## 4 Survey Results and Analysis
### Exploratory Factor Analysis
#### 4.3.1 Correlation Matrix Analysis  
Using SPSS 23.0 software [24; 37; 41; 42; 48; 49; 50; 51; 52], we determine the first correlation matrix for the 14 QIs (I.01 \(\div\) I.14). First, the calculated significance values are analyzed from the analysis of the \"significance values\" data presented in the second part of the table specific to the correlation matrix (Sig 1-tailed); it can be observed that in addition to the values of \(<\)0.001, some values of 0.001, 0.002 were also obtained, plus 0.014 and 0.144. The value of 0.144 (specific to item I.07) proves that the statistical significance threshold (\(p<0.05\)) was not met, stating that the correlation is not significant for item I.07 (there is no significant link between the item I.07 and the other variables), and therefore the calculation will be redone with the removal of item I.07.  
Second, we analyze the first part of the table (Correlation); it can be noted that all the values of item I.07 are negative compared to the positive values of the other 13 items, which demonstrates the increasing trend of the results of the 13 items in contradiction with the decreasing trend of the results of item I.07 (inverse proportionality).  
The results obtained in the calculation of the final correlation matrix after removing item I.07 are presented in Table 6.  
Analyzing the data presented in Table 6, the correlation matrix, the following aspects can be observed:  
* From the analysis of the significance of the values (\"significance values\") data presented in the second part of the table specific to the Sig 1-tailed correlation matrix (one-way significance threshold), it is observed that most of the values of the variables are \(<\)0.001 or 0.001, so the condition has been met of the statistical significance threshold (\(p<0.05\));
* The final result (present at the bottom of the table) is \(2.25\times 10^{-5}\) (Determinant = \(2.25\times 10^{-5}\)) greater than the value of 0.00001, so there is no situation of multicollinearity for the items (multicollinearity occurs when a group of independent variables are strongly  
\begin{table}
\begin{tabular}{c l c c c} \hline \hline
**Code** & **Questionnaire Items (QIs)** & **Worker/ Team Leader** & **Worker/ TESA** & **Team Leader/ TESA** \\ \hline I.01 & I use frequently the internet & 0.525 & \(<\)0.001 * & 0.037 * \\ I.02 & I use internet easily & 0.001 * & \(<\)0.001 * & 0.041 \\ I.03 & I find easy the registration/training/testing steps in the & \(<\)0.001 * & \(<\)0.001 * & 0.516 \\ I.04 & I think that I increase my knowledge through online & 0.620 & 0.001 * & 0.585 \\  & training, compared to other forms of training & 0.012 * & \(<\)0.001 * & 1.000 \\ I.05 & I think that using an electronic signature to record OSH & 0.012 * & \(<\)0.001 * & 1.000 \\ I.06 & I think that online OSH training is a better method & 0.065 & \(<\)0.001 * & 1.000 \\ I.07 & I think that traditional training (face-to-face/classroom) & 0.691 & 0.051 & 0.013 * \\ I.08 & I think that video conference training provides a better & 0.084 & 0.001 * & 1.000 \\  & experience than traditional (face-to-face) training & & & \\ I.10 & I am satisfied with understanding the material in the & & 0.200 & 0.081 & 1.000 \\  & online training & & & \\ I.14 & I am satisfied with the online training in general & 0.012 * & \(<\)0.001 * & 1.000 \\ \hline \hline \end{tabular}  
* Significant difference level at \(p<0.05\).  
\end{table}
Table 5: Results for post hoc [PERSON]’s multiple comparison test.  
correlated with each other), which means not having to eliminate any item from the questionnaire;
* From the analysis of the values of the correlation coefficients (in the first part of the table--Correlation), no values higher than 0.900 are observed, which means that there is no question of the singularity of the data (a fact that does not indicate a high correlation between the items); the highest value in the table is 0.817.