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List of Tables, List of Figures

If even one numbered table or figure appears in your manuscript, then a List of Tables and/or a List of Figures must be included in your manuscript following the Table of Contents. If both are used, arrange the List of Tables before the List of Figures.

NOTE: The templates were created using the 2013 version of Microsoft Word. If a template is downloaded in another version of Word or another word processing program, the formatting may be incorrect. Also, if a template is copied and pasted into another document, the settings of that document (margins, page number settings, font style, etc.) may affect the look of the template.

  • List of Tables template (DOC)

This Microsoft Word document can be saved to your computer to use as a template. It was created using Microsoft Office 2013 version of Word. Please email [email protected] if you have problems with the download.

  • List of Figures template (DOC)

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List of Figures and Tables in a Dissertation – Examples in Word

Published by Owen Ingram at August 13th, 2021 , Revised On September 20, 2023

“List of tables and figures is a list containing all the tables and figures that you have used in your dissertation paper. Typically, dissertations don’t have many tables and figures unless the research involved is too deep and lengthy.”

Another reason to have an independent list of figures and tables in the dissertation and corresponding page numbers is the research’s nature. For example, research on a topic from physical sciences or engineering could include many figures and tables. Ideally, quantitative research studies tend to contain more tables and/or figures than qualitative ones.

The purpose of presenting the list of figures and tables in the dissertation on a separate page is to help the readers find tables and figures of their interest without looking through the whole dissertation document.

First of all, we need to decide whether we require the figure and table list in the dissertation to begin with.

If your dissertation includes many tables and figures, this list will prove to be helpful for the readers, because the figures will have relative page numbers mentioned with them so they can navigate to the figure or table of their choice with just one click.

A list of table or figures in a dissertation typically follows this simple format:

list of table or figures in a dissertation

Also Read: How to Best Use References in a Dissertation

Referencing List of Figures and Tables in the Dissertation

When mentioning tables and figures in the list, one must be sure that they have been clearly numbered and titled. If a figure has been obtained from an external source, that source should be clearly referenced in the text and the references section.

Regardless of the  referencing style , you are using, it is mandatory to provide a reference along with the title. This will help the readers to track the origin of the figure.

Adding Titles and Numbers to Figures and Tables

Adding titles and page numbers in your list of figures and tables within Microsoft Word is very quick and straightforward. Follow the steps mentioned below to generate a Microsoft Word-supported   list of figures and tables in the dissertation with their captions and corresponding page numbers.

  • Highlight the table or the figure you want to add title and number to, right-click and click Insert Caption .
  • Next, select the Above selected item if you are working with tables. Similarly, choose Below selected items if you want to add the title and page number to a figure.

Also read: How to Write the Abstract for the Dissertation.

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Generating List of Figures and Tables Automatically

After adding all your captions, MS Word will automatically generate the figures and tables list for you. Remember, the list will only contain those you already marked using the Insert Caption … tool.

To generate a list of tables and figures in MS Word automatically:

Step #1 – Decide where to Insert the List

Place your cursor at the point where you wish to insert the tables and figures list. The most suitable spot is always right below the table of contents in your dissertation paper.

Step #2 – Insert the List of Figures and Tables in the Dissertation

  • In the Word menu bar, click on References .
  • In the dialogue box that appears, click on Insert: Table of figures .
  • In the dialogue box caption label, you can choose between a Figure or a Table , as appropriate. Moreover, you will be able to choose a design that appears most suitable for you. The reference provides all information that is required to find the source, e.g., Vinz, S.

Example of list of tables and figures

table lists in your dissertation example

Other Useful Lists you can add to your Dissertation Paper

Although tables and figures lists can be beneficial, we might need a few more lists, including abbreviations and a glossary in dissertations. We can have a sequence for this which is as follows:

  • Table of contents (ToC)
  • List of tables and figures
  • Abbreviations list

ResearchProspect has helped students with their dissertations and essays for several years, regardless of how urgent and complexes their requirements might be. We have dissertation experts in all academic subjects, so you can be confident of having each of your module requirements met. Learn more about our dissertation writing services and essay writing services .

FAQs About List of Tables and Figures in a Dissertation

Which comes first a list of figures or a list of tables.

Simply put, a list of tables comes first—right after the table of contents page, beginning from a new page—in a dissertation.

Are tables also figures?

No; tables have rows and columns in them, whereas figures in a dissertation can comprise any form of visual element, mostly images, graphs, charts, diagrams, flowcharts, etc. furthermore, tables generally summarise and represent raw data, such as the relationship between two quantitative variables.

Do I need to create a list of tables/figures even if I have only one table or figure in my dissertation?

Typically, yes; dissertation writing guidelines stipulate that we create a list even if we have used only one table and/or figure within our dissertation.

You May Also Like

Make sure to develop a conceptual framework before conducting research. Here is all you need to know about what is a conceptual framework is in a dissertation?

Finding it difficult to maintain a good relationship with your supervisor? Here are some tips on ‘How to Deal with an Unhelpful Dissertation Supervisor’.

Dissertation Methodology is the crux of dissertation project. In this article, we will provide tips for you to write an amazing dissertation methodology.

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  • Figure & Table Lists | Word Instructions, Template & Examples

Figure & Table Lists | Word Instructions, Template & Examples

Published on 24 May 2022 by Tegan George . Revised on 25 October 2022.

A list of figures and tables compiles all of the figures and tables that you used in your thesis or dissertation, along with their corresponding page numbers. These lists give your reader an overview of how you have used figures and tables in your document.

While these lists are often not required, you may want to include one as a way to stay organised if you are using several figures and tables in your paper. Your educational institution may require one, so be sure to check their guidelines. Ultimately, if you do choose to add one, it should go directly after your table of contents .

You can download our Microsoft Word template below to help you get started.

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  • Table of contents

How to create a list of figures and tables in Word

Example of a list of tables and figures, additional lists to consider, frequently asked questions.

The first step to creating your list of figures and tables is to ensure that each of your figures and tables has a caption . This way, Microsoft Word will be able to find each one and compile them in your list automatically.

To do this, follow these steps:

  • Navigate to the References tab, and click ‘Insert Caption’, which you can find in the Captions group.
  • Give your caption a name. In the Label list, you can select the label that best describes your figure or table, or make your own by selecting ‘New Label’.

Add captions to list of tables and figures

Next, you can insert the list of tables and figures directly by clicking ‘Insert Table of Figures’, which can be found to the right of the ‘Insert Caption’ button. Be careful here – the list will only include items that you have marked using the ‘Insert Caption’ tool!

You can choose the formatting and layout within this menu as well, as you can see below.

Add list of tables and figures

There are a few things to remember as you go:

  • Figures and tables always need to be numbered, with clear titles.
  • If a figure or table is taken from or based on another source, be sure to cite your sources .

Prevent plagiarism, run a free check.

list of tables and figures example

In addition to your list of tables and figures, there are a few other lists to consider for your thesis or dissertation. They can be placed in the following order:

  • title=”Abbreviations of a dissertation” Abbreviation list

Copyright information can usually be found wherever the table or figure was published. For example, for a diagram in a journal article , look on the journal’s website or the database where you found the article. Images found on sites like Flickr are listed with clear copyright information.

If you find that permission is required to reproduce the material, be sure to contact the author or publisher and ask for it.

Lists of figures and tables are often not required, and they aren’t particularly common. They specifically aren’t required for APA Style, though you should be careful to follow their other guidelines for figures and tables .

If you have many figures and tables in your thesis or dissertation, include one may help you stay organised. Your educational institution may require them, so be sure to check their guidelines.

APA doesn’t require you to include a list of tables or a list of figures . However, it is advisable to do so if your text is long enough to feature a table of contents and it includes a lot of tables and/or figures .

A list of tables and list of figures appear (in that order) after your table of contents, and are presented in a similar way.

A list of figures and tables compiles all of the figures and tables that you used in your thesis or dissertation and displays them with the page number where they can be found.

Your list of tables and figures should go directly after your table of contents in your thesis or dissertation.

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the ‘Cite this Scribbr article’ button to automatically add the citation to our free Reference Generator.

George, T. (2022, October 25). Figure & Table Lists | Word Instructions, Template & Examples. Scribbr. Retrieved 12 February 2024, from https://www.scribbr.co.uk/thesis-dissertation/list-of-figures-tables/

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Tables and Figures

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Copyright ©1995-2018 by The Writing Lab & The OWL at Purdue and Purdue University. All rights reserved. This material may not be published, reproduced, broadcast, rewritten, or redistributed without permission. Use of this site constitutes acceptance of our terms and conditions of fair use.

Note:  This page reflects the latest version of the APA Publication Manual (i.e., APA 7), which released in October 2019. The equivalent resources for the older APA 6 style  can be found at this page  as well as at this page (our old resources covered the material on this page on two separate pages).

The purpose of tables and figures in documents is to enhance your readers' understanding of the information in the document; usually, large amounts of information can be communicated more efficiently in tables or figures. Tables are any graphic that uses a row and column structure to organize information, whereas figures include any illustration or image other than a table.

General guidelines

Visual material such as tables and figures can be used quickly and efficiently to present a large amount of information to an audience, but visuals must be used to assist communication, not to use up space, or disguise marginally significant results behind a screen of complicated statistics. Ask yourself this question first: Is the table or figure necessary? For example, it is better to present simple descriptive statistics in the text, not in a table.

Relation of Tables or Figures and Text

Because tables and figures supplement the text, refer in the text to all tables and figures used and explain what the reader should look for when using the table or figure. Focus only on the important point the reader should draw from them, and leave the details for the reader to examine on their own.

Documentation

If you are using figures, tables and/or data from other sources, be sure to gather all the information you will need to properly document your sources.

Integrity and Independence

Each table and figure must be intelligible without reference to the text, so be sure to include an explanation of every abbreviation (except the standard statistical symbols and abbreviations).

Organization, Consistency, and Coherence

Number all tables sequentially as you refer to them in the text (Table 1, Table 2, etc.), likewise for figures (Figure 1, Figure 2, etc.). Abbreviations, terminology, and probability level values must be consistent across tables and figures in the same article. Likewise, formats, titles, and headings must be consistent. Do not repeat the same data in different tables.

Data in a table that would require only two or fewer columns and rows should be presented in the text. More complex data is better presented in tabular format. In order for quantitative data to be presented clearly and efficiently, it must be arranged logically, e.g. data to be compared must be presented next to one another (before/after, young/old, male/female, etc.), and statistical information (means, standard deviations, N values) must be presented in separate parts of the table. If possible, use canonical forms (such as ANOVA, regression, or correlation) to communicate your data effectively.

This image shows a table with multiple notes formatted in APA 7 style.

A generic example of a table with multiple notes formatted in APA 7 style.

Elements of Tables

Number all tables with Arabic numerals sequentially. Do not use suffix letters (e.g. Table 3a, 3b, 3c); instead, combine the related tables. If the manuscript includes an appendix with tables, identify them with capital letters and Arabic numerals (e.g. Table A1, Table B2).

Like the title of the paper itself, each table must have a clear and concise title. Titles should be written in italicized title case below the table number, with a blank line between the number and the title. When appropriate, you may use the title to explain an abbreviation parenthetically.

Comparison of Median Income of Adopted Children (AC) v. Foster Children (FC)

Keep headings clear and brief. The heading should not be much wider than the widest entry in the column. Use of standard abbreviations can aid in achieving that goal. There are several types of headings:

  • Stub headings describe the lefthand column, or stub column , which usually lists major independent variables.
  • Column headings describe entries below them, applying to just one column.
  • Column spanners are headings that describe entries below them, applying to two or more columns which each have their own column heading. Column spanners are often stacked on top of column headings and together are called decked heads .
  • Table Spanners cover the entire width of the table, allowing for more divisions or combining tables with identical column headings. They are the only type of heading that may be plural.

All columns must have headings, written in sentence case and using singular language (Item rather than Items) unless referring to a group (Men, Women). Each column’s items should be parallel (i.e., every item in a column labeled “%” should be a percentage and does not require the % symbol, since it’s already indicated in the heading). Subsections within the stub column can be shown by indenting headings rather than creating new columns:

Chemical Bonds

     Ionic

     Covalent

     Metallic

The body is the main part of the table, which includes all the reported information organized in cells (intersections of rows and columns). Entries should be center aligned unless left aligning them would make them easier to read (longer entries, usually). Word entries in the body should use sentence case. Leave cells blank if the element is not applicable or if data were not obtained; use a dash in cells and a general note if it is necessary to explain why cells are blank.   In reporting the data, consistency is key: Numerals should be expressed to a consistent number of decimal places that is determined by the precision of measurement. Never change the unit of measurement or the number of decimal places in the same column.

There are three types of notes for tables: general, specific, and probability notes. All of them must be placed below the table in that order.

General  notes explain, qualify or provide information about the table as a whole. Put explanations of abbreviations, symbols, etc. here.

Example:  Note . The racial categories used by the US Census (African-American, Asian American, Latinos/-as, Native-American, and Pacific Islander) have been collapsed into the category “non-White.” E = excludes respondents who self-identified as “White” and at least one other “non-White” race.

