Design framework for the development of tailored behavior change technologies
Authors: 
Florian Debackere, Céline Clavel, Alexandra Roren, Viet-Thi Tran, Yosra Messai, François Rannou, Christelle Nguyen, Jean-Caude MartinAuthors Info & Claims
Florian Debackere, Céline Clavel, Alexandra Roren, Viet-Thi Tran, Yosra Messai, François Rannou, Christelle Nguyen, Jean-Caude MartinAuthors Info & ClaimsPages 140 - 146
Abstract
Today, so-called persuasive or motivational technologies are developing, which refer to technologies, applications or services designed to induce changes in attitudes and behavior in those who use them. This is the subject of research in Human-Computer Interaction in connection with theories from psychology related, for example, to behavior change or motivation. Research on these technologies suggests that in order to encourage long-term adherence, these "virtual coaches" need to be personalized and/or tailored according to the individual characteristics of the users (stage of behavior change, motivations, preferences, barriers). For example, according to the Self-Determination Theory (SDT), an individual can present different forms of motivation, more or less effective. The idea is to be able to identify the forms of motivation present in users in order to propose services to reinforce or develop them. The use of such systems in the field of health has the potential to induce and reinforce health behaviors that are sometimes difficult to establish by health professionals. Providing daily, personalized care represents a considerable human and financial cost for health professionals. A mobile application has the advantage of being able to deal with these constraints. The computer coach is designed with and for patients suffering from chronic low back pain. The aim is to help them manage their condition, particularly with regard to their pain and the practice of regular physical activity. The work presented presents an innovative design approach, combining user-centered methodologies and psychological theories, which we detail through a research phase and a design phase. Currently, a first version of the application has been developed and is being tested.
References
[1]
S. Michie, L. Yardley, R. West, K. Patrick, et F. Greaves, « Developing and Evaluating Digital Interventions to Promote Behavior Change in Health and Health Care: Recommendations Resulting From an International Workshop », J Med Internet Res, vol. 19, no 6, Art. no 6, juin 2017.
[2]
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
[3]
J. Masthoff et J. Vassileva, « Tutorial on Personalization for Behaviour Change », in Proceedings of the 20th International Conference on Intelligent User Interfaces, Atlanta Georgia USA, mars 2015, p. 439‑442.
[4]
B. J. Fogg, B. J. (Stanford U. F. U.S.A.) Stanford CA, G. E. Fogg, et P. G. Zimbardo, Persuasive Technology: Using Computers to Change What We Think and Do. Morgan Kaufmann, 2003.
[5]
H. Oinas-Kukkonen, « A foundation for the study of behavior change support systems », Pers Ubiquit Comput, vol. 17, no 6, Art. no 6, août 2013.
[6]
H. Oinas-Kukkonen et M. Harjumaa, « Persuasive Systems Design: Key Issues, Process Model, and System Features », CAIS, vol. 24, 2009.
[7]
Michie, S., Richardson, M., Johnston, M., Abraham, C., Francis, J., Hardeman, W., Eccles, M. P., Cane, J., & Wood, C. E. (2013). 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 : a publication of the Society of Behavioral Medicine, 46(1), 81–95. https://doi.org/10.1007/s12160-013-9486-6
[8]
Mirsch, T.; Lehrer, C.; Jung, R. (2017): Digital Nudging: Altering User Behavior in Digital Environments, in Leimeister, J.M.; Brenner, W. (Hrsg.): Proceedings der 13. Internationalen Tagung Wirtschaftsinformatik (WI 2017), St. Gallen, S. 634-648
[9]
AlMarshedi, A., Wanick, V., Wills, G. B., & Ranchhod, A. (2017). Gamification and Behaviour. In S. Stieglitz, C. Lattemann, S. Robra-Bissantz, R. Zarnekow, & T. Brockmann (Éds.), Gamification: Using Game Elements in Serious Contexts (p. 19–29). Springer International Publishing. https://doi.org/10.1007/978-3-319-45557-0_2
[10]
Berdichevsky, D., & Neuenschwander, E. (1999). Toward an Ethics of Persuasive Technology. Commun. ACM, 42(5), 51-58. https://doi.org/10.1145/301353.301410
[11]
Smids, J. (2012). The Voluntariness of Persuasive Technology. In: Bang, M., Ragnemalm, E.L. (eds) Persuasive Technology. Design for Health and Safety. PERSUASIVE 2012. Lecture Notes in Computer Science, vol 7284. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31037-9_11
[12]
Atkinson, B.M.C. (2006). Captology: A Critical Review. In: IJsselsteijn, W.A., de Kort, Y.A.W., Midden, C., Eggen, B., van den Hoven, E. (eds) Persuasive Technology. PERSUASIVE 2006. Lecture Notes in Computer Science, vol 3962. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11755494_25
[13]
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
[14]
L. Whitehead et P. Seaton, « The Effectiveness of Self-Management Mobile Phone and Tablet Apps in Long-term Condition Management: A Systematic Review », Journal of Medical Internet Research, vol. 18, no 5, Art. no 5, mai 2016.
