Démarche de conception participative d'une application mobile motivationnelle pour l'autogestion de la lombalgie chronique: Co-design process of a motivational mobile application for the self-management of chronic low back pain
Article No.: 15, Pages 1 - 17
Abstract
The market for mobile health applications is growing rapidly, but few of these applications are based on evidence-based guidelines. In the case of chronic low back pain, some studies have attempted to identify user needs in order to propose recommendations for the design of digital interventions. However, the specification of human-machine interactions adapted to these needs is poorly described. In this study, we propose a participatory design approach for the design of a mobile application to support self-management of low back pain. We present the results of qualitative and quantitative methods to identify patients' needs and specify the associated human-machine interactions. Then we present the results of workshops conducted with patients in order to validate the human-machine interactions adapted to the previously identified needs. Finally, we propose several recommendations for the design of a mobile application for self-management of chronic low back pain.
References
[1]
James SL, Abate D, Abate KH, Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet 2018;392:1789-858. 10.1016/S0140-6736(18)32279-7
[2]
Gatchel, R. J., Peng, Y. B., Peters, M. L., Fuchs, P. N., & Turk, D. C. (2007). The biopsychosocial approach to chronic pain: scientific advances and future directions. Psychological bulletin, 133(4), 581–624.
[3]
Wong, A.Y., Karppinen, J. & Samartzis, D. Low back pain in older adults: risk factors, management options and future directions. Scoliosis 12, 14 (2017).
[4]
Michie S, Yardley L, West R, Patrick K, Greaves F. (2017). Developing and Evaluating Digital Interventions to Promote Behavior Change in Health and Health Care: Recommendations Resulting From an International Workshop. J Med Internet Res 2017;19(6):e232.
[5]
Whitehead L., Seaton P. (2016). The Effectiveness of Self-Management Mobile Review. J Med Internet Res 2016;18(5):e97. URL: https://www.jmir.org/2016/5/e97.
[6]
Du, S., Liu, W., Cai, S., Hu, Y., & Dong, J. (2020). The efficacy of e-health in the self-management of chronic low back pain : A meta analysis. International Journal of Nursing Studies, 106, 103507.
[7]
Irvine, A. B., Russell, H., Manocchia, M., Mino, D. E., Cox Glassen, T., Morgan, R., Gau, J. M., Birney, A. J., & Ary, D. V. (2015). Mobile-Web App to Self-Manage Low Back Pain : Randomized Controlled Trial. Journal of Medical Internet Research, 17(1), e1. https://doi.org/10.2196/jmir.3130
[8]
Lalloo, C., Jibb, L. A., Rivera, J., Agarwal, A., & Stinson, J. N. (2015). “There's a Pain App for That” : Review of Patient-targeted Smartphone Applications for Pain Management. The Clinical Journal of Pain, 31(6), 557-563. https://doi.org/10.1097/AJP.0000000000000171
[9]
Oyebode, O., Ndulue, C., Alhasani, M., & Orji, R. (2020). Persuasive Mobile Apps for Health and Wellness: A Comparative Systematic Review. PERSUASIVE. 10.1007/978-3-030-45712-9_13
[10]
Jonasen T., Midden C. (eds) Persuasive Technology. Designing for Future Change. PERSUASIVE 2020. Lecture Notes in Computer Science,
[11]
Machado, G. C., Pinheiro, M. B., Lee, H., Ahmed, O. H., Hendrick, P., Williams, C., & Kamper, S. J. (2016). Smartphone apps for the self-management of low back pain: A systematic review. Best Practice & Research Clinical Rheumatology, 30(6), 1098‑1109. https://doi.org/10.1016/j.berh.2017.04.002
[12]
Fogg, B.J. (2003). Persuasive Technology. Using Computers to Change What We Think and Do (1er édition, A volume In Interactive Technologies). Morgan Kaufmann. https://doi.org/10.1016/B978-1-55860-643-2.X5000-8
[13]
Oinas-Kukkonen, Harri & Harjumaa, Marja. (2009). Persuasive Systems Design: Key Issues, Process Model, and System Features. Communications of the Association for Information Systems. 24. 10.17705/1CAIS.02428.
[14]
Oinas-Kukkonen, Harri. (2013). A foundation for the study of behavior change support systems. Personal and Ubiquitous Computing. 17. 10.1007/s00779-012-0591-5.