Specific  notes explain, qualify or provide information about a particular column, row, or individual entry. To indicate specific notes, use superscript lowercase letters (e.g.  a ,  b ,  c ), and order the superscripts from left to right, top to bottom. Each table’s first footnote must be the superscript  a .

a  n = 823.  b  One participant in this group was diagnosed with schizophrenia during the survey.

Probability  notes provide the reader with the results of the tests for statistical significance. Asterisks indicate the values for which the null hypothesis is rejected, with the probability ( p value) specified in the probability note. Such notes are required only when relevant to the data in the table. Consistently use the same number of asterisks for a given alpha level throughout your paper.

* p < .05. ** p < .01. *** p < .001

If you need to distinguish between two-tailed and one-tailed tests in the same table, use asterisks for two-tailed p values and an alternate symbol (such as daggers) for one-tailed p values.

* p < .05, two-tailed. ** p < .01, two-tailed. † p <.05, one-tailed. †† p < .01, one-tailed.

Borders 

Tables should only include borders and lines that are needed for clarity (i.e., between elements of a decked head, above column spanners, separating total rows, etc.). Do not use vertical borders, and do not use borders around each cell. Spacing and strict alignment is typically enough to clarify relationships between elements.

This image shows an example of a table presented in the text of an APA 7 paper.

Example of a table in the text of an APA 7 paper. Note the lack of vertical borders.

Tables from Other Sources

If using tables from an external source, copy the structure of the original exactly, and cite the source in accordance with  APA style .

Table Checklist

(Taken from the  Publication Manual of the American Psychological Association , 7th ed., Section 7.20)

  • Is the table necessary?
  • Does it belong in the print and electronic versions of the article, or can it go in an online supplemental file?
  • Are all comparable tables presented consistently?
  • Are all tables numbered with Arabic numerals in the order they are mentioned in the text? Is the table number bold and left-aligned?
  • Are all tables referred to in the text?
  • Is the title brief but explanatory? Is it presented in italicized title case and left-aligned?
  • Does every column have a column heading? Are column headings centered?
  • Are all abbreviations; special use of italics, parentheses, and dashes; and special symbols explained?
  • Are the notes organized according to the convention of general, specific, probability?
  • Are table borders correctly used (top and bottom of table, beneath column headings, above table spanners)?
  • Does the table use correct line spacing (double for the table number, title, and notes; single, one and a half, or double for the body)?
  • Are entries in the left column left-aligned beneath the centered stub heading? Are all other column headings and cell entries centered?
  • Are confidence intervals reported for all major point estimates?
  • Are all probability level values correctly identified, and are asterisks attached to the appropriate table entries? Is a probability level assigned the same number of asterisks in all the tables in the same document?
  • If the table or its data are from another source, is the source properly cited? Is permission necessary to reproduce the table?

Figures include all graphical displays of information that are not tables. Common types include graphs, charts, drawings, maps, plots, and photos. Just like tables, figures should supplement the text and should be both understandable on their own and referenced fully in the text. This section details elements of formatting writers must use when including a figure in an APA document, gives an example of a figure formatted in APA style, and includes a checklist for formatting figures.

Preparing Figures

In preparing figures, communication and readability must be the ultimate criteria. Avoid the temptation to use the special effects available in most advanced software packages. While three-dimensional effects, shading, and layered text may look interesting to the author, overuse, inconsistent use, and misuse may distort the data, and distract or even annoy readers. Design properly done is inconspicuous, almost invisible, because it supports communication. Design improperly, or amateurishly, done draws the reader’s attention from the data, and makes him or her question the author’s credibility. Line drawings are usually a good option for readability and simplicity; for photographs, high contrast between background and focal point is important, as well as cropping out extraneous detail to help the reader focus on the important aspects of the photo.

Parts of a Figure

All figures that are part of the main text require a number using Arabic numerals (Figure 1, Figure 2, etc.). Numbers are assigned based on the order in which figures appear in the text and are bolded and left aligned.

Under the number, write the title of the figure in italicized title case. The title should be brief, clear, and explanatory, and both the title and number should be double spaced.

The image of the figure is the body, and it is positioned underneath the number and title. The image should be legible in both size and resolution; fonts should be sans serif, consistently sized, and between 8-14 pt. Title case should be used for axis labels and other headings; descriptions within figures should be in sentence case. Shading and color should be limited for clarity; use patterns along with color and check contrast between colors with free online checkers to ensure all users (people with color vision deficiencies or readers printing in grayscale, for instance) can access the content. Gridlines and 3-D effects should be avoided unless they are necessary for clarity or essential content information.

Legends, or keys, explain symbols, styles, patterns, shading, or colors in the image. Words in the legend should be in title case; legends should go within or underneath the image rather than to the side. Not all figures will require a legend.

Notes clarify the content of the figure; like tables, notes can be general, specific, or probability. General notes explain units of measurement, symbols, and abbreviations, or provide citation information. Specific notes identify specific elements using superscripts; probability notes explain statistical significance of certain values.

This image shows a generic example of a bar graph formatted as a figure in APA 7 style.

A generic example of a figure formatted in APA 7 style.

Figure Checklist 

(Taken from the  Publication Manual of the American Psychological Association , 7 th ed., Section 7.35)

  • Is the figure necessary?
  • Does the figure belong in the print and electronic versions of the article, or is it supplemental?
  • Is the figure simple, clean, and free of extraneous detail?
  • Is the figure title descriptive of the content of the figure? Is it written in italic title case and left aligned?
  • Are all elements of the figure clearly labeled?
  • Are the magnitude, scale, and direction of grid elements clearly labeled?
  • Are parallel figures or equally important figures prepared according to the same scale?
  • Are the figures numbered consecutively with Arabic numerals? Is the figure number bold and left aligned?
  • Has the figure been formatted properly? Is the font sans serif in the image portion of the figure and between sizes 8 and 14?
  • Are all abbreviations and special symbols explained?
  • If the figure has a legend, does it appear within or below the image? Are the legend’s words written in title case?
  • Are the figure notes in general, specific, and probability order? Are they double-spaced, left aligned, and in the same font as the paper?
  • Are all figures mentioned in the text?
  • Has written permission for print and electronic reuse been obtained? Is proper credit given in the figure caption?
  • Have all substantive modifications to photographic images been disclosed?
  • Are the figures being submitted in a file format acceptable to the publisher?
  • Have the files been produced at a sufficiently high resolution to allow for accurate reproduction?

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List Of Figures And Tables For Your Dissertation

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List-of-Figures-and-Tables-Definition

The list of figures and tables in a research paper , thesis, or dissertation provides a structured overview of graphic elements included in the paper. This list guides readers to find specific graphs, images, tables, or charts effortlessly. The process of compiling this list needs more than just listing the captions; it also requires proper formatting and sequencing in line with academic guidelines. This article explores creating a well-structured list of figures and tables with examples.

Inhaltsverzeichnis

  • 1 List of Figures and Tables – In a Nutshell
  • 2 Definition: List of figures and tables
  • 3 Creating the list of figures and tables in Word
  • 4 Example list of figures and tables
  • 5 List of figures and tables: Additional lists

List of Figures and Tables – In a Nutshell

The American Psychological Association publishes the APA style guide, which aims to:

  • Facilitate concise academic and scholarly communication worldwide.
  • Act as a reference for the various components and conventions of scientific and technical writing.
  • Improve the readability of documents.

Definition: List of figures and tables

Tables show numerical values or text arranged in rows and columns. In contrast, figures typically consist of graphs, illustrations, or drawings.

The APA style guide defines figures as graphical displays other than tables, including photographs, graphics, charts, and non-textual information.

Suppose a dissertation contains one or more tables or figures. In that case, the APA guide specifies including a list of figures and tables as appropriate.

Every list of figures and tables includes a tabulated, numerical enumeration of the titles of each relevant item. This uniform and consistent approach enables dissertation readers – including examiners – to quickly scan and locate the sources, findings, and key points in long documents.

By following APA recommendations to make a list of figures and tables, college and university students can present their dissertations correctly.

List of Tables

Table 1             Title of Table One ……………………………………………………………………………..2 Table 2             Title of Table Two .…………………………………………………………………………….3 Table 3             Title of Table ‘Three ………………………………………………………………………….3

List of Figures

Figure 1            Title of Figure One …………………………………………………………………………..4 Figure 2            Title of Figure Two …………………………………………………………………………..5 Figure 3            Title of Figure Three ………………………………………………………………………..5

This article will delve into how to include a list of figures and tables in APA style in your dissertation.

Creating the list of figures and tables in Word

Creating a list of figures and tables is straightforward in most word processing software, such as Microsoft Word.

  • Firstly, we must add captions to each figure or table. The figure number goes in bold above the figure (e.g. Figure 1). Then, the figure title appears as one double-spaced line below the figure number in italics in title case, i.e. with the first letter of major words capitalized.
  • Next, use the command on the “References” menu to complete the detailed settings you require. On confirming, the software will create the list sorted by page number and include it in your document.

Note: It is essential to eschew plagiarism if you are creating a list of figures and tables based on copying from another document.

Also, remember that the source document settings and format may affect how the table looks in your new paper: font style, page number conventions, margin widths, etc.

  • Firstly, we must add captions to each figure or table. The figure number goes in bold above the figure (e.g., Figure 1). Then, the figure title appears as one double-spaced line below the figure number in italics in title case, i.e., with the first letter of major words capitalized.

Further information on formatting standards for a list of figures and tables are on pages 225 to 250 of the APA Publication Manual 7th Edition (2020).

Example list of figures and tables

List-of-Figures-and-Tables-Example

List of figures and tables: Additional lists

Other lists you might consider including in a dissertation are:

  • A list of abbreviations
  • A table of contents

After the title, approval signature, and copyright page(s) as applicable, we recommend you arrange the pages of a dissertation in the following order:

  • Table of Contents

Occasionally, research results or lengthy analyses may extend to hundreds of rows. Instead of including all the detail, a clickable link or URL (universal resource locator) to an online version may be preferable.

We recommend opting for a data repository or an arXiv location, as privately hosted websites may change or disappear.

Best practice guidelines advocate the long-term availability of datasets for at least five years after publication. 2 Resources such as nature.com publish details of storage options by scientific field.

How do you list tables in a dissertation?

Your list of figures and tables comes after the table of contents. If both lists are present, the list of titles appears before the list of figures.

What are figure keys?

Figure legends (also known as keys) explain uncommon symbols used in the figure image. They should appear within the borders of the figure.

What are figure notes?

Figure notes explain, describe, clarify, or supplement the information in the image. Only some figures include notes, as and when necessary.

Where do I position notes for figures or tables?

According to the APA style guide, notes appear below the figure or table. Use double line spacing and left justification.

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10.5 List of figures and tables

If your document has more than two figures or tables create a separate list of figures. The list of figures has many of the same design considerations as the table of contents. Readers use the list of figures to quickly find the illustrations, diagrams, tables, and charts in your report.

Complications arise when you have both tables and figures. Strictly speaking, figures are illustrations, drawings, photographs, graphs, and charts. Tables are rows and columns of words and numbers; they are not considered figures.

For longer reports that contain dozens of figures and tables each, create separate lists of figures and tables. Put them together on the same page if they fit, as shown in the illustration below. You can combine the two lists under the heading, “List of Figures and Tables,” and identify the items as figure or table as is done in the illustration below.

Chapter Attribution Information

This chapter was derived by Annemarie Hamlin, Chris Rubio, and Michele DeSilva, Central Oregon Community College, from  Online Technical Writing by David McMurrey – CC: BY 4.0

Technical Writing Copyright © 2017 by Allison Gross, Annemarie Hamlin, Billy Merck, Chris Rubio, Jodi Naas, Megan Savage, and Michele DeSilva is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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How to Write the List of Figures for a Thesis or Dissertation

DiscoverPhDs

  • By DiscoverPhDs
  • September 20, 2020

List of Figures

A list of figures for your thesis or dissertation is exactly that: it’s a list of the names of all figures you’ve used in your thesis or dissertation, together with the page number that they’re on.

The list of figures is especially useful for a reader to refer to as it (1) gives the reader an overview of the types of figures you’ve included in your document and (2) helps them easily find a particular figure that they’re interested in.

Where Does the List of Figures go?

Write your list of figures and list of tables immediately after your list of contents. Unless specifically asked by a journal, you should not include a separate list of figures in a manuscript for peer-review.

Important Points to Remember

Ensure that the figure title in your list of figures are exactly the same as actually used in the main document. Double check that the page numbering is correct and the font size, margins and all other formatting is correct.

Formatting the List of Figures

Starting off, use Roman Numbers (e.g. iv and viii) to number the sections of the Table of Contents, List of Figures and List of Tables (the title page does not have a number written on it). Arabic numbering (e.g. 1, 2, 3) should start from the Introduction onwards.

Keep your margins consistent with those of the rest of the document, as required by your university. Usually this will be a margin of 4cm on the side of the paper that will be bound and 2cm on the opposing side (e.g. the pages printed that will be on the right hand side of the thesis will have a left margin of 4cm).

