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Reliability Statistics
Cronbach's
Alpha Based on
Cronbach's Standardized
Alpha Items N of Items
.868 .868 5
Item Statistics
Mean Std. Deviation N
LS1 3.59 .914 400
LS2 3.56 .874 400
LS3 3.57 .887 400
LS4 3.52 .934 400
LS5 3.63 .901 400
Inter-Item Correlation Matrix
LS1 LS2 LS3 LS4 LS5
LS1 1.000 .529 .603 .625 .593
LS2 .529 1.000 .577 .555 .534
LS3 .603 .577 1.000 .579 .540
LS4 .625 .555 .579 1.000 .550
LS5 .593 .534 .540 .550 1.000
Item-Total Statistics
Corrected Item- Squared Cronbach's
Scale Mean if Scale Variance Total Multiple Alpha if Item
Item Deleted if Item Deleted Correlation Correlation Deleted
LS1 14.27 8.622 .721 .529 .833
LS2 14.29 9.076 .662 .444 .848
LS3 14.29 8.841 .700 .495 .838
LS4 14.34 8.594 .705 .502 .837
LS5 14.23 8.908 .670 .453 .846
Scale Statistics
Mean Variance Std. Deviation N of Items
17.85 13.324 3.650 5
RELIABILITY
/VARIABLES=IQ1 IQ2 IQ3 IQ4 IQ5
Page 3
/SCALE('ALL VARIABLES') ALL
/MODEL=ALPHA
/STATISTICS=DESCRIPTIVE SCALE CORR
/SUMMARY=TOTAL.
Reliability
Notes
Output Created 19-MAY-2026 16:19:15
Comments
Input Data - Análisis de fiabilidad mediante alfa de Cronbach
- Análisis de correlación ítem-total corregida
- Análisis de alfa si se elimina el elemento
Previo a la realización de los análisis principales, se evaluó la consistencia interna de las cuatro escalas mediante el alfa de Cronbach, siguiendo los umbrales interpretativos recomendados por George y Mallery (2003). Los resultados indicaron que la escala LS (5 ítems) demostró una buena fiabilidad (α = .868), la escala IQ (5 ítems) demostró una buena fiabilidad (α = .860), la escala TU (5 ítems) demostró una buena fiabilidad (α = .871), y la escala PI (4 ítems) demostró una buena fiabilidad (α = .820). En conjunto, las cuatro escalas superaron el umbral comúnmente aceptado de α ≥ .70, lo que indica que cada instrumento demostró una consistencia interna adecuada para su uso en los análisis subsecuentes.
Se examinaron los diagnósticos a nivel de ítem para evaluar con mayor profundidad la calidad de las escalas. Se inspeccionaron los valores de correlación ítem-total corregida y de alfa de Cronbach si se elimina el elemento para cada escala, siguiendo el criterio de que las correlaciones ítem-total corregidas deben superar .30 para confirmar que los ítems miden el mismo constructo subyacente (Field, 2018). Para la escala LS, las correlaciones ítem-total corregidas oscilaron entre .662 y .721, y la eliminación de ningún ítem habría mejorado de manera significativa la fiabilidad de la escala. Para la escala IQ, las correlaciones ítem-total corregidas oscilaron entre .664 y .698, y de manera similar, la eliminación de cualquier ítem individual no habría mejorado el alfa global. Para la escala TU, las correlaciones ítem-total corregidas oscilaron entre .680 y .723, con todos los ítems contribuyendo positivamente a la fiabilidad de la escala. Para la escala PI, las correlaciones ítem-total corregidas oscilaron entre .632 y .647, y la eliminación de ningún ítem habría producido una mejora notable en el alfa. En las cuatro escalas, todos los ítems demostraron correlaciones ítem-total aceptables, muy por encima del umbral de .30, y la eliminación de cualquier ítem no habría mejorado la fiabilidad de la escala, lo que confirma que todos los ítems funcionaban según lo previsto y contribuían de manera significativa a sus respectivos constructos.
