The Exploratory Factor Analysis (EFA) was conducted using Principal Axis Factoring as the extraction method and Varimax rotation with Kaiser Normalization. These methods ...
The Exploratory Factor Analysis (EFA) was conducted using Principal Axis Factoring as the extraction method and Varimax rotation with Kaiser Normalization. These methods were chosen to identify the underlying factor structure and to achieve a clearer separation of factors.
The Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy was 0.812, indicating that the data were suitable for factor analysis. Additionally, Bartlett’s Test of Sphericity was significant (χ² = 388.256, p < .001), confirming that the variables were sufficiently correlated to proceed with EFA.
A total of 10 items were included in the analysis, and 3 factors were retained based on eigenvalues greater than 1 and the total variance explained (67.24%). The rotated component matrix showed that most items loaded clearly onto one factor, supporting the theoretical structure.
However, a few items showed cross-loadings (e.g., Item 6 and Item 8), which may indicate some overlap between constructs. These items may need to be revised or removed in future analysis to improve the clarity of the factor structure.