Patient Perspectives on AI for Mental Health Care: Cross-Sectional Survey Study.

Natalie C Benda Pooja M Desai Zayan Reza Anna Zheng Shiveen Kumar Sarah E Harkins Alison Hermann Yiye Zhang Rochelle Joly Jessica Kim Jyotishman Pathak Meghan Reading Turchioe

Published in: JMIR mental health (2024)

Future work involving the use of AI for mental health care should investigate strategies for conveying the level of AI's accuracy, factors that drive patients' mental health risks, and how data are used confidentially so that patients can determine with their health professionals when AI may be beneficial. It will also be important in a mental health care context to ensure the patient-health professional relationship is preserved when AI is used.

Keyphrases

end stage renal disease
artificial intelligence
ejection fraction
chronic kidney disease
newly diagnosed
public health
peritoneal dialysis
prognostic factors
machine learning
big data
patient reported outcomes
patient reported
climate change
current status
social media