# A Test Platform for Managing School Stress Using a Virtual Reality Group Chatbot Counseling System
## 3 Methodology  
The focus of this research is to develop a test base VR group counseling (VRGC) system that can be used to help students relieve stress at school. Figure 1 depicts VRGC research that assists students in solving stress problems, including the interaction of development, clinical experiments, analysis, and system verification processes. First, the problem was defined, and two solutions were introduced: psychotherapy and immersion technology. The background literature and patent collection provided the basic knowledge base, and hypotheses for expected results were written. The literature review includes aspects of VR, group counseling, and psychological scales. Then the test base counseling system was developed. The system included three parts: a stress survey to measure the stress of subjects, counseling scripts to interact with users, and the VR environment. The subjects were recruited in the classroom to participate in the experiment and follow-up data analysis was performed. To develop a deeper understanding of the stress and needs of students, an additional off-line survey was added to this research to collect the responses of college students. Individuals who measured high in stress were invited to use the VR system. This research has completed the preliminary system design and has recruited subjects to fill out the questionnaire and completed the analysis of the questionnaire. Inviting subjects to participate in various VRGC clinical trial experiments  
Figure 1: VRGC research flow. will be carried out in follow-up research. The test platform will be redesigned and refined to enhance validity and reliability through medical clinical trials. This study uses the results of the questionnaire (see Appendix B) to measure the subjects' mental state of stress related to school. The questionnaire consists of two parts. The first part includes two questions using a 10-point Likert scale to measure the degree of stress and the ability to cope with stress, and a series of questions with 5-point Likert scale to measure the impact of stress on life [28]. The second part is PCL-5, which is used to measure the severity of the subjects' stress [29] and shows strong internal consistency and discriminant validity [30]. Respondents rate each of 20 items that have bothered them in the past month with a 5-point Likert scale. A cut-point score of 32 (range = 0 to 80) was made by the National Center for PTSD in the United States [29]. According to the previous relevant psychological research, the agency suggested that the cut-point is 31 to 33 points, so this research adopts an average of 32. The stress level on the first scale was used for preliminary screening, and the median split was applied to screen out subjects with greater stress levels [31]. Then the cut-point score of 32 was used for the second scale to further filter the subjects. The system framework is shown in Figure 2. First, a survey module is created. This module includes problems such as the degree of stress, the source of stress, and the severity of stress which are used to measure the psychological state of subjects. The counseling module is divided into two parts, consisting of a chatbot or real counselor (chatroom). The system will suggest that subjects choose a chatbot or a real counselor based on the questionnaire results and the subjects' related information. All of the modules require subjects to be connected to the server with a VR device. The system records the subject's questionnaire scores and the content of the conversation and converts these data into information to be stored in the database. Figure 2: System framework. The therapists contribute their knowledge to the chatbot and create an avatar to connect to the group therapy environment (chatroom). Subjects can wear VR headsets and directly use the chatbot, or they can create their own avatars to join the chatroom. All the VR scenes are managed by servers provided by Photon. For record tracking of subjects, the server connects to the database.