Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.4108/icst.pervasivehealth.2015.259501 | PervasiveHealth |
Keywords | Field | DocType |
Chronic pain, quantified-self, self-management, physiological sensing, emotional wellbeing, wearables, personal informatics | Medical education,Chronic pain,Personal informatics,Information needs,Multidisciplinary approach,Computer science,Self-management,Wearable computer,Knowledge management,Computer network,Pain management,Qualitative research | Conference |
ISSN | ISBN | Citations |
2153-1633 | 978-1-63190-045-7 | 2 |
PageRank | References | Authors |
0.39 | 13 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sergio Felipe | 1 | 2 | 0.39 |
| Aneesha Singh | 2 | 100 | 11.76 |
| Caroline Bradley | 3 | 2 | 0.39 |
| Amanda Williams | 4 | 126 | 11.24 |
| Nadia Bianchi-Berthouze | 5 | 1239 | 98.61 |