Ethologicovideographic Correlates of Mental Disorders in Nonverbal Behavior (Part I: Frequency and Duration Characteristics of Facial-Pantomimic Reactions)

Background: the lack of obvious signs of mental disorders available for objective registration is known problems of psychiatry. The study of nonverbal behavior based on the ethological paradigm using automatic detection technologies may be one of the approaches to solving this problem. The aim of study was to compare the facial and pantomimic activity of patients with neurotic disorders and pathology of the schizophrenia spectrum in a controlled ethologovideographic study to search for behavioral biomarkers of these disorders. Patients, Control Group and Methods: 19 patients with schizophrenia spectrum disorders (SSD), 23 with neurotic disorders (ND), and 22 healthy subjects of control group (CG) were examined. The severity of SSD symptoms was determined using the PANSS scale; for ND on used the Hamilton Anxiety (HAMA-14) and Depression (HAMD-17) scales. Analysis of non-verbal behavior was carried out using the biometric video analytics complex “MIX VR-19” based on action units (AU) of the Facial Action Coding System (FACS). Results: according to the frequency and duration of facial and pantomimic reactions, facial mimics in patients with Sch was characterized by greater activity in the areas of the mouth and eyes, with a decrease of mimic activity in the area of eyebrows and head movements. Frontal orientation towards the interviewer was less frequent, while a longer duration of sadness expression and a shorter duration of surprise reactions were revealed in ND patients. Factor analysis showed that AU formed the facial complexes “thoughtfulness”, “remembering”, “lack of negativism”, “lack of distrust” in control; “search for a solution”, “surprise”, “helplessness”, “embarrassment/shyness”, “distrust” characterized NR group while “incredulous surprise”, “experience of failure”, “skepticism/distrust”, “satisfaction/superiority” were found in SSD group. Conclusions: the mimic-pantomimic response of mentally healthy persons reflected cognitive processes and was characterized by emotional neutrality in the structure of behavioral complexes of attention and contact as well as of exploring behavior. A combination of cognitive and affective facial reactions was observed within the framework of avoidant-defensive agonistic behavior and neophobia in ND. Facial reactions of emotionally charged content predominated within the complex of preventive-aggressive agonistic behavior were the most frequent patterns of nonverbal behavior in SSD.

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Journal
Psikhiatriya
Published
2025-02-23
DOI
https://doi.org/10.30629/2618-6667-2024-22-6-43-53
Citations
1
Primary Topic
Technology and Human Factors in Education and Health
Type
article
Field-Weighted Citation Impact
1.88
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article

Ethologicovideographic Correlates of Mental Disorders in Nonverbal Behavior (Part I: Frequency and Duration Characteristics of Facial-Pantomimic Reactions)

A. V. Lobachev, E. Yu. Shchelkanova, D. V. Moiseev, А. А. Марченко et al.
1 citations
Psikhiatriya
Technology and Human Factors in Education and Health
1.88
article

Ethologicovideographic Correlates of Mental Disorders in Nonverbal Behavior (Part I: Frequency and Duration Characteristics of Facial-Pantomimic Reactions)

A. V. Lobachev, E. Yu. Shchelkanova, D. V. Moiseev, А. А. Марченко, Vu-Tuan Dang, A. A. Volodarskaya, Olga Vinogradova, M. R. Nazarova, P. I. Dmitriev, K. V. Rudakova
article en
1 citations

Abstract

Background: the lack of obvious signs of mental disorders available for objective registration is known problems of psychiatry. The study of nonverbal behavior based on the ethological paradigm using automatic detection technologies may be one of the approaches to solving this problem. The aim of study was to compare the facial and pantomimic activity of patients with neurotic disorders and pathology of the schizophrenia spectrum in a controlled ethologovideographic study to search for behavioral biomarkers of these disorders. Patients, Control Group and Methods: 19 patients with schizophrenia spectrum disorders (SSD), 23 with neurotic disorders (ND), and 22 healthy subjects of control group (CG) were examined. The severity of SSD symptoms was determined using the PANSS scale; for ND on used the Hamilton Anxiety (HAMA-14) and Depression (HAMD-17) scales. Analysis of non-verbal behavior was carried out using the biometric video analytics complex “MIX VR-19” based on action units (AU) of the Facial Action Coding System (FACS). Results: according to the frequency and duration of facial and pantomimic reactions, facial mimics in patients with Sch was characterized by greater activity in the areas of the mouth and eyes, with a decrease of mimic activity in the area of eyebrows and head movements. Frontal orientation towards the interviewer was less frequent, while a longer duration of sadness expression and a shorter duration of surprise reactions were revealed in ND patients. Factor analysis showed that AU formed the facial complexes “thoughtfulness”, “remembering”, “lack of negativism”, “lack of distrust” in control; “search for a solution”, “surprise”, “helplessness”, “embarrassment/shyness”, “distrust” characterized NR group while “incredulous surprise”, “experience of failure”, “skepticism/distrust”, “satisfaction/superiority” were found in SSD group. Conclusions: the mimic-pantomimic response of mentally healthy persons reflected cognitive processes and was characterized by emotional neutrality in the structure of behavioral complexes of attention and contact as well as of exploring behavior. A combination of cognitive and affective facial reactions was observed within the framework of avoidant-defensive agonistic behavior and neophobia in ND. Facial reactions of emotionally charged content predominated within the complex of preventive-aggressive agonistic behavior were the most frequent patterns of nonverbal behavior in SSD.

PsikhiatriyaVol. 22(6)
S. M. Kirov Military Medical Academy (RU), Children's Center (US)
Openalex Percentile: Top 18%
Technology and Human Factors in Education and Health
1.88
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