Background: This study aimed to develop a comprehensive instrument for evaluating and ranking clinical practice guidelines, named Scientific, Transparent and Applicable Rankings tool (STAR), and test its reliability, validity, and usability.

Methods: This study set up a multidisciplinary working group including guideline methodologists, statisticians, journal editors, clinicians, and other experts. Scoping review, Delphi methods, and hierarchical analysis were used to develop the STAR tool. We evaluated the instrument's intrinsic and interrater reliability, content and criterion validity, and usability.

Results: STAR contained 39 items grouped into 11 domains. The mean intrinsic reliability of the domains, indicated by Cronbach's α coefficient, was 0.588 (95% confidence interval [CI]: 0.414, 0.762). Interrater reliability as assessed with Cohen's kappa coefficient was 0.774 (95% CI: 0.740, 0.807) for methodological evaluators and 0.618 (95% CI: 0.587, 0.648) for clinical evaluators. The overall content validity index was 0.905. Pearson's r correlation for criterion validity was 0.885 (95% CI: 0.804, 0.932). The mean usability score of the items was 4.6 and the median time spent to evaluate each guideline was 20 min.

Conclusion: The instrument performed well in terms of reliability, validity, and efficiency, and can be used for comprehensively evaluating and ranking guidelines.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10278700PMC
http://dx.doi.org/10.1097/CM9.0000000000002713DOI Listing

Publication Analysis

Top Keywords

scientific transparent
8
transparent applicable
8
applicable rankings
8
star tool
8
clinical practice
8
practice guidelines
8
evaluating ranking
8
reliability validity
8
interrater reliability
8
criterion validity
8

Similar Publications

The Journal of General Internal Medicine (JGIM) has a long-standing history of publishing manuscripts focused on health equity and is committed to diversity, equity, and inclusion (DEI) in scientific writing and publishing. This is extremely important in the current climate where false narratives and attacks on DEI and health equity are rampant. To demonstrate their commitment to DEI and health equity, the JGIM Editors-in-Chief created an inaugural DEI Advocacy Team.

View Article and Find Full Text PDF

Background: Cell culture studies play an important role in addressing fundamental scientific questions. However, inadequate reporting of these studies results in a lack of transparency and reproducibility. Recognizing the need for improvement, several ongoing efforts, such as CRIS guidelines and the ICLAC checklist, are focused on enhancing best practices for in vitro studies.

View Article and Find Full Text PDF

Face masks can impact processing a narrative in sign language, affecting several metacognitive dimensions of understanding (i.e., perceived effort, confidence and feeling of understanding).

View Article and Find Full Text PDF

We propose a double-cavity optomechanical system with nonreciprocal coupling to realize tunable optical nonreciprocity that has the prospect of making an optical device for the manipulation of information processing and communication. Here we investigate the steady-state dynamic processes of the double-cavity system and the transmission of optical waves from opposite cavity directions. The transmission spectrum of the probe field is presented in detail and the physical mechanism of the induced transparency window is analyzed.

View Article and Find Full Text PDF

Guidelines International Network: Principles for Use of Artificial Intelligence in the Health Guideline Enterprise.

Ann Intern Med

January 2025

Clinical Epidemiology and Research Center (CERC), Department of Biomedical Sciences, Humanitas University, and IRCCS Humanitas Research Hospital, Milan, Italy, and Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Allergology and Immunology, Berlin, Germany (H.J.S.).

Description: Artificial intelligence (AI) has been defined by the High-Level Expert Group on AI of the European Commission as "systems that display intelligent behaviour by analysing their environment and taking actions-with some degree of autonomy-to achieve specific goals." Artificial intelligence has the potential to support guideline planning, development and adaptation, reporting, implementation, impact evaluation, certification, and appraisal of recommendations, which we will refer to as "guideline enterprise." Considering this potential, as well as the lack of guidance for the use of AI in guidelines, the Guidelines International Network (GIN) proposes a set of principles for the development and use of AI tools or processes to support the health guideline enterprise.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!