Cargando…

ChatGPT for Systematic and Scoping Reviews in Public Health Research: An Applicable Approach

BACKGROUND: The Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) is a well-defined framework that guides researchers in compiling knowledge from a domain and presenting it with clarity, objectivity, and relevant information to their peers. PRISMA has been widely used in pu...

Descripción completa

Detalles Bibliográficos
Autores principales: Miranda, P, Kaur, J, Abhari, S, Morita, P P
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10596666/
http://dx.doi.org/10.1093/eurpub/ckad160.1237
_version_ 1785125158657196032
author Miranda, P
Kaur, J
Abhari, S
Morita, P P
author_facet Miranda, P
Kaur, J
Abhari, S
Morita, P P
author_sort Miranda, P
collection PubMed
description BACKGROUND: The Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) is a well-defined framework that guides researchers in compiling knowledge from a domain and presenting it with clarity, objectivity, and relevant information to their peers. PRISMA has been widely used in public health research to conduct systematic and scoping reviews and contribute to the body of knowledge. However, with the ever-increasing production of new studies, a valid sample of the number of papers available may not be represented by any systematic review in the future. METHODS: In this work, we propose the utilization of technologies such as chat-GPT as a tool to automate parts of the PRISMA process and increase the proportional representation that one systematic review can provide. We present an unguided exploratory experiment with chat-GPT that retro-fed information about PRISMA until chat-GPT created a data structure suitable to be used by crawlers to conduct PRISMA data collection. We also used the created data structure as input to chat-GPT in an attempt to summarize the information contained in the document in the format of a systematic review. RESULTS: The created data structure was also used to help do a systematic review summary using chat-GPT.Also, results indicate that this approach has the potential to increase the efficiency and scalability of systematic reviews. CONCLUSIONS: The proposed approach has the potential to enhance the effectiveness of systematic and scoping reviews and increase the proportional representation of the number of papers available. While further research is necessary to assess the feasibility and scalability of using chat-GPT in this context, this study highlights the promise of leveraging new technologies to improve the quality and efficiency of systematic reviews in public health research. KEY MESSAGES: • PRISMA is a systematic review framework that is both effective and intricate, requiring significant time and effort to execute. • The utilization of chat-GPT can automate parts of the PRISMA process and increase proportional representation in systematic reviews.
format Online
Article
Text
id pubmed-10596666
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-105966662023-10-25 ChatGPT for Systematic and Scoping Reviews in Public Health Research: An Applicable Approach Miranda, P Kaur, J Abhari, S Morita, P P Eur J Public Health Poster Displays BACKGROUND: The Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) is a well-defined framework that guides researchers in compiling knowledge from a domain and presenting it with clarity, objectivity, and relevant information to their peers. PRISMA has been widely used in public health research to conduct systematic and scoping reviews and contribute to the body of knowledge. However, with the ever-increasing production of new studies, a valid sample of the number of papers available may not be represented by any systematic review in the future. METHODS: In this work, we propose the utilization of technologies such as chat-GPT as a tool to automate parts of the PRISMA process and increase the proportional representation that one systematic review can provide. We present an unguided exploratory experiment with chat-GPT that retro-fed information about PRISMA until chat-GPT created a data structure suitable to be used by crawlers to conduct PRISMA data collection. We also used the created data structure as input to chat-GPT in an attempt to summarize the information contained in the document in the format of a systematic review. RESULTS: The created data structure was also used to help do a systematic review summary using chat-GPT.Also, results indicate that this approach has the potential to increase the efficiency and scalability of systematic reviews. CONCLUSIONS: The proposed approach has the potential to enhance the effectiveness of systematic and scoping reviews and increase the proportional representation of the number of papers available. While further research is necessary to assess the feasibility and scalability of using chat-GPT in this context, this study highlights the promise of leveraging new technologies to improve the quality and efficiency of systematic reviews in public health research. KEY MESSAGES: • PRISMA is a systematic review framework that is both effective and intricate, requiring significant time and effort to execute. • The utilization of chat-GPT can automate parts of the PRISMA process and increase proportional representation in systematic reviews. Oxford University Press 2023-10-24 /pmc/articles/PMC10596666/ http://dx.doi.org/10.1093/eurpub/ckad160.1237 Text en © The Author(s) 2023. Published by Oxford University Press on behalf of the European Public Health Association. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Poster Displays
Miranda, P
Kaur, J
Abhari, S
Morita, P P
ChatGPT for Systematic and Scoping Reviews in Public Health Research: An Applicable Approach
title ChatGPT for Systematic and Scoping Reviews in Public Health Research: An Applicable Approach
title_full ChatGPT for Systematic and Scoping Reviews in Public Health Research: An Applicable Approach
title_fullStr ChatGPT for Systematic and Scoping Reviews in Public Health Research: An Applicable Approach
title_full_unstemmed ChatGPT for Systematic and Scoping Reviews in Public Health Research: An Applicable Approach
title_short ChatGPT for Systematic and Scoping Reviews in Public Health Research: An Applicable Approach
title_sort chatgpt for systematic and scoping reviews in public health research: an applicable approach
topic Poster Displays
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10596666/
http://dx.doi.org/10.1093/eurpub/ckad160.1237
work_keys_str_mv AT mirandap chatgptforsystematicandscopingreviewsinpublichealthresearchanapplicableapproach
AT kaurj chatgptforsystematicandscopingreviewsinpublichealthresearchanapplicableapproach
AT abharis chatgptforsystematicandscopingreviewsinpublichealthresearchanapplicableapproach
AT moritapp chatgptforsystematicandscopingreviewsinpublichealthresearchanapplicableapproach