2021
DOI: 10.2147/prbm.s312897
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A Preliminary Validation of the Polish Version of the Social Media Fatigue Scale

Abstract: Background: As social media fatigue is a newly described phenomenon, we do not possess many tools to measure this concept. The main aim of the study was to establish a latent structure of the Social Media Fatigue Scale (SMFS) and to identify whether the Polish version is congruent with the Chinese version. The second aim was to examine whether the factor structure fits the data and yields a comparable goodness-of-fit index. The third aim was to consider the convergent validity of the SMFS and to verify whether… Show more

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Cited by 8 publications
(13 citation statements)
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References 60 publications
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“…Regarding the CFA, before proceeding with this analysis we checked for the normality of the indicators using AMOS. Next, we took into account the most universal fit indices to estimate the model: (1) Chi-square test not significant; (2) CMIN/DF < 3; (3) Goodness-of-Fit Index (GFI) > 0.9, Adjusted Goodness-of-Fit Index (AGFI) > 0.9, and Comparative Fit Index (CFI) > 0.9; (4) Root Mean Square Errors of Approximation (RMSEA) ≤ 0.06; with the confidence interval of LO and HI between 0.05 and 0.08; (5) Standardized Root Mean Squared less than 0.05; (6) 0.05 ≤ PCLOSE ≤ 1; (7) CN HOELTER index 0.05 and 0.01 ≥ 200 (Bollen and Liang 1988;Mueller and Hancock 2008;Świ ątek et al 2021). Since our samples were relatively large and were at risk of a not significant Chi-square, we opted for the CN to determine the adequacy of the samples (Froiland et al 2019).…”
Section: Discussionmentioning
confidence: 99%
“…Regarding the CFA, before proceeding with this analysis we checked for the normality of the indicators using AMOS. Next, we took into account the most universal fit indices to estimate the model: (1) Chi-square test not significant; (2) CMIN/DF < 3; (3) Goodness-of-Fit Index (GFI) > 0.9, Adjusted Goodness-of-Fit Index (AGFI) > 0.9, and Comparative Fit Index (CFI) > 0.9; (4) Root Mean Square Errors of Approximation (RMSEA) ≤ 0.06; with the confidence interval of LO and HI between 0.05 and 0.08; (5) Standardized Root Mean Squared less than 0.05; (6) 0.05 ≤ PCLOSE ≤ 1; (7) CN HOELTER index 0.05 and 0.01 ≥ 200 (Bollen and Liang 1988;Mueller and Hancock 2008;Świ ątek et al 2021). Since our samples were relatively large and were at risk of a not significant Chi-square, we opted for the CN to determine the adequacy of the samples (Froiland et al 2019).…”
Section: Discussionmentioning
confidence: 99%
“…The Social Media Fatigue Scale (SMFS) published in 2021 by Zhang et al (Collaborative Innovation Cen-tre of Assessment for Basic Education Quality, Beijing Normal University, Beijing, China) consists of 15 statements [2]. We used the Polish adaptation of the scale developed by Świątek et al [9]. This 3-factor model uses a 7-point Likert scale (1 -strongly disagree, 2 -disagree, 3 -rather disagree, 4 -have no opinion, 5 -tend to agree, 6 -agree, 7 -strongly agree) to assess the level of social media fatigue in 3 subscales: cognitive aspects -5 statements, behavioural aspects -5 statements, and emotional aspects -5 statements.…”
Section: Instrumentmentioning
confidence: 99%
“…The Social Media Fatigue Scale (SMFS) was developed by Zhang et al 12 and adapted into Polish by Świątek et al 1 It is a 15-item scale which measures three dimensions of tiredness with social networks. The cognitive dimension refers to information overload (eg: "I am frequently overwhelmed by the amount of information available on social media sites").…”
Section: Social Media Fatiguementioning
confidence: 99%
“…This phenomenon is typically called social network/networking services/media fatigue. 1 Since social media fatigue (SMF) is the most commonly used term, we assumed it in the current study.…”
Section: Introductionmentioning
confidence: 99%