There is increasing recognition that research samples in psychology are limited in size, diversity, and generalizability. However, because scientists are encouraged to reach broad audiences, we hypothesized that scientific writing may sacrifice precision in favor of bolder claims. We focused on generic statements (“Introverts and extraverts require different learning environments”), which imply broad, timeless conclusions while ignoring variability. In an analysis of 1,149 psychology articles, 89% described results using generics, yet 73% made no mention of participants’ race. Online workers and undergraduate students (n = 1,578) judged findings expressed with generic language more important than findings expressed with nongeneric language. These findings provide a window onto scientists’ views of sampling, and highlight consequences of language choice in scientific communication.

Abstract

Scientific communication poses a challenge: To clearly highlight key conclusions and implications while fully acknowledging the limitations of the evidence. Although these goals are in principle compatible, the goal of conveying complex and variable data may compete with reporting results in a digestible form that fits (increasingly) limited publication formats. As a result, authors’ choices may favor clarity over complexity. For example, generic language (e.g., “Introverts and extraverts require different learning environments”) may mislead by implying general, timeless conclusions while glossing over exceptions and variability. Using generic language is especially problematic if authors overgeneralize from small or unrepresentative samples (e.g., exclusively Western, middle-class). We present 4 studies examining the use and implications of generic language in psychology research articles. Study 1, a text analysis of 1,149 psychology articles published in 11 journals in 2015 and 2016, examined the use of generics in titles, research highlights, and abstracts. We found that generics were ubiquitously used to convey results (89% of articles included at least 1 generic), despite that most articles made no mention of sample demographics. Generics appeared more frequently in shorter units of the paper (i.e., highlights more than abstracts), and generics were not associated with sample size. Studies 2 to 4 (n = 1,578) found that readers judged results expressed with generic language to be more important and generalizable than findings expressed with nongeneric language. We highlight potential unintended consequences of language choice in scientific communication, as well as what these choices reveal about how scientists think about their data.