Alexander Burrell, Daniel Butler, Obioha C. Ukoumunne, Hajira Dambha-Miller
There is some evidence that Altmetric scores correlate with citations in medical research, but this is not consistent across different specialties. No previous studies have examined the association between Altmetric score and citations amongst primary care research journals. The aim of this study was therefore to describe this association. We identified the ten most frequently cited articles published in the top 15 highest impact factor primary care research journals. Article and journal metrics were extracted and summarized using descriptive statistics. We used Spearman's correlation coefficient (rs) and log–log linear regression modelling to examine the relationship between citations and Altmetric score. 150 articles were included with a median of 36.5 (IQR 20–59; range 5–811) citations. We found a positive association between citations and Altmetric score (rs = 0.519; p < 0.001). A unit increase in log Altmetric score was associated with increased log citations [0.175 (95% CI 0.091–0.259, p < 0.001)] in an adjusted linear regression model. The regression findings indicate that increasing Altmetric score by 10% was associated with a 1.68% increase in citation rate. This has implications for how authors, academic institutions and primary care research journals approach dissemination of articles.
有证据表明,Altmetric 分数与医学研究中的引文相关,但不同专业的情况并不一致。以前没有研究探讨过 Altmetric 分数与初级护理研究期刊引用率之间的关系。因此,本研究旨在描述这种关联。我们确定了在影响因子最高的前 15 种初级医疗研究期刊上发表的最常被引用的十篇文章。通过描述性统计提取并总结了文章和期刊的指标。我们使用斯皮尔曼相关系数(rs)和对数线性回归模型来研究引文与 Altmetric 分数之间的关系。共纳入 150 篇文章,引用次数中位数为 36.5(IQR 20-59;范围 5-811)次。我们发现引文与 Altmetric 评分之间存在正相关(rs = 0.519; p < 0.001)。在调整后的线性回归模型中,Altmetric评分对数每增加一个单位,引文对数就会增加[0.175 (95% CI 0.091-0.259, p <0.001)]。回归结果表明,Altmetric 分数增加 10%,引用率就会增加 1.68%。这对作者、学术机构和初级保健研究期刊如何传播文章具有重要意义。
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In this study, by using Beall's (Scholarly open-access, 2014; Beall's list of predatory journals and publishers, 2018) predatory journal lists as well as direct e-mail solicitations from journals, we intentionally submitted a poorly written manuscript to 58 open-access journals using counterfeit names and affiliations. Although there have been several studies examining the practices of questionable journals, there is a lack of research investigating the interactive processes in detail. Our analysis, then, was to provide a more comprehensive view of the underlying reasoning for the acceptance or rejection of a manuscript. Of the 31 journals acknowledging receipt of our manuscript, 21 accepted it either unexpurgated or asked only for cosmetic revisions. Regarding ‘positive responses’, we point to five common flaws associated with such journals, namely that (1) they lack any interest in the researchers who are submitting manuscripts; (2) they do not judge academic writing in accordance with expected conventions; (3) they appear to be indifferent to scholarship including research design, plagiarism issues, and citation quality; (4) their review process is opaque and overly hasty, and (5) the tone they use in correspondence e-mail messages is highly inappropriate. Based upon the investigation, it is clear that such journals' primary aim is in securing the article processing fee. Our findings paint a more comprehensive picture of questionable journal practices with the hope of disseminating such information to the broader scholarly community.
{"title":"Now you have to pay! A deeper look at publishing practices of predatory journals","authors":"Mark R. Freiermuth","doi":"10.1002/leap.1583","DOIUrl":"https://doi.org/10.1002/leap.1583","url":null,"abstract":"<p>In this study, by using Beall's (Scholarly open-access, 2014; Beall's list of predatory journals and publishers, 2018) predatory journal lists as well as direct e-mail solicitations from journals, we intentionally submitted a poorly written manuscript to 58 open-access journals using counterfeit names and affiliations. Although there have been several studies examining the practices of questionable journals, there is a lack of research investigating the interactive processes in detail. Our analysis, then, was to provide a more comprehensive view of the underlying reasoning for the acceptance or rejection of a manuscript. Of the 31 journals acknowledging receipt of our manuscript, 21 accepted it either unexpurgated or asked only for cosmetic revisions. Regarding ‘positive responses’, we point to five common flaws associated with such journals, namely that (1) they lack any interest in the researchers who are submitting manuscripts; (2) they do not judge academic writing in accordance with expected conventions; (3) they appear to be indifferent to scholarship including research design, plagiarism issues, and citation quality; (4) their review process is opaque and overly hasty, and (5) the tone they use in correspondence e-mail messages is highly inappropriate. Based upon the investigation, it is clear that such journals' primary aim is in securing the article processing fee. Our findings paint a more comprehensive picture of questionable journal practices with the hope of disseminating such information to the broader scholarly community.</p>","PeriodicalId":51636,"journal":{"name":"Learned Publishing","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50148253","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Academic publishers have quickly responded to the impact of artificial intelligence (AI) tools on authorship and academic integrity. However, there remains a lack of understanding about AI authorship policies and the attitude of academic journals towards these tools. This study aims to address this gap by examining the AI authorship policies of 300 top academic journals during the period of late-spring 2023. Over half of the journals examined have an AI authorship policy and guidelines for acknowledging AI usage in manuscript preparation. These acknowledgments are typically made in the methods or acknowledgement sections, although some journals have introduced a new, special section on AI usage. The study also found that AI authorship policies may differ depending on the publisher and discipline of the journal. Many publishers have adopted uniform AI authorship policies that are implemented across all journals that they publish. These results are useful for publishers, editors, and researchers who want to learn more about how academic journals are dealing with the emergence of large language models and other AI tools in scholarly communications.
{"title":"Can ChatGPT be an author? A study of artificial intelligence authorship policies in top academic journals","authors":"Brady D. Lund, K.T. Naheem","doi":"10.1002/leap.1582","DOIUrl":"10.1002/leap.1582","url":null,"abstract":"<p>Academic publishers have quickly responded to the impact of artificial intelligence (AI) tools on authorship and academic integrity. However, there remains a lack of understanding about AI authorship policies and the attitude of academic journals towards these tools. This study aims to address this gap by examining the AI authorship policies of 300 top academic journals during the period of late-spring 2023. Over half of the journals examined have an AI authorship policy and guidelines for acknowledging AI usage in manuscript preparation. These acknowledgments are typically made in the methods or acknowledgement sections, although some journals have introduced a new, special section on AI usage. The study also found that AI authorship policies may differ depending on the publisher and discipline of the journal. Many publishers have adopted uniform AI authorship policies that are implemented across all journals that they publish. These results are useful for publishers, editors, and researchers who want to learn more about how academic journals are dealing with the emergence of large language models and other AI tools in scholarly communications.</p>","PeriodicalId":51636,"journal":{"name":"Learned Publishing","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2023-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/leap.1582","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135865013","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}