Astaeva Alena

RESEARCH, TEACHING, or OTHER INTERESTS

Cognitive Neuroscience, Clinical Psychology, Psychiatry and Mental health, Neuropsychology and Physiological Psychology

Scopus Publications

Comparative analysis of russian and foreign systems for the neuropsychological diagnosis of children from the standpoint of the psychometric approach and its limitations when used in clinical practice




Comparative analysis of russian and foreign systems for the neuropsychological diagnosis of children from the standpoint of the psychometric approach and its limitations when used in clinical practice
Alena V. Astaeva and Mikhail A. Berebin
Russian Psychological Society
Modern approaches to the psychological diagnostics of children are based on need analysis and the systematization of existing trends in domestic and foreign children’s neuropsychological diagnoses. This article highlights the strengths and weaknesses of each approach, as well as identifying possible areas of integration. One of the most acute problems is the development of experimental psychological methods to determine the quantitative and expressed characteristics of the mental development of children by flexibly combining qualitative and quantitative approaches, with a view to putting into practice foreign neuroscience principles and standards of evidence. An analysis of contemporary publications on neuropsychological diagnosis reveals the need to consider the standardization of neuropsychological research in the context of current approaches, requirements, and psychodiagnostic criteria. In the domestic neuropsychological literature, these issues are need attention: standardized procedures for presenting stimuli are not, as a rule, described; basic psychometric assessment of the results of the tests is lacking; no investigation of their clinical and psychometric validity is carried out. An analysis was made of the nature of the psychometric approach in foreign child neuropsychology, which relies on mathematical procedures of processing qualitative (ordinal) data converted into quantitative indicators. We examined separately the mathematical software for clinical trials (based on the principles of «evidencebased medicine»), which relies on the «abnormal» nature of the distribution of clinical phenomena.