Abstract
Collecting data from the lived experiences of those with chronic health conditions is a delicate and challenging matter that must account for the individual differences of coping with a personally-embodied condition in psychosocial contexts. In this paper, we describe our research process for designing a mobile application that will serve as a portal for participatory research into non-pharmacological interventions which could improve the daily experiences of chronic pain patients. The process is informed by our empirical framework “affective game planning for health applications” (AGPHA), which postulates that for digital health interventions to be effective, they must minimize a user’s stress by maximizing their sense of control and agency in self-expression and self-care. We have evaluated our hypotheses through literature review, focus groups, anonymous online surveying, and participatory research with stakeholders (patients, caregivers, researchers). From this, we have designed and implemented a prototype application, PlaythePain, which includes five main features: Talk, Track, Play, Share and Report. The app incorporates elements of choice, playfulness, and social engagement, by 1) allowing users to select and introduce their own complementary and alternative forms of self-care for their pain, and 2) adding a humorous and empathetic chatbot that guides patient-partners to conduct self-research (qualitative and quantitative). Further sharing of data with designated doctors or personal stories with other community members is also available at the discretion of the user. We believe that this approach will facilitate it for users to increase awareness about the psychosocial and environmental contexts of their conditions.
S. Woods—Patient Partner.
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Holowka, E.M., Woods, S., Pahayahay, A., Roy, M., Khalili-Mahani, N. (2021). Principles for Designing an mHealth App for Participatory Research and Management of Chronic Pain. In: Duffy, V.G. (eds) Digital Human Modeling and Applications in Health, Safety, Ergonomics and Risk Management. AI, Product and Service. HCII 2021. Lecture Notes in Computer Science(), vol 12778. Springer, Cham. https://doi.org/10.1007/978-3-030-77820-0_5
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