Harnessing Language Intelligence.Innovative Approaches to Sustainable Mental Health Interventions in the Digital Age

Malik Harris Zahir ()
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Malik Harris Zahir: Department of Computer Science, University of South Asia, Lahore, 53000, Pakistan

International Journal of Innovations in Science & Technology, 2024, vol. 6, issue 4, 2027-2046

Abstract: This study explores the advanced abilities of Natural Language Processing (NLP) methods to revolutionize mental health treatment by understanding how such interventions improve therapeutic outcomes. In doing so, the work of this study is demonstrated as an innovative approach to translating conversational data into actionable insights that bridge a large gap in the detection of subtle emotional cues in mental health assessments. The research used DistilBERT, an optimized version of the BERT framework, which hasbeen fine-tuned on specially selected datasets to accurately identify emotional states such as sadness, joy, anger, and fear. Emotional and linguistic patterns were analyzed to identify oftenunarticulated signals to identify disorders such as depression, anxiety, and Post-Traumatic Stress Disorder (PTSD) much earlier. In this regard, the model has been found to significantly enhance the understanding of patients' emotional states more accurately and subtly than through traditional means. The findings of this study highlight the potential of offering individualized therapeutic interventions within digital health applications, which enables immediate emotional well-being assessments. The study showcases the flexibility of AI-based systems, making them applicable to almost any environment, including a workplace setting, to promote both wellness and productivity. This study sets the ground for developing scalable, customized, and proactive mental health care strategies that are beyond conventional therapeutic frameworks.

Keywords: Natural Language Processing; Mental Health Analysis; Digital Intelligence; Emotion Detection; Harnessing Language Intelligence (search for similar items in EconPapers)
Date: 2024
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