While the font size of your figure legends will be slightly smaller than the main text, keep the font style of the list of figures the same as the main text (usually 12 pt).

Title this section in all capital letters as “LIST OF FIGURES”.

List each new figure caption on a new line and capitalise the start of each word. Write the figure number on the left, then caption label and finally the page number the figure corresponds to on the right-hand side.

Apply the same formatting principle to the List of Tables in your thesis of dissertation. That is to insert each table numberon a new line, followed by the table title.

Example of the List of Figures

The example below was created in Microsoft Word. You could also consider incorporating other tools such as Endnote to help automate some of the work of entering a new caption for a figure or table. Be mindful of the Figure labelling convention required by your university. For example, you may need to align the Figure numbers with each chapter (e.g. Figure 1.1, 1.2, 1.3…. for Chapter 1 and Figure 2.1, 2.2, 2.3…. for Chapter 2).

List of Figures Example

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The scope of the study is defined at the start of the study. It is used by researchers to set the boundaries and limitations within which the research study will be performed.

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Effective Use of Tables and Figures in Research Papers

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Research papers are often based on copious amounts of data that can be summarized and easily read through tables and graphs. When writing a research paper , it is important for data to be presented to the reader in a visually appealing way. The data in figures and tables, however, should not be a repetition of the data found in the text. There are many ways of presenting data in tables and figures, governed by a few simple rules. An APA research paper and MLA research paper both require tables and figures, but the rules around them are different. When writing a research paper, the importance of tables and figures cannot be underestimated. How do you know if you need a table or figure? The rule of thumb is that if you cannot present your data in one or two sentences, then you need a table .

Using Tables

Tables are easily created using programs such as Excel. Tables and figures in scientific papers are wonderful ways of presenting data. Effective data presentation in research papers requires understanding your reader and the elements that comprise a table. Tables have several elements, including the legend, column titles, and body. As with academic writing, it is also just as important to structure tables so that readers can easily understand them. Tables that are disorganized or otherwise confusing will make the reader lose interest in your work.

  • Title: Tables should have a clear, descriptive title, which functions as the “topic sentence” of the table. The titles can be lengthy or short, depending on the discipline.
  • Column Titles: The goal of these title headings is to simplify the table. The reader’s attention moves from the title to the column title sequentially. A good set of column titles will allow the reader to quickly grasp what the table is about.
  • Table Body: This is the main area of the table where numerical or textual data is located. Construct your table so that elements read from up to down, and not across.
Related: Done organizing your research data effectively in tables? Check out this post on tips for citing tables in your manuscript now!

The placement of figures and tables should be at the center of the page. It should be properly referenced and ordered in the number that it appears in the text. In addition, tables should be set apart from the text. Text wrapping should not be used. Sometimes, tables and figures are presented after the references in selected journals.

Using Figures

Figures can take many forms, such as bar graphs, frequency histograms, scatterplots, drawings, maps, etc. When using figures in a research paper, always think of your reader. What is the easiest figure for your reader to understand? How can you present the data in the simplest and most effective way? For instance, a photograph may be the best choice if you want your reader to understand spatial relationships.

  • Figure Captions: Figures should be numbered and have descriptive titles or captions. The captions should be succinct enough to understand at the first glance. Captions are placed under the figure and are left justified.
  • Image: Choose an image that is simple and easily understandable. Consider the size, resolution, and the image’s overall visual attractiveness.
  • Additional Information: Illustrations in manuscripts are numbered separately from tables. Include any information that the reader needs to understand your figure, such as legends.

Common Errors in Research Papers

Effective data presentation in research papers requires understanding the common errors that make data presentation ineffective. These common mistakes include using the wrong type of figure for the data. For instance, using a scatterplot instead of a bar graph for showing levels of hydration is a mistake. Another common mistake is that some authors tend to italicize the table number. Remember, only the table title should be italicized .  Another common mistake is failing to attribute the table. If the table/figure is from another source, simply put “ Note. Adapted from…” underneath the table. This should help avoid any issues with plagiarism.

Using tables and figures in research papers is essential for the paper’s readability. The reader is given a chance to understand data through visual content. When writing a research paper, these elements should be considered as part of good research writing. APA research papers, MLA research papers, and other manuscripts require visual content if the data is too complex or voluminous. The importance of tables and graphs is underscored by the main purpose of writing, and that is to be understood.

Frequently Asked Questions

"Consider the following points when creating figures for research papers: Determine purpose: Clarify the message or information to be conveyed. Choose figure type: Select the appropriate type for data representation. Prepare and organize data: Collect and arrange accurate and relevant data. Select software: Use suitable software for figure creation and editing. Design figure: Focus on clarity, labeling, and visual elements. Create the figure: Plot data or generate the figure using the chosen software. Label and annotate: Clearly identify and explain all elements in the figure. Review and revise: Verify accuracy, coherence, and alignment with the paper. Format and export: Adjust format to meet publication guidelines and export as suitable file."

"To create tables for a research paper, follow these steps: 1) Determine the purpose and information to be conveyed. 2) Plan the layout, including rows, columns, and headings. 3) Use spreadsheet software like Excel to design and format the table. 4) Input accurate data into cells, aligning it logically. 5) Include column and row headers for context. 6) Format the table for readability using consistent styles. 7) Add a descriptive title and caption to summarize and provide context. 8) Number and reference the table in the paper. 9) Review and revise for accuracy and clarity before finalizing."

"Including figures in a research paper enhances clarity and visual appeal. Follow these steps: Determine the need for figures based on data trends or to explain complex processes. Choose the right type of figure, such as graphs, charts, or images, to convey your message effectively. Create or obtain the figure, properly citing the source if needed. Number and caption each figure, providing concise and informative descriptions. Place figures logically in the paper and reference them in the text. Format and label figures clearly for better understanding. Provide detailed figure captions to aid comprehension. Cite the source for non-original figures or images. Review and revise figures for accuracy and consistency."

"Research papers use various types of tables to present data: Descriptive tables: Summarize main data characteristics, often presenting demographic information. Frequency tables: Display distribution of categorical variables, showing counts or percentages in different categories. Cross-tabulation tables: Explore relationships between categorical variables by presenting joint frequencies or percentages. Summary statistics tables: Present key statistics (mean, standard deviation, etc.) for numerical variables. Comparative tables: Compare different groups or conditions, displaying key statistics side by side. Correlation or regression tables: Display results of statistical analyses, such as coefficients and p-values. Longitudinal or time-series tables: Show data collected over multiple time points with columns for periods and rows for variables/subjects. Data matrix tables: Present raw data or matrices, common in experimental psychology or biology. Label tables clearly, include titles, and use footnotes or captions for explanations."

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Thesis/Dissertation Formatting

  • List of Tables

Tables in your document

  • Use Times New Roman for text in the tables.  Use size 12 where able, but 10 or 11 size may also be used to fit text within the table.  Line spacing within a table should be single-spaced.
  • All tables should be labeled and formatted in APA style with numbering, title, notes, borders, etc.  
  • Tables should be placed after the paragraph where they are first mentioned.  If a table continues is very large, it can start on the next page after it is mentioned.  If your charge is longer than one page, type Table 1 (Continued) at the top of the next page and be sure the table headings are repeated.
  • References in your text to tables must reference a specific table and number, for example: "As demonstrated in Table 3..." Do not use, "As demonstrated in the following table...."
  • You are to reference your table in the paragraph immediately preceding or following the location of the table.
  • If your table needs to be rotated because it is too large, rotate just the table with the top of the table at the 1.5" margin side.
  • Repeat the headings if your table has to continue on a new page.
  • The titles of your tables should be italicized throughout the paper.
  • Tables within the appendix need to have the appendix section and table number. For example, Table A.1, refers to the first table in appendix A.

example of table in text

Note:  you only flip your table when it is too wide.  In the event that you do continue your table on a new page, be sure to label the table.  For example, insert "Table 2 (continued)" on the new page.

List of Tables page

  • Required if there are two or more tables in your document including the appendices.
  • Type List of Tables on the top line. Be sure to label this title as a page title heading to format it properly. See Content/Chapters for more information about headings.
  • Leave the next line blank.
  • Type Page (#), tab once, type Table 1: Title of Table One.
  • If your page number is a single digit, you will need to tab twice so that all table names are aligned.
  • List each table on a new line.
  • If your title is so long it goes onto another line, indent that line to match where all table names start.
  • If you have tables in the appendix, be sure to add them on this list.   Do not bold or italicize.

example of list of tables page

  • Introduction & Help
  • General Formatting
  • Acknowledgments
  • Table of Contents
  • List of Figures
  • Content/Chapters

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Getting started with tables

Hazel inskip.

MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton General Hospital, Southampton, SO16 6YD UK

Georgia Ntani

Leo westbury, chiara di gravio, stefania d’angelo, camille parsons, janis baird, associated data.

Data sharing is not applicable to this article as no datasets were generated or analysed during the current study.

Tables are often overlooked by many readers of papers who tend to focus on the text. Good tables tell much of the story of a paper and give a richer insight into the details of the study participants and the main research findings. Being confident in reading tables and constructing clear tables are important skills for researchers to master.

Common forms of tables were considered, along with the standard statistics used in them. Papers in the Archives of Public Health published during 2015 and 2016 were hand-searched for examples to illustrate the points being made. Presentation of graphs and figures were not considered as they are outside the scope of the paper.

Basic statistical concepts are outlined to aid understanding of each of the tables presented. The first table in many papers gives an overview of the study population and its characteristics, usually giving numbers and percentages of the study population in different categories (e.g. by sex, educational attainment, smoking status) and summaries of measured characteristics (continuous variables) of the participants (e.g. age, height, body mass index). Tables giving the results of the analyses follow; these often include summaries of characteristics in different groups of participants, as well as relationships between the outcome under study and the exposure of interest. For continuous outcome data, results are often expressed as differences between means, or regression or correlation coefficients. Ratio/relative measures (e.g. relative risks, odds ratios) are usually used for binary outcome measures that take one of two values for each study participants (e.g. dead versus alive, obese versus non-obese). Tables come in many forms, but various standard types are described here.

Clear tables provide much of the important detail in a paper and researchers are encouraged to read and construct them with care.

Tables are an important component of any research paper. Yet, anecdotally, many people say that they find tables difficult to understand so focus only on the text when reading a paper. However, tables provide a much richer sense of a study population and the results than can be described in the text. The tables and text complement each other in that the text outlines the main findings, while the detail is contained in the tables; the text should refer to each table at the appropriate place(s) in the paper. We aim to give some insights into reading tables for those who find them challenging, and to assist those preparing tables in deciding what they need to put into them. Producing clear, informative tables increases the likelihood of papers being published and read. Good graphs and figures can often provide a more accessible presentation of study findings than tables. They can add to the understanding of the findings considerably, but they can rarely contain as much detail as a table. Choosing when to present a graph or figure and when to present a table needs careful consideration but this article focuses only on the presentation of tables.

We provide a general description of tables and statistics commonly used when presenting data, followed by specific examples. No two papers will present the tables in the same way, so we can only give some general insights. The statistical approaches are described briefly but cannot be explained fully; the reader is referred to various books on the topic [ 1 – 6 ].

Presentation of tables

The title (or legend) of a table should enable the reader to understand its content, so a clear, concise description of the contents of the table is required. The specific details needed for the title will vary according to the type of table. For example, titles for tables of characteristics should give details of the study population being summarised and indicate whether separate columns are presented for particular characteristics, such as sex. For tables of main findings, the title should include the details of the type of statistics presented or the analytical method. Ideally the table title should enable the table to be examined and understood without reference to the rest of the article, and so information on study, time and place needs to be included. Footnotes may be required to amplify particular points, but should be kept to a minimum. Often they will be used to explain abbreviations or symbols used in the table or to list confounding factors for which adjustment has been made in the analysis.

Clear headings for rows and columns are also required and the format of the table needs careful consideration, not least in regard to the appropriateness and number of rows and columns included within the table. Generally it is better to present tables with more rows than columns; it is usually easier to read down a table than across it, and page sizes currently in use are longer than they are wide. Very large tables can be hard to absorb and make the reader’s work more onerous, but can be useful for those who require extra detail. Getting the balance right needs care.

Types of tables

Many research articles present a summary of the characteristics of the study population in the first table. The purpose of these tables is to provide information on the key characteristics of the study participants, and allow the reader to assess the generalisability of the findings. Typically, age and sex will be presented along with various characteristics pertinent to the study in question, for example smoking prevalence, socio-economic position, educational attainment, height, and body mass index. A single summary column may be presented or perhaps more than one column split according to major characteristics such as sex (i.e. separate columns for males and females) or, for trials, the intervention and control groups.

Subsequent tables generally present details of the associations identified in the main analyses. Sometimes these include results that are unadjusted or ‘crude’ (i.e. don’t take account of other variables that might influence the association) often followed by results from adjusted models taking account of other factors.

