Can Chatbots Assist With Grant Writing in Plastic Surgery? Utilizing ChatGPT to Start an R01 Grant.
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ABSTRACT:
SUBMITTER: Najafali D
PROVIDER: S-EPMC10349644 | biostudies-literature | 2023 Jul
REPOSITORIES: biostudies-literature
Publications
Can Chatbots Assist With Grant Writing in Plastic Surgery? Utilizing ChatGPT to Start an R01 Grant.
Najafali Daniel D Hinson Chandler C Camacho Justin M JM Galbraith Logan G LG Gupta Rohun R Reid Chris M CM
Aesthetic surgery journal 20230701 8
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Project description: Not available
| S-EPMC10264225 | biostudies-literature
Project description:IntroductionChatGPT, a sophisticated large language model (LLM), has garnered widespread attention for its ability to mimic human-like communication. As recent studies indicate a potential supportive role of ChatGPT in academic writing, we assessed the LLM's capacity to generate accurate and comprehensive scientific abstracts from published Randomised Controlled Trial (RCT) data, focusing on the adherence to the Consolidated Standards of Reporting Trials for Abstracts (CONSORT-A) statement, in comparison to the original authors' abstracts.MethodologyRCTs, identified in a PubMed/MEDLINE search post-September 2021 across various medical disciplines, were subjected to abstract generation via ChatGPT versions 3.5 and 4, following the guidelines of the respective journals. The overall quality score (OQS) of each abstract was determined by the total number of adequately reported components from the 18-item CONSORT-A checklist. Additional outcome measures included percent adherence to each CONOSORT-A item, readability, hallucination rate, and regression analysis of reporting quality determinants.ResultsOriginal abstracts achieved a mean OQS of 11.89 (95% CI: 11.23-12.54), outperforming GPT 3.5 (7.89; 95% CI: 7.32-8.46) and GPT 4 (5.18; 95% CI: 4.64-5.71). Compared to GPT 3.5 and 4 outputs, original abstracts were more adherent with 10 and 14 CONSORT-A items, respectively. In blind assessments, GPT 3.5-generated abstracts were deemed most readable in 62.22% of cases which was significantly greater than the original (31.11%; P = 0.003) and GPT 4-generated (6.67%; P<0.001) abstracts. Moreover, ChatGPT 3.5 exhibited a hallucination rate of 0.03 items per abstract compared to 1.13 by GPT 4. No determinants for improved reporting quality were identified for GPT-generated abstracts.ConclusionsWhile ChatGPT could generate more readable abstracts, their overall quality was inferior to the original abstracts. Yet, its proficiency to concisely relay key information with minimal error holds promise for medical research and warrants further investigations to fully ascertain the LLM's applicability in this domain.
| S-EPMC10866463 | biostudies-literature
Project description:Informed consent is a crucial requirement of a patient's surgical care but can be a burdensome task. Artificial intelligence (AI) and machine learning language models may provide an alternative approach to writing detailed, readable consent forms in an efficient manner. No studies have assessed the accuracy and completeness of AI-generated consents for aesthetic plastic surgeries. This study aims to compare the length, reading level, accuracy, and completeness of informed consent forms that are AI chatbot (ChatGPT-4; OpenAI, San Francisco, CA) generated vs plastic surgeon generated for the most commonly performed aesthetic plastic surgeries. This study is a cross-sectional design comparing informed consent forms created by the American Association of Plastic Surgeons (ASPS) with informed consent forms generated by ChatGPT-4 for the 5 most commonly performed plastic surgery procedures: liposuction, breast augmentation, abdominoplasty, breast lift, and blepharoplasty. The average word count of ChatGPT forms was lower than the ASPS-generated forms (1023 vs 2901, P = .01). Average reading level for ChatGPT forms was also lower than the ASPS forms (11.2 vs 12.5, P = .02). There was no difference between accuracy and completeness scores for general descriptions of the surgery, risks, benefits, or alternatives. The mean overall impression score for ChatGPT consents was 2.33, whereas it was 2.23 for ASPS consent forms (P = .18). In this study, the authors demonstrate that informed consent forms generated by ChatGPT were significantly shorter and more readable than ASPS forms with no significant difference in completeness and accuracy.Level of evidence 5 risk
| S-EPMC11561908 | biostudies-literature
Project description:Many granting agencies allow reviewers to know the identity of a proposal's principal investigator (PI), which opens the possibility that reviewers discriminate on the basis of PI race and gender. We investigated this experimentally with 48 NIH R01 grant proposals, representing a broad range of NIH-funded science. We modified PI names to create separate white male, white female, black male and black female versions of each proposal, and 412 scientists each submitted initial reviews for 3 proposals. We find little to no race or gender bias in initial R01 evaluations, and additionally find that any bias that might have been present must be negligible in size. This conclusion was robust to a wide array of statistical model specifications. Pragmatically, important bias may be present in other aspects of the granting process, but our evidence suggests that it is not present in the initial round of R01 reviews.
