White Papers and Gray Literature

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The page below is a sample from the LabCE course Evidence-Based Practice Applied to the Clinical Laboratory. Access the complete course and earn ASCLS P.A.C.E.-approved continuing education credits by subscribing online.

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White Papers and Gray Literature

In addition to systematic reviews, white papers are another good source of information that can be used to drive EBP. White papers are reports or technical documents that aim to help readers understand an issue, product, or concept in order to help them make a decision. In the clinical laboratory field, manufacturers may use white papers to highlight their product's performance or superiority over other current methods.
Many so-called white papers however are clearly biased (printed by vendors to highlight only the good aspects of their product), or may not be truly peer-reviewed. In this case the paper is considered to be "gray literature" rather than a white paper. Gray literature has some shortcomings in that it may not have used conventional methods, may not be peer reviewed, or may not consider other assays or vendors. While these factors do not necessarily mean that the documents are invalid, it does mean that readers have to apply the same systematic review process to them and not take the information they present as undisputed.
The relevance of a white or gray paper can be determined quickly by considering a few questions.
  • Consider the medium in which it is published. Is it a reputable journal containing peer-reviewed articles?
  • Research the author. Does he/she hold the credentials needed to write an article in that field or specialty?
  • Check the date. Is the source you found current (eg, within the last three years)?
  • Identify the source or sources used for research. Were the sources credible?
  • Identify bias. Is the author associated with the product or was the research sponsored in some way by a company that could benefit from the publication?
  • How many data points were used or how many participants in the sample? A low number could impact a study's validity.
  • Is it a blind comparison, or is there a current "gold" standard that it was compared to?
  • Is performance being compared against older outdated methods, or those that are not the current standard of care?