A Web-Based Data Collection Platform for Multisite Randomized Behavioral Intervention Trials: Development, Key Software Features, and Results of a User Survey

Riddhi A Modi, Michael J Mugavero, Rivet K Amico, Jeanne Keruly, Evelyn Byrd Quinlivan, Heidi M Crane, Alfredo Guzman, Anne Zinski, Solange Montue, Katya Roytburd, Anna Church, James H Willig, Riddhi A Modi, Michael J Mugavero, Rivet K Amico, Jeanne Keruly, Evelyn Byrd Quinlivan, Heidi M Crane, Alfredo Guzman, Anne Zinski, Solange Montue, Katya Roytburd, Anna Church, James H Willig

Abstract

Background: Meticulous tracking of study data must begin early in the study recruitment phase and must account for regulatory compliance, minimize missing data, and provide high information integrity and/or reduction of errors. In behavioral intervention trials, participants typically complete several study procedures at different time points. Among HIV-infected patients, behavioral interventions can favorably affect health outcomes. In order to empower newly diagnosed HIV positive individuals to learn skills to enhance retention in HIV care, we developed the behavioral health intervention Integrating ENGagement and Adherence Goals upon Entry (iENGAGE) funded by the National Institute of Allergy and Infectious Diseases (NIAID), where we deployed an in-clinic behavioral health intervention in 4 urban HIV outpatient clinics in the United States. To scale our intervention strategy homogenously across sites, we developed software that would function as a behavioral sciences research platform.

Objective: This manuscript aimed to: (1) describe the design and implementation of a Web-based software application to facilitate deployment of a multisite behavioral science intervention; and (2) report on results of a survey to capture end-user perspectives of the impact of this platform on the conduct of a behavioral intervention trial.

Methods: In order to support the implementation of the NIAID-funded trial iENGAGE, we developed software to deploy a 4-site behavioral intervention for new clinic patients with HIV/AIDS. We integrated the study coordinator into the informatics team to participate in the software development process. Here, we report the key software features and the results of the 25-item survey to evaluate user perspectives on research and intervention activities specific to the iENGAGE trial (N=13).

Results: The key features addressed are study enrollment, participant randomization, real-time data collection, facilitation of longitudinal workflow, reporting, and reusability. We found 100% user agreement (13/13) that participation in the database design and/or testing phase made it easier to understand user roles and responsibilities and recommended participation of research teams in developing databases for future studies. Users acknowledged ease of use, color flags, longitudinal work flow, and data storage in one location as the most useful features of the software platform and issues related to saving participant forms, security restrictions, and worklist layout as least useful features.

Conclusions: The successful development of the iENGAGE behavioral science research platform validated an approach of early and continuous involvement of the study team in design development. In addition, we recommend post-hoc collection of data from users as this led to important insights on how to enhance future software and inform standard clinical practices.

Trial registration: Clinicaltrials.gov NCT01900236; (https://ichgcp.net/clinical-trials-registry/NCT01900236 (Archived by WebCite at http://www.webcitation.org/6qAa8ld7v).

Keywords: HIV; Web application; behavioral research; iENGAGE; software design; survey; user perspective.

Conflict of interest statement

Conflicts of Interest: JHW has received research support from the Bristol-Myers Squibb Virology Fellows Research Program for the 2006 to 2008 academic years, Pfizer, Tibotec Therapeutics, and Definicare, and has consulted for Bristol-Myers Squibb and Gilead Sciences. AOW has received research support from Definicare. GAB has received research support from the Bristol-Myers Squibb Virology Fellows Research Training Program for the 2010 to 2012 academic years. MJM has received support from Bristol-Myers Squibb and personal fees from Gilead Sciences, Jansen Therapeutics, and Bristol-Myers Squibb, unrelated to the submitted work.

©Riddhi A Modi, Michael J Mugavero, Rivet K Amico, Jeanne Keruly, Evelyn Byrd Quinlivan, Heidi M Crane, Alfredo Guzman, Anne Zinski, Solange Montue, Katya Roytburd, Anna Church, James H Willig. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 16.06.2017.

Figures

Figure 1
Figure 1
Patient registration.
Figure 2
Figure 2
Worklist.

