AI Applications for Mental Health and Clinical Practice

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AI Applications for Mental Health and Clinical Practice

This course is part of The Mental Health Clinician and AI Specialization

Instructors: Oscar Kjell

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3 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

8 hours to complete

Flexible schedule

Learn at your own pace

3 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

8 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

How statistical models compare to human judgment in clinical decision-making, and how these models have advanced into modern AI systems over time.
How AI can expand mental health assessments, including how language-based approaches can measure, describe, and differentiate psychological states.
How AI can support treatment selection and personalization and psychotherapy delivery, including its potential and risks.

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This course is part of the The Mental Health Clinician and AI Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

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There are 3 modules in this course

This course is designed for students and professionals in psychology, medicine, and other clinical disciplines who want to explore how AI is transforming mental health care in practice.

Building on foundational AI concepts, you will examine how clinical decision-making is evolving, from early statistical models to modern AI systems, and what research tells us about their accuracy compared to human judgment. You will then explore how AI can expand mental health assessments, including how language-based approaches can measure, describe, and differentiate between psychological states in ways traditional rating scales cannot. Finally, you will discover how AI can support treatment selection and personalization through precision mental health approaches, and how it is beginning to be integrated into psychotherapy delivery. Throughout, you will encounter perspectives from patients, clinicians, and researchers, and be encouraged to critically reflect on the opportunities and risks of applying AI in real clinical settings. By the end of this course, you will be equipped to evaluate how AI tools can realistically enhance, and potentially transform, mental health assessment and treatment.

Welcome to this module, where we introduce you to this course and move on to clinical and statistical decision-making. Here, we step back to examine the history of AI in clinical decision-making, from the 1950s to today. We will discuss comparisons between clinical judgment and AI, and how these findings and technological developments have been perceived by mental health professionals over time.

What's included

8 videos4 readings2 assignments

8 videosTotal 37 minutes

The Mental Health Clinician and AI2 minutes
Welcome to this Module1 minute
Why Does Assessment Matter?6 minutes
Clinical Judgement versus Statistical Models5 minutes
Accuracy of Clinical and Statistical Assessments6 minutes
Statistical Decision-Making: Critiques, Fears, and Concerns4 minutes
From Early Statistical Models to Modern AI Systems6 minutes
Mental Health Assessments Nowadays6 minutes

4 readingsTotal 50 minutes

Course Overview10 minutes
Meet the Lecturers10 minutes
Person versus Person's Model 15 minutes
Summary, Key terms, and Readings15 minutes

2 assignmentsTotal 50 minutes

Clinical and Statistical Assessment Quiz30 minutes
Reflection: AI-Based Decision-Support20 minutes

Welcome to this module about AI-driven mental health assessments and AI-based decision support. Here, we focus on language-based assessments in mental health, such as how AI can analyze patient language to provide insights into mental states with the potential to assist in clinical decision-making.

What's included

6 videos2 readings2 assignments

6 videosTotal 38 minutes

Welcome to this Module3 minutes
Language in Clinical Settings6 minutes
Probed Language-Based Assessments8 minutes
Natural Language: From Social Media to Therapy Sessions11 minutes
Strengths and Weaknesses of Language-Based Assessments7 minutes
The R Language Analysis Suite3 minutes

2 readingsTotal 30 minutes

Beyond Text: Multimodal Signals in AI15 minutes
Summary, Key Terms, and Readings15 minutes

2 assignmentsTotal 50 minutes

Language-Based Assessment Quiz30 minutes
Reflection: Language vs. Ratings20 minutes

Welcome to this module about the use of AI for Precision Mental Health and psychotherapy. First, we focus on how AI can optimize treatment selection and personalize interventions. Then we move on to the potential of Large Language Models and generative AI to support clinicians and patients in psychotherapy.

What's included

11 videos3 readings3 assignments

11 videosTotal 126 minutes

Welcome to this Module3 minutes
The Idea behind Precision Mental Health5 minutes
Precision Algorithms and the Personalized Advantage Index6 minutes
Putting Precision Mental Health to the Test8 minutes
Challenges and Opportunities in Precision Mental Health6 minutes
Integration of AI in Psychotherapy5 minutes
Potential Applications of AI in Psychotherapy7 minutes
Elizabeth Stade - AI Tools to Support Evidence-Based Treatment of PTSD49 minutes
Chatbots as Psychotherapists?8 minutes
Salim Salmi - AI Tools to Support Suicide Prevention Helplines28 minutes
The Potential of AI in Mental Health: From Assessment to Treatment2 minutes

3 readingsTotal 35 minutes

Interviews: Meet the Experts10 minutes
Summary, Key Terms, and Readings15 minutes
Course Summary10 minutes

3 assignmentsTotal 70 minutes

AI for Precision and Therapy Quiz30 minutes
Reflection: Precision Models20 minutes
Reflection: Chatbot Support20 minutes

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Instructors

Oscar Kjell

Lund University

0 Courses0 learners

Offered by

Lund University

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