Özet:

The paper considers benefits and drawbacks of the Picture Naming Test (PNT) as a diagnostic method suggesting the ways to improve its diagnostic and research validity. Although this test is popular in both national and international neuropsychological assessment and research practice, its use is largely due to tradition and practical convenience. However, theoretical underpinnings for its effectiveness are not sufficiently represented in the pertinent literature, which determines the relevance of the study. The major objective of the paper is to consider the PNT as a research technique from the point of view of psycholinguistics, cognitive science, and corpus linguistics and to propose integrated approaches for the further development of these tests. The material comprises picture naming tests developed for the Russian and English languages. The study sets the following aims: 1) to define the main features of PNT and the principles of its application viewed from a historical perspective; 2) to identify the theoretical foundations (linguistic and neuropsychological) for its use as a diagnostic tool; 3) to highlight the problematic aspects of the method; 4) to suggest possible ways to eliminate them. To accomplish these tasks, various methods of corpus linguistics are applied throughout the article. The historical outline of PNT development suggests that the current design might stem from earlier contexts of use. A review of existing models of lexical access provides a theoretical basis for the test in its current form and suggests possible avenues for its development grounded in experimental research, advances in linguistics and big data analysis. A separate section of the article presents critique of the most popular tests. Finally, the analysis of the existing English and Russian tests through the corpus-based methodology clearly demonstrates the need for more detailed norming and stimuli selection. By way of conclusion the authors outline the principles of designing Picture Naming Tests for specific purposes and put forward a step-by-step algorithm that enables careful selection of the necessary indicators and parameters.

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