Tabla 1: Estadísticas Ítem-Total
| Ítem | Correlación Ítem-Total Corregida r | Alfa si se Elimina el Elemento |
|---|---|---|
| LS1 | 0.721 | 0.833 |
| LS2 | 0.662 | 0.848 |
| LS3 | 0.700 | 0.838 |
| LS4 | 0.705 | 0.837 |
| LS5 | 0.670 | 0.846 |
| IQ1 | 0.681 | 0.830 |
| IQ2 | 0.674 | 0.832 |
| IQ3 | 0.664 | 0.835 |
| IQ4 | 0.670 | 0.833 |
| IQ5 | 0.698 | 0.826 |
| TU1 | 0.680 | 0.848 |
| TU2 | 0.723 | 0.837 |
| TU3 | 0.688 | 0.846 |
| TU4 | 0.705 | 0.842 |
| TU5 | 0.685 | 0.846 |
| PI1 | 0.646 | 0.772 |
| PI2 | 0.643 | 0.773 |
| PI3 | 0.647 | 0.771 |
| PI4 | 0.632 | 0.778 |
Nota. Los ítems con correlaciones ítem-total corregidas < .30 pueden no estar midiendo el mismo constructo (Field, 2018). Todos los ítems del presente estudio superaron este umbral.
Referencias
Field, A. (2018). Discovering statistics using IBM SPSS Statistics (5th ed.). SAGE Publications.
George, D., & Mallery, P. (2003). SPSS for Windows step by step: A simple guide and reference, 11.0 update (4th ed.). Allyn & Bacon.
- Cronbach's Alpha reliability analysis
- Item-total correlation analysis
- Alpha-if-item-deleted analysis
Prior to conducting the main analyses, the internal consistency reliability of all four scales was assessed using Cronbach's alpha, following the interpretive thresholds recommended by George and Mallery (2003). Results indicated that the LS scale (5 items) demonstrated good reliability (α = .868), the IQ scale (5 items) demonstrated good reliability (α = .860), the TU scale (5 items) demonstrated good reliability (α = .871), and the PI scale (4 items) demonstrated good reliability (α = .820). Collectively, all four scales exceeded the commonly accepted threshold of α ≥ .70, indicating that each instrument demonstrated adequate internal consistency for use in subsequent analyses.
Item-level diagnostics were examined to further evaluate scale quality. Corrected item-total correlations and Cronbach's alpha-if-item-deleted values were inspected for each scale following the criterion that corrected item-total correlations should exceed .30 to confirm that items are measuring the same underlying construct (Field, 2018). For the LS scale, corrected item-total correlations ranged from .662 to .721, and no item deletion would have meaningfully improved scale reliability. For the IQ scale, corrected item-total correlations ranged from .664 to .698, and similarly, removing any individual item would not have improved the overall alpha. For the TU scale, corrected item-total correlations ranged from .680 to .723, with all items contributing positively to scale reliability. For the PI scale, corrected item-total correlations ranged from .632 to .647, and no item deletion would have resulted in a notable improvement to alpha. Across all four scales, all items demonstrated acceptable item-total correlations well above the .30 threshold, and removing any item would not have improved scale reliability, confirming that all items were functioning as intended and contributing meaningfully to their respective constructs.
Table 1: Item-Total Statistics
| Item | Corrected Item-Total r | Alpha if Item Deleted |
|---|---|---|
| LS1 | 0.721 | 0.833 |
| LS2 | 0.662 | 0.848 |
| LS3 | 0.700 | 0.838 |
| LS4 | 0.705 | 0.837 |
| LS5 | 0.670 | 0.846 |
| IQ1 | 0.681 | 0.830 |
| IQ2 | 0.674 | 0.832 |
| IQ3 | 0.664 | 0.835 |
| IQ4 | 0.670 | 0.833 |
| IQ5 | 0.698 | 0.826 |
| TU1 | 0.680 | 0.848 |
| TU2 | 0.723 | 0.837 |
| TU3 | 0.688 | 0.846 |
| TU4 | 0.705 | 0.842 |
| TU5 | 0.685 | 0.846 |
| PI1 | 0.646 | 0.772 |
| PI2 | 0.643 | 0.773 |
| PI3 | 0.647 | 0.771 |
| PI4 | 0.632 | 0.778 |
Note. Items with corrected item-total correlations < .30 may not be measuring the same construct (Field, 2018). All items in the present study exceeded this threshold.
References
Field, A. (2018). Discovering statistics using IBM SPSS Statistics (5th ed.). SAGE Publications.
George, D., & Mallery, P. (2003). SPSS for Windows step by step: A simple guide and reference, 11.0 update (4th ed.). Allyn & Bacon.
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