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This page is an AI-assisted Turkish summary of the study presented at the 26th World Congress of Psychiatry. The study belongs to the presenting authors; please refer to the original source when citing it.

SO262

The role of artificial intelligence in expanding mental health capacity in community-based settings: improving equity, development, and inclusion

ROLE OF AI IN EXPANDING MH CAPACITY IN A COMMUNITY SETTING TO IMPROVE EQUITY, DEVELOPMENT AND INCLUSION POPULATIONS

Artificial intelligence is positioned as a supportive tool for training the mental health workforce and expanding service capacity in underserved communities, under the supervision of experienced mental health professionals.

The study aims to expand mental health capacity with artificial intelligence (AI) support in underserved and trauma-affected communities in Brazil's Amazon region and the United States, and to provide a model for establishing similar programs in low- and middle-income countries. The poster introduces the Community Translational Research Institute's structure, which integrates research, education, and clinical services within a single community-embedded model; the model's four components are defined as translational research, workforce and education, culturally responsive clinical services, and AI innovation. As its methodological approach, an AI-supported training and supervision program was developed for untrained community mental health workers under the supervision and oversight of experienced doctoral-level mental health professionals. The program was evaluated using feedback collected from trainees and patients. The reported finding is that both patients and trainees considered AI an effective approach, and trainees viewed AI positively as a training tool. The poster does not report a sample size, measurement scale, proportion, or statistical test result; it describes field teams in rural and underserved communities and international collaborations established with universities in Brazil and the Amazon region. In conclusion, the authors argue that, through a multidisciplinary and culturally responsive approach, strengthening existing community resources with AI may offer clinically effective, cost-efficient, and sustainable assessment and care, while increasing capacity and enabling faster access to care.

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