Clinical Scorecard: Healthcare Professionals' Perspectives on Integrating Artificial Intelligence in Mental Health Services: A Scoping Review

At a Glance

Key Highlights

• AI implementation in mental health is complex due to the subjective nature of treatment.
• Clinicians' trust and understanding of AI tools are crucial for their acceptance.
• Concerns exist regarding patient autonomy and the therapeutic alliance with AI use.
• Ethical considerations include confidentiality and data security in AI applications.
• Clinicians' perspectives can influence the adoption of AI in mental health care.

Guideline-Based Recommendations

Diagnosis

Management

Monitoring & Follow-up

Risks

• Inappropriate advice and risk underestimation could affect patient safety.
• Erosion of relational trust may impact patient engagement in therapy.

Patient & Prescribing Data

Patients receiving mental health care.

AI tools may assist but should not replace human-led care.

Clinical Best Practices

• Ensure AI tools are used to support, not replace, human interactions in therapy.
• Maintain a focus on ethical considerations during AI implementation.
• Foster clinician education on AI capabilities and limitations.

Related Resources & Content

• Evolution of artificial intelligence in healthcare
• Use of natural language processing in the emergency department
• Balancing risks and benefits: clinicians’ perspectives on AI
• Ethical decision-making for AI in mental health
• Barriers to and facilitators of clinician acceptance of AI