## 5 Experiment 2: Deployment of Biofeedback System during Online Academic Examinations
### Results
The initial one-factor model results with the Satorra-Bentler scaled \(\chi^{2}\) (27, N = 35) = 142.12, \(p\) = 0.00, CFI = 0.53, and RMSEA = 0.32 (CI90% 0.26 to 0.36). Consequently, a second CFA was performed, using a revised item set of the scale. In the revised item set, according to the suggested modifications, as indicated by the Lagrange Multiplier and Wald tests, and the Largest Standardized Residuals as well, four items (items 1, 2, 5, and 8 of the original questionnaire) that failed to come up with a one-factor solution corresponding to the Insecurity Questionnaire were dropped. The model using the revised item set yielded a better fit to the data than the first model [Satorra-Bentler scaled \(\chi^{2}\) (27, N = 35) = 1.13, \(p\) = 0.57, CFI = 1.00, and RMSEA = 0.00 (CI90% 0.00 to 0.25)]. We derived one factor--consisting of five items--, which is probably explained by the users' insecurity related to the biofeedback system under study. * Discomfort Scale: It captures the inconvenience people may experience because of the biofeedback system [8]. The one-factor structure of the scale, based on 10 items, was not confirmed by the initially applied CFA. The initial one-factor model results with the Satorra-Bentler scaled \(\chi^{2}\) (35, N = 35) = 278.40, \(p\) = 0.00, CFI = 0.27, and RMSEA = 0.40(CI90% 0.35 to 0.44). Consequently, a second CFA was performed, using a revised item set of the questionnaire. According to the suggested modifications, as indicated by the Lagrange Multiplier and Wald tests, and the Largest Standardized Residuals as well, five items (items 2, 5, 6, 8, and 10 of the original questionnaire) that failed to come up with a one-factor solution corresponding to the Discomfort Questionnaire were dropped. The model using the revised item set yielded a better fit to the data than the first model [Satorra-Bentler scaled \(\chi^{2}\) (4, N = 35) = 0.31, \(p\) = 0.99, CFI = 1.00, and RMSEA = 0.00]. Thus, we derived one factor--consisting of five items--, which could be explained by the users' discomfort in relation to the system under study. [PERSON]'s alpha internal consistency estimates, obtained for each of the aforementioned scales/factors, were found to be higher than or equal to 0.77. This finding is comparable to a sound reliability with [PERSON]'s alpha ranging from 0.74 to 0.81 as found by [PERSON] [8] and to a replication in Great Britain that has further strengthened the soundness of the TRI. More specifically, [PERSON] [62] extracted the same four-factor structure, with [PERSON]'s alpha ranging from 0.74 to 0.88. We then used structural equation modeling (SEM) analysis in order to test the relationship between the students' TRI personality traits, as described by optimism (9-item average, OPTAVG), innovativeness (7-item average, INNOAVG), insecurity (5-item average, INSAVG) and discomfort (5-item average, DISAVG), the state anxiety levels provided by the biofeedback system and academic performance. A total of four parameters (optimism, insecurity, anxiety, and performance) were estimated as being statistically significant in the path model. The confirmed relationships between the derived parameters are shown in Table 4.  
The confirmed path model is displayed in Figure 7 with an excellent overall fit, \(\chi^{2}\) (2, N = 35) = 0.11, \(p\) = 0.95, CFI = 1.00, GFI = 0.99, NFI = 0.99, and RMSEA = 0.00.