Publicações
O NEURONAPIS desenvolve pesquisas interdisciplinares nas fronteiras entre neurociência aplicada, psicofarmacologia, saúde mental e inteligência computacional. Nossos estudos buscam compreender os mecanismos neurobiológicos e psicossociais envolvidos em transtornos como depressão e ansiedade, utilizando abordagens inovadoras que combinam métodos clínicos, computacionais e éticos.
As linhas de pesquisa do grupo exploram temas como inteligência artificial em diagnóstico e monitoramento, ética na tecnologia aplicada à saúde mental, farmacodinâmica de psicotrópicos, e modelagem de dados em neurociência. Todos os projetos são orientados por rigor científico, impacto translacional e compromisso com o avanço do conhecimento em saúde mental.
Depression and Work Absence or Job Loss in Organizations: An Integrative Review of Psychosocial Impacts and Occupational Performance
Recognized as one of the leading global causes of disability, depression broadly impairs emotional functioning, interpersonal relationships, and occupational performance, making it a phenomenon of increasing relevance within organizational contexts. Despite the growing body of scientific inquiry into the subject, integrative reviews that systematically address its multidimensional effects on working life remain scarce. Against this backdrop, the present study aimed to critically and comprehensively examine the psychosocial impacts of depression on job loss, productivity, and occupational reintegration processes across diverse work environments. To this end, the six-stage integrative review protocol proposed by Mendes, Silveira, and Galvão (2008) was adopted, with searches conducted across PubMed, Scopus, Web of Science, PsycINFO, SciELO, and Google Scholar, covering the period from February 2025 to January 2026. A total of 95 studies published between 2015 and 2025 were selected and subjected to quantitative descriptive analysis, qualitative thematic analysis, and the TF-IDF technique, enabling the identification of substantial convergences around cognitive symptoms, presenteeism, institutional stigma, and deficiencies in reintegration policies — evidence organized into eight thematic axes, with a notable increase in scientific output from 2020 onward. The findings indicate that addressing depression in the workplace requires integrated approaches that combine clinical management, psychosocial support, and occupational risk management, with intersectional and longitudinal studies representing a priority to bridge the gaps that persist in the existing literature.
AI-based anxiety monitoring: development and clinical applications
This article presents the development of the Self-Care Journey app, an artificial intelligence (AI)--based tool for monitoring and managing anxiety symptoms. Considering the high prevalence of anxiety disorders in Brazil, which affect around 18.6 million people, the development of accessible and effective interventions is essential. It is known that anxiety is a stress-inducing behavior that reduces productivity and negatively impacts personal and professional relationships, making monitoring essential (Stein; Sareen, 2015). This study aimed to create a technological solution to promote self-awareness about mental health and support communication with health professionals. The app allows for the daily recording of physical and emotional symptoms and identifying stress triggers, using an interactive interface. The AI processes the clinical data and generates detailed reports, integrating information on anxiety patterns and recommendations based on scientific evidence. Although formal tests with users have not been carried out, analysis of the functionalities suggests that the system makes it easier to identify symptoms and monitor the evolution of anxiety, as well as improving communication with health professionals. It is concluded that the Self-Care Journey represents a practical and accessible approach to anxiety management, with potential for expansion and validation in clinical contexts. Future studies are recommended to assess usability and effectiveness in different populations.