Research support essentials: Overview

Abstract
Introduction: Regional anaesthesia provides important clinical benefits to patients but is underutilised. A barrier to widespread adoption may be the focus of regional anaesthesia research on novel techniques rather than evaluating and optimising existing approaches. Research priorities in regional anaesthesia identified by anaesthetists have been published, but the views of patients, carers and other healthcare professionals have not been considered previously. Therefore, we launched a multidisciplinary research priority setting partnership that aimed to establish key regional anaesthesia research priorities for the UK.

Methods: Research suggestions from key stakeholders (defined by their interaction with regional anaesthesia) were gathered using an online survey. These suggestions were analysed to identify common themes and then combined to formulate indicative research questions. After an extensive literature review, unanswered and partially answered questions were prioritised via an interim online survey and then ranked as a top 10 list during a final live virtual multidisciplinary prioritisation workshop.

Results: In total, 210 individuals completed the initial survey and suggested 518 research questions. Fifty-seven indicative questions were formed, of which three were considered fully answered after literature review and one not feasible. The interim online survey received 335 responses, which identified the 24 highest priority questions from the 53 presented. At the final live prioritisation workshop, through a nominal group process, we identified the top 10 regional anaesthesia research priorities. These aligned with three broad thematic areas: pain management (two questions); patient safety (six questions); and recovery from surgery (two questions).

Discussion: This initiative has resulted in a list of research questions prioritised by patients, carers and a multidisciplinary group of healthcare professionals that should be used to inform and support future regional anaesthesia research in the UK.

Abstract
Objectives: Metrics and instruments can provide guidance for clinical researchers to assess their potential research projects at an early stage before significant investment. Furthermore, metrics can also provide structured criteria for peer reviewers to assess others' clinical research manuscripts or grant proposals. This study aimed to develop, test, validate, and use evaluation metrics and instruments to accurately, consistently, systematically, and conveniently assess the quality of scientific hypotheses for clinical research projects.

Materials and methods: Metrics development went through iterative stages, including literature review, metrics and instrument development, internal and external testing and validation, and continuous revisions in each stage based on feedback. Furthermore, two experiments were conducted to determine brief and comprehensive versions of the instrument.

Results: The brief version of the instrument contained three dimensions: validity, significance, and feasibility. The comprehensive version of metrics included novelty, clinical relevance, potential benefits and risks, ethicality, testability, clarity, interestingness, and the three dimensions of the brief version. Each evaluation dimension included 2 to 5 subitems to evaluate the specific aspects of each dimension. For example, validity included clinical validity and scientific validity. The brief and comprehensive versions of the instruments included 12 and 39 subitems, respectively. Each subitem used a 5-point Likert scale.

Conclusion: The validated brief and comprehensive versions of metrics can provide standardized, consistent, systematic, and generic measurements for clinical research hypotheses, allow clinical researchers to prioritize their research ideas systematically, objectively, and consistently, and can be used as a tool for quality assessment during the peer review process.

Abstract
With breakthroughs in Natural Language Processing and Artificial Intelligence (AI), the usage of Large Language Models (LLMs) in academic research has increased tremendously. Models such as Generative Pre-trained Transformer (GPT) are used by researchers in literature review, abstract screening, and manuscript drafting. However, these models also present the attendant challenge of providing ethically questionable scientific information. Our study provides a snapshot of global researchers' perception of current trends and future impacts of LLMs in research. Using a cross-sectional design, we surveyed 226 medical and paramedical researchers from 59 countries across 65 specialties, trained in the Global Clinical Scholars' Research Training certificate program of Harvard Medical School between 2020 and 2024. Majority (57.5%) of these participants practiced in an academic setting with a median of 7 (2,18) PubMed Indexed published articles. 198 respondents (87.6%) were aware of LLMs and those who were aware had higher number of publications (p < 0.001). 18.7% of the respondents who were aware (n = 37) had previously used LLMs in publications especially for grammatical errors and formatting (64.9%); however, most (40.5%) did not acknowledge its use in their papers. 50.8% of aware respondents (n = 95) predicted an overall positive future impact of LLMs while 32.6% were unsure of its scope. 52% of aware respondents (n = 102) believed that LLMs would have a major impact in areas such as grammatical errors and formatting (66.3%), revision and editing (57.2%), writing (57.2%) and literature review (54.2%). 58.1% of aware respondents were opined that journals should allow for use of AI in research and 78.3% believed that regulations should be put in place to avoid its abuse. Seeing the perception of researchers towards LLMs and the significant association between awareness of LLMs and number of published works, we emphasize the importance of developing comprehensive guidelines and ethical framework to govern the use of AI in academic research and address the current challenges.

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