| S-EPMC6699508 | biostudies-literature
Project description:PurposeTo evaluate the ability of ChatGPT-4 to generate a biomedical review article on fertility preservation.MethodsChatGPT-4 was prompted to create an outline for a review on fertility preservation in men and prepubertal boys. The outline provided by ChatGPT-4 was subsequently used to prompt ChatGPT-4 to write the different parts of the review and provide five references for each section. The different parts of the article and the references provided were combined to create a single scientific review that was evaluated by the authors, who are experts in fertility preservation. The experts assessed the article and the references for accuracy and checked for plagiarism using online tools. In addition, both experts independently scored the relevance, depth, and currentness of the ChatGPT-4's article using a scoring matrix ranging from 0 to 5 where higher scores indicate higher quality.ResultsChatGPT-4 successfully generated a relevant scientific article with references. Among 27 statements needing citations, four were inaccurate. Of 25 references, 36% were accurate, 48% had correct titles but other errors, and 16% were completely fabricated. Plagiarism was minimal (mean = 3%). Experts rated the article's relevance highly (5/5) but gave lower scores for depth (2-3/5) and currentness (3/5).ConclusionChatGPT-4 can produce a scientific review on fertility preservation with minimal plagiarism. While precise in content, it showed factual and contextual inaccuracies and inconsistent reference reliability. These issues limit ChatGPT-4 as a sole tool for scientific writing but suggest its potential as an aid in the writing process.
| S-EPMC11263262 | biostudies-literature
Project description: Not available
| S-EPMC8691166 | biostudies-literature
Project description:BackgroundA diverse research workforce is essential for catalyzing biomedical advancements, but this workforce goal is hindered by persistent sex and racial/ethnic disparities among investigators receiving research grants from the National Institutes of Health (NIH). In response, the NIH-funded National Research Mentoring Network implemented a Grant Writing Coaching Program (GCP) to provide diverse cohorts of early-career investigators across the United States with intensive coaching throughout the proposal development process. We evaluated the GCP's national reach and short-term impact on participants' proposal submissions and funding outcomes.MethodsThe GCP was delivered as six similar but distinct models. All models began with an in-person group session, followed by a series of coaching sessions over 4 to 12 months. Participants were surveyed at 6-, 12- and 18-months after program completion to assess proposal outcomes (submissions, awards). Self-reported data were verified and supplemented by searches of public repositories of awarded grants when available. Submission and award rates were derived from counts of participants who submitted or were awarded at least one grant proposal in a category (NIH, other federal, non-federal).ResultsFrom June 2015 through March 2019, 545 investigators (67% female, 61% under-represented racial/ethnic minority, URM) from 187 different institutions participated in the GCP. Among them, 324 (59% of participants) submitted at least one grant application and 134 (41% of submitters) received funding. A total of 164 grants were awarded, the majority being from the NIH (93, 56%). Of the 74 R01 (or similar) NIH research proposals submitted by GCP participants, 16 have been funded thus far (56% to URM, 75% to women). This 22% award rate exceeded the 2016-2018 NIH success rates for new R01s.ConclusionInter- and intra-institutional grant writing coaching groups are a feasible and effective approach to supporting the grant acquisition efforts of early-career biomedical investigators, including women and those from URM groups.
