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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

33 Scopus citations

Abstract

Psychosocial disability involves actual or perceived impairment due to a diversity of mental, emotional, or cognitive experiences. While assistive technology for psychosocial disabilities has been understudied in communities such as ASSETS, advances in computing have opened up a number of new avenues for assisting those with psychosocial disabilities beyond the clinic. However, these tools continue to emerge primarily within the framework of “treatment,” emphasizing resolution or improvement of mental health symptoms. This work considers what it means to adopt a social model lens from disability studies and incorporate the expertise of assistive technology researchers in relation to mental health. Our investigation draws on interviews conducted with 18 individuals who have complex health needs that include mental health symptoms. This work highlights the potential role for assistive technology in supporting psychosocial disability outside of a clinical or medical framework.

Original languageEnglish (US)
Title of host publicationASSETS 2019 - 21st International ACM SIGACCESS Conference on Computers and Accessibility
PublisherAssociation for Computing Machinery, Inc
Pages156-170
Number of pages15
ISBN (Electronic)9781450366762
DOIs
StatePublished - Oct 24 2019
Event21st International ACM SIGACCESS Conference on Computers and Accessibility, ASSETS 2019 - Pittsburgh, United States
Duration: Oct 28 2019Oct 30 2019

Publication series

NameASSETS 2019 - 21st International ACM SIGACCESS Conference on Computers and Accessibility

Conference

Conference21st International ACM SIGACCESS Conference on Computers and Accessibility, ASSETS 2019
Country/TerritoryUnited States
CityPittsburgh
Period10/28/1910/30/19

Funding

We thank the participants of this study. This work is supported by the National Institute of Mental Health (T32MH115882). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.

Keywords

  • Anxiety
  • Depression
  • Mental health
  • Psychosocial disability
  • Social model of disability

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Computer Graphics and Computer-Aided Design

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