Other types of tables occur in some papers. For example, systematic review papers contain tables giving the inclusion and exclusion criteria for the review as well as tables that summarise the characteristics and results of each study included in the review; such tables can be extremely large if the review covers many studies. Qualitative studies often provide tables describing the characteristics of the study participants in a more narrative format than is used for quantitative studies. This paper however, focuses on tables that present numerical data.

Statistics commonly presented in tables

The main summary statistics provided within a table depend on the type of outcome under investigation in the study. If the variable is continuous (i.e. can take any numerical value, between a minimum and a maximum, such as blood pressure, height, birth weight), then means and standard deviations (SD) tend to be given when the distribution is symmetrical, and particularly when it follows the classical bell shaped curve known as a Normal or Gaussian distribution (see Fig.  1a ). The mean is the usual arithmetic average and the SD is an indication of the spread of the values. Roughly speaking, the SD is about a quarter of the difference between the largest and the smallest value excluding 5% of values at the extreme ends. So, if the mean is 100 and the SD is 20 we would expect 95% of the values in our data to be between about 60 (i.e. 100–2×20) and 140 (100 + 2×40).

An external file that holds a picture, illustration, etc.
Object name is 13690_2017_180_Fig1_HTML.jpg

Distribution of heights and weights of young women from the Southampton Women’s Survey [ 7 ]. a Shows the height distribution, which is symmetrical and generally follows a standard normal distribution, while b shows weight, which is skewed to the right

The median and inter-quartile range (IQR) are usually provided when the data are not symmetrical as in Fig.  1b , which gives an example of data that are skewed, such that if the values are plotted in a histogram there are many values at one end of the distribution but fewer at the other end [ 7 ]. If all the values of the variable were listed in order, the median would be the middle value and the IQR would be the values a quarter and three-quarters of the way through the list. Sometimes the lower value of the IQR is labelled Q1 (quartile 1), the median is Q2, and the upper value is Q3. For categorical variables, frequencies and percentages are used.

Common statistics for associations between continuous outcomes include differences in means, regression coefficients and correlation coefficients. For these statistics, values of zero indicate no association between the exposure and outcome of interest. A correlation coefficient of 0 indicates no association, while a value of 1 or −1 would indicate perfect positive or negative correlation; values outside the range −1 to 1 are not possible. Regression coefficients can take any positive or negative value depending on the units of measurement of the exposure and outcome.

For binary outcome measures that only take two possible values (e.g. diseased versus not, dead versus alive, obese versus not obese) the results are commonly presented in the form of relative measures. These include any measure with the word ‘relative’ or ‘ratio’ in their name, such as odds ratios, relative risks, prevalence ratios, incidence rate ratios and hazard ratios. All are interpreted in much the same way: values above 1 indicate an elevated risk of the outcome associated with the exposure under study, whereas below 1 implies a protective effect. No association between the outcome and exposure is apparent if the ratio is 1.

Typically in results tables, 95% confidence intervals (95% CIs) and/or p -values will be presented. A 95% CI around a result indicates that, in the absence of bias, there is a 95% probability that the interval includes the true value of the result in the wider population from which the study participants were drawn. It also gives an indication of how precisely the study team has been able to estimate the result (whether it is a regression coefficient, a ratio/relative measure or any of the summary measures mentioned above). The wider the 95% CI, the less precise is our estimate of the result. Wide 95% CIs tend to arise from small studies and hence the drive for larger studies to give greater precision and certainty about the findings.

If a 95% CI around a result for a continuous variable (difference in means, regression or correlation coefficient) includes 0 then it is unlikely that there is a real association between exposure and outcome whereas, for a binary outcome, a real association is unlikely if the 95% CI around a relative measure, such as a hazard or odds ratio, includes 1.

The p -value is the probability that the finding we have observed could have occurred by chance, and therefore there is no identifiable association between the exposure of interest and the outcome measure in the wider population. If the p -value is very small, then we are more convinced that we have found an association that is not explained by chance (though it may be due to bias or confounding in our study). Traditionally a p -value of less than 0.05 (sometimes expressed as 5%) has been considered as ‘statistically significant’ but this is an arbitrary value and the smaller the p -value the less likely the result is simply due to chance [ 8 ].

Frequently, data within tables are presented with 95% CIs but without p -values or vice versa. If the 95% CI includes 0 (for a continuous outcome measure) or 1 (for a binary outcome), then generally the p -value will be greater than 0.05, whereas if it does not include 0 or 1 respectively, then the p -value will be less than 0.05 [ 9 ]. Generally, 95% CIs are more informative than p -values; providing both may affect the readability of a table and so preference should generally be given to 95% CIs. Sometimes, rather than giving exact p-values, they are indicated by symbols that are explained in a footnote; commonly one star (*) indicates p  < 0.05, two stars (**) indicates p  < 0.01.

Results in tables can only be interpreted if the units of measurement are clearly given. For example, mean or median age could be in days, weeks, months or years if infants and children are being considered, and 365, 52, 12 or 1 for a mean age of 1 year could all be presented, as long the unit of measurement is provided. Standard deviations should be quoted in the same units as the mean to which they refer. Relative measures, such as odds ratios, and correlation coefficients do not have units of measurement, but for regression coefficients the unit of measurement of the outcome variable is required, and also of the exposure variable if it is continuous.

The examples are all drawn from recent articles in Archives of Public Health. They were chosen to represent a variety of types of tables seen in research publications.

Tables of characteristics

The table of characteristics in Table  1 is from a study assessing knowledge and practice in relation to tuberculosis control among in Ethiopian health workers [ 10 ]. The authors have presented the characteristics of the health workers who participated in the study. Summary statistics are based on categories of the characteristics, so numbers (frequencies) in each category and the percentages of the total study population within each category are presented for each characteristic. From this, the reader can see that:

  • the study population is quite young, as only around 10% are more than 40 years old;
  • the majority are female;
  • more than half are nurses;
  • about half were educated to degree level or above.

Table of study population characteristics from a paper on the assessment of knowledge and practice in relation to tuberculosis control in health workers in Ethiopia [ 10 ]. Socio demographic characteristics of the study population in public health facilities, Addis Ababa, 2014

OPD outpatient department; TB Tuberculosis.

a Midwife, radiology, physiotherapy; b MCH, delivery,EPI, FP, physiotherapy

The table of characteristics in Table  2 is from a study of the relationship between distorted body image and lifestyle in adolescents in Japan [ 11 ]. Here the presentation is split into separate columns for boys and girls. The first four characteristics are continuous variables, not split into categories but, instead, presented as means, with the SDs given in brackets. The three characteristics in the lower part of the table are categorical variables and, similar to Table  1 , the frequency/numbers and percentages in each category are presented. The p -values indicate that boys and girls differ on some of the characteristics, notably height, self-perceived weight status and body image perception.

Table of study population characteristics from a paper on the relationship between distorted body image and lifestyle in adolescents in Japan [ 11 ]. Characteristics of study participants by sex (Japan; 2005–2009)

Data are expressed as numbers (%), values are means (standard deviation). The unpaired t- test and chi-squad test were used to compare characteristics between boys and girls

In Table  3 , considerable detail is given for continuous variables in the table. This comes from an article describing the relationship between mid-upper-arm circumference (MUAC) and weight changes in young children admitted to hospital with severe acute malnutrition from three countries [ 12 ]. For each country, the categorical characteristic of sex is presented as in the previous two examples, but more detail is given for the continuous variables of age, MUAC and height. The mean is provided as in Table  2 , though without a standard deviation, but we are also given the minimum value, the 25th percentile (labelled Q1 – for quartile 1), the median (the middle value), the 75th percentile (labelled Q2, here though correctly it should be Q3 – see above) and the maximum value. The table shows:

  • Ethiopian children in this study were older and taller than those from the other two countries but their MUAC measurements tended to be smaller;
  • in Bangladesh, disproportionally more females than males were admitted for treatment compared with the other two countries.

Table of study population characteristics from a paper describing the relationship between mid-upper-arm circumference (MUAC) and weight changes in young children [ 12 ]. Characteristics of study population at admission

It is unusual to present as much detail on continuous characteristics as is given in Table  3 . Usually, for each characteristic, either (a) mean and SD or (b) median and IQR would be given, but not both.

Tables of results – summary findings

Many results tables are simple summaries and look similar to tables presenting characteristics, as described above. Sometimes the initial table of characteristics includes some basic comparisons that indicate the main results of the study. Table  4 shows part of a large table of characteristics for a study of risk factors for acute lower respiratory infections (ALRI) among young children in Rwanda [ 13 ]. In addition to presenting the numbers of children in each category of a variety of characteristics, it also shows the percentage in each category among those who suffered ALRI in the previous two weeks, and provides p- values for the differences between the categories among those who did and did not suffer from ALRI. Thus only 2.9% of older children (24–59 months) within the study suffered from ALRI, compared with about 5% in the two youngest categories. The p -value of 0.001, well below 0.05, indicates that this difference is statistically significant. The other finding of some interest is that children who took vitamin A supplements appeared to be less likely to suffer from ALRI than those who did not, but the p -value of 0.04 is close to 0.05 so not as remarkable a finding as for the difference between the age groups.

Part of a table of basic results from a study of risk factors for acute lower respiratory infections (ALRI) among young children in Rwanda [ 13 ]. Bivariate analysis of factors associated with acute lower respiratory infection among children under five in Rwanda, RDHS 2010

Table  5 shows a summary table of average life expectancy in British Columbia by socioeconomic status [ 14 ]. The average life expectancy at birth and the associated 95% CIs are given according to level of socio-economic status for the total population (column 1), followed by males and females separately. The study is large so the 95% CIs are quite narrow, and the table indicates that there are considerable differences in life expectancy between the three socioeconomic groups, with the lowest category having the poorest life expectancy. The gap in life expectancy between the lowest and highest category is more than three years, as shown in the final row.

Summary table of average life expectancy in British Columbia by socioeconomic status [ 14 ]. British Columbia regional average life expectancy at birth by regional socioeconomic status, 2007–2011

SES Socioeconomic status, LE 0 Life expectancy at birth, CI Confidence interval

Tables of results – continuous outcomes

Continuous outcome measures can be analysed in a variety of ways, depending on the purpose of the study and whether the measure of the exposure is continuous, categorical or binary.

Table  6 shows an example of correlation coefficients indicating the degree of association between the exposure of interest (cognitive test scores) and the outcome measure (academic performance) [ 15 ]. No confidence intervals are presented, but the results show that almost all the particular cognitive test scores are statistically significantly associated ( p -value < 0.05) with the two measures of academic performance. Note that this table is an example of where a footnote is used to give information about the p-values. Not surprisingly, all the correlations are positive; one would expect that as cognitive score increase so too would academic performance. The numbers labelled “N” give the number of children who contributed data to each correlation coefficient.

Correlation coefficients from a study assessing the association between cognitive function and academic performance in Ethiopia [ 15 ]. Correlation between cognitive fuinction test and academic performance among school aged children in Goba Town, South east Ethiopia, May 2014

*Statistically significant at p <0.05, **Statistically significant a p >0.01

Table  7 is quite a complex table, but one that bears examination. It presents regression coefficients from an analysis of pregnancy exposure to nitrogen dioxide (NO 2 ) and birth weight of the baby in a large study of four areas in Norway; more than 17,000 women-baby pairs contributed to the complete crude analysis [ 16 ]. Regression coefficients are presented and labelled “Beta”, the usual name for such coefficients, though the Greek letter β, B or b are sometimes used. They are interpreted as follows: for one unit increase in the exposure variable then the outcome measure increases by the amount of the regression coefficient. Regression coefficients of zero indicate no association. In this table, the Beta in the top left of the table indicates that as NO 2 exposure of the mother increases by 1 unit (a ‘unit’ in this analysis is 10 μg/m 3 , see the footnote in the table, which gives the units of measurement used for the regression coefficients: grams per 10 μg/m 3 NO 2 ) then the birth weight of her baby decreases (because the Beta is negative) by 37.9 g. The 95% CI does not include zero and the p -value is small (<0.001) implying that the association is not due solely to chance.

Table of regression coefficients for the relationship between exposure to NO 2 in pregnancy and birth weight [ 16 ]. Main and stratified analysis of association between pregnancy exposure to NO 2 and birth weight

Effect estimate in grams per 10μg/m 3 NO 2

GA gestational age, LMP last menstrual period

a Model 1 adjusted for: maternal education, birth season, sex of child, maternal age, maternal marital status, maternal smoking during pregnancy, maternal height

b Model 2 adjusted for: maternal education, birth season, sex of child, maternal age, maternal marital status, maternal smoking during pregnancy, maternal height, area

c Model 3 adjusted for: maternal education, birth season, sex of child, maternal age, maternal marital status, maternal smoking during pregnancy, maternal height, parity, maternal weight, in stratified analysis the corresponding stratification variable is not included in the adjusment

However, reading across the columns of the table gives a different story. The successive sets of columns include adjustment for increasing numbers of factors that might affect the association. While model 1 still indicates a negative association between NO 2 and birth weight that is highly significant ( p  < 0.001), models 2 and 3 do not. Inclusion of adjustment for parity or area and maternal weight has reduced the association such that the Betas have shrunk in magnitude to be closer to 0, with 95% CIs including 0 and p -values >0.05.

