Do we trust AI to help us make decisions for mental health?

New research shows that learning about AI in mental health decision-making is important for people to be able to trust AI systems, but this information unfortunately has little impact on increasing ts’ well in AI. AI-based clinical decision support systems (CDSS) are being developed to assist psychiatrists and mental health practitioners, providing new tools to improve diagnostic accuracy, stratification risk, and treatment plan. However, implementing AI in mental health and mental illness raises important questions about patient trust and acceptance of this technology. Do patients trust these systems, and how can AI be incorporated without undermining patient trust and confidence?

A recent study published in European Psychiatry examined patient trust in machine learning (ML) based clinical decision support systems within psychiatric services. The study examined how much trust patients have for AI-powered devices and how basic information about these systems can improve trust in AI.

AI in Mental Health Care Decision Making Will Impact Patient Confidence

An AI-based clinical decision support system uses machine learning algorithms to analyze electronic health records, clinical data, and patient-provided data to make evidence-based recommendations. In psychiatric facilities, these systems can help predict risks such as hospitalization, suggest diagnoses, and recommend treatment plans. While AI can reduce human error and provide data-driven recommendations, patient trust and safety remain important, especially in psychiatry, where the therapeutic relationship is essential.

Fear or mistrust of AI—whether in how data is used or the role of AI in clinical decisions—can undermine the therapeutic relationship. People should be informed in advance if AI is involved and have control over their data usage.

Just Giving Information About AI Improves Trust and Reduces Distrust of AI

The study included 992 participants receiving mental health care, divided into three groups: one group received an electronic pamphlet with four slides explaining AI-supported decisions, group the second received general information about cognitive decision-making, and the third group did not. provide any information. Next, each group completed a survey examining trust and distrust in AI-based clinical decision support systems in psychiatric services. Questions included safety issues, risk of errors, physicians’ reliance on AI, and whether participants felt they should opt out.

Participants given information about machine learning reported slightly higher confidence compared to those who did not receive information. On average, trust increased by 5% and mistrust decreased by 4% when people received information through AI methods.

In general, people were more receptive to AI when human doctors had final control over recommendations. The study also highlights that a key factor in trusting AI is “clarity,” or the transparency of the AI’s reasons for its recommendations. Providing an explanation will be challenging, however, due to the “black box” nature of many AI systems.

Confidence varies across demographics and situations

Interestingly, the impact information has on trust varies by demographic. Women tended to report higher levels of trust in AI after receiving the information, while men, who generally reported higher basic knowledge about AI and machine learning, showed little change in levels of confidence after intervention. Participants with mood or anxiety disorders showed greater increases in confidence than those with mental disorders. The latter group may have high levels of distrust of mental health services in general.

Future Directions

Trust is essential for the successful implementation and integration of AI in mental health care. Although AI holds promise, its integration into psychology raises unique challenges and ethical questions regarding transparency and informed consent. This study highlights the need to deliver AI information to people quickly and empower them with autonomy over data use and participation. People will want to know if and how AI tools are being used in their medical care and can choose opt-out options.

As mental health care becomes data driven, it is important to maintain trust as the center of the therapeutic relationship and to ensure that the patient/client relationship with the clinician is always collaborative, informed , and has good manners.

For policy makers and healthcare providers, these findings highlight the importance of investing in clear communication and definition of AI-based clinical decision support systems as critical to its successful integration into care. of mental health.

Marlynn Wei, MD PLLC © Copyright 2024. All rights reserved.