# Evaluation of AI-Assisted Telemedicine Service Using a Mobile Pet Application
## 5 Discussion  
From the results of H5 in Table 8, we confirmed that the ease of use of the app has a positive effect on telemedicine and a negative significant effect on negative perceptions. In other words, among users who are highly adept at using apps, negative perceptions about telemedicine for pets and humans are reduced. We were thus able to reinforce the significance of the existing hypothesis. In addition, according to the results of H6, we confirmed that interest in telemedicine is rather low when the companion animal's disease is severe. In other words, H2 reveals that users have a high positive perception of telemedicine in case of poor health. However, it was confirmed that the H6 test by moderation effect played a role in lowering interest in telemedicine in severe cases depending on the severity of the disease. It revealed that actual face-to-face treatment is more urgent than the user using the mobile app service. It can also be assumed that the user forgoes treatment for the companion animal due to cost problems. On the other hand, in mild cases, users are interested in both expert treatment or counseling and general counseling through collective intelligence among other pet owners. The H7 results reveal that among those who had negative perceptions about telemedicine for companion animals, those with a high degree of ease of use of mobile app services have a high proportion of positive evaluations about telemedicine services for people. This trend disproves the claim that people who find it easy to use mobile apps are more familiar with the IT environment than are those who do not. Despite the significance of this study, it has some limitations. First, assuming the widespread use of telemedicine for humans, advanced technologies such as X-ray and ultrasound cannot be applied. In this respect, simple comparisons with simple techniques such as pet telemedicine are problematic. This is similar to the same fundamental problem with safety that medical associations consistently highlight. Second, in pet telemedicine, the animal's unusual behavior or abnormal symptoms can be detected through dialogue with its owner, but the diagnoses may differ depending on the person expressing the symptoms. In other words, because pet owners who experienced the same symptoms when posting on social media or portal communities have different opinions and methods of expression, \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Hypothesis** & **Path** & **t-Value (for H5a, b)** & **Test Result** \\  & & **/Z-score (H6, 7)** & \\ \hline \multirow{3}{*}{H5a} & Ease of use of mobile application service & & \\  & \(\rightarrow\) negative perception of pet & \(-\)3.472 *** & Accept \\  & telemedicine service & & \\ \hline \multirow{3}{*}{H5b} & Ease of use of mobile application service & & \\  & \(\rightarrow\) negative perception of telemedicine & \(-\)2.627 ** & Accept \\  & service for people & & \\ \hline \multirow{3}{*}{H6} & Health condition \(\rightarrow\) severity of disease \(\rightarrow\) & & \\  & positive perception of pet & & \\  & telemedicine service & & \\ \hline \multirow{3}{*}{H7} & Negative perception of pet telemedicine & & \\  & service \(\rightarrow\) Ease of use of mobile & & \\ \cline{1-1}  & application service \(\rightarrow\) negative perception & & \\ \cline{1-1}  & of telemedicine service for people & & \\ \hline \hline \end{tabular}
\end{table} 
Table 8: Result of moderation effect. remote prescriptions may also vary. Third, while conducting this study, we felt that the research on pet telemedicine platforms was insufficient. There are quite a few communities that serve as a forum for dialogue and communication, in addition to being a professional medical platform. In other words, although a specialized online medical device is required, we have not been able to clearly present a specific alternative for establishing a platform for such telemedicine. The following is a summary of future research plans based on the problems identified.