[15]
Michie, S., van Stralen, M.M. & West, R. The behaviour change wheel: A new method for characterising and designing behaviour change interventions. Implementation Sci 6, 42 (2011). https://doi.org/10.1186/1748-5908-6-42
[16]
Michie. S., Richardson, M., Johnston, M., Abraham, C., Francis, J., Hardeman, W., P. Eccles, M., Cane, J., E. Wood, C, The Behavior Change Technique Taxonomy (v1) of 93 Hierarchically Clustered Techniques: Building an International Consensus for the Reporting of Behavior Change Interventions, Annals of Behavioral Medicine, Volume 46, Issue 1, August 2013, Pages 81–95, https://doi.org/10.1007/s12160-013-9486-6
[17]
Peters, D., Calvo, R. A., & Ryan, R. M. (2018). Designing for Motivation, Engagement and Wellbeing in Digital Experience. Frontiers in Psychology, 9. https://doi.org/10.3389/fpsyg.2018.00797
[18]
Deci, E. L., & Ryan, R. M. (1985). Intrinsic motivation and self- determination in human behavior. New York: Plenum Press.
[19]
Ryan, R.M., & Deci, E.L. (2000). Intrinsic and extrinsic motivations: classic definitions and new directions. Contemporary Educational Psychology,25,54-67.
[20]
Saparamadu A, Fernando P, Zeng P, Teo H, Goh A, Lee J, Lam C. User-Centered Design Process of an mHealth App for Health Professionals: Case Study. JMIR Mhealth Uhealth 2021;9(3):e18079 URL: https://mhealth.jmir.org/2021/3/e18079
[21]
Kamphorst, B. A. (2017). E-coaching systems: What they are, and what they aren't. Personal and Ubiquitous Computing, 21(4), 625‑632. https://doi.org/10.1007/s00779-017-1020-6
[22]
Kramer, L. L., ter Stal, S., Mulder, B. C., de Vet, E., & van Velsen, L. (2019). Developing Embodied Conversational Agents for Coaching People towards a Healthy Lifestyle: A Scoping Review . Journal of Medical Internet Research. https://doi.org/10.2196/14058
[23]
Olafsson, S., Wallace, B., & Bickmore, T. (n.d.). Towards a Computational Framework for Automating Substance Use Counseling with Virtual Agents Towards a Computational Framework for Automating Substance Use Counseling with Virtual Agents. In Proc. of the 19th International Conference on Autonomous Agents and Multiagent Systems (AAMAS). Retrieved from www.ifaamas.org
[24]
Bickmore T, Trinh H, Olafsson S, O'Leary T, Asadi R, Rickles N, Cruz R. Patient and Consumer Safety Risks When Using Conversational Assistants for Medical Information: An Observational Study of Siri, Alexa, and Google Assistant. J Med Internet Res 2018;20(9):e11510 URL: https://www.jmir.org/2018/9/e11510
[25]
Lucas, G. M., Krämer, N., Peters, C., Taesch, L. S., Mell, J., & Gratch, J. (2018). Effects of perceived agency and message tone in responding to a virtual personal trainer. Proceedings of the 18th International Conference on Intelligent Virtual Agents, IVA 2018. https://doi.org/10.1145/3267851.3267855
[26]
Carter, D. D., Robinson, K., Forbes, J., & Hayes, S. (2018). Experiences of mobile health in promoting physical activity: A qualitative systematic review and meta-ethnography. PLOS ONE, 13(12), e0208759. https://doi.org/10.1371/journal.pone.0208759
[27]
Thurnheer, S. E., Gravestock, I., Pichierri, G., Steurer, J., & Burgstaller, J. M. (2018). Benefits of Mobile Apps in Pain Management: Systematic Review. JMIR MHealth and UHealth, 6(10), e11231. https://doi.org/10.2196/11231
[28]
Rintala A, Rantalainen R, Kaksonen A, Luomajoki H, Kauranen K. mHealth Apps for Low Back Pain Self-management: Scoping Review. JMIR Mhealth Uhealth 2022;10(8):e39682 36018713
[29]
Nicholl, B. I., Sandal, L. F., Stochkendahl, M. J., McCallum, M., Suresh, N., Vasseljen, O., Hartvigsen, J., Mork, P. J., Kjaer, P., Søgaard, K., & Mair, F. S. (2017). Digital Support Interventions for the Self-Management of Low Back Pain: A Systematic Review. Journal of Medical Internet Research, 19(5), e179. https://doi.org/10.2196/jmir.7290
[30]
Palazzo, C., Klinger, E., Dorner, V., Kadri, A., Thierry, O., Boumenir, Y., Martin, W., Poiraudeau, S., & Ville, I. (2016). Barriers to home-based exercise program adherence with chronic low back pain : Patient expectations regarding new technologies. Annals of Physical and Rehabilitation Medicine, 59(2), 107-113. https://doi.org/10.1016/j.rehab.2016.01.009
[31]
Van Weering, M. G. H. D.-, Vollenbroek-Hutten, M. M. R., & Hermens, H. J. (2012). Do Personalized Feedback Messages about Activity Patterns Stimulate Patients with Chronic Low Back Pain to Change their Activity Behavior on a Short Term Notice? Applied Psychophysiology and Biofeedback, 37(2), 81–89.
