TY - JOUR
AU - H. Khan
AU - S. F. H. Bokhari
A1 - 
AB - Depression is a prevalent mental health disorder that significantly impacts primary care settings. This editorial explores the potential of artificial intelligence (AI)-powered chatbots in managing depression within primary care environments. AI chatbots offer innovative solutions to challenges faced by healthcare providers, including limited appointment times, delayed access to specialists, and stigma associated with mental health issues. These digital tools provide continuous support, personalized interactions, and early symptom detection, potentially improving accessibility and outcomes in depression management. The integration of AI chatbots in primary care presents opportunities for round-the-clock patient support, personalized interventions, and the reduction of mental health stigma. However, challenges persist, including concerns about assessment accuracy, data privacy, and integration with existing healthcare systems. Successful implementation requires systematic approaches, stakeholder engagement, and comprehensive training for healthcare providers. Ethical considerations, such as ensuring informed consent, managing algorithmic biases, and maintaining the human element in care, are crucial for responsible deployment. As AI technology evolves, future directions may include enhanced natural language processing, multimodal integration, and AI-augmented clinical decision support. This editorial emphasizes the need for a balanced approach that leverages the potential of AI while acknowledging its limitations and the irreplaceable value of human clinical judgment in depression management within primary care settings.
AD - Medicine, Naseer Teaching Hospital, Peshawar, PAK.; Surgery, King Edward Medical University, Lahore, PAK.
AN - 39280487
BT - Cureus
C5 - HIT & Telehealth; Medically Unexplained Symptoms
CP - 8
DA - Aug
DO - 10.7759/cureus.66857
DP - NLM
ET - 20240814
IS - 8
JF - Cureus
LA - eng
N2 - Depression is a prevalent mental health disorder that significantly impacts primary care settings. This editorial explores the potential of artificial intelligence (AI)-powered chatbots in managing depression within primary care environments. AI chatbots offer innovative solutions to challenges faced by healthcare providers, including limited appointment times, delayed access to specialists, and stigma associated with mental health issues. These digital tools provide continuous support, personalized interactions, and early symptom detection, potentially improving accessibility and outcomes in depression management. The integration of AI chatbots in primary care presents opportunities for round-the-clock patient support, personalized interventions, and the reduction of mental health stigma. However, challenges persist, including concerns about assessment accuracy, data privacy, and integration with existing healthcare systems. Successful implementation requires systematic approaches, stakeholder engagement, and comprehensive training for healthcare providers. Ethical considerations, such as ensuring informed consent, managing algorithmic biases, and maintaining the human element in care, are crucial for responsible deployment. As AI technology evolves, future directions may include enhanced natural language processing, multimodal integration, and AI-augmented clinical decision support. This editorial emphasizes the need for a balanced approach that leverages the potential of AI while acknowledging its limitations and the irreplaceable value of human clinical judgment in depression management within primary care settings.
PY - 2024
SN - 2168-8184 (Print); 2168-8184
SP - e66857
ST - Integrating Artificial Intelligence (AI) Chatbots for Depression Management: A New Frontier in Primary Care
T1 - Integrating Artificial Intelligence (AI) Chatbots for Depression Management: A New Frontier in Primary Care
T2 - Cureus
TI - Integrating Artificial Intelligence (AI) Chatbots for Depression Management: A New Frontier in Primary Care
U1 - HIT & Telehealth; Medically Unexplained Symptoms
U3 - 10.7759/cureus.66857
VL - 16
VO - 2168-8184 (Print); 2168-8184
Y1 - 2024
ER -