There are several criteria for determination of the most appropriate cut-off value in a diagnostic test with continuous results. Mostly based on receiver operating characteristic (ROC) analysis, there are various methods to determine the test cut-off value. The most common criteria are the point on ROC curve where the sensitivity and specificity of the test are equal; the point on the curve with minimum distance from the left-upper corner of the unit square; and the point where the Youden's index is maximum. There are also methods mainly based on Bayesian decision analysis. Herein, we show that a proposed method that maximizes the weighted number needed to misdiagnose, an index of diagnostic test effectiveness we previously proposed, is the most appropriate technique compared to the aforementioned ones. For determination of the cut-off value, we need to know the pretest probability of the disease of interest as well as the costs incurred by misdiagnosis. This means that even for a certain diagnostic test, the cut-off value is not universal and should be determined for each region and for each disease condition.

Habibzadeh F. J Korean Med Sci. 2024 Jan;39(3):e35. https://doi.org/10.3346/jkms.2024.39.e35

This statement revises our earlier “WAME Recommendations on ChatGPT and Chatbots in Relation to Scholarly Publications” (January 20, 2023). The revision reflects the proliferation of chatbots and their expanding use in scholarly publishing over the last few months, as well as emerging concerns regarding lack of authenticity of content when using chatbots. These recommendations are intended to inform editors and help them develop policies for the use of chatbots in papers published in their journals. They aim to help authors and reviewers understand how best to attribute the use of chatbots in their work and to address the need for all journal editors to have access to manuscript screening tools. In this rapidly evolving field, we will continue to modify these recommendations as the software and its applications develop.

To investigate the correlation between the length of the title of a scientific article and the number of citations it receives, in view of the common editorial call for shorter titles. Title and the number of citations to all articles published in 2005 in 22 arbitrarily chosen English-language journals (n = 9031) were retrieved from citation database Scopus. The 2008 journal impact factors of these 22 journals were also retrieved from Thomson Reuters’ Journal Citation Report (JCR). Assuming the article title length as the independent variable, and the number of citations to the article as the dependent variable, a linear regression model was applied. The slope of the regression line for some journals (n = 6, when titles were measured in characters but 7 when titles were measured in words) was negative – none was significantly different from 0. The overall slope for all journals was 0.140 (when titles were measured in characters) and 0.778 (when titles were measured in words), significantly different from 0 (P < 0.001). Overall, articles with longer titles received more citations – Spearman ρ = 0.266 – when titles were measured in characters, and ρ = 0.244 when titles were measured in words (P < 0.001). This association was found for 7 of 8 journals with impact factor >10 and for 2 out of 14 journals with impact factor <10 (P < 0.001, Fisher exact test). Longer titles seem to be associated with higher citation rates. This association is more pronounced for journals with high impact factors. Editors who insist on brief and concise titles should perhaps update the guidelines for authors of their journals and have more flexibility regarding the length of the title.

Habibzadeh F. J Korean Med Sci. 2017 Jul;32(7):1072-1076. https://doi.org/10.3346/jkms.2017.32.7.1072