Psychometric Evaluation of the Serbian Adaptation of the Presentation of Online Self Scale (POSS) and Further Construct Validation

在线自我呈现量表(POSS)塞尔维亚语版的心理测量学评价及进一步的结构效度验证

阅读:1

Abstract

The Presentation of Self Scale (POSS) was designed to measure four aspects of online self-presentation behaviour: Ideal self, Multiple selves, Consistent self, and Online presentation preference. Very few scales have been developed to measure online-self presentation attitudes and behaviour in Serbia. Thus, there is a need to validate a Serbian language version of the POSS to support further investigation of an increasingly ubiquitous aspect of the daily lives of Serbian people. This study aimed to examine psychometric properties of the POSS in the Serbian context i.e., its reliability, factor validity, and construct validity. The study was conducted on a sample of 360 adults. The four-factor model was confirmed, and it is invariant across genders. The Ideal self, Multiple selves, and Online presentation preference scales converge and show a similar pattern of relationships with validity variables, with Ideal self and Multiple selves showing high profile similarity. These three scales are associated with less sensitivity to the expressive behaviour of others, greater fear of negative evaluation, social media addiction, anxiety, lower self-esteem, and less loneliness. On the other hand, the Consistent self-scale is generally unrelated to the other POSS scales and correlates with better sensitivity to the expressive behaviours of others, less fear of negative evaluation, but greater loneliness. The POSS proved to be useful for examining self-presentation behaviours in the Serbian cultural context. The study revealed two main self-presentational patterns: one that is inauthentic and facilitated by the features of online communication and the other that is authentic and related to better social sensitivity.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。