Challenges and opportunities of mobile data collection in clinical studies
Authors: 
Ekjyot Kaur, Pari Delir Haghighi, Frada Burstein, Donna Urquhart, Flavia CicuttiniAuthors Info & Claims
Pages 129 - 137
Abstract
The advancement in mobile technologies, especially smartphones, has brought a huge change to data collection methods in recent years. The ubiquity of smartphones makes them a useful tool for collecting data in real-time. Ecological Momentary Assessment (EMA) is an effective data collection method that involves repeated sampling of an individual's behavior, symptoms, and experiences in real-time in their natural environment, maximizing ecological validity. However, the burden that smartphone-based EMA imposes on individuals could result in high numbers of dropouts and limit its use in research and clinical practice. Investigating and identifying the reasons and factors that contribute to the individual's dropout could highly benefit the outcomes of EMA studies. This study applies the Model of Technology Appropriation (MTA) as a theoretical lens to explain the process of individual's appropriation of smartphones for the EMA data collection. We report the results of our user study on a group of volunteers.
References
[1]
Jennie Carroll., Steve Howard, Jane Peck, and John Murphy. 2002. A field study of perceptions and use of mobile telephones by 16 to 22 year olds. Journal of Information Technology Theory and Application 4, 2(2002), 49--61.
[2]
Jinhyuk Kim, David Marcusson-Clavertz, Kazuhiro Yoshiuchi and Joshua M. Smyth. 2019. Potential benefits of integrating ecological momentary assessment data into mHealth care systems. BioPsychoSocial medicine 13, 1(2019).
[3]
Arthur Stone, Saul Shiffman, Audie Atienza, Linda Nebeling. 2007. The science of real-time data capture: Self-reports in health research (1st edition). Oxford University Press.
[4]
Tian Y. Goh, Frada Burstein, Pari DelirHaghighi, Flavia Cicuttini and Donna M. Urquhart. Empirical study of user experience on mobile data collection for chronic low back pain. ACIS 2017 Proceedings, 2017. https://aisel.aisnet.org/acis2017/31
[5]
Timothy D. Noblet, John F. Marriott and Alison B. Rushton. 2019. Independent prescribing by advanced physiotherapists for patients with low back pain in primary care: protocol for a feasibility trial with an embedded qualitative component. BMJ open, 9(4).
[6]
Roni Evans, Mitchell Haas, Craig Schulz, Brent Leininger, Linda Hanson and Gert Bronfort. 2018. Spinal manipulation and exercise for low back pain in adolescents: a randomized trial. Pain 159, 7(2018), 1297--1307.
[7]
Jacqueline Mogle, Elizabeth Muhoz, Nikki L. Hill, Joshua M. Smyth and Martin J. Sliwinski. Daily memory lapses in adults: Characterization and influence on affect. The Journals of Gerontology: Series B: Psychological Sciences and Social Sciences 74, 1(2019), 59--68.
[8]
Dennis C. Turk and Ronald Melzack. 2011. Handbook of Pain Assessment (3rd. ed.). Guilford Press.
[9]
Saul Shiffman, Arthur A. Stone and Michael R. Hufford. 2008. Ecological momentary assessment. Annual Review of Clinical Psychology, 4 (2008), 1--32.
[10]
Arthur A. Stone and Joan E. Broderick. 2007. Real-time data collection for pain: Appraisal and current status. Pain Medicine 8, issue suppl_3(Oct. 2007), S85--S93.
[11]
Joan E. Broderick, Joseph E. Schwartz, Saul Shiffman, Michael Hufford and Arthur A. Stone. 2003. Signaling does not adequately improve diary compliance. Annals of Behavioral Medicine 26, 2(Oct. 2003), 139--148.
[12]
Fred D. Davis. 1989. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly 13, 3(1989), 319--340.
[13]
Viswanath Venkatesh, Michael G. Morris, Gordon B. Davis and Fred D. Davis. 2003. User acceptance of information technology: Toward a unified view. MIS Quarterly 27, 3(2003), 425--478.
[14]
Daniel W. Surry and John D. Farquhar. 1997. Diffusion theory and instructional technology. Journal of Instructional Science and Technology 2, 1(Feb. 1997), 24--36.
[15]
Icek Ajzen. 1991. The theory of planned behavior. Organizational behavior and human decision processes 50, 2(1991), 179--211.
[16]
Victoria L. Champion and Celette S. Skinner. 2008. The health belief model. Health behavior and health education: Theory, research, and practice, 4(2008), 45--65.
[17]
Arthur A. Stone and Saul Shiffman. 1994. Ecological momentary assessment (EMA) in behavorial medicine. Annals of Behavioral Medicine 16, 3(1994), 199--202.
[18]
Marcella May, Doerte U. Junghaenel, Masakatsu Ono, Arthur A. Stone and Stefan Schneider. 2018. Ecological momentary assessment methodology in chronic pain research: a systematic review. The Journal of Pain 19, 7(2018), 699--716.
[19]
Nitya Bakshi, Meagan E. Smith, Diana Ross and Lakshmanan Krishnamurti. 2017. Novel metrics in the longitudinal evaluation of pain data in sickle cell disease. Clinical Journal of Pain 33, 6(2017), 517--527.
[20]
Jeong-Wook Park, Min K. Chu, Jae-Moon Kim, Sang-Gue Park and Soo-Jin Cho. 2016. Analysis of trigger factors in episodic migraineurs using a smartphone headache diary applications. PLoS One 11, 2(2016).
[21]
Pamela Newland, Rebecca Lorenz, Florian Thomas and Mary Bordner. 2017. Initial evaluation of an electronic sleep/symptom diary for adults with multiple sclerosis. MEDSURG Nursing 26, 6(2017), 403--409.
