, Szulczewski L, Mara C, Davies S. Poor adherence is associated with more infections after pediatric hematopoietic stem cell transplant. Biol Blood Marrow Transplant. 2018 Feb;24(2):381–385. doi: 10.1016/j.bbmt.2017.10.033. S1083-8791(17)30802-9
    1. McGrady ME, Williams SN, Davies SM, Pai AL. Adherence to outpatient oral medication regimens in adolescent hematopoietic stem cell transplant recipients. Eur J Oncol Nurs. 2014 Apr;18(2):140–4. doi: 10.1016/j.ejon.2013.11.007. S1462-3889(13)00163-4
    1. Skeens M, Akard TF, Gilmer MJ, Garee A, Miller A. Toward a better understanding of pediatric BMT adherence: an exploration of provider perceptions. Bio Blood Marrow Transplant. 2014 Feb;20(2):S315. doi: 10.1016/j.bbmt.2013.12.553.
    1. Patel MS, Volpp KG, Asch DA. Nudge units to improve the delivery of health care. N Engl J Med. 2018 Jan 18;378(3):214–216. doi: 10.1056/nejmp1712984.
    1. Linnemayr S, MacCarthy S, Kim A, Giguere R, Carballo-Dieguez A, Barreras JL. Behavioral economics-based incentives supported by mobile technology on HIV knowledge and testing frequency among Latino/a men who have sex with men and transgender women: Protocol for a randomized pilot study to test intervention feasibility and acceptability. Trials. 2018 Oct 05;19(1):540. doi: 10.1186/s13063-018-2867-1. 10.1186/s13063-018-2867-1
    1. Stevens Jack. Behavioral economics as a promising framework for promoting treatment adherence to pediatric regimens. J Pediatr Psychol. 2014 Sep;39(10):1097–103. doi: 10.1093/jpepsy/jsu071.jsu071
    1. van Mierlo T, Hyatt D, Ching AT, Fournier R, Dembo RS. Behavioral economics, wearable devices, and cooperative games: results from a population-based intervention to increase physical activity. JMIR Serious Games. 2016 Jan 28;4(1):e1. doi: 10.2196/games.5358. v4i1e1
    1. Mitchell MS, Goodman JM, Alter DA, John LK, Oh PI, Pakosh MT, Faulkner GE. Financial incentives for exercise adherence in adults: systematic review and meta-analysis. Am J Prev Med. 2013 Nov;45(5):658–67. doi: 10.1016/j.amepre.2013.06.017.S0749-3797(13)00436-4
    1. Angellotti E, Wong JB, Pierce A, Hescott B, Pittas AG. Combining Wireless Technology and Behavioral Economics to Engage Patients (WiBEEP) with cardiometabolic disease: a pilot study. Pilot Feasibility Stud. 2019 Jan 15;5(1):7. doi: 10.1186/s40814-019-0395-8. 395
    1. Chang LL, DeVore AD, Granger BB, Eapen ZJ, Ariely D, Hernandez AF. Leveraging behavioral economics to improve heart failure care and outcomes. Circulation. 2017 Aug 22;136(8):765–772. doi: 10.1161/circulationaha.117.028380.
    1. Malo TL, Hall ME, Brewer NT, Lathren CR, Gilkey MB. Why is announcement training more effective than conversation training for introducing HPV vaccination? A theory-based investigation. Implement Sci. 2018 Apr 19;13(1):57. doi: 10.1186/s13012-018-0743-8. 10.1186/s13012-018-0743-8
    1. Opel DJ, Taylor JA, Zhou C, Catz S, Myaing M, Mangione-Smith R. The relationship between parent attitudes about childhood vaccines survey scores and future child immunization status: a validation study. JAMA Pediatr. 2013 Nov 01;167(11):1065–71. doi: 10.1001/jamapediatrics.2013.2483. 1740762
    1. Taylor NK, Buttenheim AM. Improving utilization of and retention in PMTCT services: can behavioral economics help? BMC Health Serv Res. 2013 Oct 10;13(1):406. doi: 10.1186/1472-6963-13-406. 1472-6963-13-406
    1. Barth S, de Jong MD, Junger M. Lost in privacy? Online privacy from a cybersecurity expert perspective. Telemat Inform. 2022 Mar;68:101782. doi: 10.1016/j.tele.2022.101782.
