Predicting first session working alliances using deep learning algorithms: A proof-of-concept study for personalized psychotherapy.

Journal: Psychotherapy research : journal of the Society for Psychotherapy Research
PMID: 35635836

Abstract

OBJECTIVE: The aim of this proof-of-concept study is to develop a predictive model based on deep learning algorithms to predict working alliances after the first therapeutic session and to provide a basis for clinical decisions.

Authors

  • Ying Zhou
    Institute of Drug Metabolism and Pharmaceutical Analysis, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China.
  • Xiao-Yu Chen
    Department of Psychology, School of Public Health, Southern Medical University, Guangzhou, People's Republic of China.
  • Ding Liu
    College of Psychology, Shenzhen University, Shenzhen, People's Republic of China.
  • Yu-Lin Pan
    School of Computer Science and Engineering, South China University of Technology, Guangzhou, People's Republic of China.
  • Yan-Fei Hou
    Department of Humanities and Mental Nursing, School of Nursing, Southern Medical University, Guangzhou, People's Republic of China.
  • Ting-Ting Gao
    Department of Psychology, School of Public Health, Southern Medical University, Guangzhou, People's Republic of China.
  • Fei Peng
    College of Food Science and Engineering, Northwest A&F University, Yangling 712100, China.
  • Xiao-Cong Wang
    Department of Obstetrics and Gynaecology, Nanfang Hospital, Southern Medical University, Guangzhou, People's Republic of China.
  • Xiao-Yuan Zhang
    Department of Psychology, School of Public Health, Southern Medical University, Guangzhou, People's Republic of China.

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