How Can AI Help Mental Health Practitioners?
Author Information
Author(s): Orrù Luisa, Cuccarini Marco, Moro Christian, Turchi Gian Piero
Primary Institution: Department of Philosophy, Sociology, Education and Applied Psychology, University of Padova
Hypothesis
Different types of clinical questions can foster psychological change in patients.
Conclusion
The study confirmed that machine learning can distinguish between different types of clinical questions based on patients' responses, suggesting potential for AI to assist therapists.
Supporting Evidence
- The study found that the presence of a clinical question improves the accuracy of text analysis.
- Different types of questions led to different distributions of discursive repertoires in patient responses.
- Machine learning models can enhance therapists' understanding of patient narratives.
Takeaway
This study shows that asking different types of questions can help therapists understand their patients better and improve mental health treatment.
Methodology
The study used a machine learning model to analyze therapist-patient interactions based on 14,567 text excerpts.
Limitations
The study only considered two types of questions and had a limited dataset size.
Participant Demographics
Participants were 28 individuals aged 18 to 65, including both males and females.
Digital Object Identifier (DOI)
Want to read the original?
Access the complete publication on the publisher's website