The table has multiple rows, with each one providing information on a different subset of the data, so the numbers in the analyses are all smaller than in the first row. The second row restricts the analysis to women who did not move address during pregnancy, an important consideration in estimating NO 2 exposure from home addresses. The third row restricts the analysis to those whose gestational age was based on the last menstrual period. These second two rows present ‘sensitivity analyses’, performed to check that the results were not due to potential biases resulting from women moving house or having uncertain gestational ages. The remaining rows in the table present stratified analyses, with results given for each category of various variables of interest, namely geographical area, maternal smoking, parity, baby’s sex, mother’s educational level and season of birth. Only one row of this table has a statistically significant result for models 2 and 3, namely babies born in spring, but this finding is not discussed in the paper. Note the gap in the table in the model 2 column as it is not possible to adjust for area (one of the adjustment factors in model 2) when the analysis is being presented for each area separately.

Tables of results – binary outcomes

Table  8 presents results from a study assessing whether children’s eating styles are associated with having a waist-hip ratio greater or equal to 0.5 (the latter being the outcome variable expressed in binary form – ≥0.5 versus <0.5) [ 17 ]. Results for boys and girls are presented separately, along with the number of children in each of the eating style categories. The main results are presented as crude and adjusted odds ratios (ORs). The adjusted ORs take account of age, exercise, skipping breakfast and having a snack after dinner, all of these being variables thought to affect the association between eating style and waist-hip ratio. Looking at the crude OR column, the value of 2.04 in the first row indicates that, among boys, those who report eating quickly have around twice the odds of having a high waist-hip ratio than those who do not eat quickly (not eating quickly is the baseline category, with an odds ratio given as 1.00). The 95% CI for the crude OR for eating quickly is 1.31 – 3.18. This interval does not include 1, indicating that the elevated OR for eating quickly is unlikely to be a chance finding and that there is a 95% probability that the range of 1.31 – 3.18 includes the true OR. The p -value is 0.002, considerably smaller than 0.05, indicating that this finding is ‘statistically significant’. The other ORs can be considered in the same way, but note that, for both boys and girls, the ORs for eating until full are greater than 1 but their 95% CIs include 1 and the p- values are considerably greater than 0.05, so not ‘statistically significant’, indicating chance findings.

Results table from a study assessing whether children’s eating styles are associated with having a waist-hip ratio ≥0.5 or not [ 17 ]. Crude and adjusted odds ratios of eating quickly or eating until full for waist-to-height ratio (WHtr) ≥ 0.5

OR odds ratio; CI confidence interval

Adjusted for age, exercise, skipping breakfast, and snack after dinner

The final columns present the ORs after adjustment for various additional factors, along with their 95% CIs and p -values. The ORs given here differ little from the crude ORs in the table, indicating that the adjustment has not had much effect, so the conclusions from examining the crude ORs are unaltered. It thus appears that eating quickly is strongly associated with a greater waist-hip ratio, but that eating until full is not.

Summary tables of characteristics describe the study population and set the study in context. The main findings can be presented in different ways and choice of presentation is determined by the nature of the variables under study. Scrutiny of tables allows the reader to acquire much more information about the study and a richer insight than if the text only is examined. Constructing clear tables that communicate the nature of the study population and the key results is important in the preparation of papers; good tables can assist the reader enormously as well as increasing the chance of the paper being published.

Acknowledgement

Not applicable.

The work was funded by the UK Medical Research Council which funds the work of the MRC Lifecourse Epidemiology Unit where the authors work. The funding body had no role in the design and conduct of the work, or in the writing the manuscript.

Availability of data and materials

Authors’ contributions.

HI conceived the idea for the paper in discussion with JB. HI wrote the first draft and all other authors commented on successive versions and contributed ideas to improve content, clarity and flow of the paper. All authors read and approved the final manuscript.

Competing interests

The authors declare that they have no competing interests.

Consent for publication

Ethics approval and consent to participate, abbreviations, contributor information.

Hazel Inskip, Email: ku.ca.notos.crm@imh .

Georgia Ntani, Email: ku.ca.notos.crm@ng .

Leo Westbury, Email: ku.ca.notos.crm@wl .

Chiara Di Gravio, Email: ku.ca.notos.crm@gdc .

Stefania D’Angelo, Email: ku.ca.notos.crm@ds .

Camille Parsons, Email: ku.ca.notos.crm@pc .

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  • Five tips for developing useful literature summary tables for writing review articles
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  • http://orcid.org/0000-0003-0157-5319 Ahtisham Younas 1 , 2 ,
  • http://orcid.org/0000-0002-7839-8130 Parveen Ali 3 , 4
  • 1 Memorial University of Newfoundland , St John's , Newfoundland , Canada
  • 2 Swat College of Nursing , Pakistan
  • 3 School of Nursing and Midwifery , University of Sheffield , Sheffield , South Yorkshire , UK
  • 4 Sheffield University Interpersonal Violence Research Group , Sheffield University , Sheffield , UK
  • Correspondence to Ahtisham Younas, Memorial University of Newfoundland, St John's, NL A1C 5C4, Canada; ay6133{at}mun.ca

https://doi.org/10.1136/ebnurs-2021-103417

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Introduction

Literature reviews offer a critical synthesis of empirical and theoretical literature to assess the strength of evidence, develop guidelines for practice and policymaking, and identify areas for future research. 1 It is often essential and usually the first task in any research endeavour, particularly in masters or doctoral level education. For effective data extraction and rigorous synthesis in reviews, the use of literature summary tables is of utmost importance. A literature summary table provides a synopsis of an included article. It succinctly presents its purpose, methods, findings and other relevant information pertinent to the review. The aim of developing these literature summary tables is to provide the reader with the information at one glance. Since there are multiple types of reviews (eg, systematic, integrative, scoping, critical and mixed methods) with distinct purposes and techniques, 2 there could be various approaches for developing literature summary tables making it a complex task specialty for the novice researchers or reviewers. Here, we offer five tips for authors of the review articles, relevant to all types of reviews, for creating useful and relevant literature summary tables. We also provide examples from our published reviews to illustrate how useful literature summary tables can be developed and what sort of information should be provided.

Tip 1: provide detailed information about frameworks and methods

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Tabular literature summaries from a scoping review. Source: Rasheed et al . 3

The provision of information about conceptual and theoretical frameworks and methods is useful for several reasons. First, in quantitative (reviews synthesising the results of quantitative studies) and mixed reviews (reviews synthesising the results of both qualitative and quantitative studies to address a mixed review question), it allows the readers to assess the congruence of the core findings and methods with the adapted framework and tested assumptions. In qualitative reviews (reviews synthesising results of qualitative studies), this information is beneficial for readers to recognise the underlying philosophical and paradigmatic stance of the authors of the included articles. For example, imagine the authors of an article, included in a review, used phenomenological inquiry for their research. In that case, the review authors and the readers of the review need to know what kind of (transcendental or hermeneutic) philosophical stance guided the inquiry. Review authors should, therefore, include the philosophical stance in their literature summary for the particular article. Second, information about frameworks and methods enables review authors and readers to judge the quality of the research, which allows for discerning the strengths and limitations of the article. For example, if authors of an included article intended to develop a new scale and test its psychometric properties. To achieve this aim, they used a convenience sample of 150 participants and performed exploratory (EFA) and confirmatory factor analysis (CFA) on the same sample. Such an approach would indicate a flawed methodology because EFA and CFA should not be conducted on the same sample. The review authors must include this information in their summary table. Omitting this information from a summary could lead to the inclusion of a flawed article in the review, thereby jeopardising the review’s rigour.

Tip 2: include strengths and limitations for each article

Critical appraisal of individual articles included in a review is crucial for increasing the rigour of the review. Despite using various templates for critical appraisal, authors often do not provide detailed information about each reviewed article’s strengths and limitations. Merely noting the quality score based on standardised critical appraisal templates is not adequate because the readers should be able to identify the reasons for assigning a weak or moderate rating. Many recent critical appraisal checklists (eg, Mixed Methods Appraisal Tool) discourage review authors from assigning a quality score and recommend noting the main strengths and limitations of included studies. It is also vital that methodological and conceptual limitations and strengths of the articles included in the review are provided because not all review articles include empirical research papers. Rather some review synthesises the theoretical aspects of articles. Providing information about conceptual limitations is also important for readers to judge the quality of foundations of the research. For example, if you included a mixed-methods study in the review, reporting the methodological and conceptual limitations about ‘integration’ is critical for evaluating the study’s strength. Suppose the authors only collected qualitative and quantitative data and did not state the intent and timing of integration. In that case, the strength of the study is weak. Integration only occurred at the levels of data collection. However, integration may not have occurred at the analysis, interpretation and reporting levels.

Tip 3: write conceptual contribution of each reviewed article

While reading and evaluating review papers, we have observed that many review authors only provide core results of the article included in a review and do not explain the conceptual contribution offered by the included article. We refer to conceptual contribution as a description of how the article’s key results contribute towards the development of potential codes, themes or subthemes, or emerging patterns that are reported as the review findings. For example, the authors of a review article noted that one of the research articles included in their review demonstrated the usefulness of case studies and reflective logs as strategies for fostering compassion in nursing students. The conceptual contribution of this research article could be that experiential learning is one way to teach compassion to nursing students, as supported by case studies and reflective logs. This conceptual contribution of the article should be mentioned in the literature summary table. Delineating each reviewed article’s conceptual contribution is particularly beneficial in qualitative reviews, mixed-methods reviews, and critical reviews that often focus on developing models and describing or explaining various phenomena. Figure 2 offers an example of a literature summary table. 4

Tabular literature summaries from a critical review. Source: Younas and Maddigan. 4

Tip 4: compose potential themes from each article during summary writing

While developing literature summary tables, many authors use themes or subthemes reported in the given articles as the key results of their own review. Such an approach prevents the review authors from understanding the article’s conceptual contribution, developing rigorous synthesis and drawing reasonable interpretations of results from an individual article. Ultimately, it affects the generation of novel review findings. For example, one of the articles about women’s healthcare-seeking behaviours in developing countries reported a theme ‘social-cultural determinants of health as precursors of delays’. Instead of using this theme as one of the review findings, the reviewers should read and interpret beyond the given description in an article, compare and contrast themes, findings from one article with findings and themes from another article to find similarities and differences and to understand and explain bigger picture for their readers. Therefore, while developing literature summary tables, think twice before using the predeveloped themes. Including your themes in the summary tables (see figure 1 ) demonstrates to the readers that a robust method of data extraction and synthesis has been followed.

Tip 5: create your personalised template for literature summaries

Often templates are available for data extraction and development of literature summary tables. The available templates may be in the form of a table, chart or a structured framework that extracts some essential information about every article. The commonly used information may include authors, purpose, methods, key results and quality scores. While extracting all relevant information is important, such templates should be tailored to meet the needs of the individuals’ review. For example, for a review about the effectiveness of healthcare interventions, a literature summary table must include information about the intervention, its type, content timing, duration, setting, effectiveness, negative consequences, and receivers and implementers’ experiences of its usage. Similarly, literature summary tables for articles included in a meta-synthesis must include information about the participants’ characteristics, research context and conceptual contribution of each reviewed article so as to help the reader make an informed decision about the usefulness or lack of usefulness of the individual article in the review and the whole review.

In conclusion, narrative or systematic reviews are almost always conducted as a part of any educational project (thesis or dissertation) or academic or clinical research. Literature reviews are the foundation of research on a given topic. Robust and high-quality reviews play an instrumental role in guiding research, practice and policymaking. However, the quality of reviews is also contingent on rigorous data extraction and synthesis, which require developing literature summaries. We have outlined five tips that could enhance the quality of the data extraction and synthesis process by developing useful literature summaries.

  • Aromataris E ,
  • Rasheed SP ,

Twitter @Ahtisham04, @parveenazamali

Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

Competing interests None declared.

Patient consent for publication Not required.

Provenance and peer review Not commissioned; externally peer reviewed.

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Home » Figures in Research Paper – Examples and Guide

Figures in Research Paper – Examples and Guide

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Figures in Research Paper

Figures in Research Paper

Figures play an essential role in research papers as they provide a visual representation of data, results, and concepts presented in the text. Figures can include graphs, charts, diagrams, photographs, and other visual aids that enhance the reader’s understanding of the research.

Importance of Figures in Research Paper

Here are some specific ways in which figures can be important in a research paper:

  • Visual representation of data : Figures can be used to present data in a clear and concise way. This makes it easier for readers to understand the results of experiments and studies.
  • Simplify complex ideas: Some concepts can be difficult to explain using words alone. Figures can be used to simplify complex ideas and make them more accessible to a wider audience.
  • Increase reader engagement : Figures can make a research paper more engaging and interesting to read. They break up long blocks of text and can make the paper more visually appealing.
  • Support arguments: Figures can be used to support arguments made in the paper. For example, a graph or chart can be used to show a correlation between two variables, providing evidence for a particular hypothesis.
  • Convey important information: Figures can be used to convey important information quickly and efficiently. This is particularly useful when the paper is being read by someone who is short on time and needs to quickly understand the main points.

