@article{anderson_generative_2023,
	title = {Generative {AI} as a {Tool} for {Environmental} {Health} {Research} {Translation}},
	volume = {7},
	issn = {2471-1403, 2471-1403},
	url = {https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023GH000875},
	doi = {10.1029/2023GH000875},
	abstract = {Abstract
            One valuable application for generative artificial intelligence (AI) is summarizing research studies for non‐academic readers. We submitted five articles to Chat Generative Pre‐trained Transformer (ChatGPT) for summarization, and asked the article's author to rate the summaries. Higher ratings were assigned to more insight‐oriented activities, such as the production of eighth‐grade reading level summaries, and summaries highlighting the most important findings and real‐world applications. The general summary request was rated lower. For the field of environmental health science, no‐cost AI technology such as ChatGPT holds the promise to improve research translation, but it must continue to be improved (or improve itself) from its current capability.
          , 
            Plain Language Summary
            This study explored the use of generative artificial intelligence (AI), specifically Chat Generative Pre‐trained Transformer (ChatGPT), to summarize environmental health research articles. The field of environmental health sciences exemplifies this opportunity given the specialized language surrounding environmental contamination. Four differerent ChatGPT‐generated summaries were evaluated from each of five articles. The average rating of summaries indicated good content quality, though sometimes removed important details or had minor inaccuracies. This study suggests that no‐cost AI technology such as ChatGPT holds the promise to improve research translation to support environmental justice communities, mainstream media outlets, and community science groups, but within some boundaries.
          , 
            Key Points
            
              
                
                  Generative artificial intelligence (AI), popularized by services like Chat Generative Pre‐trained Transformer (ChatGPT), has been the source of much recent popular attention for publishing health research
                
                
                  AI production of high‐quality plain language summaries could improve access to scientific information
                
                
                  ChatGPT holds the promise to improve research translation, but it must continue to be improved from its current capability},
	language = {en},
	number = {7},
	urldate = {2025-09-24},
	journal = {GeoHealth},
	author = {Anderson, Lauren B. and Kanneganti, Dhiraj and Houk, Mary Bentley and Holm, Rochelle H. and Smith, Ted},
	month = jul,
	year = {2023},
	pages = {e2023GH000875},
}

