Dataset Information

Generic language 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.

SUBMITTER: DeJesus JM

PROVIDER: S-EPMC6744883 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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Generic language in scientific communication.

DeJesus Jasmine M JM Callanan Maureen A MA Solis Graciela G Gelman Susan A SA

Proceedings of the National Academy of Sciences of the United States of America 20190826 37

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 requir ...[more]

PMID: 31451665

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Project description:EFSA Strategy 2027 outlines the need for fit-for-purpose protocols for EFSA generic scientific assessments to aid in delivering trustworthy scientific advice. This EFSA Scientific Committee guidance document helps address this need by providing a harmonised and flexible framework for developing protocols for EFSA generic assessments. The guidance replaces the 'Draft framework for protocol development for EFSA's scientific assessments' published in 2020. The two main steps in protocol development are described. The first is problem formulation, which illustrates the objectives of the assessment. Here a new approach to translating the mandated Terms of Reference into scientifically answerable assessment questions and sub-questions is proposed: the 'APRIO' paradigm (Agent, Pathway, Receptor, Intervention and Output). Owing to its cross-cutting nature, this paradigm is considered adaptable and broadly applicable within and across the various EFSA domains and, if applied using the definitions given in this guidance, is expected to help harmonise the problem formulation process and outputs and foster consistency in protocol development. APRIO may also overcome the difficulty of implementing some existing frameworks across the multiple EFSA disciplines, e.g. the PICO/PECO approach (Population, Intervention/Exposure, Comparator, Outcome). Therefore, although not mandatory, APRIO is recommended. The second step in protocol development is the specification of the evidence needs and the methods that will be applied for answering the assessment questions and sub-questions, including uncertainty analysis. Five possible approaches to answering individual (sub-)questions are outlined: using evidence from scientific literature and study reports; using data from databases other than bibliographic; using expert judgement informally collected or elicited via semi-formal or formal expert knowledge elicitation processes; using mathematical/statistical models; and - not covered in this guidance - generating empirical evidence ex novo. The guidance is complemented by a standalone 'template' for EFSA protocols that guides the users step by step through the process of planning an EFSA scientific assessment.

Dataset Information

Generic language in scientific communication.

Publications

Generic language in scientific communication.

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