Scientific research on verbal fluency tests: a bibliometric analysis
Verbal fluency tests are easy and quick to use in neuropsychological assessments. The aim of this study is to explore their relevance through a bibliometric analysis. We performed a search in the Web of Science, involving documents published between 1960 and 2021. We used bibliometric indicators to...
| Autores: | , , , , , |
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| Formato: | artículo |
| Fecha de publicación: | 2022 |
| País: | España |
| Recursos: | Universidad Complutense de Madrid (UCM) |
| Repositorio: | Docta Complutense |
| Idioma: | inglés |
| OAI Identifier: | oai:docta.ucm.es:20.500.14352/91325 |
| Acesso em linha: | https://hdl.handle.net/20.500.14352/91325 |
| Access Level: | acceso abierto |
| Palavra-chave: | Verbal fluency Bibliometric Neuropsychology Assessment Psicología (Psicología) Neuropsicología 61 Psicología |
| Resumo: | Verbal fluency tests are easy and quick to use in neuropsychological assessments. The aim of this study is to explore their relevance through a bibliometric analysis. We performed a search in the Web of Science, involving documents published between 1960 and 2021. We used bibliometric indicators to explore articles distribution, doubling time, and annual growth. We calculated the participation index of the different countries and institutions. Through bibliometric mapping, we explored the co-occurrence networks for the most frequently used terms in verbal fluency research. 1718 articles were found, distributed in two different periods (1960–1995 and 1995 to 2021), the second one containing more than 88% of the documents. Price's law shows an exponential growing. Literature on verbal fluency has grown at a rate of 6,7% per year, doubling its size every 10.7 years. Bradford's law shows a high concentration of articles published in a small core of specialized journals. Finally, the map network visualization shows a change in the most important topic related to verbal fluency during the most recent period analysed. Verbal fluency task has undergone an exponential growth. Its easy application, its sensitivity to different brain dysfunction, the possibility of implementation with neuroimaging studies, and the potential analysis of more complex components (clustering or switching) might have played a key role in its growing interest. |
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