With predatory publishing continuing to escalate, there is a need to evaluate the extent to which it has infiltrated academic practice. In a recent analysis of Scopus, a leading scholarly database, researchers found that almost 3% of indexed studies had been published in potentially predatory journals.

As highlighted in a recent Nature news article, researchers searched Scopus for the names of “potential, possible or probable” predatory journals and publishers identified by Beall (2016). A total of 324 suspected predatory journals were identified; these titles published over 160,000 articles between 2015–2017, accounting for 2.8% of the studies indexed during this period.

Unfortunately, this isn’t an isolated problem — predatory journals have previously been found to be indexed on other databases such as PubMed. It is widely recognized that predatory publishing threatens research integrity, however defining “safelists” and “watchlists” isn’t easy and they are difficult to maintain as these journals constantly evolve their practices.

Although a spokesperson for Scopus told Nature that it has stopped indexing new content for 65% of flagged journals, old content remains. This means that their  citation counts still increase, and may continue to misinform important institutional decisions such as employee evaluation and funding. The authors of the analysis suggest that the current filters used to assess journals are proving ineffective against the more convincing predatory journals, and call for fact checking and upgraded selection criteria to address the issue.

They warn that “unless the selection criteria are upgraded and/or the bar for inclusion is raised significantly, fake scientific journals will keep creeping in the database”.

We look forward to seeing how scholarly databases adapt to this evolving threat.

After reading the article, click here for a brief survey and to receive your authorization code for your Credit Tracker. This serves as documentation for the activity.

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Systematic reviews and meta-analyses play a crucial role in evidence-based medicine, combining data from multiple studies on a topic to arrive at more robust conclusions than if individual studies are considered in isolation. However, it’s possible that poorly conducted literature reviews introduce bias into the findings and undermine the validity of systematic reviews. The lack of consensus guidelines on the transparent reporting of literature searches compounds this problem and has led to the development and recent publication of the Preferred Reporting Items for Systematic reviews and Meta-Analyses literature search (PRISMA-S) extension to the PRISMA Statement.

PRISMA-S was published in Systematic Reviews by Melissa Rethlefsen and colleagues. Designed to complement the PRISMA Statement and its existing extensions, the checklist of 16 items provides consensus-based guidance on reporting the literature search components of systematic reviews under the following headings:

• information sources and methods
• search strategies
• peer review
• managing records.

The checklist is designed for use in all fields of research and to cover the whole range of literature review types including scoping reviews, mixed methods reviews and metanarrative reviews. Importantly, PRISMA-S also provides guidance on reporting searches of sources other than literature databases, such as web search engines and study registries, for which there is little existing guidance.

The authors hope that PRISMA-S will be adopted by researchers – and by journals as part of the peer review process – to promote greater transparency and reproducibility of systematic literature reviews.

With the checklist available and a webinar planned to discuss how best to implement PRISMA-S, the authors hope that PRISMA-S will be adopted by researchers – and by journals as part of the peer review process – to promote greater transparency and reproducibility of systematic literature reviews.

After reading the PRISMA-S article, click here for a brief survey and to receive your authorization code for your Credit Tracker. This serves as documentation for the activity.

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The Publication Plan is excited to announce that starting today, our readers with Certified Medical Publication Professional (CMPP) credentials are able to earn recertification credits for the International Society of Medical Publication Professionals’ (ISMPP) CMPP programme.

Our eligible articles will now be tagged with a CMPP logo, and can be found under our #CMPP tag, or found directly through your list of CMPP approved activities. After reading each article, follow the link provided to the additional reading required to qualify for your credit. You can earn continuing education (CE) credit for your activity by entering it into your ISMPP CE Credit Tracker. New articles will be added to the #CMPP list regularly, and will always capture the latest key developments representing best practice across all aspects of medical publication planning.

As medical publication professionals, we are expected to uphold the highest scientific standards and ensure scientific integrity throughout our industry. The ISMPP CMPP certification offers medical publication professionals the opportunity to formally demonstrate:

• expertise as a medical publication professional
• proficiency in good publication practices
• commitment to ethical and transparent data dissemination standards
• leadership in upholding and fostering integrity and excellence in medical publication

If you have not yet considered taking the CMPP exam, find out more – including dates for the next exam, certification study materials and application instructions – under the certification tab on the ISMPP website.

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Artificial intelligence (AI) is a rapidly evolving field that has many potential health applications, including systems that can be used for screening and triage, diagnosis, decision support and treatment recommendation. Concerns regarding the design and reporting of recent trials evaluating such systems have led to the development of an extension to the SPIRIT (The Standard Protocol Items: Recommendations for Interventional Trials) 2013 statement, an international guideline aiming to standardise the quality and completeness of published trial protocols. Details of the extension and the methods used in its development were recently published by Samantha Cruz Rivera et al in the British Medical Journal.

The SPIRIT-AI extension, which complements the CONSORT-AI guidelines for the reporting of AI trials, provides consensus-based, AI-specific guidance on what should be included in the trial protocol, and should be used alongside SPIRIT 2013 and other relevant extensions. Items recommended for inclusion in the new checklist include:

• algorithm version
• input and output data
• expertise of users
• plans to identify and analyse performance errors
• prior level of evidence for validation of the AI intervention.

The latter two points were added to address safety concerns raised by the consensus group in recognition that that AI systems may unpredictably produce errors that are not easily detectable or explainable by human judgment, which could have unintended but harmful consequences.

Furthermore, as some AI systems continuously learn from new data their safety performance can evolve and change over time. While the issue of continuously evolving systems has not been covered in the current SPIRIT-AI extension, the authors suggest that software changes should be identified and documented and note that this topic may be addressed in future versions of SPIRIT-AI. Due to the relative newness of the field, there were few published AI trials and no published AI trial protocols at the time that the SPIRIT-AI guidance was developed. The authors acknowledge the importance of re-evaluating and updating SPIRIT-AI as AI technology continues to evolve and as its application expands to include therapeutic uses in addition to detection and diagnostics.

After reading the SPIRIT-AI article, click here for a brief survey and to receive your authorization code for your Credit Tracker. This serves as documentation for the activity.

After reading the CONSORT-AI article, click here for a brief survey and to receive your authorization code for your Credit Tracker. This serves as documentation for the activity.

Note: There is a poll embedded within this post, please visit the site to participate in this post's poll.

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Summary by Alice Wareham PhD, CMPP from Aspire Scientific

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With thanks to our sponsor, Aspire Scientific Ltd