General characteristics
The mean age of the participants was 22.66 years (SD = 2.11). Most of the participants (90.9%, n = 130) were under 25, and women (85.3%, n = 122). More than half (78.8%, n = 84) had an academic grade of 3.5 or higher. Seventy-two preferred a lecture class. 110 subjects responded that they were satisfied with their nursing major and clinical practice (Table 1).
Table 1
Differences in simulation education satisfaction according to general characteristics (N = 143)
Characteristics | Categories | n(%) | M ± SD | t/F/r | p |
Age (years) | < 25 | 130(90.9) | 3.93 ± 0.43 | 0.96 | .384 |
| 25-<30 | 9(6.3) | 4.05 ± 0.47 | | |
| 30–31 | 4(2.8) | 3.69 ± 0.64 | | |
Gender | Female | 122(85.3) | 3.95 ± 0.42 | 1.33 | .187 |
| Male | 21(14.7) | 3.82 ± 0.50 | | |
Academic achievement | < 3.0 | 16(11.2) | 3.88 ± 0.53 | 2.23 | .087 |
| 3.0∼<3.5 | 43(30.1) | 3.83 ± 0.38 | | |
| 3.5-<4.0 | 55(38.5) | 4.04 ± 0.41 | | |
| ≥ 4.0 | 29(20.3) | 3.90 ± 0.45 | | |
Satisfaction of major | Very satisfieda | 26(18.2) | 4.33 ± 0.39 | 15.29 | < .001 |
| Satisfiedb | 84(58.7) | 3.87 ± 0.36 | d < b,c < a | |
| Moderatec | 29(20.3) | 3.85 ± 0.42 | | |
| Unsatisfiedd | 4(2.8) | 3.22 ± 0.42 | | |
Satisfaction of clinical | Very satisfieda | 22(15.4) | 4.31 ± 0.41 | 13.75 | < .001 |
practice | Satisfiedb | 88(61.5) | 3.92 ± 0.35 | d < a,b,c | |
| Moderatec | 29(20.3) | 3.78 ± 0.45 | <a | |
| Unsatisfiedd | 4(2.8) | 3.17 ± 0.36 | | |
Preferred learning style | Lecture | 72(50.3) | 3.88 ± 0.46 | 1.34 | .266 |
| Discussion | 14(9.8) | 3.90 ± 0.35 | | |
| Practice | 57(39.9) | 4.00 ± 0.41 | | |
(Please insert Table 1 here)
Differences in simulation educational satisfaction according to general characteristics
The differences in simulation educational satisfaction according to the general characteristics of participants are shown in Table 1. There were statistically significant differences in simulation educational satisfaction in satisfaction of major (F = 15.29, p < .001), and satisfaction of clinical practice (F = 13.75, p < .001) (Table 1).
Degree of variables
The mean of simulation educational satisfaction, simulation design, and flow scores were established as 3.93 (SD = 0.43), 4.17 (SD = 0.45), and 3.73 (SD = 0.53), respectively. There was a significant relationship between simulation educational satisfaction and simulation design (r = .65, p < .001), and flow (r = .47, p < .001). There was also a significant relationship between flow and simulation design (r = .55, p < .001) (Table 2).
Table 2
Degrees of variables (N = 143)
Variables | M ± SD | Item mean ± SD |
Simulation education satisfaction | 62.90 ± 6.93 | 3.93 ± 0.43 |
Learning content | 25.85 ± 2.93 | 4.31 ± 0.49 |
Situational competency | 25.34 ± 2.92 | 4.22 ± 0.49 |
Emotional response | 11.71 ± 3.77 | 2.93 ± 0.94 |
Simulation design | 87.50 ± 9.40 | 4.17 ± 0.45 |
Educational goal and contents | 24.69 ± 3.00 | 4.12 ± 0.50 |
Support | 16.41 ± 2.28 | 4.10 ± 0.57 |
Problem-solving | 20.94 ± 2.44 | 4.19 ± 0.49 |
Feedback | 17.29 ± 2.04 | 4.32 ± 0.51 |
Fidelity | 8.17 ± 1.33 | 4.09 ± 0.67 |
Flow | 37.30 ± 5.30 | 3.73 ± 0.53 |
Correlation among simulation educational satisfaction, simulation design, and flow
The simulation educational satisfaction of the participants was positively correlated with simulation design (r = .65, p < .001) and flow (r = .47, p < .001), and simulation design was positively correlated with the flow (r = .55, p < .001) (Table 3).
Table 3
Correlations among variables (N = 143)
Variables | Simulation education satisfaction | Simulation design |
r (p) | r (p) |
Simulation education satisfaction | 1 | .65 (< .001) |
Simulation design | .65 (< .001) | 1 |
Flow | .47 (< .001) | .550 (< .001) |
Mediating effect of flow on the relationship between simulation design and simulation educational satisfaction
The results of assessing the mediating effect of flow on the relationship between simulation design and simulation educational satisfaction of the participants were as follows (Table 4, Fig. 1). As a result of checking for multicollinearity among the independent variables to verify the assumptions for the regression analysis, the tolerance was 0.70 and the variance expansion factor was 1.43, indicating that there was no multicollinearity. As a result of checking the autocorrelation of the dependent variable, the Durbin-Watson value was 2.06, which was close to 2, indicating that they were independent of each other. Therefore, a regression analysis was conducted.
Table 4
The mediating effect of flow on the relationship between simulation design and simulation educational satisfaction (N = 143)
Variables | B | SE | β | t | p | R2 | F | p |
1. SD → SES | .63 | .06 | .65 | 10.09 | < .001 | .42 | 101.81 | < .001 |
2. SD → Flow | .65 | .08 | .55 | 7.81 | < .001 | .30 | 60.99 | < .001 |
3. SD, Flow → SES | | | | | | .44 | 54.67 | < .001 |
SD → SES | .54 | .07 | .56 | 7.34 | < .001 | | | |
Flow → SES | .14 | .06 | .17 | 2.19 | .030 | | | |
Sobel test: Z = 5.36, p < .001 |
SD = Simulation design; SES = Simulation educational satisfaction |
The mediation analysis was conducted in three steps, as follows: Step 1 analysis showed that the independent variable, simulation design, had a significant effect on the dependent variable, simulation educational satisfaction (β = .65, p < .001). Step 2 analysis showed that the independent variable, simulation design, had a significant effect on the mediator variable, flow (β = .47, p < .001). Step 3 analysis showed that the mediator variable, flow, had a significant effect on simulation educational satisfaction while controlling for the independent variable, simulation design (β = .17, p = .003). Controlling for the influence of the mediator variable, flow, the effect of the independent variable, simulation design, on simulation educational satisfaction decreased compared to Step 1, where the influence of the mediator variable was not considered but was still statistically significant (β = .56, p < .001), confirming the partial mediating effect of flow.
In other words, there was a direct effect of simulation design on simulation educational satisfaction and an indirect effect of simulation design on simulation educational satisfaction via flow. The model had an explanatory power of 44.0% and was statistically significant (F = 54.67, p < .001). Using the hierarchical regression analysis proposed by Baron and Kenny [23] to test the mediating effect as well as the Sobel test to confirm the significance of the mediating effect, a partial mediating effect of flow was identified in the relationship between simulation design and simulation educational satisfaction (Z = 5.36, p < .001).