[15]
J. Bort-Roig, N. D. Gilson, A. Puig-Ribera, R. S. Contreras, et S. G. Trost, « Measuring and Influencing Physical Activity with Smartphone Technology: A Systematic Review », Sports Med, vol. 44, no 5, Art. no 5, mai 2014.
[16]
S. Du, W. Liu, S. Cai, Y. Hu, et J. Dong, « The efficacy of e-health in the self-management of chronic low back pain: A meta analysis », International Journal of Nursing Studies, vol. 106, p. 103507, juin 2020.
[17]
L. F. Sandal, « Effectiveness of App-Delivered, Tailored Self-management Support for Adults With Lower Back Pain–Related Disability: A selfBACK Randomized Clinical Trial », JAMA Internal Medicine, vol. 181, no 10, Art. no 10, oct. 2021.
[18]
A. B. Irvine, « Mobile-Web App to Self-Manage Low Back Pain: Randomized Controlled Trial », J Med Internet Res, vol. 17, no 1, Art. no 1, janv. 2015.
[19]
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
[20]
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
[21]
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
[22]
Deci, E. L., & Ryan, R. M. (1985). Intrinsic motivation and self- determination in human behavior. New York: Plenum Press.
[23]
Ryan, R.M., & Deci, E.L. (2000). Intrinsic and extrinsic motivations: classic definitions and new directions. Contemporary Educational Psychology,25,54-67.
[24]
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
[25]
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
[26]
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
[27]
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
[28]
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.
[29]
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
[30]
R. Schwarzer, « Health Action Process Approach (HAPA) as a Theoretical Framework to Understand Behavior Change », Actualidades en Psicología, vol. 30, no 121, Art. no 121, déc. 2016.
[31]
L. Boutevillain, A. Dupeyron, C. Rouch, E. Richard, et E. Coudeyre, « Facilitators and barriers to physical activity in people with chronic low back pain: A qualitative study », PLoS ONE, vol. 12, no 7, Art. no 7, juill. 2017.
[32]
J. Saner, E. M. Bergman, R. A. de Bie, et J. M. Sieben, « Low back pain patients’ perspectives on long-term adherence to home-based exercise programmes in physiotherapy », Musculoskeletal Science and Practice, vol. 38, p. 77‑82, déc. 2018.
[33]
K. Oyibo, I. Adaji, R. Orji, J. Ham, et J. Vassileva, « Adaptive and Personalized Persuasive Technologies », in Adjunct Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization, Utrecht Netherlands, juin 2021, p. 255‑256.
[34]
N. Aldenaini, F. Alqahtani, R. Orji, et S. Sampalli, « Trends in Persuasive Technologies for Physical Activity and Sedentary Behavior: A Systematic Review », Front. Artif. Intell., vol. 3, p. 7, avr. 2020.
[35]
B. A. Kamphorst, « E-coaching systems », Pers Ubiquit Comput, vol. 21, no 4, Art. no 4, août 2017.
[36]
H. op den Akker, V. M. Jones, et H. J. Hermens, « Tailoring real-time physical activity coaching systems: a literature survey and model », User Model User-Adap Inter, vol. 24, no 5, p. 351‑392, déc. 2014.
[37]
F. Monteiro-Guerra, O. Rivera-Romero, L. Fernandez-Luque, et B. Caulfield, « Personalization in Real-Time Physical Activity Coaching Using Mobile Applications: A Scoping Review », IEEE Journal of Biomedical and Health Informatics, vol. 24, no 6, Art. no 6, juin 2020.
[38]
Debackere, F., Clavel, C., Roren, A., Tran, V., Snoubra, G., Messai, Y., Rannou, F., Nguyen, C., & Martin, J. (2022). Profiling of low back pain patients for the design of a tailored coaching application. 2022 10th International Conference on Affective Computing and Intelligent Interaction (ACII), 1‑8. https://doi.org/10.1109/ACII55700.2022.9953873
[39]
T. Dekkers, « Data-driven Patient Profiles: Definition, validation, and implementation for tailored orthopaedic healthcare services », Delft University of Technology, 2020.
[40]
B. Groeneveld, M. Melles, S. Vehmeijer, N. Mathijssen, L. van Dijk, et R. Goossens, « Tailored patient experiences: IEA 2018: 20th Congress of the International Ergonomics Association », Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018) - Volume I, vol. 1, p. 198‑207, 2018.
[41]
C. K. J. Wang et S. J. H. Biddle, « Young People's Motivational Profiles in Physical Activity: A Cluster Analysis », Journal of Sport and Exercise Psychology, vol. 23, no 1, Art. no 1, mars 2001.
[42]
H. Matsumoto et K. Takenaka, « Motivational Profiles and Stages of Exercise Behavior Change », International Journal of Sport and Health Science, vol. 2, p. 89‑96, 2004.
