Characteristics Of Tables For Disseminating Biobehavioral Results

Document Type

Article

Publication Date

1-1-2018

Publication Title

Biological Research for Nursing

Publisher

SAGE Publications Inc.

Volume

20

Issue

1

First page number:

70

Last page number:

76

Abstract

Background: To report the complexity and richness of study variables within biological nursing research, authors often use tables; however, the ease with which consumers understand, synthesize, evaluate, and build upon findings depends partly upon table design. Objectives: To assess and compare table characteristics within research and review articles published in Biological Research for Nursing and Nursing Research. Method: A total of 10 elements in tables from 48 biobehavioral or biological research or review articles were analyzed. To test six hypotheses, a two-level hierarchical linear model was used for each of the continuous table elements, and a two-level hierarchical generalized linear model was used for each of the categorical table elements. Additionally, the inclusion of probability values in statistical tables was examined. Results: The mean number of tables per article was 3. Tables in research articles were more likely to contain quantitative content, while tables in review articles were more likely to contain both quantitative and qualitative content. Tables in research articles had a greater number of rows, columns, and column-heading levels than tables in review articles. More than one half of statistical tables in research articles had a separate probability column or had probability values within the table, whereas approximately one fourth had probability notes. Conclusions: Authors and journal editorial staff may be generating tables that better depict biobehavioral content than those identified in specific style guidelines. However, authors and journal editorial staff may want to consider table design in terms of audience, including alternative visual displays. © 2017, © The Author(s) 2017.

Keywords

and visual displays; APA style; audience analysis; biomarkers; numeracy; table

Language

English

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