IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0321309.html
   My bibliography  Save this article

Using large language models to learn from recent climate change discourse in public health

Author

Listed:
  • Anna Belova
  • Raquel A Silva
  • Dylan M Vorndran
  • Natalie R Sampson

Abstract

Background: Public health has increasingly recognized the links between climate change and health, emphasizing the need to address related inequities. This is reflected in work led by the Intergovernmental Panel on Climate Change, the UN Framework Convention on Climate Change, the U.S. National Climate Assessment, and leading health-related professional associations, such as the American Public Health Association (APHA). We ask how the focus of climate change-related topics in public health discourse has evolved, and what does this signal about the field’s role and capacity to address this global crisis? Methods: We analyzed close to 41,000 abstracts from APHA annual meetings (2017–2023). Using a combination of large language models and expert review, we identified and analyzed over 1,100 abstracts with climate change-related content. We used a fine-tuned OpenAI GPT-3.5 model to detect abstracts with climate change-related content and the Claude 3.0 Sonnet model to categorize these abstracts into 21 themes and 12 health outcome categories. Results: Since 2017, the discussion of climate change at APHA has declined both in terms of volume and topic diversity. The impacts of climate change on heat-related illness, stress and mental illness, and vector-borne diseases were the most common topics discussed. Fewer abstracts discussed the role of public health, workforce development, and policy and advocacy, with slightly more attention focused on health communication and education. Conclusions: Although this is only a snapshot of recent discourse in the field, trends suggest the need to build capacity for climate action. Addressing the climate crisis is not solely an environmental health issue; it is a public health issue. Advocates, policymakers, and scholars know that innovative and intersectoral solutions are critical for effective and equitable climate action. However, within public health, we must work together and jointly contribute to reducing the unequal and extensive burdens associated with our changing climate.

Suggested Citation

  • Anna Belova & Raquel A Silva & Dylan M Vorndran & Natalie R Sampson, 2025. "Using large language models to learn from recent climate change discourse in public health," PLOS ONE, Public Library of Science, vol. 20(4), pages 1-13, April.
  • Handle: RePEc:plo:pone00:0321309
    DOI: 10.1371/journal.pone.0321309
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0321309
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0321309&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0321309?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0321309. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.