Analysis Sequence | Description | Rationale |

1 | Data screening | To detect Outliers with Mahalanobis distance control. |

2 | Multivariate Normality Test with Multiple tests | To test the multivariate normality assumption with Mardia’s multivariate kurtosis and multivariate skewness test, Henze–Zirkler’s consistent test, Doornik-Hansen omnibus test, and Energy test. |

3 | Confirmatory Factor Analysis (CFA) of the study measures | To confirm structure in this sample. |

4 | Descriptive Statistics | To calculate means, medians, standard deviations, and reliability coefficients (see |

5 | Test the SEM measurement model fit and indicator reliability | To evaluate the fit of the measurement model since four out of five measures were partially used. Reliability of the observed variables was evaluated to reject the likelihood that the exogenous constructs are redundant or they have a multicollinearity problem. |

6 | Model-based Reliability and Validity Analysis of the latent variables in the measurement model | To evaluate the Composite Reliability (CR; |

7 | Cross-validating model-based Discriminant Validity with additional methods | To cross-validate model-based discriminant validity with the |

8 | Full measurement invariance of the SEM measurement model | To test if the measurement model has invariant factors, factor loadings, intercepts, and residuals across gender. |

9 | Test the full SEM model fit | To evaluate the structural model fit. |

10 | A priori & post hoc power analysis of the full SEM model with the RMSEA | To evaluate the sample required for 80% power to reject a wrong model. An alpha level of 0.05 was assumed with RMSEA misspecification 0.05 |

11 | Hypotheses testing (H1-H4) | Ten direct paths were specified. |