Ensuring patient and public involvement in the transition to AI‐assisted mental health care: A systematic scoping review and agenda for design justice
Abstract Background Machine‐learning algorithms and big data analytics, popularly known as ‘artificial intelligence’ (AI), are being developed and taken up globally. Patient and public involvement (PPI) in the transition to AI‐assisted health care is essential for design justice based on diverse pat...
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doaj-384a2b3e2628483d80d2a7045eb5a1ce2021-08-17T05:09:01ZengWileyHealth Expectations1369-65131369-76252021-08-012441072112410.1111/hex.13299Ensuring patient and public involvement in the transition to AI‐assisted mental health care: A systematic scoping review and agenda for design justiceTeodor Zidaru0Elizabeth M. Morrow1Rich Stockley2Department of Anthropology London School of Economics and Political Science (LSE) London UKResearch Support NI Belfast UKSurrey Heartlands Health and Care Partnership Guildford and Waverley CCG Guildford UKAbstract Background Machine‐learning algorithms and big data analytics, popularly known as ‘artificial intelligence’ (AI), are being developed and taken up globally. Patient and public involvement (PPI) in the transition to AI‐assisted health care is essential for design justice based on diverse patient needs. Objective To inform the future development of PPI in AI‐assisted health care by exploring public engagement in the conceptualization, design, development, testing, implementation, use and evaluation of AI technologies for mental health. Methods Systematic scoping review drawing on design justice principles, and (i) structured searches of Web of Science (all databases) and Ovid (MEDLINE, PsycINFO, Global Health and Embase); (ii) handsearching (reference and citation tracking); (iii) grey literature; and (iv) inductive thematic analysis, tested at a workshop with health researchers. Results The review identified 144 articles that met inclusion criteria. Three main themes reflect the challenges and opportunities associated with PPI in AI‐assisted mental health care: (a) applications of AI technologies in mental health care; (b) ethics of public engagement in AI‐assisted care; and (c) public engagement in the planning, development, implementation, evaluation and diffusion of AI technologies. Conclusion The new data‐rich health landscape creates multiple ethical issues and opportunities for the development of PPI in relation to AI technologies. Further research is needed to understand effective modes of public engagement in the context of AI technologies, to examine pressing ethical and safety issues and to develop new methods of PPI at every stage, from concept design to the final review of technology in practice. Principles of design justice can guide this agenda.https://doi.org/10.1111/hex.13299artificial intelligencebig datadesign justicedigital health technologymachine learningmental health |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Teodor Zidaru Elizabeth M. Morrow Rich Stockley |
spellingShingle |
Teodor Zidaru Elizabeth M. Morrow Rich Stockley Ensuring patient and public involvement in the transition to AI‐assisted mental health care: A systematic scoping review and agenda for design justice Health Expectations artificial intelligence big data design justice digital health technology machine learning mental health |
author_facet |
Teodor Zidaru Elizabeth M. Morrow Rich Stockley |
author_sort |
Teodor Zidaru |
title |
Ensuring patient and public involvement in the transition to AI‐assisted mental health care: A systematic scoping review and agenda for design justice |
title_short |
Ensuring patient and public involvement in the transition to AI‐assisted mental health care: A systematic scoping review and agenda for design justice |
title_full |
Ensuring patient and public involvement in the transition to AI‐assisted mental health care: A systematic scoping review and agenda for design justice |
title_fullStr |
Ensuring patient and public involvement in the transition to AI‐assisted mental health care: A systematic scoping review and agenda for design justice |
title_full_unstemmed |
Ensuring patient and public involvement in the transition to AI‐assisted mental health care: A systematic scoping review and agenda for design justice |
title_sort |
ensuring patient and public involvement in the transition to ai‐assisted mental health care: a systematic scoping review and agenda for design justice |
publisher |
Wiley |
series |
Health Expectations |
issn |
1369-6513 1369-7625 |
publishDate |
2021-08-01 |
description |
Abstract Background Machine‐learning algorithms and big data analytics, popularly known as ‘artificial intelligence’ (AI), are being developed and taken up globally. Patient and public involvement (PPI) in the transition to AI‐assisted health care is essential for design justice based on diverse patient needs. Objective To inform the future development of PPI in AI‐assisted health care by exploring public engagement in the conceptualization, design, development, testing, implementation, use and evaluation of AI technologies for mental health. Methods Systematic scoping review drawing on design justice principles, and (i) structured searches of Web of Science (all databases) and Ovid (MEDLINE, PsycINFO, Global Health and Embase); (ii) handsearching (reference and citation tracking); (iii) grey literature; and (iv) inductive thematic analysis, tested at a workshop with health researchers. Results The review identified 144 articles that met inclusion criteria. Three main themes reflect the challenges and opportunities associated with PPI in AI‐assisted mental health care: (a) applications of AI technologies in mental health care; (b) ethics of public engagement in AI‐assisted care; and (c) public engagement in the planning, development, implementation, evaluation and diffusion of AI technologies. Conclusion The new data‐rich health landscape creates multiple ethical issues and opportunities for the development of PPI in relation to AI technologies. Further research is needed to understand effective modes of public engagement in the context of AI technologies, to examine pressing ethical and safety issues and to develop new methods of PPI at every stage, from concept design to the final review of technology in practice. Principles of design justice can guide this agenda. |
topic |
artificial intelligence big data design justice digital health technology machine learning mental health |
url |
https://doi.org/10.1111/hex.13299 |
work_keys_str_mv |
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