# Pareto-Optimized AVQI Assessment of Dysphonia: A Clinical Trial Using Various Smartphones
## 4 Results  
### AVQI Evaluation Outcomes  
First, we used two statistical measures to assess the agreement and reliability of the data collected through individual smartphone AVQI evaluations and inter smartphone AVQI measurements. [PERSON]'s alpha was used as a statistical measure to assess the internal consistency or reliability of AVQI. It ranges from 0 to 1, where 0 indicates no internal consistency or reliability, and 1 indicates perfect internal consistency or reliability. The [PERSON]'s alpha for individual smartphone AVQI evaluations was calculated to be 0.99, which is an excellent agreement. Next, we calculated the intraclass correlation coefficient (ICC), which is a statistical measure used to assess the reliability or consistency of the measurements taken by different raters or methods, in our case, different smartphones. It ranges from 0 to 1, where 0 indicates that there is no reliability or consistency, and 1 indicates perfect reliability or consistency. Therefore, the ICC was used to assess the reliability of the intersmartphone AVQI measurements, and we determined the average ICC to be 0.9115, which is an excellent result. The range of ICC values from 0.8885 to 0.9316 suggests that the measurements taken by different smartphones are consistent and reliable throughout the range. Table 2 displays the mean AVQI scores obtained from various smartphones and a studio microphone. We also performed a one-way ANOVA test to determine whether there are statistically significant differences between the means of three or more independent groups. In our case, a one-way ANOVA was performed to compare the mean AVQI scores obtained from different smartphones. The results of the analysis (presented in Table 2) indicate that there were significant differences in mean AVQI scores between different smartphones (\(F=9.035\); \(p\leq 0.001\)). Therefore, pairwise comparisons were conducted to determine which smartphones differed significantly from each other. The results of the pairwise comparisons (pairwise analysis) revealed that there were significant differences between AKG Perception 220 (studio microphone) and Samsung S22 Ultra (\(p<0.001\)). We also explored the differences in mean AVQI scores (ranged from 0.17 to 0.99 points) when comparing different smartphones. These indicate that some smartphones performed better than others in terms of producing accurate and high-quality sound recordings. Table 3 reports that there was a nearly perfect direct linear correlation between the AVQI results obtained from both the studio microphone and different smartphones. This means that the AVQI scores obtained from different smartphones were highly correlated with the AVQI scores obtained from the studio microphone. Pearson's correlation coefficients ranged from 0.976 to 0.99, which is a strong positive correlation. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Microphone** & **n** & **Mean AVQI** & **Std. Deviation** & **F** & \(p\) \\ \hline AKG Perception 220 & 134 & 3.412 & 1.823 & 9.03 & \textless{}0.001 \\ iPhone SE & & 3.238 & 1.798 & & \\ iPhone PRO MAX 13 & 3.016 & 1.735 & & \\ Huawei P50 pro & 3.581 & 1.977 & & \\ Samsung S22 Ultra & 4.407 & 2.014 & & \\ OnePlus 9 PRO & 3.736 & 1.817 & & \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Comparison of the mean results of the AVQI obtained with different smartphones and studio microphones. For analysis, the Bland-Altman plot, often known as the difference plot, is used as a visual way to contrast two measuring methods ([PERSON] and [PERSON], 2017). The ratios (or disparities, as an alternative) between the two procedures are shown. For all devices compared to the reference microphone, bias and critical difference were computed, and the relevant Bland-Altman graphs are shown in Figure 11.  
The bias's 95% confidence interval was used. If 0 was omitted from the confidence interval, the bias was considered substantial.