was rather small, although the random forest algorithm is known to handle such situations more effectively than other machine learning models. Therefore, similar studies with larger sample sizes are needed to confirm the findings of the present study. A larger sample is also warranted to explore associations among the features from multiple domains, since the current study did not identify potential associations among the features, possibly due to a lack of statistical power. Given these limitations, it is to be noted that the obtained results are only preliminary, while the findings of the present study might help to design future studies avoiding or mitigating these limitations.
