Utilizing artificial intelligence to optimize psychological trauma intervention in social assistances

Area of Science:

• Mental Health
• Artificial Intelligence
• Social Assistance

Background:

• Psychological trauma is common among social assistance recipients, challenging traditional interventions due to resource limits and lack of personalization.
• Artificial intelligence (AI) presents opportunities to improve efficiency and precision in psychological trauma care.
• This study investigates integrating AI into social assistance systems for enhanced mental health support.

Purpose of the Study:

• To explore the feasibility and effectiveness of AI in psychological trauma interventions within social assistance.
• To propose an AI-driven framework for psychological trauma support.
• To evaluate user experience and outcomes of AI-assisted mental health interventions.

Main Methods:

• Review of current AI applications in mental health (NLP, emotion recognition, recommendation systems).
• Development of an AI framework including intelligent diagnostics and personalized plans.
• Empirical data collection via surveys to assess user satisfaction and mental health improvements.

Main Results:

• AI-assisted interventions significantly boosted user satisfaction (75% satisfied/very satisfied).
• Approximately 60% of participants showed noticeable improvements in mental health.
• 85% found personalized AI intervention plans highly relevant to their needs.

Conclusions:

• AI technologies effectively address limitations of traditional psychological support, enhancing accessibility, responsiveness, and personalization.
• Integrating AI into social assistance improves intervention outcomes and provides scalable solutions.
• This research empirically validates AI's role in advancing mental health governance within social assistance programs.