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Respiratory research articles use complex data analysis methods, similar to other top medical journals. However, statistical reporting often lacks detail, requiring significant reader expertise for critical evaluation.

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Area of Science:

  • Medical research methodology
  • Respiratory medicine statistics

Background:

  • Data analysis is crucial in respiratory research.
  • The complexity and reporting of statistical methods in respiratory journals warrant investigation.
  • Comparison with other high-impact medical journals is needed to contextualize findings.

Purpose of the Study:

  • To evaluate the application and complexity of data analytical methods in leading respiratory journals.
  • To compare statistical reporting in respiratory articles with that in other eminent medical journals.
  • To assess the adequacy of detail in statistical method reporting.

Main Methods:

  • Manual review of 160 respiratory research papers (2015) and 680 papers from other medical journals (2007-2015).
  • Analysis focused on the reporting of data analysis methods and statistical procedures.
  • Journals included: European Respiratory Journal, American Journal of Respiratory and Critical Care Medicine, Chest, Thorax, The Lancet, and New England Journal of Medicine.

Main Results:

  • Statistical intensity in respiratory journals is comparable to other eminent medical journals.
  • Traditional methods for testing statistical significance are prevalent in respiratory articles.
  • Statistical procedures were frequently not described with sufficient detail.
  • No significant differences in statistical content profiles were observed among prominent respiratory journals.

Conclusions:

  • Readers of top respiratory journals require advanced statistical knowledge for critical appraisal.
  • Inconsistent detail in reporting statistical methods may hinder full understanding and evaluation.
  • Further improvements in statistical reporting are recommended for clarity and accessibility.