住宅项目施工人员的人口学特征与心理社会工作条件的关系

Q3 Engineering
N. Suriyanon, Pitch Sutheerawatthana
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引用次数: 0

摘要

2018年10月,收集了曼谷八个分区住房项目438名建筑工人的三个心理社会因素数据,这些项目的售价在250万至500万泰铢之间。受试者被分为两组。第一组由71名在高压力隔离(HSI)心理社会工作条件下工作的工人组成(工人认为他们的工作需要高需求,他们对工作的可控性低,与工作相关的社会支持低)。第二组由367名在其他条件下工作的工人组成。工人的人口统计学特征与其心理社会工作条件之间的卡方检验结果表明,不同性别、年龄、教育水平、工作经验、工作岗位和月平均收入的工人在HSI条件下工作的概率不同。它坚持建筑工人在HSI条件下工作的异质性。本研究利用工人的人口统计学特征,建立了一个用于预测HSI条件下工作概率的逻辑回归模型。该模型由五个人口特征变量组成,即工作岗位、教育水平、月平均收入、工作经验和年龄。通过对模型常数的分析得出的调整后的比值比值表明,工作岗位、月平均收入、年龄、教育水平和工作经验对工人在HSI条件下工作的概率有降序影响。最后,本文最后给出了一个应用该模型识别需要特别关注的工人的特定人口特征的例子。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Relationship between demographic characteristics and psychosocial working conditions of construction workers in housing projects
Data regarding three psychosocial factors of 438 construction workers in eight Bangkok subdivision housing projects, which had a selling price between 2.50 and 5.00 million Baht, were collected in October 2018. The subjects were divided into two groups. The first group consisted of 71 workers who worked under high strain isolated (HSI) psychosocial working condition (workers felt that their work entailed high demand, they possessed a low controllability over their job and low work–related social support). The second group consisted of 367 workers who worked under other conditions. The result from the chi-square test between workers’ demographic characteristics and their psychosocial working conditions revealed that the probability of working under HSI condition for workers with different Gender, Age, Education Level, Work Experience, Work Position, and Average Monthly Income are different. It insisted the heterogeneity of working under HSI condition among construction workers. A logistic regression model for forecasting the probability of working under HSI condition, using the workers’ demographic characteristics, has then been developed in this study. The model consists of five demographic characteristic variables, namely Work Position, Education Level, Average Monthly Income, Work Experience, and Age. The adjusted odds ratio value, which was obtained from the analysis of the model constants, indicates that Work Position, Average Monthly Income, Age, Education Level, and Work Experience have influence on workers’ probability of working under HSI condition in descending order. Finally, an example of applying the model to identify specific demographic characteristics of workers who need special attention is presented at the end of this paper.
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CiteScore
2.00
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