[43]
A. Lacasse, P. Bourgault, Y. Tousignant-Laflamme, R. Courtemanche-Harel, et M. Choinière, « Development and Validation of the French-Canadian Chronic Pain Self-Efficacy Scale », Pain Research and Management, vol. 20, no 2, Art. no 2, 2015.
[44]
K. Kroenke, R. L. Spitzer, et J. B. W. Williams, « The PHQ-9: Validity of a brief depression severity measure », J Gen Intern Med, vol. 16, no 9, Art. no 9, sept. 2001.
[45]
J. Boiché, M. Gourlan, D. Trouilloud, et P. Sarrazin, « Development and validation of the ‘Echelle de Motivation envers l'Activité Physique en contexte de Santé’: A motivation scale towards health-oriented physical activity in French », J Health Psychol, vol. 24, no 3, Art. no 3, mars 2019.
[46]
G. Waddell, M. Newton, I. Henderson, D. Somerville, et C. J. Main, « A Fear-Avoidance Beliefs Questionnaire (FABQ) and the role of fear-avoidance beliefs in chronic low back pain and disability », Pain, vol. 52, no 2, Art. no 2, févr. 1993.
[47]
Jane. Clatworthy, Deanna. Buick, Matthew. Hankins, John. Weinman, et Robert. Horne, « The use and reporting of cluster analysis in health psychology: A review », British Journal of Health Psychology, vol. 10, no 3, Art. no 3, sept. 2005.
[48]
L. Breiman, J. Friedman, C. J. Stone, et R. A. Olshen, Classification and Regression Trees. Taylor & Francis, 1984.
[49]
B. Groeneveld, M. Melles, S. Vehmeijer, N. Mathijssen, T. Dekkers, et R. Goossens, « Developing digital applications for tailored communication in orthopaedics using a Research through Design approach », DIGITAL HEALTH, vol. 5, p. 205520761882491, janv. 2019.
[50]
Lagger, G., Pataky, Z., & Golay, A. (2010). Efficacy of therapeutic patient education in chronic diseases and obesity. Patient Education and Counseling, 79(3), 283-286. https://doi.org/10.1016/j.pec.2010.03.015
[51]
S. Rozenberg, V. Foltz, et B. Fautrel, « Treatment strategy for chronic low back pain », Joint Bone Spine, vol. 79, no 6, Art. no 6, déc. 2012.
[52]
W. R. Marchand, « Mindfulness-Based Stress Reduction, Mindfulness-Based Cognitive Therapy, and Zen Meditation for Depression, Anxiety, Pain, and Psychological Distress », Journal of Psychiatric Practice, vol. 18, no 4, Art. no 4, juill. 2012.
[53]
C. Williamson, G. Baker, N. Mutrie, A. Niven, et P. Kelly, « Get the message? A scoping review of physical activity messaging », Int J Behav Nutr Phys Act, vol. 17, no 1, Art. no 1, déc. 2020.
[54]
D. Markland et D. K. Ingledew, « The measurement of exercise motives: Factorial validity and invariance across gender of a revised Exercise Motivations Inventory », British Journal of Health Psychology, vol. 2, no 4, Art. no 4, nov. 1997.
Recommendations
Beyond Behavior: The Coach's Perspective on Technology in Health Coaching
CHI '19: Proceedings of the 2019 CHI Conference on Human Factors in Computing SystemsRapid innovations in electronic healthcare and behavior tracking systems are challenging health coaches (dietitians, personal trainers, etc.) to rethink their traditional roles and healthcare practices. At the same time, many current e-coaching systems ...
Exploring the Effect of mHealth Technologies on Communication and Information Sharing in a Pediatric Critical Care Unit: A Case Study
Communication and information sharing is an important aspect of healthcare information technology and mHealth management. A main requirement in the quality of patient care is the ability of all health care participants to communicate. Research ...
Development of a cognitive framework of patient record summary review in the formative phase of user-centered design
Display Omitted We developed a cognitive framework and prototype to review a summary of a patient record.Open card sorting, walkthrough think aloud and in-person interviews were performed.Clinicians focused on an anchor point then intermediate history ...
Comments
Information & Contributors
Information
Published In
June 2023
446 pages
ISBN:9781450398916
DOI:10.1145/3563359
Copyright © 2023 ACM.
Publication rights licensed to ACM. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of a national government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.
Sponsors
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 16 June 2023
Check for updates
Author Tags
Qualifiers
- Research-article
- Research
- Refereed limited
Funding Sources
- Fondation Arthritis
- Société Française de Rhumatologie
- Association Malakoff Médéric
Conference
UMAP '23: 31st ACM Conference on User Modeling, Adaptation and Personalization
June 26 - 29, 2023
Limassol, Cyprus
Acceptance Rates
Overall Acceptance Rate 162 of 633 submissions, 26%
Upcoming Conference
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 194Total Downloads
- Downloads (Last 12 months)77
- Downloads (Last 6 weeks)10
Reflects downloads up to 03 Mar 2025
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign inFull Access
View options
View or Download as a PDF file.
PDFeReader
View online with eReader.
eReaderHTML Format
View this article in HTML Format.
HTML Format