Karen Nieto Rodríguez

Background The functional-cognitive impact of first-episode psychosis (FEP) is extremely relevant and implies dysfunction from early life stages like adolescence and youth. Like other illnesses, FEP incidence is also influenced by environmental factors. It is necessary to attend to this age group with early interventions and to act on the environmental factors that the literature correlates with increased FEP incidence: socio-economic aspects, social adversity, bullying at school or cannabis use. In this context, identifying the areas of cities where FEP patients concentrate is important to perform early interventions. The spatial analysis of patient distribution in a whole city is one way to identify the most vulnerable areas and to propose psycho-social interventions for the possible prevention and/or early detection of FEP by improving urban mental health. Methods An epidemiological study of point patterns to determine the areas of a city with a higher incidence of patients with FEP. To do so, the addresses of FEP cases were georeferenced from 1 January 2016 to 31 October 2022, and 109 FEP patients were analysed. Data from a random sample of 383 controls, comprising their addresses, age, and sex, were randomly obtained from the official city council database. By GIS, the areas with higher FEP incidence were analysed to see if they coincided with the zones where inhabitants with lower incomes lived. Results The risk ratio of the FEP patients was compatible with the constant risk ratio in Albacete (p = 0.22). When performing the process separately with cases and controls only in men and women, the results were not significant for both distributions (p value: 0.12 and 0.57, respectively). Nonetheless, areas within the city had a significantly higher risk. These groups of cases coincided with those who had lower income and more inequality for women, but this pattern was not clear for men. Conclusions Classifying city areas per income can help to determine the zones at higher risk of FEP, which would allow early healthcare and preventive measures for these zones.

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.