War, emotions, mental health, and artificial intelligence

Area of Science:

• Psychiatry
• Computational Linguistics
• Artificial Intelligence

Background:

• War-time negative emotions disrupt societal values and mental health.
• Assessing war-time emotions is complex due to neuro-psycho-physiology.
• Existing natural language processing (NLP) tools analyze emotional content in text.

Purpose of the Study:

• To explore AI-driven technologies for enhancing mental health care in war-affected societies.
• To investigate the potential of digital therapeutics and AI in addressing mental health consequences of war.
• To propose a framework for positive emotional transformation using cognitive behavioral therapy (CBT) and emotionally based strategic communications (EBSC).

Main Methods:

• Utilizing advanced NLP and machine learning for emotional content analysis.
• Developing AI-driven digital therapeutic tools and wearable devices.
• Combining online CBT for individuals and EBSC for public-level interventions.
• Employing AI tools like ChatGPT and Gemini for EBSC stimulus design and semantic analysis.

Main Results:

• AI technologies show immense potential for cost-effective and accessible mental health care.
• Digital therapeutics and AI offer a promising approach to address war-related trauma.
• AI-enhanced EBSC can significantly improve strategic communications by understanding semantic and linguistic patterns.
• Human-in-the-loop systems with AI can create resonant, emotionally annotated messages.

Conclusions:

• AI-driven tools and digital therapeutics are crucial for future psychiatric interventions.
• A combined approach of CBT and EBSC, enhanced by AI, can positively transform dominant emotional maps.
• This strategy can effectively protect the mental health of civilian populations in war-torn regions.