References

    1. Krishnankutty B, Bellary S, Kumar NB, Moodahadu LS. Data management in clinical research: an overview. Indian J Pharmacol. 2012 Mar;44(2):168–72. doi: 10.4103/0253-7613.93842.
    1. Zheng H, Rosal MC, Oatis CA, Li W, Franklin PD. Tailored system to deliver behavioral intervention and manage data in randomized trials. J Med Internet Res. 2013 Apr 11;15(4):e58. doi: 10.2196/jmir.2375.
    1. Dunbar J, McKeown MB. Organization and management of recruitment. Circulation. 1982 Dec;66(6 Pt 2):IV49–53.
    1. Toddenroth D, Sivagnanasundaram J, Prokosch H, Ganslandt T. Concept and implementation of a study dashboard module for a continuous monitoring of trial recruitment and documentation. J Biomed Inform. 2016 Dec;64:222–231. doi: 10.1016/j.jbi.2016.10.010.
    1. Campbell MK, Snowdon C, Francis D, Elbourne D, McDonald AM, Knight R, Entwistle V, Garcia J, Roberts I, Grant A, Grant A. Recruitment to randomised trials: strategies for trial enrollment and participation study. The STEPS study. Health Technol Assess. 2007 Nov;11(48):iii, ix–105.
    1. Gardner LI, Marks G, Craw JA, Wilson TE, Drainoni M, Moore RD, Mugavero MJ, Rodriguez AE, Bradley-Springer LA, Holman S, Keruly JC, Sullivan M, Skolnik PR, Malitz F, Metsch LR, Raper JL, Giordano TP, Retention in Care Study Group A low-effort, clinic-wide intervention improves attendance for HIV primary care. Clin Infect Dis. 2012 Oct;55(8):1124–34. doi: 10.1093/cid/cis623.
    1. Mugavero MJ, Lin H, Willig JH, Westfall AO, Ulett KB, Routman JS, Abroms S, Raper JL, Saag MS, Allison JJ. Missed visits and mortality among patients establishing initial outpatient HIV treatment. Clin Infect Dis. 2009 Jan 15;48(2):248–56. doi: 10.1086/595705.
    1. Cohen MS, Chen YQ, McCauley M, Gamble T, Hosseinipour MC, Kumarasamy N, Hakim JG, Kumwenda J, Grinsztejn B, Pilotto JH, Godbole SV, Mehendale S, Chariyalertsak S, Santos BR, Mayer KH, Hoffman IF, Eshleman SH, Piwowar-Manning E, Wang L, Makhema J, Mills LA, de BG, Sanne I, Eron J, Gallant J, Havlir D, Swindells S, Ribaudo H, Elharrar V, Burns D, Taha TE, Nielsen-Saines K, Celentano D, Essex M, Fleming TR, HPTN 052 Study Team Prevention of HIV-1 infection with early antiretroviral therapy. N Engl J Med. 2011 Aug 11;365(6):493–505. doi: 10.1056/NEJMoa1105243.
    1. Mugavero MJ, Amico KR, Westfall AO, Crane HM, Zinski A, Willig JH, Dombrowski JC, Norton WE, Raper JL, Kitahata MM, Saag MS. Early retention in HIV care and viral load suppression: implications for a test and treat approach to HIV prevention. J Acquir Immune Defic Syndr. 2012 Jan 01;59(1):86–93. doi: 10.1097/QAI.0b013e318236f7d2.
    1. Bruno V, Tam A, Thom J. Characteristics of web applications that affect usability: a review. Proceedings of the 17th Australia Conference on Computer-Human Interaction: Citizens Online: Considerations for Today and the Future; 2005 Nov 23-25; Canberra, Australia. 2005.
    1. Deshpande Y, Murugesan S, Ginige A, Hansen S, Schwabe D, Gaedke M. Web engineering. J Web Eng. 2002;1:003–017.
    1. Efird J. Blocked randomization with randomly selected block sizes. Int J Environ Res Public Health. 2011 Jan;8(1):15–20. doi: 10.3390/ijerph8010015.
    1. Aladwani AM, Palvia PC. Developing and validating an instrument for measuring user-perceived web quality. Inform Manage. 2002 May;39(6):467–476. doi: 10.1016/S0378-7206(01)00113-6.
    1. Cross SS, Palmer IR, Stephenson TJ. How to design and use a research database. Diagn Histopathol. 2009 Oct;15(10):490–495. doi: 10.1016/j.mpdhp.2009.07.003.
    1. Rosa C, Campbell AN, Miele GM, Brunner M, Winstanley EL. Using e-technologies in clinical trials. Contemp Clin Trials. 2015 Nov;45(Pt A):41–54. doi: 10.1016/j.cct.2015.07.007.

Source: PubMed

Próximos ensaios clínicos

Se inscrever