| Literature DB >> 35898977 |
Xin Wang1, Xiang-Fei Gong1, Ke-Xin Xiong1, De-Sheng Guo1, Li-Jun Liu2, Chia-Min Lin3, Wei-Yin Chang1,2.
Abstract
Exposure to forest environments promotes human health. The number of relevant studies in this area has increased rapidly. However, an overall review of relevant analyses from the perspectives of bibliometrics and visualization is lacking. A scientometric analysis of 2,545 publications from 2007 to 2021 via the Web of Science database was conducted to identify the knowledge structure and frontiers objectively. The publications were subsequently analyzed in terms of the distribution of journals and countries, citation bursts, major subject areas, and evolutionary stages. The findings showed that the knowledge foundation of forest therapy was multidisciplinary with most published in the fields of environmental sciences and ecology but lacking input from social disciplines. The research hotspots evolved from the early focus on individual benefits obtained from nature to increasing attention on human well-being at the social-ecological scale. More rigorous experiments with strict randomized controlled trials and blinding are needed to accommodate the trend of forest therapy toward non-pharmacological treatments. According to Shneider's four-stage theory, forest therapy research is in the third stage of the scientific research process. More future studies utilizing novel technologies and decision-making frameworks to solve practical issues are needed for introducing health into policies and promoting human well-being.Entities:
Keywords: bibliometric analysis; forest therapy; green spaces; human well-being; intellectual development
Year: 2022 PMID: 35898977 PMCID: PMC9309728 DOI: 10.3389/fpsyg.2022.930713
Source DB: PubMed Journal: Front Psychol ISSN: 1664-1078
FIGURE 1Methodology steps used in the bibliometric analysis developed for forest therapy.
FIGURE 2Annual growth in the number of publications in our research area.
The top 10 journals containing references to forest therapy research.
| Rank | Journal | TCb | N/2545 (%) | IFa | EF | AI |
| 1 |
| 339 | 13.30 | 2.948 | 0.023 | 0.7 |
| 2 |
| 142 | 5.58 | 5.356 | 0.003 | 0.6 |
| 3 |
| 101 | 3.96 | 3.473 | 0.007 | 0.4 |
| 4 |
| 81 | 3.18 | 7.96 | 0.013 | 1.0 |
| 5 |
| 74 | 2.91 | 3.618 | 0.047 | 1.0 |
| 6 |
| 52 | 2.04 | 3.788 | 1.814 | 1.1 |
| 7 |
| 46 | 1.81 | 7.871 | 0.006 | 1.3 |
| 8 |
| 45 | 1.77 | 6.824 | 0.014 | 1.2 |
| 9 |
| 45 | 1.77 | 2.453 | 0.003 | 0.5 |
| 10 |
| 43 | 1.69 | 5.145 | 0.013 | 1.1 |
TCb, the total number of citations in the journal; N, number of publications in the corresponding journal; IFa, Five-year impact factor, impact factor data from the 2020 edition of Journal Citation Reports
The top 10 countries and regions in terms of publications.
| Countries/Regions | Number of manuscripts | Centralities (Rank) | Year |
| United States | 586 | 0.18 (2) | 2007 |
| China | 447 | 0.01 (30) | 2009 |
| England | 322 | 0.31 (1) | 2009 |
| Australia | 219 | 0.17 (3) | 2008 |
| Japan | 206 | 0.03 (20) | 2008 |
| South Korea | 162 | 0.03 (21) | 2010 |
| Germany | 149 | 0.05 (11) | 2008 |
| Spain | 131 | 0.13 (4) | 2012 |
| Canada | 130 | 0.07 (5) | 2012 |
| Sweden | 121 | 0.04 (15) | 2010 |
FIGURE 3The collaboration network of authors that published studies on forest therapy.
FIGURE 4Keyword co-occurrence visualization network.
FIGURE 5The keywords with the strongest citation bursts in publications on forest therapy research.
FIGURE 6A landscape view of the main clusters.
FIGURE 7A timeline visualization of the main clusters.
FIGURE 8High-impact publications in Cluster #0.
FIGURE 9High-impact publications in Cluster #1.
FIGURE 10High-impact publications in Cluster #2.