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在一项混合方法研究中,通过比较基于聊天机器人的方法与感知压力问卷(PSQ20)来评估医学生的感知压力水平。

Assessing medical students' perceived stress levels by comparing a chatbot-based approach to the Perceived Stress Questionnaire (PSQ20) in a mixed-methods study.

作者信息

Moldt Julia-Astrid, Festl-Wietek Teresa, Mamlouk Amir Madany, Herrmann-Werner Anne

机构信息

TIME - Tübingen Institute for Medical Education, University Hospital Tuebingen, Tuebingen, Germany.

Institute for Neuro- and Bioinformatics, University of Luebeck, Luebeck, Germany.

出版信息

Digit Health. 2022 Nov 22;8:20552076221139092. doi: 10.1177/20552076221139092. eCollection 2022 Jan-Dec.

Abstract

OBJECTIVE

Digital transformation in higher education has presented medical students with new challenges, which has increased the difficulty of organising their own studies. The main objective of this study is to evaluate the effectiveness of a chatbot in assessing the stress levels of medical students in everyday conversations and to identify the main condition for accepting a chatbot as a conversational partner based on validated stress instruments, such as the Perceived Stress Questionnaire (PSQ20).

METHODS

In this mixed-methods research design, medical-student stress level was assessed using a quantitative (digital- and paper-based versions of PSQ20) and qualitative (chatbot conversation) study design. PSQ20 items were also shortened to investigate whether medical students' stress levels can be measured in everyday conversations. Therefore, items were integrated into the chat between medical students and a chatbot named Melinda.

RESULTS

PSQ20 revealed increased stress levels in 43.4% of medical students who participated (  =  136). The integrated PSQ20 items in the conversations with Melinda obtained similar subjective stress degree results in the statistical analysis of both PSQ20 versions. Qualitative analysis revealed that certain functional and technical requirements have a significant impact on the expected use and success of the chatbot.

CONCLUSION

The results suggest that chatbots are promising as personal digital assistants for medical students; they can detect students' stress factors during the conversation. Increasing the chatbot's technical and social capabilities could have a positive impact on user acceptance.

摘要

目的

高等教育中的数字化转型给医学生带来了新的挑战,增加了他们自主安排学习的难度。本研究的主要目的是评估聊天机器人在日常对话中评估医学生压力水平的有效性,并根据经过验证的压力测量工具,如感知压力问卷(PSQ20),确定将聊天机器人作为对话伙伴接受的主要条件。

方法

在这项混合方法研究设计中,采用定量(PSQ20的数字版和纸质版)和定性(聊天机器人对话)研究设计评估医学生的压力水平。还对PSQ20的项目进行了简化,以研究是否可以在日常对话中测量医学生的压力水平。因此,这些项目被整合到医学生与名为梅林达的聊天机器人之间的对话中。

结果

PSQ20显示,参与研究的43.4%的医学生(n = 136)压力水平有所增加。在与梅林达的对话中整合的PSQ20项目在两个PSQ20版本的统计分析中获得了相似的主观压力程度结果。定性分析表明,某些功能和技术要求对聊天机器人的预期使用和成功有重大影响。

结论

结果表明,聊天机器人有望成为医学生的个人数字助手;它们可以在对话中检测学生的压力因素。提高聊天机器人的技术和社交能力可能会对用户接受度产生积极影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b36f/9706047/6c0e1bd9ef29/10.1177_20552076221139092-fig1.jpg

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