[22]
Jennifer E. Graham-Engeland, Mathew J. Zawadzki, Danica C. Slavish and Joshua M. Smyth. 2016. Depressive symptoms and momentary mood predict momentary pain among rheumatoid arthritis patients. Annals of Behavioral Medicine 50, 1(2016), 12--23.
[23]
Andrèa A.G. Nes, Sandra van Dulmen, Rikard Wicksell, Egil A. Fors and Hilde Eide. 2017. Analyzing change processes resulting from a smartphone maintenance intervention based on acceptance and commitment therapy for women with chronic widespread pain. International Journal of Behavioral Medicine 24, 2(Apr. 2017), 215--229.
[24]
Mark D. Litt, David M. Shafer, Carlos R. Ibanez, Donald L. Kreutzer and Zeena Tawfik-Yonkers. 2009. Momentary pain and coping in temporomandibular disorder pain: Exploring mechanisms of cognitive behavioral treatment for chronic pain. Pain 145, 1-2(2009), 160--168.
[25]
David A. Williams, Michael Gendreau, Michael R. Hufford, Kimberly Groner, Richard H. Gracely and Daniel J. Clauw. 2005. Pain assessment in patients with fibromyalgia syndrome: a consideration of methods for clinical trials. The Clinical Journal of Pain 20, 5(2004), 348--356.
[26]
Alexandra Linnemann, Mattes B. Kappert, Susanne Fischer, Johanna M. Doerr, Jana Strahler and Urs M. Nater. 2015. The effects of music listening on pain and stress in the daily life of patients with fibromyalgia syndrome. Frontiers in Human Neuroscience, 9(July 2015).
[27]
Michael S. Christian, Noah Eisenkraft and Chaitali Kapadia. 2015. Dynamic associations among somatic complaints, human energy, and discretionary behaviors: Experiences with pain fluctuations at work. Administrative Science Quarterly 60, 1(2015), 66--102.
[28]
Jennie Carroll, Steve Howard, Jane Peck and John Murphy. 2003. From adoption to use: the process of appropriating a mobile phone. Australasian Journal of Information Systems 10, 2(2003).
[29]
Steve Baron, Anthony Patterson and Kim Harris. 2006. Beyond technology acceptance: understanding consumer practice. International Journal of Service Industry Management 17, 2(2006), 111--135.
[30]
Simon Snowden, John Spafford, Roula Michaelides and John Hopkins. 2006. Technology acceptance and m-commerce in an operational environment. Journal of Enterprise Information Management 19, 5(Sep. 2006), 525--539.
[31]
Jennie Carroll, Steve Howard, Frank Vetere, Jane Peck and John Murphy. 2001. Identity, power and fragmentation in cyberspace: technology appropriation by young people. In ACIS 2001 proceedings, 6(2001).
[32]
Jennie Carroll. 2004. Completing design in use: closing the appropriation cycle. In ECIS 2004 Proceedings, 44(2004).
[33]
Ken Peffers, Tuure Tuunanen, Marcus A. Rothenberger and Samir Chatterjee. 2014. A design science research methodology for information systems research. Journal of Management Information Systems 24, 3(2007), 45--77.
[34]
Rachelle Buchbinder, Maurits van Tulder, Birgitta Öberg, Lucíola M. Costa, Anthony Woolf, Mark Schoene, Peter Croft; Lancet Low Back Pain Series Working Group. 2018. Low back pain: a call for action. The Lancet 391, 10137(2018), 2384--2388.
[35]
Armin Wu, Lyn March, Xuanqi Zheng, Jinfeng Huang, Xiangyang Wang, Jie Zhao, Fiona M. Blyth, Emma Smith, Rachelle Buchbinder and Damian Hoy. 2017. Global low back pain prevalence and years lived with disability from 1990 to 2017: estimates from the Global Burden of Disease Study 2017. Annals of Translational Medicine 8, 6(2020).
[36]
Chris Maher, Martin Underwood and Rachelle Buchbinder. 2017. Non-specific low back pain. The Lancet 389, 10070(Feb. 2017), 736--747.
[37]
Martin Roland and Richard Morris. 1983. A study of the natural history of low-back pain. Part II: development of guidelines for trials of treatment in primary care. Spine 8, 2(1983), 145--150.
[38]
Julia M. Hush, Kathryn M. Refshauge, Gerard Sullivan, Lorraine De Souza and James H. McAuley. 2010. Do numerical rating scales and the Roland-Morris Disability Questionnaire capture changes that are meaningful to patients with persistent back pain? Clinical Rehabilitation 24, 7(2010), 648--657.
[39]
Jeff Sauro. 2011. Measuring usability with the system usability scale (SUS). (February 2011). Retrieved September 12, 2020 from https://measuringu.com/sus/
[40]
Dorotea Kovačević, Maja Brozović and Klementina Možina. 2016. Improving visual search in instruction manuals using pictograms. Ergonomics 59, 11(2016), 1405--1419.
[41]
Tim A. Majchrzak, Andreas Biørn-Hansen and Tor-Morten Grønli. 2017. Comprehensive analysis of innovative cross-platform app development frameworks. In Proceedings of the 50th Hawaii International Conference on System Sciences, 2017.
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Published In
November 2020
239 pages
ISBN:9781450389242
DOI:10.1145/3428690
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Published: 19 January 2021
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MoMM '20
MoMM '20: The 18th International Conference on Advances in Mobile Computing and Multimedia
November 30 - December 2, 2020
Chiang Mai, Thailand
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