| S-EPMC7652313 | biostudies-literature
Project description:BackgroundThe lack of race/ethnic and gender diversity in grants funded by the National Institutes of Health (NIH) is a persistent challenge related to career advancement and the quality and relevance of health research. We describe pilot programs at nine institutions supported by the NIH-sponsored Building Infrastructure Leading to Diversity (BUILD) program aimed at increasing diversity in biomedical research.MethodsWe collected data from the 2016-2017 Higher Education Research Institute survey of faculty and NIH progress reports for the first four years of the program (2015-2018). We then conducted descriptive analyses of data from the nine BUILD institutions that had collected data and evaluated which activities were associated with research productivity. We used Poisson regression and rate ratios of the numbers of BUILD pilots funded, students included, abstracts, presentations, publications, and submitted and funded grant proposals.ResultsTeaching workshops were associated with more abstracts (RR 4.04, 95% CI 2.21-8.09). Workshops on grant writing were associated with more publications (RR 2.64, 95% CI 1.64-4.34) and marginally with marginally more presentations. Incentives to develop courses were associated with more abstracts published (RR 4.33, 95% CI 2.56-7.75). Workshops on research skills and other incentives were not associated with any positive effects.ConclusionsPilot interventions show promise in supporting diversity in NIH-level research. Longitudinal modeling that considers time lags in career development in moving from project development to grants submissions can provide more direction for future diversity pilot interventions.
| S-EPMC9499285 | biostudies-literature
Project description:Grant writing is an essential skill necessary to secure financial support for community programs and research projects. Increasingly, funding opportunities for translational biomedical research require studies to engage community partners, patients, or other stakeholders in the research process to address their concerns. However, there is little evidence on strategies to prepare teams of academic and community partners to collaborate on grants. This paper presents the description and formative evaluation of a two-part community-academic partnered grant writing series designed to help community organizations and academic institutions build infrastructure for collaborative research projects using a partnered approach. The first phase of the series was a half-day workshop on grant readiness, which was open to all interested community partners. The second phase, open only to community-academic teams that met eligibility criteria, was a 12-week session that covered partnered grant writing for foundation grants and National Institutes of Health grants. Participants in both phases reported an increase in knowledge and self-efficacy for writing partnered proposals. At 1-year follow-up, participants in Phase 2 had secured approximately $1.87 million in funding. This community-academic partnered grant writing series helped participants obtain proposal development skills and helped community-academic teams successfully compete for funding.
| S-EPMC5300023 | biostudies-literature
Project description:BackgroundChatGPT is widely used for writing tasks, yet its effects on medical students' academic writing remain underexplored. This study aims to elucidate ChatGPT's impact on academic writing efficiency and quality among medical students, while also evaluating students' attitudes towards its use in academic writing.MethodsWe collected systematic reviews from 130 third-year medical students and administered a questionnaire to assess ChatGPT usage and student attitudes. Three independent reviewers graded the papers using EASE guidelines, and statistical analysis compared articles generated with or without ChatGPT assistance across various parameters, with rigorous quality control ensuring survey reliability and validity.ResultsIn this study, 33 students (25.8%) utilized ChatGPT for writing (ChatGPT group) and 95 (74.2%) did not (Control group). The ChatGPT group exhibited significantly higher daily technology use and prior experience with ChatGPT (p < 0.05). Writing time was significantly reduced in the ChatGPT group (p = 0.04), with 69.7% completing tasks within 2-3 days compared to 48.4% in the control group. They also achieved higher article quality scores (p < 0.0001) with improvements in completeness, credibility, and scientific content. Self-assessment indicated enhanced writing skills (p < 0.01), confidence (p < 0.001), satisfaction (p < 0.001) and a positive attitude toward its future use in the ChatGPT group.ConclusionsIntegrating ChatGPT in medical academic writing, with proper guidance, improves efficiency and quality, illustrating artificial intelligence's potential in shaping medical education methodologies.
| S-EPMC11574940 | biostudies-literature