## 5 Results and Discussion
### The Structural Model Test  
After confirming the measurement model, we tested the independent relationships (H1 to H6) among the study's proposed constructs using variance-based structural equation modeling (SEM) with the collected data. We formulated the structural model with SmartPLS 2.0, generating two important values: The path coefficients (standardized betas: \(\beta\)) and the squared multiple correlations (R\({}^{2}\)) value for each endogenous variable. Path coefficients indicate the strength of the relationships between two constructs. Acceptance or rejection of hypotheses is based on the value of the path coefficient along with the corresponding \(t\)-value. The squared multiple correlations (R\({}^{2}\)) value for each endogenous construct indicates the predictive power of the research model [47]. The R\({}^{2}\) values can be used to determine the amount of variance explained by exogenous constructs within the structural model [51]. As shown in Figure 3, we found that three external constructs had significant positive impacts on SNS fatigue, which was also significantly associated with living disorder, though the strengths of the paths varied. First, irrelevant information overload had a standardized path coefficient of 0.297 with a \(t\)-value of 4.120, which was significant at \(p<0.01\). Thus, H1 was supported. This result implies that there is a large amount of information on SNSs, but much of it is not relevant to users' purposes. This predominance of irrelevant information makes it necessary for SNS users to spend considerable time searching for the information they want. This phenomenon can cause immense mental and physical fatigue among SNS users. In this regard, [PERSON] and [PERSON] [3] argued that SNSs are the main gateway to substantial information production, but that excessive unnecessary information is generated, which may increase fatigue by increasing SNS users' Internet usage time. Second, we found that engagement (\(\beta\) = 0.323, \(t\)-value = 5.129) and maintaining self-reputation (\(\beta\) = 0.406, \(t\)-value = 5.235) were positively associated with SNS fatigue. Thus, H3 and H4 were supported at \(p<0.01\). These results concern SNS users' personal use habits, suggesting that users become immersed in SNSs to express themselves on the web, and this phenomenon results in transient SNS use, resulting in fatigue. Prior studies e.g., [10; 52] have shown that transient commitment to specific services produced negative results. In addition, many SNS users share information about their interests on the web with others, and constantly strive to maintain their reputations by garnering praise from others who use this information. This process leads to excessive SNS use, resulting in \begin{table}
\begin{tabular}{l c c c c c c c c} \hline \hline
**Latent Construct** & **(1)** & **(2)** & **(3)** & **(4)** & **(5)** & **(6)** & **(7)** & **(8)** \\ \hline (1) Irrelevant Information Overload & **0.771** & & & & & & & \\ (2) Open Reachability & 0.283 & **0.767** & & & & & & \\ (3) Engagement & 0.304 & 0.267 & **0.825** & & & & & \\ (4) Maintaining Self-Reputation & 0.197 & 0.223 & 0.300 & **0.828** & & & & \\ (5) SNS Fatigue & 0.273 & 0.281 & 0.315 & 0.410 & **0.848** & & & \\ (6) Living Disorder & 0.362 & 0.406 & 0.299 & 0.324 & 0.283 & **0.867** & & \\ (7) Experience of Privacy Violations & 0.291 & 0.472 & 0.313 & 0.357 & 0.260 & 0.400 & **0.820** & \\ (8) Reduced Intention to Use SNSs & 0.416 & 0.403 & 0.355 & 0.327 & 0.394 & 0.286 & 0.367 & **0.823** \\ \hline \hline \end{tabular} Note: The values in bold are the AVE (average variance extracted) square root values.  
\end{table} 
Table 7: Discriminant validity test. mental and physical fatigue [20]. Among the three constructs, maintaining self-reputation had the greatest effect on SNS fatigue. Meanwhile, we did not find a significant association between open reachability and SNS fatigue; therefore, H2 was rejected. These results can be interpreted as evidence that users use SNS in self-centered manners.