Other Titles
The Utilization of Artificial Intelligence (AI) to Address the Impact of Climate Change on Black Pediatric Mental Health [Title Slide]
Abstract
Introduction: Climate change significantly impacts mental health, especially in vulnerable populations such as Black pediatric communities who experience compounded climate stressors due to socioeconomic and environmental inequalities. Artificial Intelligence (AI) provides innovative methods for predicting, managing, and mitigating these mental health risks.
Purpose: This integrative review aims to explore AI's potential in addressing the mental health challenges posed by climate change, specifically within Black pediatric populations.
Methods: A systematic approach was used to review studies examining climate change, mental health, and AI interventions targeting Black pediatric populations. Out of 183 screened studies, 20 met the criteria for inclusion based on their focus on AI-driven mental health interventions.
Results: AI demonstrates potential in identifying at-risk populations, tailoring mental health interventions, and facilitating early detection of mental health conditions linked to climate stressors. However, ethical considerations, including data privacy and equitable access, are essential to avoid perpetuating existing health disparities.
Nursing Implications: Nurses play a critical role in applying AI to assess risks, coordinate care, and advocate for fair access to mental health resources in underserved communities. Their involvement is also vital in policy development to ensure AI technologies benefit vulnerable populations.
Conclusions: AI offers promising solutions for addressing climate-related mental health impacts in Black pediatric populations through predictive analytics and personalized care. Future research should focus on refining AI algorithms to incorporate social determinants of health, ensuring equitable access, and evaluating long-term outcomes. Nurses and healthcare professionals are essential in implementing these tools ethically and effectively, enhancing support for those most affected by climate change.
Notes
References:
Cowls, J., Tsamados, A., Taddeo, M., & Floridi, L. (2023). The AI gambit: Leveraging artificial intelligence to combat climate change—Opportunities, challenges, and recommendations. AI & Society, 1-25. https://doi.org/10.1007/s00146-022-01376-1
Dominguez-Rodriguez, A., Villarreal-Zegarra, D., Malaquias-Obregon, S., Herdoiza-Arroyo, P. E., González-Cantero, J. O., Chávez-Valdez, S. M., & Cruz-Martínez, R. R. (2023). Measurement scales of mental health related to climate change: A scoping review protocol using artificial intelligence. BMJ Open, 13(10), e071073. https://doi.org/10.1136/bmjopen-2023-071073
Morganstein, J. C. (2023). Disaster and mental health: The critical role of human behavior. Psychiatry (New York), 86(4), 272-277. https://doi.org/10.1080/00332747.2023.2226567
Walinski, A., Sander, J., Gerlinger, G., Clemens, V., Meyer-Lindenberg, A., & Heinz, A. (2023). The effects of climate change on mental health. Deutsches Ärzteblatt International, 120(8), 117-123. https://doi.org/10.3238/arztebl.m2023.0087
Zhang, A. Y., Bennett, M. B., Martin, S., & Grow, H. M. (2024). Climate change and heat: Challenges for child health outcomes and inequities. Current Pediatrics Reports, 1-11. https://doi.org/10.1007/s40124-023-00292-2
Sigma Membership
Nu Beta at-Large
Type
Presentation
Format Type
Text-based Document
Study Design/Type
Other
Research Approach
Other
Keywords:
Health Equity or Social Determinants of Health, Implementation Science, Stress and Coping, Artificial Intelligence, AI, Mental Health, Climate Change
Recommended Citation
Rodney, Tamar and Josiah, Nia, "AI-Driven Solutions for Climate-Related Mental Health Risks in Black Pediatric Populations" (2025). International Nursing Research Congress (INRC). 235.
https://www.sigmarepository.org/inrc/2025/presentations_2025/235
Conference Name
36th International Nursing Research Congress
Conference Host
Sigma Theta Tau International
Conference Location
Seattle, Washington, USA
Conference Year
2025
Rights Holder
All rights reserved by the author(s) and/or publisher(s) listed in this item record unless relinquished in whole or part by a rights notation or a Creative Commons License present in this item record.
Review Type
Abstract Review Only: Reviewed by Event Host
Acquisition
Proxy-submission
AI-Driven Solutions for Climate-Related Mental Health Risks in Black Pediatric Populations
Seattle, Washington, USA
Introduction: Climate change significantly impacts mental health, especially in vulnerable populations such as Black pediatric communities who experience compounded climate stressors due to socioeconomic and environmental inequalities. Artificial Intelligence (AI) provides innovative methods for predicting, managing, and mitigating these mental health risks.
Purpose: This integrative review aims to explore AI's potential in addressing the mental health challenges posed by climate change, specifically within Black pediatric populations.
Methods: A systematic approach was used to review studies examining climate change, mental health, and AI interventions targeting Black pediatric populations. Out of 183 screened studies, 20 met the criteria for inclusion based on their focus on AI-driven mental health interventions.
Results: AI demonstrates potential in identifying at-risk populations, tailoring mental health interventions, and facilitating early detection of mental health conditions linked to climate stressors. However, ethical considerations, including data privacy and equitable access, are essential to avoid perpetuating existing health disparities.
Nursing Implications: Nurses play a critical role in applying AI to assess risks, coordinate care, and advocate for fair access to mental health resources in underserved communities. Their involvement is also vital in policy development to ensure AI technologies benefit vulnerable populations.
Conclusions: AI offers promising solutions for addressing climate-related mental health impacts in Black pediatric populations through predictive analytics and personalized care. Future research should focus on refining AI algorithms to incorporate social determinants of health, ensuring equitable access, and evaluating long-term outcomes. Nurses and healthcare professionals are essential in implementing these tools ethically and effectively, enhancing support for those most affected by climate change.
Description
Climate change impacts mental health, particularly in vulnerable Black pediatric populations facing compounded stressors due to systemic inequalities. AI offers potential to predict, manage, and mitigate these risks through early intervention and tailored support. This review highlights AI's ability to address climate-induced mental health issues but stresses the need for ethical application, equitable access, and nurse involvement in policy and care delivery.