Model summary rotationa (total variance explained by each component of sensitivity) indicators
| Dimension | Cronbach's alpha | Variance accounted for | |
|---|---|---|---|
| Total (Eigenvalue) | % of variance | ||
| 1 | 0.494 | 1.797 | 11.230 |
| 2 | 0.058 | 1.002 | 6.261 |
| 3 | 0.146 | 1.001 | 6.258 |
| 4 | 0.069 | 1.001 | 6.257 |
| 5 | 0.081 | 1.001 | 6.257 |
| 6 | 0.070 | 1.001 | 6.255 |
| 7 | 0.161 | 1.001 | 6.255 |
| 8 | 0.040 | 1.001 | 6.253 |
| 9 | 0.134 | 1.000 | 6.252 |
| 10 | 0.015 | 1.000 | 6.252 |
| 11 | 0.148 | 1.000 | 6.250 |
| 12 | 0.065 | 1.000 | 6.249 |
| 13 | 0.147 | 0.999 | 6.245 |
| 14 | 0.262 | 0.996 | 6.226 |
| 15 | 0.272 | 0.994 | 6.215 |
| 16 | −4.048 | 0.206 | 1.284 |
| Total | 1.000b | 16.000 | 100.000 |
| Dimension | Cronbach's alpha | Variance accounted for | |
|---|---|---|---|
| Total (Eigenvalue) | % of variance | ||
| 1 | 0.494 | 1.797 | 11.230 |
| 2 | 0.058 | 1.002 | 6.261 |
| 3 | 0.146 | 1.001 | 6.258 |
| 4 | 0.069 | 1.001 | 6.257 |
| 5 | 0.081 | 1.001 | 6.257 |
| 6 | 0.070 | 1.001 | 6.255 |
| 7 | 0.161 | 1.001 | 6.255 |
| 8 | 0.040 | 1.001 | 6.253 |
| 9 | 0.134 | 1.000 | 6.252 |
| 10 | 0.015 | 1.000 | 6.252 |
| 11 | 0.148 | 1.000 | 6.250 |
| 12 | 0.065 | 1.000 | 6.249 |
| 13 | 0.147 | 0.999 | 6.245 |
| 14 | 0.262 | 0.996 | 6.226 |
| 15 | 0.272 | 0.994 | 6.215 |
| 16 | −4.048 | 0.206 | 1.284 |
| Total | 1.000 | 16.000 | 100.000 |
Notes:
Rotation method: Varimax with Kaiser normalisation;
Total Cronbach's alpha is based on the total eigenvalue