Reporting of data analysis methods in psychiatric journals: Trends from 1996 to 2018

Abstract

Objectives: The article aims to evaluate how study designs and data analysis methods in psychiatric studies have changed over the last 22 years. Methods: This study involved a total of 320 papers published in 1996 and 2018 in the American Journal of Psychiatry, Acta Psychiatrica Scandinavica, British Journal of Psychiatry, and JAMA Psychiatry. We manually reviewed the articles to determine the way in which they reported the study characteristics and the methods applied in data analysis. Results: The statistical intensity in psychiatric journals has changed over the past 20 years. Traditional methods of testing statistical significance were widely used both in 1996 and in 2018. In 2018, there was an increase in reporting more complex methods, such as multivariable regression models, multilevel modelling, and intracluster correlation methods. However, computationally complex data mining or machine learning procedures were not adopted by psychiatric researchers. Conclusion: The increase in statistical intensity in the literature suggests that readers of prominent psychiatric journals must possess a substantial level of statistical expertise if they wish to critically evaluate the findings published in these journals. It is essential to include an awareness of this substantial change in data analysis methods in psychiatric undergraduate and postgraduate education.