Tuesday, May 23, 2017

B - Fake editors

Sorokowski P, Kulczycki E, Sorokowska A, et al. Predatory journals recruit fake editor. Nature 2017;543:481-483
Predatory journals exhibit questionable marketing schemes, follow lax or non-existent peer review procedures and fail to provide scientific rigour or transparency. Crucial to a journal's quality is its editors. Such roles have usually been assigned to established experts in the journal's field, and are considered prestigious positions. Many predatory journals recruit academics to build legitimate-looking editorial boards. The authors conceived a sting operation and submitted a fake indequate application for an editor position to 360 journals, a mix of legitimate titles and suspected predators. Forty-eight titles accepted. Four titles immediately appointed the fake editor as editor-in chief, while others required some form of payment or profit.

B - Potential COI

McCoy MS, Emanuel EJ. Why there are no "potential" conflicts of interest. JAMA 2017;317(17):1721-1722
doi: 10.1001/jama.2017.2308

The notion of a potential conflict of interest (COI) reflects the mistaken view that a COI exists only when bias or harm actually occurs. Distinctions between potential and actual COI are rooted in a basic misunderstanding of the concept of a COI and its ethical significance. These invidious distinctions should be avoided. A COI exists when a secondary interest has the potential to bias a physician’s or a researcher’s primary interest in pursuing patient well-being and generalizable knowledge. Achieving greater conceptual clarity is essential to develop policies that effectively regulate COIs.

B - A checklist to improve medical writing

Leventhal PS. A checklist to improve your writing. Medical Writing 2017;26(1):43-45

A checklist of eight items to improve medical writing is provided, with explanations and  examples for each item. Several of the checklist items are discussed in detail in other articles in the same issue of Medical Writing journal. A series of exercises to help readers put them into practice is also included.

B - Scientists on Twitter

Ke q, Ahn Y-Y, Sugimoto CR. A systematic identification and analysis of scientists on Twitter. PLoS ONE 2017;12(4):e0175368.
doi: 10.1371/journal.pone.0175368

The authors developed a systematic method to discover scientists who are recognized as scientists by other Twitter users and self-identify as scientists through their profile. They studied the demographics, sharing behaviors, and interconnectivity of the identified scientists in terms of discipline and gender. Twitter has been employed by scholars across the disciplinary spectrum, with an over-representation of social and computer and information scientists, under-representation of mathematical, physical, and life scientists, and a better representation of women.

B - Meta-assessment of bias

Fanelli D, Costas R, Ioannidis JP. Meta-assessment of bias in science. Proceedings of the National Academy of Science 2017;114(14):3714-3719
(doi: 10.1073/pnas.1618569114)

Actual prevalence of biases across disciplines is unknown. To gain a comprehensive picture of the potential imprint of bias in science, the authors probed for multiple bias-related patterns and risk factors in a large random sample of meta-analyses taken from all disciplines. The magnitude of these biases varied widely across fields and was overall relatively small. However, it was observed a significant risk of small, early, and highly cited studies to overestimate effects and of studies not published in peer-reviewed journals to underestimate them.