Statistical literacy for readers of Pediatrics: a moving target

Abstract

Objective: Pediatric residents are expected to study research design and statistical methods to enable them to critically appraise the pediatric literature and apply the findings to patient care. However, it is not clear how best to teach these skills or even which statistical concepts are most important. An earlier study demonstrated that the statistical complexity of articles published in Pediatrics increased from 1952 to 1982. The goals of our study were to assess whether this trend has continued and to determine the statistical measures and procedures most commonly encountered in Pediatrics.

Methods: We reviewed the print research articles published in Pediatrics, volume 115, 2005, and recorded the statistical measures and procedures reported in each article to determine how many articles used statistics or statistical procedures and what statistical procedures were encountered most commonly.

Results: The proportion of articles that used any inferential statistics increased from 48% in 1982 to 89% in 2005. The mean number of inferential procedures per article increased from 2.5 in 1982 to 3.9 in 2005. The most commonly encountered statistical procedures or measures were descriptive statistics, tests of proportions, measures of risk, logistic regression, t tests, nonparametric tests, analysis of variance, multiple linear regression, sample size and power calculation, and tests of correlation. However, a reader who is familiar with only these concepts can understand the analyses used in only 47% of articles.

Conclusions: Our results confirm a trend toward the use of new and increasingly complex statistical techniques in Pediatrics. Educational efforts might most profitably focus on the principles underlying statistical analysis rather than on specific statistical tests. Authors, reviewers, and journal editors have a greater responsibility for ensuring that statistical procedures are used appropriately, as it may be increasingly unrealistic to expect readers to fully understand the statistical analyses used in journal articles.