Therapists and psychotherapy side effects in China: A machine learning-based study
Objective: Side effects in the psychotherapy are sometimes unavoidable. Therapists play a significant role in the side effects of psychotherapy, but there have been few quantitative studies on the mechanisms by which therapists contribute to them. Methods: We designed the psychotherapy Side Effects...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-11-01
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| Series: | Heliyon |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844022031097 |
| _version_ | 1797987922905923584 |
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| author | Lijun Yao Zhiwei Xu Xudong Zhao Yang Chen Liang Liu Xiaoming Fu Fazhan Chen |
| author_facet | Lijun Yao Zhiwei Xu Xudong Zhao Yang Chen Liang Liu Xiaoming Fu Fazhan Chen |
| author_sort | Lijun Yao |
| collection | DOAJ |
| description | Objective: Side effects in the psychotherapy are sometimes unavoidable. Therapists play a significant role in the side effects of psychotherapy, but there have been few quantitative studies on the mechanisms by which therapists contribute to them. Methods: We designed the psychotherapy Side Effects Questionnaire-Therapist Version (PSEQ-T) and released it online through an official WeChat account, where 530 therapists participated in the cross-sectional analysis. The therapists were classified into groups with and without perceptions of clients’ side effects. A number of features were selected to distinguish the therapists by category. Six machine learning-based algorithms were selected and trained by our dataset to build classification models. We leveraged the Shapley Additive exPlanations (SHAP) method to quantify the importance of each feature to the therapist categories. Results: Our study demonstrated the following: (1) Of the therapists, 316 perceived clients’ side effects in psychotherapy, with a 59.6% incidence of side effects; the most common type was “make the clients or patients feel bad” (49.8%). (2) A Random Forest-based machine-learning classifier offered the best predictive performance to distinguish the therapists with and without perceptions of clients' side effects, with an F1 score of 0.722 and an AUC value of 0.717. (3) “Therapists’ psychological activity” was the most relevant feature for distinguishing the therapist category. Conclusions: Our study revealed that the therapist's mastery of the limitations of psychotherapy technology and theory, especially the awareness and construction of their psychological states, was the most critical factor in predicting the therapist's perception of the side effects of psychotherapy. |
| first_indexed | 2024-04-11T07:54:33Z |
| format | Article |
| id | doaj.art-2bc51d1ed7cb4a19ac2d41eb04914a69 |
| institution | Directory Open Access Journal |
| issn | 2405-8440 |
| language | English |
| last_indexed | 2024-04-11T07:54:33Z |
| publishDate | 2022-11-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj.art-2bc51d1ed7cb4a19ac2d41eb04914a692022-12-22T04:35:58ZengElsevierHeliyon2405-84402022-11-01811e11821Therapists and psychotherapy side effects in China: A machine learning-based studyLijun Yao0Zhiwei Xu1Xudong Zhao2Yang Chen3Liang Liu4Xiaoming Fu5Fazhan Chen6Clinical Research Center for Mental Disorders, Shanghai Pudong New Area Mental Health Center, Tongji University School of Medicine, Shanghai 200124, PR ChinaShanghai Key Laboratory of Intelligent Information Processing, School of Computer Science, Fudan University, Shanghai 200434, PR China; School of Software, Tsinghua University, 100084, PR ChinaClinical Research Center for Mental Disorders, Shanghai Pudong New Area Mental Health Center, Tongji University School of Medicine, Shanghai 200124, PR ChinaShanghai Key Laboratory of Intelligent Information Processing, School of Computer Science, Fudan University, Shanghai 200434, PR ChinaClinical Research Center for Mental Disorders, Shanghai Pudong New Area Mental Health Center, Tongji University School of Medicine, Shanghai 200124, PR ChinaInstitute of Computer Science, University of Göttingen, Göttingen 37077, GermanyClinical Research Center for Mental Disorders, Shanghai Pudong New Area Mental Health Center, Tongji University School of Medicine, Shanghai 200124, PR China; Corresponding author.Objective: Side effects in the psychotherapy are sometimes unavoidable. Therapists play a significant role in the side effects of psychotherapy, but there have been few quantitative studies on the mechanisms by which therapists contribute to them. Methods: We designed the psychotherapy Side Effects Questionnaire-Therapist Version (PSEQ-T) and released it online through an official WeChat account, where 530 therapists participated in the cross-sectional analysis. The therapists were classified into groups with and without perceptions of clients’ side effects. A number of features were selected to distinguish the therapists by category. Six machine learning-based algorithms were selected and trained by our dataset to build classification models. We leveraged the Shapley Additive exPlanations (SHAP) method to quantify the importance of each feature to the therapist categories. Results: Our study demonstrated the following: (1) Of the therapists, 316 perceived clients’ side effects in psychotherapy, with a 59.6% incidence of side effects; the most common type was “make the clients or patients feel bad” (49.8%). (2) A Random Forest-based machine-learning classifier offered the best predictive performance to distinguish the therapists with and without perceptions of clients' side effects, with an F1 score of 0.722 and an AUC value of 0.717. (3) “Therapists’ psychological activity” was the most relevant feature for distinguishing the therapist category. Conclusions: Our study revealed that the therapist's mastery of the limitations of psychotherapy technology and theory, especially the awareness and construction of their psychological states, was the most critical factor in predicting the therapist's perception of the side effects of psychotherapy.http://www.sciencedirect.com/science/article/pii/S2405844022031097Side effectsPsychotherapyTherapistMachine learningArtificial intelligence |
| spellingShingle | Lijun Yao Zhiwei Xu Xudong Zhao Yang Chen Liang Liu Xiaoming Fu Fazhan Chen Therapists and psychotherapy side effects in China: A machine learning-based study Heliyon Side effects Psychotherapy Therapist Machine learning Artificial intelligence |
| title | Therapists and psychotherapy side effects in China: A machine learning-based study |
| title_full | Therapists and psychotherapy side effects in China: A machine learning-based study |
| title_fullStr | Therapists and psychotherapy side effects in China: A machine learning-based study |
| title_full_unstemmed | Therapists and psychotherapy side effects in China: A machine learning-based study |
| title_short | Therapists and psychotherapy side effects in China: A machine learning-based study |
| title_sort | therapists and psychotherapy side effects in china a machine learning based study |
| topic | Side effects Psychotherapy Therapist Machine learning Artificial intelligence |
| url | http://www.sciencedirect.com/science/article/pii/S2405844022031097 |
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