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自我报告的 COVID-19 预防指南遵守情况的预测因素:分位数回归模型。

Predictors of Self-Reported Compliance with COVID-19 Preventive Guidelines: A Quantile Regression Model.

机构信息

Center for Health Related Social and Behavioral Sciences Research, Shahroud University of Medical Sciences, Shahroud, Iran.

Ophthalmic Epidemiology Research Center, Shahroud University of Medical Sciences, Shahroud, Iran.

出版信息

Soc Work Public Health. 2022 Oct 3;37(7):643-654. doi: 10.1080/19371918.2022.2071372. Epub 2022 Apr 28.

DOI:10.1080/19371918.2022.2071372
PMID:35484901
Abstract

The research used an online, convenience cross-sectional sample of adults aged ≥18 years old recruited from Shahroud County, Northeast of Iran. We measured the contribution of multiple determinants for association with behavioral compliance, at the time of the COVID-19 pandemic. The compliance score measured with this questionnaire can be within a range of 5 and 100. Compliance was bounded between 19 and 80 that has been distributed J-shape, so quantile logistic regression model has been fitted for that. Variables related to people's knowledge, including self-reported knowledge and following the news related to COVID-19, were the two main factors that accompanied behavioral compliance at all of its levels in the period of pandemic.

摘要

这项研究使用了一种在线便利的横断面样本,样本由伊朗东北部沙赫鲁德县≥18 岁的成年人组成。我们测量了在 COVID-19 大流行期间,与行为遵从性相关的多种决定因素的贡献。该问卷测量的遵从评分范围在 5 到 100 之间。遵从性的范围在 19 到 80 之间,呈 J 形分布,因此,针对该范围拟合了分位数逻辑回归模型。在大流行期间,与人们的知识相关的变量,包括自我报告的知识和关注与 COVID-19 相关的新闻,是伴随行为遵从性的两个主要因素,而且在所有水平上都存在这种关系。

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