Understanding Mental Ill-health as Psychosocial Disability: Implications for Assistive Technology
Kathryn E. Ringland, Jennifer Nicholas, Rachel Kornfield, Emily G. Lattie, David C. Mohr, Madhu Reddy · 2019 · Proceedings of the 21st International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS 2019) · doi:10.1145/3308561.3353785
Summary
This paper argues that mental ill-health — including depression, anxiety, and other mental, emotional, or cognitive experiences — should be understood as psychosocial disability and examined through a social model lens rather than exclusively through the medical model that dominates digital mental health technology. The authors conducted semi-structured interviews with 18 individuals (ages 33-88, mean 58) recruited through a care management service at a large Midwestern US health system, all experiencing moderate depression and/or anxiety alongside complex physical health conditions. The study is grounded in the tension between two disability frameworks: the medical model (which pathologises mental health conditions as disorders to be diagnosed, treated, and cured) and the social model (which locates disability in societal barriers — stigma, discrimination, lack of accommodation — rather than in the individual). While the ASSETS community has developed substantial expertise in assistive technology through a social model lens for physical disabilities, this perspective has rarely been applied to psychosocial disability. Meanwhile, the digital mental health field has produced numerous apps and interventions but frames them almost exclusively as clinical treatment tools aimed at symptom reduction. Three themes emerged: how physical and mental health are both disabling and deeply intertwined; how participants framed their mental health experiences and how others’ conflicting framings created tension; and how participants cared for their mental health through both the medical system and self-management practices.
Key findings
Participants described mental ill-health as genuinely disabling — limiting their ability to work, maintain relationships, and participate in daily activities — yet most did not identify as "disabled" or adopt psychiatric labels readily. While physical health conditions were discussed matter-of-factly with established diagnostic labels, mental health was framed contextually, episodically, and with significant hesitation around medicalised language. Participants fell on a spectrum from rejecting diagnostic labels ("did I feel that I was depressed? No. I just saw these as another set of challenges I needed to meet and overcame") to partial acceptance ("not depression really, anxiety off and on") to full acceptance as a chronic condition. Physical and mental health were deeply intertwined: anxiety manifested physically ("muscles will tighten up"), physical disability limited mental health strategies (inability to walk for exercise), and physical conditions increased depression risk. Stigma powerfully shaped disclosure decisions — participants carefully selected who to tell about mental health, fearing employment consequences or social judgment, while physical health was discussed openly. Self-stigma influenced willingness to adopt psychiatric labels or use medication. Participants employed a wide range of self-management strategies (exercise, meditation, apps, cognitive restructuring, being social) but felt pressured by others to try specific treatments, wanting autonomy respected. The healthcare system was perceived as siloed (physical and mental health care disconnected) and overstretched, with participants feeling unheard.
Relevance
This paper makes a significant theoretical contribution by bridging the assistive technology and digital mental health communities, arguing that each has something the other needs. The assistive technology community brings expertise in the social model, empowerment-focused design, and technology that supports daily functioning rather than treating deficits. The digital mental health community brings clinical knowledge and established intervention frameworks but is limited by its medical model framing. The three design considerations are directly actionable: (1) view the whole person beyond the medical context — technology should support documentation of patterns across physical and mental health to help providers see the "whole picture" rather than treating conditions in isolation; (2) reframe research and design to match user experiences — framing tools in terms of "wellness" rather than "mental illness" or "psychosocial disability" may increase acceptability, and allowing users to define their own language is essential; (3) move away from a solely medical model — assistive technology for psychosocial disability should support self-directed goals, functional roles, and quality of life rather than purely targeting symptom reduction. The paper also highlights how technologies could help individuals navigate stigma-related disclosure decisions.
Tags: psychosocial disability · mental health · depression · anxiety · social model of disability · stigma · assistive technology · disability studies · self-management · invisible disability