IRB-draft-generator: A generative AI tool to streamline the creation of institutional review board applications
The Institutional Review Board (IRB) is fundamental to conducting ethical research involving human subjects. IRB applications require detailed descriptions of the research and specific indications of how the research will be implemented. This can be difficult for inexperienced researchers. Preparing...
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| Format: | Article |
| Language: | English |
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Elsevier
2024-02-01
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| Series: | SoftwareX |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352711023002972 |
| _version_ | 1797398599787610112 |
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| author | Ryan C. Godwin Ayesha S. Bryant Brant M. Wagener Timothy J. Ness Jennifer J. DeBerry LaShun L. Horn Shanna H. Graves Ashley C. Archer Ryan L. Melvin |
| author_facet | Ryan C. Godwin Ayesha S. Bryant Brant M. Wagener Timothy J. Ness Jennifer J. DeBerry LaShun L. Horn Shanna H. Graves Ashley C. Archer Ryan L. Melvin |
| author_sort | Ryan C. Godwin |
| collection | DOAJ |
| description | The Institutional Review Board (IRB) is fundamental to conducting ethical research involving human subjects. IRB applications require detailed descriptions of the research and specific indications of how the research will be implemented. This can be difficult for inexperienced researchers. Preparing the application is a significant time commitment, even for experienced researchers. In order to lighten the administrative burden on busy clinical professionals, this software application will automatically generate a draft human subject research protocol (the most laborious element of an IRB application) based on responses to a short form. This technology uses generative AI and a custom literature search plug-in to draft the protocol from succinct, user-provided details. User inputs include a brief description of the research, including the hypothesis, inclusion/exclusion criteria, and the study design type (e.g., randomized clinical trial). This tool can expedite the IRB application creation process, provide additional consistency for reviewers, and may reduce clinician researcher burnout through a reduction in clerical work thereby facilitating participation in meaningful research. |
| first_indexed | 2024-03-09T01:27:53Z |
| format | Article |
| id | doaj.art-e678c47e31d841579b6b230da55c4d03 |
| institution | Directory Open Access Journal |
| issn | 2352-7110 |
| language | English |
| last_indexed | 2024-03-09T01:27:53Z |
| publishDate | 2024-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | SoftwareX |
| spelling | doaj.art-e678c47e31d841579b6b230da55c4d032023-12-10T06:16:24ZengElsevierSoftwareX2352-71102024-02-0125101601IRB-draft-generator: A generative AI tool to streamline the creation of institutional review board applicationsRyan C. Godwin0Ayesha S. Bryant1Brant M. Wagener2Timothy J. Ness3Jennifer J. DeBerry4LaShun L. Horn5Shanna H. Graves6Ashley C. Archer7Ryan L. Melvin8Department of Anesthesiology and Perioperative Medicine, The University of Alabama at Birmingham School of Medicine, United States; Department of Radiology, The University of Alabama at Birmingham School of Medicine, United States; Corresponding author.Department of Anesthesiology and Perioperative Medicine, The University of Alabama at Birmingham School of Medicine, United StatesDepartment of Anesthesiology and Perioperative Medicine, The University of Alabama at Birmingham School of Medicine, United StatesDepartment of Anesthesiology and Perioperative Medicine, The University of Alabama at Birmingham School of Medicine, United StatesDepartment of Anesthesiology and Perioperative Medicine, The University of Alabama at Birmingham School of Medicine, United StatesDepartment of Anesthesiology and Perioperative Medicine, The University of Alabama at Birmingham School of Medicine, United StatesDepartment of Anesthesiology and Perioperative Medicine, The University of Alabama at Birmingham School of Medicine, United StatesThe University of Alabama at Birmingham School of Medicine, United StatesDepartment of Anesthesiology and Perioperative Medicine, The University of Alabama at Birmingham School of Medicine, United StatesThe Institutional Review Board (IRB) is fundamental to conducting ethical research involving human subjects. IRB applications require detailed descriptions of the research and specific indications of how the research will be implemented. This can be difficult for inexperienced researchers. Preparing the application is a significant time commitment, even for experienced researchers. In order to lighten the administrative burden on busy clinical professionals, this software application will automatically generate a draft human subject research protocol (the most laborious element of an IRB application) based on responses to a short form. This technology uses generative AI and a custom literature search plug-in to draft the protocol from succinct, user-provided details. User inputs include a brief description of the research, including the hypothesis, inclusion/exclusion criteria, and the study design type (e.g., randomized clinical trial). This tool can expedite the IRB application creation process, provide additional consistency for reviewers, and may reduce clinician researcher burnout through a reduction in clerical work thereby facilitating participation in meaningful research.http://www.sciencedirect.com/science/article/pii/S2352711023002972Institutional review boardGenerative AILarge language models |
| spellingShingle | Ryan C. Godwin Ayesha S. Bryant Brant M. Wagener Timothy J. Ness Jennifer J. DeBerry LaShun L. Horn Shanna H. Graves Ashley C. Archer Ryan L. Melvin IRB-draft-generator: A generative AI tool to streamline the creation of institutional review board applications SoftwareX Institutional review board Generative AI Large language models |
| title | IRB-draft-generator: A generative AI tool to streamline the creation of institutional review board applications |
| title_full | IRB-draft-generator: A generative AI tool to streamline the creation of institutional review board applications |
| title_fullStr | IRB-draft-generator: A generative AI tool to streamline the creation of institutional review board applications |
| title_full_unstemmed | IRB-draft-generator: A generative AI tool to streamline the creation of institutional review board applications |
| title_short | IRB-draft-generator: A generative AI tool to streamline the creation of institutional review board applications |
| title_sort | irb draft generator a generative ai tool to streamline the creation of institutional review board applications |
| topic | Institutional review board Generative AI Large language models |
| url | http://www.sciencedirect.com/science/article/pii/S2352711023002972 |
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