Psychometric Properties of the Moral Disengagement through Technologies Questionnaire (MDTech-Q) in a Sample of Chilean University Students
Abstract
:1. Introduction
2. Materials and Methods
2.1. Participants
2.2. Instruments
2.3. Procedure
2.4. Data Analysis
3. Results
3.1. Descriptive Analysis
3.2. Factorial Structure
3.3. Factorial Invariance
3.4. Evidence of Reliability
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Mean | Standard Deviation | Skewness | Kurtosis | |
---|---|---|---|---|
| 1.61 | 0.83 | 1.26 | 0.92 |
| 1.91 | 1.05 | 1.01 | 0.10 |
| 1.46 | 0.68 | 1.58 | 2.69 |
| 1.63 | 0.89 | 1.41 | 1.42 |
| 1.36 | 0.67 | 1.89 | 3.29 |
| 1.38 | 0.71 | 2.31 | 6.46 |
| 1.31 | 0.62 | 2.40 | 6.96 |
| 1.42 | 0.75 | 2.06 | 4.44 |
| 1.24 | 0.58 | 2.99 | 1.74 |
| 1.22 | 0.55 | 3.13 | 12.41 |
| 1.19 | 0.49 | 3.02 | 11.42 |
| 1.31 | 0.60 | 2.23 | 5.43 |
| 1.64 | 0.99 | 1.59 | 1.79 |
| 1.56 | 0.83 | 1.49 | 1.91 |
| 1.54 | 0.78 | 1.46 | 1.89 |
| 1.61 | 0.90 | 1.55 | 1.87 |
Variable | Model | SB − χ2 (df) | CFI | TLI | RMSEA | Comp. | ΔSB − χ2 | Δgl | p (ΔSB − χ2) |
---|---|---|---|---|---|---|---|---|---|
Sex | 1 M0 | 279.732 (196) | 0.958 | 0.948 | 0.040 | ||||
2 M1 | 287.340 (208) | 0.960 | 0.954 | 0.038 | 2 vs. 1 | 9.223 | 12 | 0.684 | |
3 M2 | 306.161 (220) | 0.956 | 0.952 | 0.039 | 3 vs. 2 | 19.665 | 12 | 0.0737 | |
Social media use | 1 M0 | 300.568 (196) | 0.954 | 0.943 | 0.045 | ||||
2 M1 | 305.138 (208) | 0.957 | 0.950 | 0.042 | 2 vs. 1 | 6.353 | 12 | 0.8973 | |
3 M2 | 317.230 (220) | 0.957 | 0.953 | 0.041 | 3 vs. 2 | 9.219 | 12 | 0.6841 |
Sex | Social Media Use | |||
---|---|---|---|---|
Factors | Student’s t-Test (df) | Cohen’s d | Student’s t-Test (df) | Cohen’s d |
Moral Justification through Technology | 5.292 ** (527) | 0.473 | −1.123 (527) | −0.098 |
Diffusion of Responsibility through Technology | 3.787 ** (527) | 0.338 | 0.280 (527) | 0.024 |
Distortion of Consequences through Technology | 4.603 ** (527) | 0.411 | −0.751 (527) | −0.065 |
Attribution of Blame through Technology | 8.113 ** (527) | 0.725 | 1.082 (527) | 0.094 |
McDonald’s ω | Cronbach’s α | Greatest Lower Bound (GLB) | |
---|---|---|---|
Moral Justification through Technology | 0.839 | 0.838 | 0.883 |
Diffusion of Responsibility through Technology | 0.820 | 0.815 | 0.850 |
Distortion of Consequences through Technology | 0.834 | 0.833 | 0.848 |
Attribution of Blame through Technology | 0.889 | 0.888 | 0.895 |
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Polanco-Levicán, K.; Salvo-Garrido, S. Psychometric Properties of the Moral Disengagement through Technologies Questionnaire (MDTech-Q) in a Sample of Chilean University Students. Healthcare 2023, 11, 1097. https://doi.org/10.3390/healthcare11081097
Polanco-Levicán K, Salvo-Garrido S. Psychometric Properties of the Moral Disengagement through Technologies Questionnaire (MDTech-Q) in a Sample of Chilean University Students. Healthcare. 2023; 11(8):1097. https://doi.org/10.3390/healthcare11081097
Chicago/Turabian StylePolanco-Levicán, Karina, and Sonia Salvo-Garrido. 2023. "Psychometric Properties of the Moral Disengagement through Technologies Questionnaire (MDTech-Q) in a Sample of Chilean University Students" Healthcare 11, no. 8: 1097. https://doi.org/10.3390/healthcare11081097