Abstract
People with schizophrenia have difficulty recognizing the emotions in the facial expressions of others, which affects their social interaction and functioning in the community. Static stimuli such as photographs have been used traditionally to examine deficiencies in the recognition of emotions in patients with schizophrenia, which has been criticized by some authors for lacking the dynamism that real facial stimuli have. With the aim of overcoming these drawbacks, in recent years, the creation and validation of virtual humans has been developed. This work presents the results of a study that evaluated facial recognition of emotions through a new set of dynamic virtual humans previously designed by the research team, in patients diagnosed of schizophrenia. The study included 56 stable patients, compared with 56 healthy controls. Our results showed that patients with schizophrenia present a deficit in facial affect recognition, compared to healthy controls (average hit rate 71.6% for patients vs 90.0% for controls). Facial expressions with greater dynamism (compared to less dynamic ones), as well as those presented from frontal view (compared to profile view) were better recognized in both groups. Regarding clinical and sociodemographic variables, the number of hospitalizations throughout life did not correlate with recognition rates. There was also no correlation between functioning or quality of life and recognition. A trend showed a reduction in the emotional recognition rate as a result of increases in Positive and Negative Syndrome Scale (PANSS), being statistically significant for negative PANSS. Patients presented a learning effect during the progression of the task, slightly greater in comparison to the control group. This finding is relevant when designing training interventions for people with schizophrenia. Maintaining the attention of patients and getting them to improve in the proposed tasks is a challenge for today’s psychiatry.
Highlights
Schizophrenia is among the disorders with the greatest impact on a clinical, economic and social level [1]
The negative correlation indicates that the patients who take the longest to answer do worse. This finding is in line with another study that has analyzed the relationship between reaction times and recognition rates in schizophrenia patients [34]
Some authors pointed out the possibility that the use of dynamic avatars could improve successful recognition in patients with schizophrenia [37], deficits in facial emotion recognition appear to expand for the emotions expressed by VHs [13,38,39,40]
Summary
Schizophrenia is among the disorders with the greatest impact on a clinical, economic and social level [1]. Social cognition may be defined as those mental operations involved in social interactions, including the processes of perception, interpretation, and generation of responses to the intentions, dispositions and attitudes of others [3,5]. It is divided into four partially overlapping domains: social perception, attributional style, theory of mind and emotional processing [5,6]. In this article we focus on emotional processing, described as the aptitude to identify, facilitate, regulate, understand and handle emotions [7] This domain is in turn divided into three subdomains that include lower and upper-level processes. Facial recognition is a cornerstone in this process of perceiving the intentions and dispositions of others and guiding social interactions [8]
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