Table 2.
Three scenarios applied to convolutional neural network for the prediction of nurse burnout (n=1002).
| Sample | True condition | ||||
|
|
BO+a | BO–b | BO+/row # | BO–/row # | |
| Scenario A (only 20 items) |
|
|
|
|
|
|
|
Positive | 507 | 26 | 0.95 | 0.05 |
|
|
Negative | 24 | 445 | 0.05 | 0.95 |
| Scenario B (Scenario A and MPRSAc) training |
|
|
|
|
|
|
|
Positive | 531 | 0 | 1.00 | 0 |
|
|
Negative | 0 | 471 | 0 | 1.00 |
aBO+: suspicious for burnout.
bBO–: not suspicious for burnout.
cMPRSA: matching personal response scheme to adapt for the correct classification.