# Validating the Threat of a Virtual Reality Clinical Environment: A Mixed Methods Study
## 2 Materials and Methods
### Statistical Analysis  
A statistical analysis was performed using SPSS (IBM, version 27.0, Armonk, NY, USA). Visual inspections of histograms and the Shapiro-Wilk test were used to assess the normality of outcomes (Wilcoxon (W) statistic reported). For all outcomes, normally distributed data are presented as the mean \(\pm\) standard deviation (M \(\pm\) SD); non-normally distributed data are presented as the median \(\pm\) inter-quartile range (Mdn \(\pm\) IQR), unless otherwise specified.  
Regarding 2 QT, data for 'calming','safe' and'reassuring' were transformed such that a higher score on all adjectives indicated a higher level of threat. Adjectives pertaining to the threat and non-threat rooms were assessed for internal consistency to determine whether the adjective scores could be combined into an overall 2 QT score; Cronbach's alpha (\(\alpha\)) was used to express internal consistency, with a minimum acceptability threshold of 0.69 [32]. Calculation of the 2 QT scores was performed using the sum of each statement's transformed rank (1 = Disagree, 2 = Disagree, 3 = Neutral, 4 = Agree, 5 = Agree). In the threat condition, responses to four of the adjectives were not normally distributed ('calming' [W = 0.74, \(p\) = 0.001],'stressful' [W = 0.84, \(p\) = 0.02], 'unpleasant' [W = 0.75, \(p\) = 0.002] and'reassuring' [W = 0.81, \(p\) = 0.008]), while the responses to'safe' (W = 0.93, \(p\) = 0.356) and 'threatening' (W = 0.90, \(p\) = 0.116) were normally distributed. None of the responses in the non-threat condition were normally distributed ('threatening' [W = 0.75, \(p\) = 0.002], 'calming' [W = 0.68, \(p\) < 0.001],'safe' [W = 0.77, \(p\) = 0.003],'stressful' [W = 0.81, \(p\) = 0.009], 'unpleasant' [W = 0.73, \(p\) = 0.001] and'reassuring' [W = 0.83, \(p\) = 0.014]). The Mann-Whitney U test (MWU) was performed for the between-group comparisons of 2 QT data; the test variables were the combined threat scores, with the condition ('threat' or 'non-threat') as the grouping variable (Mann-Whitney (U) statistic and \(Z\) score (Z) reported). The effect size was calculated as \(Z/\surd n\), where \(Z=Z\) value of MWU test and \(n\) = observation number, and was interpreted as follows: 0.2, small effect; 0.5, medium effect; 0.8, large effect [33].  
The cortisol concentration in the threat condition at all 3 timepoints did not follow a normal distribution (cortisol0 [W = 0.81, \(p\)= 0.012], cortisol20 [W = 0.78, \(p\) = 0.006], cortisol26 [W = 0.81, \(p\) = 0.012]). The cortisol concentration in the non-threat condition was normally distributed at all three timepoints (cortisol0 [W = 0.97, \(p\) = 0.938], cortisol20 [W = 0.92, \(p\) = 0.240], cortisol26 [W = 0.93, \(p\) = 0.324]). Analyses of within-group cortisol concentrations determined differences across time (cortisol0, cortisol20 and cortisol26). The threat condition was analysed with the Friedman test with [PERSON]'s pairwise post hoc tests and Bonferroni correction; the non-threat condition was analysed with a one-way repeated-measures analysis of variance (ANOVA; cortisol0, cortisol20 and cortisol26 as within-subject factors). An MWU test was used to assess between-group differences.