## 3 Results and Discussion
### Factor Analysis  
In Table 9, which shows explained variance; three factors explain 55.166% of the variance. These factors are extracted via the analysis of main components, and the criteria that support its application are the Kaiser-Meyer-Olkin measurement test result, which takes a value of 0.913, and the Bartlett sphericity test, in which the \(p\)-value \(<\) 0.05; hence, it makes sense to perform the factor analysis. With regard to the component matrix, to be able to perform the interpretation of the factors, we used Table 10 on the rotated component matrix by rotating varimax [39; 40; 41] to discover hidden relationships within the components and the respective indicators, which facilitates the interpretability of the factors. The table highlights values above 0.45 to achieve better exposure of the initial variables obtained for each component or factor. \begin{table}
\begin{tabular}{l c c} \hline Kaiser–Meyer–Olkin sampling adequacy measurement & 0.913 \\ [PERSON]’s sphericity test & Approx. Chi squared & 2748.056 \\ df & 120 \\ Sig. & 0.000 \\ \hline \end{tabular}
\end{table} 
Table 8: Kaiser–Meyer–Olkin and Bartlett Test. \begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline
**Component** & \multicolumn{3}{c}{**Initial Eigenvalues**} & \multicolumn{3}{c}{**Extraction Sums of Squared Loadings**} & \multicolumn{3}{c}{**Rotation Sums of Squared Loadings**} \\ \hline  & **Total** & **\% Variance** & **\% Gathered** & **Total** & **\% Variance** & **\% Gathered** & **Total** & **\% Variance** & **\% Gathered** \\ \hline
1 & 6.187 & 38.668 & 38.668 & 6.187 & 38.668 & 38.668 & 3.517 & 21.984 & 21.984 \\
2 & 1.453 & 9.084 & 47.752 & 1.453 & 9.085 & 47.752 & 2.917 & 18.231 & 40.214 \\
3 & 1.186 & 7.414 & 55.166 & 1.186 & 7.414 & 55.166 & 2.392 & 14.952 & 55.166 \\ \hline \hline \end{tabular}
\end{table} 
Table 9: Total explained variance. Extraction method: Principal component analysis. The matrix shows three components, where each component has 16 items, and on the basis of Table 10, we can interpret each of them:  
**Component 1:** This component includes the set of attributes of the nomophobia questionnaire that describe the students' sense of need to be with their smartphones. This component will consist of the following items: Q9, Q15, Q10, Q16, Q14 and Q8. They will be the factor that we call the \"Anxiety Sensation\" factor, which explains 38.668% of the total variability. The sense of anxiety of UNI students is related to the unfounded need for smartphones. This factor is basically caused by \"not being able to communicate\"; it refers to the feelings of losing instant communication with people and not being able to use the services that allow instant communication. **Component 2:** This component contains six variables that are considered to be within those that do not find alternative resources to entertain themselves. This component will consist of the following items: Q12, Q6, Q13, Q5, Q11 and Q7. They will be the factor that we call \"Compulsive Smartphone Use\" factor, which explains 9.084% of the total variability, and which is reflected in the students compulsive need to interact with their smartphones. This factor is basically caused by \"abuse and interference with other activities\"; it refers to the excessive use of mobile devices even in situations where such use is dangerous or inconvenient. **Component 3:** This includes the characteristics of low emotion. This component will consist of the following items: Q1, Q2, Q3 and Q4. They will be the factor that we call \"Anxiety and Panic Sensation\" factor, which explains 7.414% of the total variability. This factor reflects the mood of UNI students if they feel that they have been away from their smartphones for a long period of time. It is basically caused by \"abstinence\"; it refers to the withdrawal symptoms that appear if an addicted person cannot use the mobile.