Types of Figures in Research Paper

There are several types of figures commonly used in research papers, including:

  • Line graphs: These are used to show trends or changes in data over time.
  • Bar graphs: These are used to compare data across different categories or groups.
  • Pie charts: These are used to show proportions or percentages of data.
  • Scatterplots : These are used to show the relationship between two variables.
  • Tables : These are used to present large amounts of data in a structured format.
  • Photographs or images : These are used to provide visual context or examples of the research being presented.
  • Diagrams or schematics : These are used to illustrate complex processes or systems.

How to add Figures to Research Paper

Adding figures to a research paper can be a great way to visually convey important information to the reader. Here are some general guidelines for adding figures to your research paper:

  • Determine the appropriate type of figure: Depending on the information you want to convey, you may want to use a graph, chart, table, photograph, or other type of figure.
  • Label the figure: Give your figure a descriptive title and number it. Also, include a brief caption that explains what the figure shows.
  • Place the figure in the appropriate location : Generally, figures should be placed as close as possible to the text that refers to them. For example, if you mention a figure in the middle of a paragraph, it should be placed within that paragraph.
  • Format the figure appropriately: Ensure that the figure is clear and easy to read. Use consistent fonts and font sizes, and make sure the figure is large enough to be easily seen.
  • Cite the source of the figure: If the figure was not created by you, you must cite the source of the figure in your paper. This includes citing the author or creator, the date of creation, and any relevant publication information.
  • Consider copyright : Ensure that you have permission to use any figures that are copyrighted. If the figure is copyrighted, you may need to obtain permission from the copyright holder to use it in your paper.

How to Label Figures in Research Paper

Labeling figures in a research paper is an important task that helps readers to understand the content of the paper. Here are the steps to label figures in a research paper:

  • Decide on the numbering system: Before labeling the figures, decide on the numbering system that you want to use. Typically, figures are numbered consecutively throughout the paper, with the first figure being labeled as “Figure 1,” the second figure as “Figure 2,” and so on.
  • Choose a clear and concise caption: A caption is a brief description of the figure that appears below the figure. It should be clear and concise and should describe the content of the figure accurately. The caption should be written in a way that readers can understand the figure without having to read the entire paper.
  • Place the label and caption appropriately: The label and caption should be placed below the figure. The label should be centered and should include the figure number and a brief title. The caption should be placed below the label and should describe the figure in detail.
  • Use consistent formatting: Make sure that the formatting of the labels and captions is consistent throughout the paper. Use the same font, size, and style for all figures in the paper.
  • Reference figures in the text : When referring to a figure in the text, use the figure number and label. For example, “As shown in Figure 1, the results indicate that…”

Figure 1. Distribution of survey responses

In this example, “Figure 1” is the figure number, and “Distribution of survey responses” is a brief title or description of the figure.

The label should be placed at the top of the figure and should be centered. It should be clear and easy to read. It’s important to use a consistent format for all figures in the paper to make it easier for readers to follow.

Examples of Figures in Research Paper

Examples of Figures in Research Papers or Thesis are as follows:

Line graphs Example

Line graphs Example

Bar graphs Example

Bar graphs Example

Pie charts Example

Pie charts Example

Scatterplots Example

Scatterplots Example

Tables Example

Tables Example

Photographs or images Example

Photographs or images Example

Diagrams or schematics Example

Diagrams or schematics Example

Purpose of Figures in Research Paper

Some common purposes of figures in research papers are:

  • To summarize data: Figures can be used to present data in a concise and easy-to-understand manner. For example, graphs can be used to show trends or patterns in data, while tables can be used to summarize numerical information.
  • To support arguments : Figures can be used to support arguments made in the text of the research paper. For example, a figure showing the results of an experiment can help to demonstrate the validity of the conclusions drawn from the experiment.
  • To illustrate concepts: Figures can be used to illustrate abstract or complex concepts that are difficult to explain in words. For example, diagrams or illustrations can be used to show the structure of a complex molecule or the workings of a machine.
  • To enhance readability: Figures can make a research paper more engaging and easier to read. By breaking up long blocks of text, figures can help to make the paper more visually appealing and easier to understand.
  • To provide context : Figures can be used to provide context for the research being presented. For example, a map or diagram can help to show the location or layout of a study site or experimental setup.
  • To compare results : Figures can be used to compare results from different experiments or studies. This can help to highlight similarities or differences in the data and draw comparisons between different research findings.
  • To show relationships : Figures can be used to show relationships between different variables or factors. For example, a scatter plot can be used to show the correlation between two variables, while a network diagram can be used to show how different elements are connected to each other.
  • To present raw data: Figures can be used to present raw data in a way that is easier to understand. For example, a heat map can be used to show the distribution of data over a geographic region, while a histogram can be used to show the distribution of data within a single variable.

Advantages of Figures in Research Paper

Figures (such as charts, graphs, diagrams, and photographs) are an important component of research papers and offer several advantages, including:

  • Enhancing clarity : Figures can help to visually communicate complex data or information in a clear and concise manner. They can help readers better understand the research and its findings.
  • Saving space : Figures can often convey information more efficiently than text, allowing researchers to present more information in less space.
  • Improving readability : Figures can break up large blocks of text and make a paper more visually appealing and easier to read.
  • Supporting arguments: Figures can be used to support arguments made in the text and help to strengthen the overall message of the paper.
  • Enabling comparisons: Figures can be used to compare different data points, which can be difficult to do with text alone. This can help readers to see patterns and relationships in the data more easily.
  • Providing context : Figures can provide context for the research, such as showing the geographic location of study sites or providing a visual representation of the study population.

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How to Create a Table of Contents for Dissertation, Thesis or Paper & Examples

Dissertation Table of Contents

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A dissertation table of contents is a list of the chapters and sections included in a dissertation or thesis, along with their page numbers. It helps to navigate the document easily and locate specific information. Each chapter or section should be listed with its corresponding page number. The table of contents should be formatted according to the guidelines of the specific style guide being used, such as APA or MLA.

We would guess that students usually start working on the table of contents at the last minute. It is quite apparent and makes sense, as this is the list of chapters and sections with page locations. Do you think it's easy? 

From our experience, it can be quite tricky to organize everything according to APA, Chicago, or any other academic writing style. In this blog, we will discuss how to write a table of contents for a research paper , thesis or dissertation in Microsoft Word. We will create it together to guide students through the process. 

Also, here you will find examples of table of contents created by thesis writers at StudyCrumb . Let’s go!

What Is a Table of Contents: Definition

It is obvious that the table of contents (TOC) is an essential manuscript part you can’t skip. If you are dealing with a dissertation, thesis or research paper, you need to know how to build it in accordance with academic guidance. This is a detailed roadmap for your work and outlined structure you can follow for a research presentation. 

In case you are working on an essay or report, you may not include the table of contents, as it is a short academic text. But for the research paper, thesis or dissertation, table of contents is essential and required. It is possible to say the same about any Master’s project. It should be located between the dissertation abstract and introduction chapter. In most cases, it is about 2-3 pages long. 

Our expert dissertation writing service prepared a great template that can be used for your work. Make your research formatting easy with ready solutions!

Types of Table of Contents

How to choose which table of contents will fit your research paper, thesis, dissertation, or report best? Make a decision based on your work length. Some academic writing styles, such as APA paper format or MLA style , have specific formatting for this list. 

However, we will outline the most commonly used typology:

  • Single-level table of contents. At this type, we use only chapters. For instance, you will have an Introduction, Literature Review, methodology, and other chapters with page numbers. It can be used for shorter research work. For long writing forms like manuscripts, it can be too broad, and you will need to go into details.
  • Subdivided table of contents. The most frequently used form to organize the contents table. It will include not only chapters but also sections — a level 2 subheading for each part. It will help to be more specific about what to expect in each part of your research work.
  • Table of contents with multiple levels. This is a more divided structure, including subheadings with a level 3 for each section. Quite often, those subheadings can be rewritten or deleted during the last editing. It is essential to keep them in the right order.

Before you decide which type will work best for you, let us share with you some examples of each formatting style.

Example of Table of Contents With a Single Level

Introduction: The Misinformation Roots ………..…… 3 Literature Review .....................................….....………… 10 Research Methodology and Design ……................. 24 Results.............................................................................. 28 Discussion ....................................................................... 32

Sometimes, you will need to put an extra emphasis on subsections. Check this layout to see how your subheadings can be organized.

Example of Table of Contents Page with Subdivided Levels

Introduction: Information War ............……………….. 3       Background…………………………………….………..…… 4       Current State ……………………………………...…...…… 5       Defining Research Questions………………………. 9 Literature Review………………………...……………..……... 11       The Roots of Information Warfare ………....… 11        Information Wars …………………………….………..… 14        Cyber Wars Research ........................................ 17

If you are working on a lengthy, complex paper, this outline will suit your project most. It will help readers navigate through your document by breaking it down into smaller, more manageable sections.

Multi-Level Table of Contents Page Example

Introduction……………………………………………….......……….… 3       Emergence of Climate Change ………..……....….….. 3       Key Activist Groups in Climate Change .............. 5              Greenpeace International ………..…………......... 9              European Climate Foundation …….……………. 10              WWF ……………………………………….……….............. 11        Significant Movements ……………….………....……… 13 Literature Review ……………………………………......…………. 15

What Sections Should Be Included in a Table of Contents?

To start with, the scientific table of contents should include all chapters and its subheading. It is important to choose the formatting that will give your readers a full overview of your work from the very beginning. However, there are other chapters that you may miss constructing the 2-pager table. So, let's look at all you need to include:

  • Dissertation introduction
  • Literature review
  • Research methodology
  • Results section
  • Dissertation discussion
  • Conclusion of a thesis
  • Reference list. Mention a number of a page where you start listing your sources.
  • Appendices. For instance, if you have a data set, table or figure, include it in your research appendix .

This is how the ideal structured dissertation or research paper table of contents will look like. Remember that it still should take 2 pages. You need to choose the best formatting style to manage its length.

Tables, Figures, and Appendices in TOC

While creating a table of contents in a research paper, thesis or dissertation, you will need to include appendices in each case you have them. However, the formatting and adding tables and figures can vary based on the number and citation style. If you have more than 3 tables or figures, you may decide to have all of them at the end of your project. So, add them to the table of contents. 

Figures, graphics, and diagrams in research papers, dissertations and theses should be numbered. If you use them from another source, ensure that you make a proper citation based on the chosen style guide.

Appendix in Table of Contents Example

Appendix A. Row Data Set…………………………………… 41 Appendix B. IBR Data………………………………………….… 43 Appendix C. SPSS Data………………………………………… 44

What Shouldn't Be Included in a Table of Contents?

When creating a dissertation table of contents, students want to include everything they have in a document. However, some components should not be on this page. Here is what we are talking about:

  • Thesis acknowledgement
  • Paper abstract
  • The content list itself

Acknowledgement and abstract should be located before the content list, so there is no need to add them. You need to present a clear structure that will help your readers to navigate through the work and quickly find any requested information.

How to Create a Table of Contents for a Research Paper or Dissertation In Word?

It may look like working with this list can take a long. But we have one proposal for our users. Instead of writing a table of contents manually, create it automatically in Microsoft Word. You do not need any specific tech knowledge to do this. Let’s go through this process step-by-step and explain how to make a table of contents for a research paper or dissertation in a few clicks.

  • Open Home tab and choose the style for your table of contents (ToC next).
  • Apply heading 1 to your chapters, heading 2 to the subheading, and if needed heading 3 to the level 3 heading.
  • Next, you are going to create a research paper or PhD dissertation table of contents. Open References and choose ToC.
  • Choose the citation style for your work. For example, let’s choose APL for now. Meeting all style requirements (bold font, title formatting, numbers) is essential.
  • Define the number of levels for your dissertation or thesis table of contents. In case you want to have 3 levels, choose Automatic Table 2.
  • You are done! Click ok, and here is your page with listed chapters!

You see how easy it can be! Every time you make changes to your text or headings, it will be automatic.

Updating Your Table of Contents in MS Word

Table of contents of a research paper or dissertation is created, and you continue to edit your work until submission. It is common practice, and with MS Word, you can automate all the updates. 

Let’s outline this process in our step-by-step guide!

  • Right-click on your ToC in a document.
  • Update field section is next.
  • Choose “update ToC."
  • Here, you can update your entire ToC — choose an option that works the best for you!

As you may see, working with automated solutions is much easier when you write a dissertation which has manifold subsections. That is why it is better to learn how to work on MS Word with the content list meaning be able to manage it effectively.

Table of Contents Examples

From our experience, students used to think that the content list was quite a complicated part of the work. Even with automated solutions, you must be clear about what to include and how to organize formatting. To solve the problem and answer all your questions, use our research paper or dissertation contents page example. Our paper writers designed a sample table of contents to illustrate the best practices and various styles in formatting the work. 

Check our samples to find advanced options for organizing your own list.

Example of Table of Contents in Research Paper

Research Paper Table of Contents Example

As you can see, this contents page includes sections with different levels.