    1. Camacho E, LoPresti M, Appelboom G, Dumont ELP, Taylor B, Connolly ES. The ubiquitous role of smartphones in mobile health. BBIJ. 2014 Sep 27;1(1):14–19. doi: 10.15406/bbij.2014.01.00004.
    1. Asch DA, Muller RW, Volpp KG. Automated hovering in health care — watching over the 5000 hours. N Engl J Med. 2012 Jul 05;367(1):1–3. doi: 10.1056/nejmp1203869.
    1. Skrabal Ross X, Gunn KM, Suppiah V, Patterson P, Olver I. A review of factors influencing non-adherence to oral antineoplastic drugs. Support Care Cancer. 2020 Sep 25;28(9):4043–4050. doi: 10.1007/s00520-020-05469-y.10.1007/s00520-020-05469-y
    1. Unni E, Sternbach N, Goren A. Using the Medication Adherence Reasons Scale (MAR-Scale) to identify the reasons for non-adherence across multiple disease conditions. PPA. 2019 Jun;Volume 13:993–1004. doi: 10.2147/ppa.s205359.
    1. Duncan S, Annunziato RA, Dunphy C, LaPointe Rudow D, Shneider BL, Shemesh E. A systematic review of immunosuppressant adherence interventions in transplant recipients: Decoding the streetlight effect. Pediatr Transplant. 2018 Feb 07;22(1):e13086. doi: 10.1111/petr.13086.
    1. Alwashmi MF, Hawboldt J, Davis E, Fetters MD. The iterative convergent design for mobile health usability testing: mixed methods approach. JMIR Mhealth Uhealth. 2019 Apr 26;7(4):e11656. doi: 10.2196/11656.
    1. Fedele DA, Cushing CC, Fritz A, Amaro CM, Ortega A. Mobile health interventions for improving health outcomes in youth: a meta-analysis. JAMA Pediatr. 2017 May 01;171(5):461–469. doi: 10.1001/jamapediatrics.2017.0042. 2611946
    1. Hommel KA, Davis CM, Baldassano RN. Objective versus subjective assessment of oral medication adherence in pediatric inflammatory bowel disease. Inflamm Bowel Dis. 2009 Apr;15(4):589–93. doi: 10.1002/ibd.20798.
    1. Quittner AL, Modi AC, Lemanek KL, Ievers-Landis CE, Rapoff MA. Evidence-based assessment of adherence to medical treatments in pediatric psychology. J Pediatr Psychol. 2008 Oct 18;33(9):916–36; discussion 937. doi: 10.1093/jpepsy/jsm064. jsm064
    1. Ingerski LM, Hente EA, Modi AC, Hommel KA. Electronic measurement of medication adherence in pediatric chronic illness: a review of measures. J Pediatr. 2011 Oct;159(4):528–34. doi: 10.1016/j.jpeds.2011.05.018. S0022-3476(11)00496-3
    1. Lewis JR, Sauro J, editors. The Factor Structure of the System Usability Scale. Berlin, Heidelberg: Springer; 2009.
    1. Bangor A, Kortum PT, Miller JT. An empirical evaluation of the system usability scale. International Journal of Human-Computer Interaction. 2008 Jul 30;24(6):574–594. doi: 10.1080/10447310802205776.
    1. Shemesh E, Bucuvalas JC, Anand R, Mazariegos GV, Alonso EM, Venick RS, Reyes-Mugica M, Annunziato RA, Shneider BL. The Medication Level Variability Index (MLVI) predicts poor liver transplant outcomes: a prospective multi-site study. Am J Transplant. 2017 Oct 22;17(10):2668–2678. doi: 10.1111/ajt.14276. doi: 10.1111/ajt.14276.

Source: PubMed

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