A Text-Mining Analysis of Research Trends in Animal-Assisted Therapy

SIMPLE SUMMARY: Animal-assisted therapy (AAT) has recently gained increasing attention in various disciplines. However, understanding of the specific fields and topics being studied in this area remains limited, with most studies conducted using experimental approaches. Therefore, this study determined trends in AAT research based on an analysis of studies published via PubMed (n = 776 studies). Python programming was used for the analysis, employing techniques such as word cloud, n-gram, two-way word tree, and CONCOR (convergence of iteration correlation) analyses. ABSTRACT: Text-mining techniques were used to provide basic data to related policy stakeholders and academic researchers by collecting and analyzing research trends related to animal-mediated healing in a short time. A total of 776 studies were collected using the keyword “animal-assisted therapy” (AAT) in the search engine PubMed, which covers a wide range of topics related to health sciences, biomedical research, and health psychology. Four analysis methods were employed. “Dog” was the most commonly utilized animal in AAT. This study also identified individuals with autism spectrum disorder and post-traumatic stress disorder as the primary research participants. Finally, the terms “health care” and “blood pressure” were identified, indicating that AAT has a positive impact on improving blood pressure and enhancing heart rate. These findings demonstrate that AAT research is being actively pursued in various fields, such as social sciences, medicine, and psychology.