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Psychotherapy01:28

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Psychotherapy is a versatile, nonmedical approach aimed at helping individuals address emotional, behavioral, and interpersonal issues to enhance their overall well-being. It can involve one-on-one sessions, couples counseling, or small group discussions with a therapist. The therapeutic process includes various techniques such as open discussion, interpretation of thoughts and behaviors, active listening, positive reinforcement, and role modeling. Psychotherapy aims to support individuals in...
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Correlation Analysis Between Japanese Literature and Psychotherapy Based on Diagnostic Equation Algorithm.

Jun Shen1, Leping Jiang2

  • 1School of Foreign Languages, Changshu Institute of Technology, Suzhou, China.

Frontiers in Psychology
|June 16, 2022
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Summary

This study introduces a novel hybrid neural network model for analyzing Japanese healing literature. The model accurately quantifies psychotherapy effects, enhancing mental health research through literary analysis.

Keywords:
BiGRUJapanese literatureText-CNNattention mechanismequation diagnostic algorithmspsychotherapy

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Area of Science:

  • Computational Linguistics
  • Psychology
  • Digital Humanities

Background:

  • Literary therapy is a growing field with implications for modern mental health.
  • Quantitative evaluation of psychotherapy effects in Japanese healing literature is a current research focus.

Purpose of the Study:

  • To develop and validate a novel computational model for analyzing the correlation between Japanese healing literature and psychotherapy effects.
  • To enhance the accuracy and adaptability of quantitative methods in literary therapy research.

Main Methods:

  • Utilized a text convolutional neural network (Text-CNN) for multi-granularity feature extraction.
  • Employed a Bidirectional Gated Recurrent Unit (BiGRU) to model the relationship between literature and psychotherapy outcomes.
  • Developed a parallel hybrid network integrating CNN, BiGRU, and an attention mechanism for comprehensive analysis.

Main Results:

  • The proposed hybrid model demonstrated improved accuracy in classifying the correlation between literature and psychotherapy.
  • Experimental verification confirmed the model's strong adaptability and effectiveness in analyzing healing literature.

Conclusions:

  • The developed attention-integrated hybrid network offers a robust tool for quantitative analysis in literary therapy.
  • This approach advances the understanding of psychotherapy effects within Japanese healing literature, contributing to mental health research.