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https://hdl.handle.net/20.500.14365/6231
Title: | An Analysis of Sample Size Calculations in Randomized Control Trials in Emergency Medicine | Authors: | Limon, Onder Dogan, Nurettin Ozgur Limon, Gulsum Aksay, Ersin |
Keywords: | Sample Size Consort Randomized Clinical Trials Research Design |
Publisher: | W B Saunders Co-Elsevier Inc | Abstract: | Introduction: Sample size calculation enhances the quality of randomized clinical trials (RCTs) and, according to the CONSORT statement, should be reported and justified in published articles. This study aimed to evaluate the current quality of sample size calculation reporting in RCTs published in emergency medicine journals. Methods: The Web of Science (WoS) database was used for article retrieval. Journals indexed in WoS, published in English, categorized under "emergency medicine," and ranked in Q1 were included in the search. The sample size calculation method, power value, alpha value, effect size, and consideration of missing data were evaluated. Results: A total of 252 RCTs from 12 emergency medicine journals were included in the study. Only 30% of the articles explicitly stated compliance with CONSORT guidelines. Sample size calculations were reported in 84% of the articles. Alpha values were omitted in 12 % and beta (power) values in 8% of the articles. Effect sizes were not reported in 90 % of the studies. Notably, 11 % of the articles claiming CONSORT compliance did not include a sample size analysis. In the logistic regression analysis, none of the variables showed a statistically significant association with the presence of sample size analysis. Conclusion: Although emergency medicine journals show relatively better adherence to sample size calculation reporting compared to some other disciplines, their overall performance remains suboptimal. The findings highlight ongoing and significant deficiencies in the quality of RCT reporting, indicating that even leading journals in the field fall short of fully meeting recommended standards. (c) 2025 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies. | URI: | https://doi.org/10.1016/j.ajem.2025.05.020 https://hdl.handle.net/20.500.14365/6231 |
ISSN: | 0735-6757 1532-8171 |
Appears in Collections: | PubMed İndeksli Yayınlar Koleksiyonu / PubMed Indexed Publications Collection Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection |
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