Thesis/Dissertation Table of Contents Example

Thesis/Dissertation Table of Contents Example

Have a question about your specific case? Check samples first, as we are sure you can get almost all the answers in our guides and sample sets. 

>> Read more: APA Format Table of Contents

Tips on Creating a Table of Contents

To finalize all that we shared on creating the table of contents page, let’s go through our tips list. We outline the best advice to help you with a dissertation table of contents.

  • Use automated solutions for creating a list of chapters for your report, research papers, or dissertations — it will save you time in the future.
  • Be clear with the formatting style you use for the research.
  • Choose the best level type of list based on the paper length.
  • Update a list after making changes to the text.
  • Check the page list before submitting the work.

Bottom Line on Making Table of Contents for Dissertations/ Papers

To summarize, working with a research paper, thesis or dissertation table of contents can be challenging. This article outlines how to create a table of contents in Word and how to update it appropriately. You can learn what to include in the content list, how long it can be, and where to locate it. Write your work using more than one table of contents sample we prepared for students. It is often easy to check how the same list was made for other dissertations before finalizing yours. We encourage you to learn how to create a list with pages automatically and update it. It will definitely make your academic life easier.

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APA table of contents

  • Open access
  • Published: 08 February 2024

Evaluating the impact of the supporting the advancement of research skills (STARS) programme on research knowledge, engagement and capacity-building in a health and social care organisation in England

  • Gulshan Tajuria   ORCID: orcid.org/0000-0001-5559-0333 1 , 2 ,
  • David Dobel-Ober   ORCID: orcid.org/0000-0001-8457-4148 1 ,
  • Eleanor Bradley   ORCID: orcid.org/0000-0001-5877-2298 3 ,
  • Claire Charnley 1 ,
  • Ruth Lambley-Burke   ORCID: orcid.org/0000-0003-0416-6908 1 ,
  • Christian Mallen   ORCID: orcid.org/0000-0002-2677-1028 1 , 2 ,
  • Kate Honeyford 1 &
  • Tom Kingstone   ORCID: orcid.org/0000-0001-9179-2303 1 , 2  

BMC Medical Education volume  24 , Article number:  126 ( 2024 ) Cite this article

241 Accesses

Metrics details

To evaluate the impact a novel education programme - to improve research engagement, awareness, understanding and confidence - had on a diverse health and social care workforce. Barriers and facilitators to engagement were explored together with research capacity-building opportunities and ways to embed a research culture. The programme is entitled ‘Supporting The Advancement of Research Skills’ (STARS programme); the paper reports findings from a health and social care setting in England, UK.

A four-level outcome framework guided the approach to evaluation and was further informed by key principles of research capacity development and relevant theory. Quantitative data were collected from learners before and after engagement; these were analysed descriptively. Semi-structured online interviews were conducted with learners and analysed thematically. A purposive sample was achieved to include a diversity in age, gender, health and social care profession, and level of attendance (regular attendees, moderate attendees and non-attenders).

The evaluation spanned 18 half-day workshops and 11 seminars delivered by expert educators. 165 (2% of total staff at Midlands Partnership University NHS Foundation Trust (MPFT)) staffs booked one or more education sessions; 128 (77%) including Allied Health Professionals (AHPs), psychologists, nursing and midwifery, and social workers attended one or more session. Key themes of engagement with teaching sessions, relevance and impact of training and promoting a research active environment were identified with relevant sub-themes. Positive impacts of training were described in terms of research confidence, intentions, career planning and application of research skills as a direct result of training. Lack of dedicated time for research engagement, work pressures and time commitments required for the programme were key barriers. Facilitators that facilitated engagement are also described.

Conclusions

Findings demonstrate the impact that a free, virtual and high-quality research education programme had at individual and organisational levels. The programme is the product of a successful collaboration between health and social care and academic organisations; this provides a useful framework for others to adapt and adopt. Key barriers to attendance and engagement spoke to system-wide challenges that an education programme could not address in the short-term. Potential solutions are discussed in relation to protecting staff time, achieving management buy-in, recognising research champions, and having a clear communication strategy.

Peer Review reports

Research has played a pivotal role in the advancement of health and social care by, for example, informing early diagnosis, the development and testing of new treatments for prevention, cure, recovery and palliative care [ 1 ]. The importance of research is heralded by key health and social care bodies in the UK, the context for this paper. The UK Government policy paper on clinical research delivery identifies the need to: ‘support healthcare professionals to develop research skills relevant to their clinical role and to design studies in ways which ensure delivering research is a rewarding experience, rather than an additional burden’ [ 2 ]. The Chief Nursing Officer for England’s strategic plan for research also emphasises the importance of developing a culture where research is relevant to all nurses, either through direct involvement or the use of research evidence as a key element in professional decision-making [ 3 ]. Similarly, the Royal College of Physicians [ 4 ] states that healthcare providers should see research as an integral element in care delivery, and to emphasise its ongoing commitment to social care research, the NIHR became the ‘National Institute for Health and Care Research’ in April 2022. The response from the research community to the Covid-19 pandemic has further boosted the impetus and appetite for health and social care to embed global and multi-disciplinary research strategies for the future [ 5 ].

Having sufficient research capacity and capability is important to enabling health and social care services and workers to translate research into practice [ 6 ]. However, inequalities exist in so far as research is not perceived as accessible and inclusive by all. Several studies describe workplace barriers including time [ 4 , 7 , 8 ] resources, such as access to published research [ 8 , 9 ] and lack of research knowledge, experience and expertise, both in terms of carrying out their own research and putting the findings of published research into practice [ 9 ]. Some professional groups describe lack of access to relevant training as a barrier to developing research knowledge and skills, (e.g. nurses [ 8 , 9 , 10 ]). Fry and Attawet [ 8 ] also identified a lack of organisational and management support for research linked to the absence of a culture that promotes research as an integral part of clinical practice. Thus, to nurture research engagement an individual (bottom-up) and service-level (top-down) approach to research capacity development (RCD) is necessary [ 11 ].

A recent evaluation of National Institute for Health and Care Research (NIHR) funding awards suggested that whilst funding could be transformative and contribute to a healthy research culture in health and care organisations, issues of inequality were identified by professionals working in specialisms with less research experience or expertise. These were in organisations without connections to more research-intensive universities and by those working in non-medical professional groups (e.g. Allied Health Professionals (AHPs), nurses) [ 12 ]. This was further highlighted by a study with social care staff, which found they valued research but showed low levels of engagement and skill [ 13 ]. Authors would like to highlight here that they recognise that social care staff and social workers provide different functions. Social workers aim, “to provide support for people to help them to deal with the personal and social issues which affect their lives”… whereas “Social care is one of the terms which is used to refer to the strategies which are used to help to care for people who are in need” [ 14 ]. Even though these terms may be used sometimes interchangeably they are different in terms of qualification required to attain the title and the duties they perform. A growing evidence base identifies the key mechanisms to support Research Capacity Development (RCD) in health and social care. A rapid evidence review [ 15 ] highlighted intrinsic factors (e.g. attitudes and beliefs) and extrinsic factors (such as recognition of research skills acquisition within career progression and professional development via professional bodies, creation of personal awards); and observation of impacts on practice as helpful to encourage NHS staff to engage with researcher development.

Context to the STARS programme

MPFT is a health and social care NHS trust with a track record in research delivery and is in the process of developing research leadership. At the time of writing, the NHS Trust had not achieved university hospital status, although it works closely with two universities which developed the STARS programme in partnership (see Fig.  1 and Supplementary File 1 for a full overview of the structure of the programme). The STARS programme provides a useful resource to address disparities in research engagement between different professional groups in health and social care. Despite more opportunities for research having been generated for nurses and AHPs by organizations such as the NIHR Collaborations for Leadership in Applied Health Research and Care (CLAHRCs) and Clinical Research Networks (CRNs), disparities persist between non-academic clinicians and the opportunities available to certain clinical specialities [ 16 , 17 , 18 ]. Challenges and barriers to research training engagement highlighted in this paper are likely to have global relevance [ 19 ]. Thus, more broadly, offering programmes such as STARS may also help address global disparities in research engagement given the UK has the highest percentage of doctors (28.6%) and nurses (15%) who are trained in foreign countries [ 20 ]. STARS was designed in consultation with staff to identify existing barriers to engagement in research training, provide all staff with improved access to high-quality research training to enhance their confidence in research and enable the best use of empirical evidence in practice. The STARS programme was launched in January 2021.

figure 1

Supporting the advancement of research skills (STARS) programme

This paper reports findings from the evaluation which aimed to evaluate the delivery of the STARS programme to assess delivery outcomes, understand learner experiences, facilitators and barriers to engagement, and future opportunities

The approach to evaluation of this training programme was informed by Kirkpatrick’s four-level outcome framework: reaction (was training enjoyed?), learning (did learning occur?), behaviour (did behaviour change?) and results (was performance effected?) [ 21 ]. As this is a new programme, data was gathered against the first three levels of Kirkpatrick’s evaluation model. Contemporary criticisms and revisions of the model were incorporated to better understand the chains of evidence and wider contextual factors that may influence the delivery of a new programme [ 22 ], such as the STARS programme.

Data collection

Quantitative data.

Data including information such as highest educational qualification, job role, the reason for attending and the line manager’s approval to attend the training was collected at the point learners registered for a teaching session. Data indicating service areas, rate of dropouts, staff backgrounds, highest and lowest rate of attendance was collected from the attendance record. Data was also collected using a brief post-session feedback (see Supplementary material - Learner Evaluation Form) form, which included a likert scale question inviting learners to rate the quality of the training.

Statistical analysis

Quantitative analysis was performed at a descriptive level, using Microsoft Excel (2016).

Qualitative methods

Semi-structured interviews were conducted with programme participants to explore learner experiences (aligned with Kirkpatrick’s reaction level), outcomes (learning) and intentions to apply research knowledge ( intended behaviours). Flexible interview formats were offered to encourage participation, such as online interviews and providing responses via email. Interviews were facilitated using a topic guide (see Supplementary material - STARS Interview Guide) that was iteratively revised.

Recruitment and sampling

A purposive sample of participants was identified using data from the programme booking form and attendance records:

Regular attenders: Those who attended a minimum of five teaching sessions across the whole programme or a single pathway.

Occasional attenders: Those who attended very few (1–2) sessions across the whole programme.

Non-attenders: Those who registered to attend, but eventually didn’t attend, to explore barriers to engagement.

Participants were invited by email for a maximum 30-minute interview. All potential participants were emailed a participant information sheet. They were given time to read the information and a contact name for any questions related to their participation, before being asked to confirm their participation in the study.

Description of sample

Thirty-six staff members were categorised as regular attenders; all were invited to take part in an interview. Two individuals declined to participate citing a lack of relevance, as they left their learning events halfway; two individuals declined due to work pressure following illness; three were ‘out of office’ according to email replies, and no response was received from 14 individuals. The remaining 15 agreed to participate in an interview with 10 choosing to use Microsoft Teams and five to provide written responses- ‘email interviews’. This method is becoming increasingly used to help supplement other forms of data and support involvement of healthcare professionals, who may have limited time/capacity for research but valuable knowledge to share [ 23 , 24 ]. Participants represented a diverse range of professional backgrounds, including: AHPs, psychologists, nursing and midwifery, and social workers; this reflected the broad range of learners on the programme. A semi-structured interview guide was used. The interviews were audio recorded and later transcribed in full by the lead author (GT).

Occasional ( n  = 17) and non-attenders ( n  = 13) were invited to participate in an interview. These were staff members who had booked several teaching sessions (1–12) but either did not attend any with/without apologies ( n  = 30) or attended only one or two. Seven email addresses were not valid as the staff had either left the service or changed role; four had an automated ‘out of office’ response set; four staff declined to participate and there was no response from 11 email addresses. Five staff agreed to be interviewed. A brief topic guide was used with questions aiming to find out just the reason/s behind non-attendance in the training. As these interviews were brief, non-verbatim notes were taken by the interviewer and included in analysis. At the end of each of these interviews, the notes were validated with the interviewee.

Qualitative analysis

The data analysis followed a thematic approach [ 22 ] to identify key themes. Data-driven coding was conducted to establish meaning from the words of participants; coding was also informed, a-priori, by the levels of the evaluation framework [ 25 ]. Initial coding was done by GT and TK who read all transcripts to support familiarisation before generating an initial set of codes. Right from initial codes to final themes, other than the authors, the wider STARS team gave input in various Team meetings. Similar codes were then compared and grouped to identify initial themes; these were reviewed to shape a preliminary set of main themes. Preliminary themes were shared and discussed with the team before finalising.

Quantitative findings

Over the 12-month evaluation period, a total of 18 half-day workshops were delivered, six from the research in clinical practice pathway; four from the research delivery pathway; eight from the research leader pathway (refer to Fig.  1 ); and 11 seminars to support the development of key skills. In total, 165 (2% of total staff at MPFT) staff members booked one or more teaching session. 128 (77%) attended one or more teaching session. On average, sessions in the research in practice pathway were attended by 25 staff; 12 in research delivery pathway; 21 in the research leader pathway; and 17 in seminars.

