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Developing Al-Powered Chatbots for Mental Health Support in Rural America

Author

Listed:
  • Jesmin Ul Zannat Kabir

    (MSA, IT Project Management, Central Michigan University, Mount Pleasant, Michigan, USA)

  • Ashrafur Rahman Nabil

    (MS in Information Technology Management, St. Francis College, Brooklyn, New York, USA)

  • Reshad Ahmed

    (Master’s in Exercise Physiology, Department of Exercise Physiology, Central Michigan University, Mount Pleasant, Michigan, USA)

Abstract

The Substance Abuse and Mental Health Services Administration [SAMHSA] (2021) reports that rural America faces three major challenges when dealing with mental health needs because of geographic separation combined with insufficient mental health professionals and widespread stigma against mental health. The integration of Artificial Intelligence (AI)-powered chatbots establishes a revolutionary designment for accessible cost-efficient scalable mental health assistance. The chatbots deliver cognitive-behavioral therapy techniques together with real-time crisis intervention and customized guidance that adapts to the specific needs of each rural population (Fitzpatrick et al., 2017). This research examines culturally appropriate AI-powered chatbot design methods together with ethical practices alongside protective measures for user privacy and data security (Reddy et al., 2019). Through technological innovation rural communities can overcome mental health service gaps which create new possibilities for both mental healthcare intervention and better mental well-being results. AI chatbot research shows their effectiveness for reshaping mental health services in rural locations while both protecting patient well-being and building resilience among local populations.

Suggested Citation

  • Jesmin Ul Zannat Kabir & Ashrafur Rahman Nabil & Reshad Ahmed, 2025. "Developing Al-Powered Chatbots for Mental Health Support in Rural America," Journal of Computer Science and Technology Studies, Al-Kindi Center for Research and Development, vol. 7(2), pages 23-35, March.
    • Handle: RePEc:alk:jcsts0:v:7:y:2025:i:2:id:8975
    DOI: 10.32996/jcsts.2025.7.2.3
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