- Sergio Felipe
- Aneesha Singh
- Caroline Bradley
- Amanda CdeC Williams
- Nadia Bianchi-Berthouze
Self-management of chronic pain is a complex and demanding activity. Multidisciplinary pain management programs are designed to provide patients with the skills to improve, maintain functioning and self-manage their pain but gains diminish in the long-term due to lack of support from clinicians. Sensing technology can be a cost-effective way to extend support for self-management outside clinical settings but they are currently under-explored. In this paper, we report studies carried out to investigate how Personal Informatics Systems (PIS) based on wearable body sensing technology could facilitate pain self-management and functioning. Five roles for PIS emerged from a qualitative study with people with chronic pain and physiotherapists: (i) assessment, planning and prevention (ii) a direct supervisory and co-management role, (iii) facilitating deeper understanding, (iv) managing emotional states, and (v) sharing for social acceptability. A web-based survey was conducted to understand the parameters that should be tracked to support self-management and what tracked information should be shared with others. Finally, we suggest an extension to previous PIS models and propose design implications to address immediate, short-term and long-term information needs for personal use of people with chronic pain and for sharing with others.
I. Li, A. Dey and J. Forlizzi, “A stage-based model of personal informatics systems”, Proc. 28th Int. Conf. Hum. factors Comput. Syst. – CHI ’10, pp. 557, 2010.
E. Thomaz, “A Human-centered conceptual model for personal health informatics data”, Pers. Inform. in the Wild: Hacking Habits for Health & Happiness – CHI 20 13 Workshop, 2013.
M. S. McDermott and A. E. While, “Maximizing the healthcare environment: a systematic review exploring the potential of computer technology to promote self-management of chronic illness in healthcare settings”, Patient Educ. Couns., Apr. 2013.
R. J. Gatchel, Y. B. Peng, M. L. Peters, P. N. Fuchs and D. C. Turk, “The biopsychosocial approach to chronic pain: scientific advances and future directions”, Psychol. Bull., vol. 133, no. 4, pp. 581-624, 2007.
G. Crombez, C. Eccleston, S. Van Damme, J. W. S. Vlaeyen and P. Karoly, “Fear-avoidance model of chronic pain”, Pain, vol. 28, no. 6, pp. 475-483, 2012.
I. Tracey and M. C. Bushnell, “How neuroimaging studies have challenged us to rethink: is chronic pain a disease?”, J. Pain, vol. 10, pp. 1113-1120, 2009.
A. Benjamin, J. Bimholtz, R. Baecker, D. Gromala and A. Furlan, “Impression management work”, Proc. of ACM 2012 Conf. Computer Supported Cooperative Work – CSCW ’12, pp. 799, 2012.
M. O. Martel, P. Thibault and M. J. L. Sullivan, “Judgments about pain intensity and pain genuineness: the role of pain behavior and judgmental heuristics”, J. Pain, vol. 12, no. 4, pp. 468-475, 2011.
A. Singh, A. Klapper, J. Jia, A. Fidalgo, A. Tajadura-Jimenez, N. Kanakam, et al., “Motivating people with chronic pain to do physical activity: opportunities for technology design”, CHI’ 14, pp. 2803-2812, 2014.
C. Harstall and M. Ospina, “How prevalent is chronic pain?”, Pain Clin. Updat., vol. XI, no. 2, pp. 7-9, 2003.
M. Geisser, M. Robinson, F. Keefe and M. Weiner, “Catastrophizing depression and the sensory affective and evaluative aspects of chronic pain”, Pain, vol. 59, pp. 79-83, 1994.
M. P. Jensen, J. A Turner and J. M. Romano, “Changes after multidisciplinary pain treatment in patient pain beliefs and coping are associated with concurrent changes in patient functioning”, Pain, vol. 131, no. 1–2, pp. 38-47, Sep. 2007.
L. Ruehlman, P. Karoly and C. Enders, “A randomized controlled evaluation of an online chronic pain self management program”, Pain, vol. 153, no. 2, pp. 319-330, 2012.
M. J. L. Sullivan and W. D. Stanish, “Psychologically based occupational rehabilitation: the pain-disability prevention program”, Clin. J. Pain, vol. 19, no. 2, pp. 97-104, 2003.
V. Harding and A. Williams, “Extending physiotherapy skills using a psychological approach: cognitive-behavioural management of chronic pain”, Physiotherapy, vol. 81, no. 11, pp. 681-688, Nov. 1995.
J. L. Bender, A. Radhakrishnan, C. Diorio, M. Englesakis and A. R. Jadad, “Can pain be managed through the internet? a systematic review of randomized controlled trials”, Pain, vol. 152, no. 8, pp. 1740-50, 2011.
O. B. Kristjánsdóttir, E. A Fors, E. Eide, A. Finset, T. L. Stensrud, S. Van Dulmen, et al., “A smartphone-based intervention with diaries and therapist-feedback to reduce catastrophizing and increase functioning in women with chronic widespread pain: randomized controlled trial”, J. Med. Internet Res., vol. 15, no. 1, Jan 2013.
C. Rini, D. Williams, J. Broderick and F. Keefe, “Meeting them where they are: using the internet to deliver behavioral medicine interventions for pain”, Behav. Med., vol. 2, no. 1, pp. 82-92, 2012.
Y. Huang, H. Zheng, C. Nugent, P. McCullagh, N. Black, K. E. Vowles, et al., “Feature selection and classification in supporting report-based self-management for people with chronic pain”, IEEE Trans. Inf. Technol. Biomed., vol. 15, no. 1, pp. 54-61, Jan. 2011.
