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© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

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.

Details

Title
A Text-Mining Analysis of Research Trends in Animal-Assisted Therapy
Author
Shin-Ja, Lee 1   VIAFID ORCID Logo  ; Geun-Hyeon, Kim 2 ; Yea-Hwang Moon 3 ; Sung-Sill, Lee 4   VIAFID ORCID Logo 

 University-Centered Labs, Institute of Agriculture and Life Science, Gyeongsang National University, Gyeongsangnam-do, Jinju-si 52828, Republic of Korea; [email protected] 
 Jeonju City Council Legislative Policy Division, Wansangu Nosonggwangjang-ro 10, Jeollabuk-do, Jeonju-si 54994, Republic of Korea; [email protected] 
 Division of Animal Bioscience and Integrated Biotechnology, Gyeongsang National University, Gyeongsangnam-do, Jinju-si 52725, Republic of Korea; [email protected] 
 University-Centered Labs, Institute of Agriculture and Life Science, Gyeongsang National University, Gyeongsangnam-do, Jinju-si 52828, Republic of Korea; [email protected]; Division of Applied Life Science (BK21), Gyeongsang National University, Gyeongsangnam-do, Jinju-si 52828, Republic of Korea 
First page
3133
Publication year
2023
Publication date
2023
Publisher
MDPI AG
e-ISSN
20762615
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2876358644
Copyright
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.