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Information overload regarding COVID-19: Adaptation and validation of the cancer information overload scale

机译:关于Covid-19的信息过载:癌症信息超载量表的适应和验证

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Background: Access to excessive information from multiple sources relating to COVID-19 in a short span of time can have detrimental effects on individuals. Aim: The study aims to validate Corona Information Overload Scale (CoIOS) by adaptation of Cancer Information Overload scale (CIOS) on English speaking Indian citizens. Materials and Methods: An online survey was carried out using Google Form on 300 individuals out of whom 183 responded. The CoIOS was to be filled up. It was an 8 item Likert type scale with responses ranging from “strongly agree” to “strongly disagree.” Results: Principal components analysis showed two components with an initial eigenvalue unity (3.38 and 1.09), with 42.33% and 13.64% of variance, respectively, making a total of 55.97% variance. The composite reliability value was also found to be 0.789 and 0.815 for factors I and II, respectively, convergent validity and discriminant validity calculation also affirmed good construct reliability. Conclusion: CoIOS appears to be a valid and reliable scale for measuring health information overload in relation to COVID-19. However, it has a two factor component, namely “excessiveness of information” and “rejection of information.”.
机译:背景:在短时间内,访问与Covid-19相关的多个源过多的信息可能对个体产生不利影响。目的:该研究旨在通过对英语英语印度公民的癌症信息过载量表(CIO)进行验证电晕信息过载量表(CoIS)。材料和方法:在183名响应的300个人中使用Google表格进行了在线调查。十字架要填补。这是一个8件李克特类型规模,响应从“非常同意”到“非常不同意”。结果:主要成分分析显示了初始特征值>统一(3.38和1.09)的两种组分,分别具有42.33%和13.64%的差异,总共方差为55.97%。因素I和II还发现复合可靠性值为0.789和0.815,收敛有效性和判别有效性计算也肯定了良好的构造可靠性。结论:同步似乎是一种有效且可靠的规模,用于测量与Covid-19有关的健康信息过载。然而,它有两个因素组成部分,即“信息的过度”和“拒绝信息”。

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