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探索建筑工人对虚拟现实培训系统的接受度：一种结合结构方程建模和人工神经网络的方法。

Exploring the acceptance of virtual reality training systems among construction workers: a combined structural equation modeling and artificial neural network approach.

作者信息

Liu Hui, Miao Xinyue, Shi Chunyan, Xu Tongyu

机构信息

School of Emergency Science and Engineering, Jilin Jianzhu University, Changchun, China.

The University of Kitakyushu, Fukuoka, Japan.

出版信息

Front Public Health. 2024 Dec 18;12:1478615. doi: 10.3389/fpubh.2024.1478615. eCollection 2024.

DOI:10.3389/fpubh.2024.1478615
PMID:39744356
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11688313/
Abstract

Virtual Reality Training System (VRTS) has been verified effective in safety training in the construction field. However, in China, it is not widely used as a regular training tool. Among all the reasons, the acceptance level of construction workers (CWs) has the decisive impact on the promotion of VRTS. In view of this, this study is devoted to constructing a training model of CWs' acceptance level of VRTS training that integrates the technology acceptance level model with the theory of planned behavior. What's more, this paper innovatively introduces three crucial elements of external influences, namely, risk perception (RP), safety climate (SC) and self-efficacy (SE). In order to more accurately figure out the linear and nonlinear relationship between every structure and the factors of CWs' acceptance level, 528 participating CWs in this study filled in structured questionnaires, through the data of which the analyzing process uses structural equation model and artificial neural network two-stage analysis method. Based on the analyzing results of the study, this paper put forward a series of specific strategies and suggestions to significantly promote the acceptance level of CWs to VRTS training considering the designment, the enterprises and the government.

摘要

虚拟现实培训系统（VRTS）已被证实对建筑领域的安全培训有效。然而，在中国，它作为一种常规培训工具并未得到广泛应用。在所有原因中，建筑工人（CWs）的接受程度对VRTS的推广具有决定性影响。有鉴于此，本研究致力于构建一个将技术接受程度模型与计划行为理论相结合的建筑工人对VRTS培训接受程度的培训模型。此外，本文创新性地引入了外部影响的三个关键要素，即风险感知（RP）、安全氛围（SC）和自我效能感（SE）。为了更准确地找出各结构与建筑工人接受程度因素之间的线性和非线性关系，本研究中的528名参与建筑工人填写了结构化问卷，通过这些数据，分析过程采用结构方程模型和人工神经网络两阶段分析方法。基于该研究的分析结果，本文从设计、企业和政府方面提出了一系列具体策略和建议，以显著提高建筑工人对VRTS培训的接受程度。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6029/11688313/717df57cf683/fpubh-12-1478615-g009.jpg
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