Research on the Construction of Psychological Crisis Intervention Strategy Service System

Yahong Yao, Shaofu Lin*, Zhisheng Huang, Shushi Li, Chaohui Guo, Ying Wu

*Corresponding author for this work

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

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Abstract

Purpose: Traditional psychological crisis intervention requires one-to-one and long-term consultation by psychotherapists, which has high time cost and expense. The public has a strong realistic demand for more convenient psychological crisis intervention services. In order to solve the above problem, this paper presents an approach which transforms the actual professional psychological consultation data into knowledge graph, establishes a terminology/ontology of psychological crisis intervention, and constructs an automatic service prototype system of psychological crisis intervention. Method: This paper takes actual professional psychological crisis intervention cases as prior knowledge, expresses and stores them in the form of triples. The natural language generation model based on GPT-2 model is constructed by using the data in PsyQA as the training set for several rounds of training. The terminology of psychological crisis intervention is constructed. Then the psychological crisis intervention system is constructed, including modules as keyword extraction, deep semantic matching, knowledge graph retrieval crisis intervention strategy providing module and natural language generation. Result: The test results show that for the users which can correctly input the psychological problem description text, the system can Identify crisis types, provide the corresponding intervention strategies and return the targeted crisis intervention text. Conclusion: This system avoids the constraints of traditional crisis intervention such as high price, poor timeliness and few professionals, and provides a feasible method for people who need to get simple crisis intervention services in time.

Original languageEnglish
Title of host publicationHealth Information Science
Subtitle of host publication11th International Conference, HIS 2022, Virtual Event, October 28–30, 2022, Proceedings
EditorsAgma Traina, Hua Wang, Yong Zhang, Siuly Siuly, Rui Zhou, Lu Chen
PublisherSpringer Science and Business Media Deutschland GmbH
Pages209-216
Number of pages8
ISBN (Electronic)9783031206276
ISBN (Print)9783031206269
DOIs
Publication statusPublished - 2022
Event11th International Conference on Health Information Science, HIS 2022 - Virtual, Online
Duration: 28 Oct 202230 Oct 2022

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13705 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference11th International Conference on Health Information Science, HIS 2022
CityVirtual, Online
Period28/10/2230/10/22

Bibliographical note

Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Keywords

  • Knowledge graph
  • Mental health
  • Natural language processing
  • Psychological crisis intervention

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