ArticleASSETS. Annual ACM Conference on Assistive Technologies2019
Understanding Mental Ill-health as Psychosocial Disability: Implications for Assistive Technology.
Article in ASSETS. Annual ACM Conference on Assistive Technologies, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed, 56 citations in OpenAlex.
- Modeling Accessibility: Characterizing What We Mean by "Accessible".ASSETS. Annual ACM Conference on Assistive Technologies · 2025Article
- Advancing psychosocial disability and psychosocial rehabilitation research through large language models and computational text mining.Global mental health (Cambridge, England) · 2024Article
- Use of Assistive Technology for Persons with Psychosocial Disability: Systematic Review.JMIR rehabilitation and assistive technologies · 2023Review
- "Our Job is to be so Temporary": Designing Digital Tools that Meet the Needs of Care Managers and their Patients with Mental Health Concerns.Proceedings of the ACM on human-computer interaction · 2023Article
- Involving Crowdworkers with Lived Experience in Content-Development for Push-Based Digital Mental Health Tools: Lessons Learned from Crowdsourcing Mental Health Messages.Proceedings of the ACM on human-computer interaction · 2022Article
- "I Wanted to See How Bad it Was": Online Self-screening as a Critical Transition Point Among Young Adults with Common Mental Health Conditions.Proceedings of the SIGCHI conference on human factors in computing systems. CHI Conference · 2022Article
- Accessibility and Digital Mental Health: Considerations for More Accessible and Equitable Mental Health Apps.Frontiers in digital health · 2021Article
- Designing Mental Health Technologies that Support the Social Ecosystem of College Students.Proceedings of the SIGCHI conference on human factors in computing systems. CHI Conference · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 1 institution in 1 country.
Funding
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.