Clinical Questions and Psychological Change: How Can Artificial Intelligence Support Mental Health Practitioners?
Despite their diverse assumptions, clinical psychology approaches share the goal of mental health promotion. The literature highlights their usefulness, but also some issues related to their effectiveness, such as their difficulties in monitoring psychological change. The elective strategy for activ...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-12-01
|
| Series: | Behavioral Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-328X/14/12/1225 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850041222770458624 |
|---|---|
| author | Luisa Orrù Marco Cuccarini Christian Moro Gian Piero Turchi |
| author_facet | Luisa Orrù Marco Cuccarini Christian Moro Gian Piero Turchi |
| author_sort | Luisa Orrù |
| collection | DOAJ |
| description | Despite their diverse assumptions, clinical psychology approaches share the goal of mental health promotion. The literature highlights their usefulness, but also some issues related to their effectiveness, such as their difficulties in monitoring psychological change. The elective strategy for activating and managing psychological change is the clinical question. But how do different types of questions foster psychological change? This work tries to answer this issue by studying therapist–patient interactions with a ML model for text analysis. The goal was to investigate how psychological change occurs thanks to different types of questions, and to see if the ML model recognized this difference in analyzing patients’ answers to therapists’ clinical questions. The experimental dataset of 14,567 texts was divided based on two different question purposes, splitting answers in two categories: those elicited by questions asking patients to start describing their clinical situation, or those from asking them to detail how they evaluate their situation and mental health condition. The hypothesis that these categories are distinguishable by the model was confirmed by the results, which corroborate the different valences of the questions. These results foreshadow the possibility to train ML and AI models to suggest clinical questions to therapists based on patients’ answers, allowing the increase of clinicians’ knowledge, techniques, and skills. |
| format | Article |
| id | doaj-art-cb7cbd4f0f8f4ad79dbf589af3d84b8a |
| institution | DOAJ |
| issn | 2076-328X |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Behavioral Sciences |
| spelling | doaj-art-cb7cbd4f0f8f4ad79dbf589af3d84b8a2025-08-20T02:55:49ZengMDPI AGBehavioral Sciences2076-328X2024-12-011412122510.3390/bs14121225Clinical Questions and Psychological Change: How Can Artificial Intelligence Support Mental Health Practitioners?Luisa Orrù0Marco Cuccarini1Christian Moro2Gian Piero Turchi3Department of Philosophy, Sociology, Education and Applied Psychology, University of Padova, 35122 Padova, ItalyDepartment of Mathematics and Computer Science, University of Perugia, 06123 Perugia, ItalyDepartment of Philosophy, Sociology, Education and Applied Psychology, University of Padova, 35122 Padova, ItalyDepartment of Philosophy, Sociology, Education and Applied Psychology, University of Padova, 35122 Padova, ItalyDespite their diverse assumptions, clinical psychology approaches share the goal of mental health promotion. The literature highlights their usefulness, but also some issues related to their effectiveness, such as their difficulties in monitoring psychological change. The elective strategy for activating and managing psychological change is the clinical question. But how do different types of questions foster psychological change? This work tries to answer this issue by studying therapist–patient interactions with a ML model for text analysis. The goal was to investigate how psychological change occurs thanks to different types of questions, and to see if the ML model recognized this difference in analyzing patients’ answers to therapists’ clinical questions. The experimental dataset of 14,567 texts was divided based on two different question purposes, splitting answers in two categories: those elicited by questions asking patients to start describing their clinical situation, or those from asking them to detail how they evaluate their situation and mental health condition. The hypothesis that these categories are distinguishable by the model was confirmed by the results, which corroborate the different valences of the questions. These results foreshadow the possibility to train ML and AI models to suggest clinical questions to therapists based on patients’ answers, allowing the increase of clinicians’ knowledge, techniques, and skills.https://www.mdpi.com/2076-328X/14/12/1225mental healthclinical questionsclinical psychologypsychological changemachine learningArtificial Intelligence |
| spellingShingle | Luisa Orrù Marco Cuccarini Christian Moro Gian Piero Turchi Clinical Questions and Psychological Change: How Can Artificial Intelligence Support Mental Health Practitioners? Behavioral Sciences mental health clinical questions clinical psychology psychological change machine learning Artificial Intelligence |
| title | Clinical Questions and Psychological Change: How Can Artificial Intelligence Support Mental Health Practitioners? |
| title_full | Clinical Questions and Psychological Change: How Can Artificial Intelligence Support Mental Health Practitioners? |
| title_fullStr | Clinical Questions and Psychological Change: How Can Artificial Intelligence Support Mental Health Practitioners? |
| title_full_unstemmed | Clinical Questions and Psychological Change: How Can Artificial Intelligence Support Mental Health Practitioners? |
| title_short | Clinical Questions and Psychological Change: How Can Artificial Intelligence Support Mental Health Practitioners? |
| title_sort | clinical questions and psychological change how can artificial intelligence support mental health practitioners |
| topic | mental health clinical questions clinical psychology psychological change machine learning Artificial Intelligence |
| url | https://www.mdpi.com/2076-328X/14/12/1225 |
| work_keys_str_mv | AT luisaorru clinicalquestionsandpsychologicalchangehowcanartificialintelligencesupportmentalhealthpractitioners AT marcocuccarini clinicalquestionsandpsychologicalchangehowcanartificialintelligencesupportmentalhealthpractitioners AT christianmoro clinicalquestionsandpsychologicalchangehowcanartificialintelligencesupportmentalhealthpractitioners AT gianpieroturchi clinicalquestionsandpsychologicalchangehowcanartificialintelligencesupportmentalhealthpractitioners |