Diagnostics of signs of neuropsychic instability in military personnel using stabilometry

BACKGROUND: Extreme conditions and the specific demands of military profession cause stress in military personnel who exhibit signs of neuropsychological instability, which disrupts their functional state and can lead to erroneous actions, emergency situations and, consequently, failure in training and combat missions. Existing methods for assessing an individual’s neuropsychological stability have certain limitations, so the development and introduction of additional, objective techniques for diagnosing neuropsychological stability and signs of instability in military personnel are highly relevant. AIM: To develop a mathematical model for diagnosing signs of neuropsychological instability in military personnel using stabilometry. MATERIALS AND METHODS: The study involved 50 servicemen with similar military occupational specialty, whose average age was 24.05±1.02 years. Assessment of their professional skills and personal traits was carried out using the General Fitness for Military Service-3 method. Based on the data obtained, the sample was split into two groups: No signs of neuropsychological instability (n=36; 72%) and Signs of neuropsychological instability (n=14; 28%). The short-term locomotion memory was analyzed using the Triangle test on the Stabilan-01-2 stabilizer. The significance of differences between the groups was assessed using the Mann–Whitney U test. The multiple regression method and discriminant analysis were used to develop decision rules. RESULTS: Servicemen with signs of neuropsychological instability exhibited lower balance function stability at all stages of testing. Locomotion memory — along with image, emotional, and verbal-logical memory, which characterizes mental activity — can serve as a marker for identifying signs of neuropsychological instability. We developed a diagnostic model for assessing signs of neuropsychological instability in servicemen, which has high sensitivity and specificity. We also proposed the decision rules to classify military personnel into either exhibiting or not exhibiting signs of neuropsychological instability based on the results of short-term locomotion memory testing using stabilometry. CONCLUSIONS: The use of stabilometry as an additional method for objectifying aptitude screening results will enhance the effectiveness of selection processes in the Armed Forces of the Russian Federation.

Authors

Institutions

Publication Details

Journal
Humanitarian Military Journal
Published
2025-04-27
DOI
https://doi.org/10.17816/hmj646479
Primary Topic
Occupational Health and Performance
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Diagnostics of signs of neuropsychic instability in military personnel using stabilometry

Evgeniy A. Zhurbin, E. Yu. Shchelkanova, Ilya V. Markin, M. R. Nazarova et al.
Humanitarian Military Journal
Occupational Health and Performance
article

Diagnostics of signs of neuropsychic instability in military personnel using stabilometry

Evgeniy A. Zhurbin, E. Yu. Shchelkanova, Ilya V. Markin, M. R. Nazarova, Igor I. Cherednikov
article en

Abstract

BACKGROUND: Extreme conditions and the specific demands of military profession cause stress in military personnel who exhibit signs of neuropsychological instability, which disrupts their functional state and can lead to erroneous actions, emergency situations and, consequently, failure in training and combat missions. Existing methods for assessing an individual’s neuropsychological stability have certain limitations, so the development and introduction of additional, objective techniques for diagnosing neuropsychological stability and signs of instability in military personnel are highly relevant. AIM: To develop a mathematical model for diagnosing signs of neuropsychological instability in military personnel using stabilometry. MATERIALS AND METHODS: The study involved 50 servicemen with similar military occupational specialty, whose average age was 24.05±1.02 years. Assessment of their professional skills and personal traits was carried out using the General Fitness for Military Service-3 method. Based on the data obtained, the sample was split into two groups: No signs of neuropsychological instability (n=36; 72%) and Signs of neuropsychological instability (n=14; 28%). The short-term locomotion memory was analyzed using the Triangle test on the Stabilan-01-2 stabilizer. The significance of differences between the groups was assessed using the Mann–Whitney U test. The multiple regression method and discriminant analysis were used to develop decision rules. RESULTS: Servicemen with signs of neuropsychological instability exhibited lower balance function stability at all stages of testing. Locomotion memory — along with image, emotional, and verbal-logical memory, which characterizes mental activity — can serve as a marker for identifying signs of neuropsychological instability. We developed a diagnostic model for assessing signs of neuropsychological instability in servicemen, which has high sensitivity and specificity. We also proposed the decision rules to classify military personnel into either exhibiting or not exhibiting signs of neuropsychological instability based on the results of short-term locomotion memory testing using stabilometry. CONCLUSIONS: The use of stabilometry as an additional method for objectifying aptitude screening results will enhance the effectiveness of selection processes in the Armed Forces of the Russian Federation.

Humanitarian Military JournalVol. 1(1)
Technopolis (Finland) (FI)
Openalex Percentile: Top 83%
Occupational Health and Performance
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.