{"_id":"6dZjCuouQrBtLdMBo","bibbaseid":"anderson-kanneganti-houk-holm-smith-generativeaiasatoolforenvironmentalhealthresearchtranslation-2023","author_short":["Anderson, L. B.","Kanneganti, D.","Houk, M. B.","Holm, R. H.","Smith, T."],"bibdata":{"bibtype":"article","type":"article","title":"Generative AI as a Tool for Environmental Health Research Translation","volume":"7","issn":"2471-1403, 2471-1403","url":"https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023GH000875","doi":"10.1029/2023GH000875","abstract":"Abstract One valuable application for generative artificial intelligence (AI) is summarizing research studies for non‐academic readers. We submitted five articles to Chat Generative Pre‐trained Transformer (ChatGPT) for summarization, and asked the article's author to rate the summaries. Higher ratings were assigned to more insight‐oriented activities, such as the production of eighth‐grade reading level summaries, and summaries highlighting the most important findings and real‐world applications. The general summary request was rated lower. For the field of environmental health science, no‐cost AI technology such as ChatGPT holds the promise to improve research translation, but it must continue to be improved (or improve itself) from its current capability. , Plain Language Summary This study explored the use of generative artificial intelligence (AI), specifically Chat Generative Pre‐trained Transformer (ChatGPT), to summarize environmental health research articles. The field of environmental health sciences exemplifies this opportunity given the specialized language surrounding environmental contamination. Four differerent ChatGPT‐generated summaries were evaluated from each of five articles. The average rating of summaries indicated good content quality, though sometimes removed important details or had minor inaccuracies. This study suggests that no‐cost AI technology such as ChatGPT holds the promise to improve research translation to support environmental justice communities, mainstream media outlets, and community science groups, but within some boundaries. , Key Points Generative artificial intelligence (AI), popularized by services like Chat Generative Pre‐trained Transformer (ChatGPT), has been the source of much recent popular attention for publishing health research AI production of high‐quality plain language summaries could improve access to scientific information ChatGPT holds the promise to improve research translation, but it must continue to be improved from its current capability","language":"en","number":"7","urldate":"2025-09-24","journal":"GeoHealth","author":[{"propositions":[],"lastnames":["Anderson"],"firstnames":["Lauren","B."],"suffixes":[]},{"propositions":[],"lastnames":["Kanneganti"],"firstnames":["Dhiraj"],"suffixes":[]},{"propositions":[],"lastnames":["Houk"],"firstnames":["Mary","Bentley"],"suffixes":[]},{"propositions":[],"lastnames":["Holm"],"firstnames":["Rochelle","H."],"suffixes":[]},{"propositions":[],"lastnames":["Smith"],"firstnames":["Ted"],"suffixes":[]}],"month":"July","year":"2023","pages":"e2023GH000875","bibtex":"@article{anderson_generative_2023,\n\ttitle = {Generative {AI} as a {Tool} for {Environmental} {Health} {Research} {Translation}},\n\tvolume = {7},\n\tissn = {2471-1403, 2471-1403},\n\turl = {https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023GH000875},\n\tdoi = {10.1029/2023GH000875},\n\tabstract = {Abstract\n One valuable application for generative artificial intelligence (AI) is summarizing research studies for non‐academic readers. We submitted five articles to Chat Generative Pre‐trained Transformer (ChatGPT) for summarization, and asked the article's author to rate the summaries. Higher ratings were assigned to more insight‐oriented activities, such as the production of eighth‐grade reading level summaries, and summaries highlighting the most important findings and real‐world applications. The general summary request was rated lower. For the field of environmental health science, no‐cost AI technology such as ChatGPT holds the promise to improve research translation, but it must continue to be improved (or improve itself) from its current capability.\n , \n Plain Language Summary\n This study explored the use of generative artificial intelligence (AI), specifically Chat Generative Pre‐trained Transformer (ChatGPT), to summarize environmental health research articles. The field of environmental health sciences exemplifies this opportunity given the specialized language surrounding environmental contamination. Four differerent ChatGPT‐generated summaries were evaluated from each of five articles. The average rating of summaries indicated good content quality, though sometimes removed important details or had minor inaccuracies. This study suggests that no‐cost AI technology such as ChatGPT holds the promise to improve research translation to support environmental justice communities, mainstream media outlets, and community science groups, but within some boundaries.\n , \n Key Points\n \n \n \n Generative artificial intelligence (AI), popularized by services like Chat Generative Pre‐trained Transformer (ChatGPT), has been the source of much recent popular attention for publishing health research\n \n \n AI production of high‐quality plain language summaries could improve access to scientific information\n \n \n ChatGPT holds the promise to improve research translation, but it must continue to be improved from its current capability},\n\tlanguage = {en},\n\tnumber = {7},\n\turldate = {2025-09-24},\n\tjournal = {GeoHealth},\n\tauthor = {Anderson, Lauren B. and Kanneganti, Dhiraj and Houk, Mary Bentley and Holm, Rochelle H. and Smith, Ted},\n\tmonth = jul,\n\tyear = {2023},\n\tpages = {e2023GH000875},\n}\n\n\n\n\n\n\n\n","author_short":["Anderson, L. B.","Kanneganti, D.","Houk, M. B.","Holm, R. H.","Smith, T."],"key":"anderson_generative_2023","id":"anderson_generative_2023","bibbaseid":"anderson-kanneganti-houk-holm-smith-generativeaiasatoolforenvironmentalhealthresearchtranslation-2023","role":"author","urls":{"Paper":"https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023GH000875"},"metadata":{"authorlinks":{}},"html":""},"bibtype":"article","biburl":"https://bibbase.org/zotero/andreasmartin","dataSources":["jurZeGzSpYdkQ8rm4"],"keywords":[],"search_terms":["generative","tool","environmental","health","research","translation","anderson","kanneganti","houk","holm","smith"],"title":"Generative AI as a Tool for Environmental Health Research Translation","year":2023}