N. Pombo, P. Araújo and J. Viana, “Contribution of Web Services to Improve Pain Diaries Experience”, Proc. Int. MultiConf. Eng. Comp. Scient., vol. I, pp. 14-17, 2012.
H. MacLeod, A. Tang and S. Carpendale, “Personal Informatics in Chronic Illness Management”, Graph. Interf, pp. 149-156, 2013.
F. Spyridonis, J. Hansen, T.-M. Granli and G. Ghinea, “PainDroid: an android-based virtual reality application for pain assessment”, Multimed. Tools Appl., Jan. 2013.
J. E. Bardram, M. Frost, K. Szántó, M. Faurholt-Jepsen, M. Vinberg and L. V. Kessing, “Designing mobile health technology for bipolar disorder:a field trial of the monarca system”, Proc. SIGCHI Conf. on Human Factors in Compo Systems, pp. 2627-2636, 2013.
B. A. Rosser, K. E. Vowles, E. Keogh, C. Eccleston and G. A. Mountain, “Technologically-assisted behaviour change: a systematic review of studies of novel technologies for the management of chronic illness”, J. Telemed. Telecare, vol. 15, no. 7, pp. 327-38, Jan. 2009.
C. Perera, “The evolution of e-health – mobile technology and mhealth”, J. Mob. Technol. Med., vol. 1, no. 1, pp. 1-2, Mar. 2012.
S. Patel, H. Park, P. Bonato, L. Chan and M. Rodgers, “A review of wearable sensors and systems with application in rehabilitation”, J. Neuroeng. Rehabil., vol. 9, no. 1, pp. 21, Jan. 2012.
D. Morris, T. Saponas, A. Guillory and I. Kelner, “Recofit: using a wearable sensor to find recognize and count repetitive exercises”, CHI’14 Proc. SIGCHI Conf. on HF in Comp. Sys., pp. 3225-3234, 2014.
F. Casamassima, A. Ferrari, B. Milosevic, L. Rocchi and E. Farella, “Wearable audio-feedback system for gait rehabilitation in subjects with Parkinson’s disease”, Proc. 2013 ACM Conf. Pervas. and Ubiq. Comp. adjunct publication, pp. 275-278, 2013.
C. Schonauer and T. Pintaric, “Chronic pain rehabilitation with a serious game using multimodal input”, Virtual Rehabil., 2011.
D. Gromala, M. Song, J.-D. Yim, T. Fox, S. J. Barnes, M. Nazemi, et al., “immersive vr: a non-pharmacological analgesic for chronic pain ?”, Proc. Annual Conf. on HF in Comp. Sys. (CHI ’11), pp. 1171-1176, 2011.
H. Joffe and L. Yardley, “Content and thematic analysis” in Research Methods for Clinical and Health Psychology, Sage Publications Ltd, pp. 56-68, 2003.
C. Fan, “The Future of data visualization in personal informatics tools”, Personal Inform. in the Wild: Hacking Habits for Health & Happiness – CHI 2013 Workshop, 2013.
J. Rooksby, M. Rost, A. Morrison and M. C. Chalmers, “personal tracking as lived informatics”, Proc. 32nd Annual ACM Conf. on HF in Comp. Sys., pp. 1163-1172, 2014.
M. Aung, N. Bianchi-Berthouze, P. Watson and A. C. De Williams, “Automatic Recognition of fear-avoidance behavior in chronic pain physical rehabilitation”, Pervas. Comp. Techn. Healthc., pp. 0-3, 2014.
T. Olugbade, M. Aung, N. Marquardt, N. Bianchi-Berthouze and A. de C Williams, “Bi-modal detection of painful reaching for chronic pain rehabilitation systems”, Sep. 2014.
J. Hernandez and R. W. Picard, “SenseGlass”, Proc. of the adjunct publication of 27th annual ACM symposium on User interface software and technology – UIST’ 14 Adjunct, pp. 77-78, 2014.
R. Johnson, N. Bianchi-Berthouze, Y. Rogers and J. van der Linden, “Embracing calibration in body sensing: using self-tweaking to enhance ownership and performance”, UbiComp ’13 Proc. 2013 ACM Int. Jt. Conf. Pervasive Ubiquit. Comput., pp. 811, 2013.
A. Singh et al., Go with the flow: Tracking analysis and sonification of movement and breathing to build confidence in activity despite chronic pain Human-Computer Interaction (in revision).
S. Faisal, A. Blandford and H. W. Potts, “Making sense of personal health information: challenges for information visualization”, Health Informatics J., vol. 19, no. 3, pp. 198-217, Sep. 2013.
C. E. Ashton-James, D. C. Richardson, A. C. C De Williams, N. Bianchi-Berthouze and P. H. Dekker, “Impact of pain behaviors on evaluations of warmth and competence”, vol. 155, no. 12, pp. 2656-61, Dec. 2014.
M. S. H. Aung et al., “The automatic detection of chronic pain-related expression: requirements challenges and a multimodal dataset”, Trans. Affective Computing, 2015.
J. Rainville, R. J. E.M. Smeets, T. Bendix, T. H. Tveito, S. Poiraudeau and A. J. Indahl, “Fear-avoidance beliefs and pain avoidance in low back pain-translating research into clinical practice”, Spine J., vol. 11, no. 9, pp. 895-903, Sep. 2011.
S. Schmidt, J. R. Naranjo, C. Brenneisen, J. Gundlach, C. Schultz, H. Kaube, et al., “Pain ratings psychological functioning and quantitative EEG in a controlled study of chronic back pain patients”, PLoS One, vol. 7, no. 3, pp. e31138, Jan. 2012.