验证性因素分析
探索性因素分析
心理学
社会化媒体
感觉
社会认知理论
比例(比率)
符号的认知维度
认知
临床心理学
透视图(图形)
社会心理学
结构方程建模
应用心理学
心理测量学
计算机科学
统计
人工智能
数学
万维网
精神科
物理
量子力学
作者
Shiyi Zhang,Yanni Shen,Tao Xin,Haoqi Sun,Yilu Wang,Xiaotong Zhang,Siheng Ren
出处
期刊:PLOS ONE
[Public Library of Science]
日期:2021-01-22
卷期号:16 (1): e0245464-e0245464
被引量:30
标识
DOI:10.1371/journal.pone.0245464
摘要
Social media fatigue (SMF), which refers to social media users’ tendency to withdraw from social media because of feeling overwhelmed, is closely related to individuals’ social life and well-being. Many studies focused on understanding SMF and exploring its enablers and influences. However, few pieces of research administered a standard measurement of SMF. This study aimed to develop and validate a measure of SMF, and a cross-sectional survey was conducted among 1599 participants in total. Semi-structured interviews of 30 participants were firstly conducted as a pilot study, and an initial version of the social media fatigue scale (SMFS) with 24 items was generated. Then, both exploratory factor analysis (N = 509) and confirmatory factor analysis (N = 552) as well as reliability and validity analysis (N = 508) were conducted and a 15-item SMFS was finally developed. The results demonstrated that: 1) SMF was a multi-dimension concept including a cognitive aspect, an emotional aspect and a behavioral aspect; 2) the three-dimensional structure of the SMFS (cognitive-behavioral-emotional structure) fitted the data well; 3) the McDonald’s Omega coefficients for the SMFS was 0.83, suggesting that the SMFS was reliable; 4) criterion validity was satisfactory as indicated by both the significant correlations between self-rated scores of fatigue and total SMFS scores and the significant regression model of SMF on social media privacy, social media confidence, and negative feeling after comparison. Based on the Limited Capacity Model, the present study expanded SMF from a unidimensional model to a three-dimension model, and developed a 15-item SMFS. The study enriched the existing knowledge of SMF, and coined a reliable and valid tool for measuring it. Besides, concluding the typical characteristics of SMF, the study may provide some inspiration for both researchers and social media managers and operators in mitigating SMF.
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