[32]
Grolier, M., Arefyev, A., Pereira, B., Tavares Figueiredo, I., Gerbaud, L., & Coudeyre, E. (2020). Refining the design of a smartphone application for people with chronic low back pain using mixed quantitative and qualitative approaches. Disability and Rehabilitation: Assistive Technology. https://doi.org/10.1080/17483107.2020.1839575
[33]
Garofoli, R., Boisson, M., Segretin, F., Linières, J., Gérard, C., Moreau, S., Nguyen, C. (2019, September 1). Feasibility of a short multidisciplinary education and exercise therapy program for patients with non-specific low back pain: A 3-month retrospective open pilot study. Annals of Physical and Rehabilitation Medicine. Elsevier Masson SAS. https://doi.org/10.1016/j.rehab.2019.05.005
[34]
Kallio, Hanna; Pietilä, Anna-Maija; Johnson, Martin; Kangasniemi, Mari (2016). Systematic methodological review: developing a framework for a qualitative semi-structured interview guide. Journal of Advanced Nursing, (), –. 87–98. https://doi.org/10.1145/244130.244151
[35]
Uchino, B. N. (2006). Social support and health: a review of physiological processes potentially underlying links to disease outcomes. Journal of behavioral medicine, 29:377–87.
[36]
Dionne CE, Dunn KM, Croft PR: Does back pain prevalence really decrease with increasing age? A systematic review. Age Ageing 2006, 35(3):229-234.
[37]
Gourmelen, J. & Chastang, J.-F & Ozguler, Anna & Lanoë, J.-L & Ravaud, Jean-François & Leclerc, A. (2007). Fréquence des lombalgies dans la population française de 30 à 64 ans. Résultats issus de deux enquêtes nationales. Annales de Réadaptation et de Médecine Physique. 50. 633-639. 10.1016/j.annrmp.2007.05.008.
[38]
Zhou, H., Stone, T., Hu, H., & Harris, N. (2008). Use of multiple wearable inertial sensors in upper limb motion tracking. Medical Engineering & Physics, 30(1), 123‑133. https://doi.org/10.1016/j.medengphy.2006.11.010
[39]
Allseits E, Kim KJ, Bennett C, Gailey R, Gaunaurd I, Agrawal V. A Novel Method for Estimating Knee Angle Using Two Leg-Mounted Gyroscopes for Continuous Monitoring with Mobile Health Devices. Sensors. 2018; 18(9):2759. https://doi.org/10.3390/s18092759
[40]
Deci, E. L., & Ryan, R. M. (2008). Self-determination theory: A macrotheory of human motivation, development, and health. Canadian Psychology / Psychologie canadienne, 49(3), 182–185. https://doi.org/10.1037/a0012801
[41]
Schwarzer, R. (2016). Health action process approach (HAPA) as a theoretical framework to understand behavior change. Actualidades en Psicología, 30(121), 119–130. https://doi.org/10.15517/ap.v30i121.23458
[42]
Rozenberg, S., Foltz, V., & Fautrel, B. (2012). Treatment strategy for chronic low back pain. Joint Bone Spine, 79(6), 555‑559. https://doi.org/10.1016/j.jbspin.2012.09.003
[43]
Hoy, D., Brooks, P., Blyth, F., & Buchbinder, R. (2010). The Epidemiology of low back pain. Best Practice & Research Clinical Rheumatology, 24(6), 769‑781. https://doi.org/10.1016/j.berh.2010.10.002
[44]
Bouzit, S., Calvary, G., Chêne, D., and Vanderdonckt., J. 2017. Polymodal Menus: A Model-based Approach for Designing Multimodal Adaptive Menus for Small Screens. Proc. ACM Hum.-Comput. Interact. 1, EICS, Article 15 (June 2017), 19 pages. https://doi.org/10.1145/3099585
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April 2023
288 pages
ISBN:9781450398244
DOI:10.1145/3583961
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Published: 29 May 2023
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IHM '23: 34th International Francophone Conference on Human-Computer Interaction
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