Qualifications, backgrounds and expectations

According to the booking form, attenders represented a range of professional groups.

Nursing registered − 29 (23%).

AHPs − 23 (17%).

Additional clinical services (all healthcare services) − 21 (16%).

Additional professional scientific and technical (such as pharmacist, qualified psychological therapist, social worker etc.) -15 (12%).

Medical profession − 14 (11%).

Other (e.g. research staff) − 26 (20%).

Approximately 85% of staff had reported prior educational qualifications, the majority included: 20% ( n  = 33) bachelor’s, 19% ( n  = 31) master’s, 3% ( n  = 5) doctoral degrees, 6% ( n  = 10) diplomas and nearly 2% ( n  = 3) MBBS (Bachelor of Medicine, Bachelor of Surgery); remaining attenders did not provide information on their educational background.

Explanations for booking the training and number of staff

At the time of booking the course, staff were asked to provide reasons and expectations from STARS sessions using an open text box. Descriptive analysis of responses is presented in Table  1 :

A better understanding of research in practice, additional support for academic work and the development of research in trust were the most common reasons provided (Table  1 ).

Post session evaluation feedback

Learners demonstrated their learning from the sessions in a variety of ways and more often using the session specific feedback. In total, 195 feedback forms were completed and covered 24 sessions. The number of ratings completed per session ranged from 1 to 25. 136 (70%) learners rated the session they attended as ‘very good’, 52 (27%) rated as ‘good’, 4 (2%) rated ‘adequate’ and 2 (1%) rated ‘poor’. Qualitative findings, presented below, help us to make sense of the session ratings.

Qualitative findings

The main themes and sub-themes from the analysis of qualitative data from interviews are summarised in Table  2 and described with illustrative quotes in the following sections.

Engagement with teaching sessions

The reasons given by staff attending the training in booking forms (Table  1 ) and discussed in interviews were reflected to a large extent in the way participants chose the teaching sessions they attended. Eight interviewees had received research training as part of their degree-level qualifications; one was currently involved in conducting research at work.

Factors considered while selecting teaching sessions

Some staff were much focused on what they wanted to take from teaching sessions and booked selectively; however, some wanted to attend all, indiscriminately, due to unequal access in such training opportunities in the past and/or in their departments:

“I wanted to do them all because my concern is that they might not be offered again because we’ve never had them in social care… we’ve never had researchers come and talk to us in social care and social work unless you go to Uni.” P 4.

Some staff described their learning as focused on intrinsic factors such as:

“It’s always good to update because I think you find your own way in doing things like informed consent. P 11.

For other staff, learning on the programme was driven by extrinsic factors like:

“Social work and social care does have a huge gap in terms of research participation. We are trying to develop that within the organization and regionally” P 13.

Relevance of a teaching session to the current role was considered before booking by staff who either had knowledge or were currently involved in doing research but the staff without previous opportunities like this booked relatively indiscriminately. Intrinsic factors such as personal interest and career progressions and extrinsic factors such as organisational development were additional reasons to attend the teaching sessions.

Barriers to attendance

Getting data from those who did not attend after booking proved difficult. Four staff declined to take part in evaluation interviews because of work pressure or illnesses; this may reflect some of the reasons for non-attendance. Another five agreed to take part in short interviews to discuss their lack of attendance with the programme. All interviewees pointed towards time pressure as the main issue.

Qualitative data from the interviews with the regular attenders about barriers to attending some of the training after booking revealed similarities in reasons as the non-attenders. A general lack of time due to staff shortages highlighted the role of the line manager’s approval in attending the training as discussed by two staff members:

“some sessions that I could not attend as my manager didn’t think I should attend so many sessions, because of the pressures of the service following the covid backlogs etc” P 5.

One staff member briefly raised the issues of empowerment where some staff might find it difficult to get the line manager’s approval to attend such training:

“And perhaps you need to get the buy in from the managers, because there’s an awful, awful lot of staff that aren’t really empowered to be able to go off and do this and then influence their work” P 7.

Communication and marketing of the new training was highlighted as a barrier to attendance by staff from one of the departments:

“I think one was probably in the promotion, I came across it by chance…that’s something to do with our organization because it kind of sits slightly outside of MPFT, so I think sometimes that messaging doesn’t always get through” P3 .

Prioritising paid training over STARS training was also a reason for one of the staff to miss some of the teaching sessions:

“I’ve missed some STARS trainings because of attending other trainings which are paid training or conferences that have cost money. So obviously I’ve prioritized them over some of the STARS training” P 9.

Barriers to engagement

Providing training across different professional groups highlighted difficulties in understanding respective languages. Two respondents reported that some content used clinical language that was difficult to understand:

“There’s also an element of understanding research and how it can be applied there’s probably an element of language as well, so it’s not just clinical…or health orientated, it’s also care. So it is just understanding that language barrier so that social work and social care staff know that it’s appropriate for everybody in the organization” P 13.

For one staff member the pace of delivering the graphic and statistical information teaching was very fast and difficult to understand:

“Sometimes it felt like the presenters for some statistical information went too fast when that was the area that most people are weaker on, so perhaps some courses tried to fit too much into one session” P 5.

A couple of staff discussed the workshops as disengaging due to long presentations and less interaction:

“the ones where you will just kind of like listening for three hours. They were really hard to stay engaged with” P 9.

For two staff the breakout rooms were not as helpful as explained by one:

“it can be awkward when you’re with people you don’t know and haven’t got a full grasp of the subject, and trying to think of contributions” P 5.

One staff also highlighted how attending the training from a shared office space can be problematic compared to a private space:

“As when doing it in the office, it’s harder to engage in group discussions due to fear of disrupting other colleagues” P 2.

Other ways of delivering the training were also suggested due to long commitments for the workshops. Two participants suggested that three-hour workshops were too long when delivered online; face-to-face learning was preferred:

“it would be nice to have it when we can to have some classroom based stuff because again, it just feels more natural to ask questions and you get to have those conversations in breaks” P 1.

And according to one participant, the training could be delivered using pre-recorded content:

“If there was a way to like the website on the Internet, all these links that you could click on to watch re-watch everything so you know where to go to one place to see all” P 6.

However, for two participants the recordings of teaching sessions were not as good as attending in real-time, as explained by one:

“You’re not the one engaging in it like because obviously you’re just watching it after the fact, so I don’t sit through the whole thing…If you’ve got questions, there’s nowhere to ask those questions” P 9.

Facilitators to engagement

Online synchronous delivery of the teaching sessions was valued by all interview participants, in the context of the Covid-19 pandemic. Use of breakout rooms for small group discussion and interaction was considered useful by most of the interview participants, for example:

“that was quite nice that you’d catch up with people that you were in the breakout rooms and could get to know a bit more about what they were doing and so I found that quite helpful from like a networking perspective” P 10.

Most of the staff members discussed keeping the recorded videos for future reference as very helpful:

“I know I’m not going to have time to apply myself to do in any sort of research at the moment with how things are at work, but I’ve got all the recordings and so could go back to those” P 10.

To summarise, barriers to attend the training included a lack of time on the participants’ end and lack of promotion. Perceived value due to no direct cost associated with the training was also revealed as a reason to miss a session after booking. Pace, professional-specific language, length of teaching and shared office space were highlighted as some of the barriers to engagement. Regarding facilitators to attend and maintain engagement, all staff were happy with online delivery and the availability of recordings was useful. However, mixed opinions were shared about the usefulness of breakout rooms given the range of professional groups that the staff belonged to.

Relevance and impact of training

Staff described various benefits to their research practice since attending STARS sessions, such as, writing and publishing a short report; working on a literature review; signing on to a university course; successfully receiving regulatory research approvals; and completing preliminary work to attend a professional doctorate or equivalent.

Training content relevance and suitability

All interview participants commented on the programme content and described it as comprehensive and well-balanced in terms of topics and delivery:

“I think it was really well balanced. The presenters came from diverse backgrounds and research was treated holistically by all, so everything felt relevant” P 12.

Impact on knowledge, skills and attributes

One participant described how learning was helpful to understand key areas in greater depth:

“I have an understanding of some critical appraisal and things like that, but it was probably more surface level and the STARS programme helped me to develop that quite significantly” P 1.

For another staff it helped with attending and presenting at different teaching sessions:

“So I’ve attended the regional teaching partnership programs we’ve presented our [name] project across [organisation] who are now looking at setting up a regional program. We’ve presented at NIHR events so yeah, definitely useful” P 13 .

The teaching sessions had a prompt impact on the knowledge and skills of those staff who already had some knowledge of research and also those who had identified specific opportunities to put into practice.

Applying new learning

Some learning on the training had wider applications that went beyond research, topics such as informed consent:

“Things like the informed consent training because for all our new staff that’s a major part of research. So from that we’ve drafted kind of a memoirs and processes formally based on sort of training materials on how an informed consent should be conducted so that we know that everybody starting at the same level” P 11.

Learning on one particular workshop helped to build a participant’s confidence in reading, making sense, and talking about research followed by conducting their own literature review:

“I used the literature review knowledge that I gained to do a very comprehensive literature review. Very rapid, quite comprehensive and then presented it. So I was able to put it into practice straight away” P 3 .

Overall, most of the participants mentioned using the new learning in practice but only a few staff members were able to provide practical examples.

Promoting a research-active environment

Staff discussed how they were using more resources from the organisation such as websites, the local research department, and library services in creating a research identity for themselves and contributing towards a research-active environment within and across their respective departments.

Research career pathways

The STARS programme helped to awaken ambitions for research and staff showed how keen they were on getting involved in doing research. Participants described doing their own research as a better option when other routes for progression were limited in their department:

“where I’m at in my role, there isn’t really anywhere to go unless you want to be a team leader, which isn’t really what I want to do. I really enjoy the patient facing side of things, and so I’ve always kind of said I’d be more interested in more specialized role or doing some research” P 10.

STARS was also useful in the stages of career development and for some it was helpful in starting the new paths as discussed by one:

“It’s either doing a feasibility or that sort of level today as part of a master’s course or doing their pre doctoral the NIHR sort of work to get a project effectively ready” P 6.

However, there was also a sense of being unfulfilled among some of the participants:

“I’d like to progress in it, but it’s where do I take it because I don’t know what opportunities are out there and how to apply for anything really” P 4.
“I’m really interested in doing some research in the area that I work in because I feel like there’s lots of improvements and things that could be made with how we do things and for the clients to get the most out of the service…I think with the STARS stuff I’ve sort of parked it so I’ve got it all saved together in a folder like ready so I can go and access it” P 10.

STARS opened up different routes for career progression for some staff. On the other hand, staff without immediate opportunities to get involved in research reported experiencing frustration because of the fact that there were no obvious opportunities for them to put their improved skills into practice. Success stories (going on a pre-doctoral path; progression for those who were already doing their master’s/doctorate etc.) of those who had some research base highlights the initiation of research identities.

Workforce satisfaction

In addition to feeling motivated to complete their academic qualifications, two staff members discussed how much they valued the STARS training and one participant described staying in their job, in order to access the training:

“I’ve not come across any other type of research training that is like is what the STARS programme offered. I purposely stayed within my role to access this stars training” P 9.

Improving awareness about research support services

The staff interviewees appreciated the associations to other support and resources that they had found out about while attending the STARS training. This included the library services and the R&I team:

“And the fact that our library helps us is phenomenal…So it’s given me a lot of knowledge about the wide organization and just how invested we are in research and that there are people [R&I] to help” P 7.

The STARS programme has been developed with contributions from different departments in order to make it suitable for all staff members to access and understand. This was reflected in the discussion where the interviewees appreciated the other links and resources.

The current paper reports findings from a mixed-methods study, which aimed to evaluate the delivery of a novel research training programme to health and social care staff in a single organisation in England (MPFT). The mixed methods approach generated key data against three of Kirkpatrick’s framework (reaction, learning and behaviour). Quantitative findings demonstrated good engagement with the programme from a diverse range of professional groups; a broad range of reasons were given for engagement. All of which demonstrates the broad appeal and initial reaction to the programme offer, particularly among professional groups who may not ordinarily engage in research (e.g. social care, nursing and midwifery staff). Ratings of session quality were very positive with 97% of ratings either very good or good. Qualitative findings highlighted three key themes: engagement with training, relevance, and impact of training, and promoting a research-active environment. Within these themes, positive reactions to training (e.g. appreciation, satisfaction, collaboration with others, access to new resources), evidence of learning (e.g. understanding critical appraisal) and change in behaviour through practical application (e.g. conducting a literature review) and sharing learning (e.g. networking) were identified. However, barriers still exist for many, including research terminology, limited capacity and the need for wider promotional campaigns.

Comparisons with findings from previous research in other areas and with elements of Gee and Cooke [ 26 ] framework for Research Capacity Development in health care are made, particularly within the areas of Close to Practice (CTP), Infrastructure (INF) and Skills and Confidence Building, which closely align with our findings and help support transferability to other contexts whilst also realising that a training programme can only do so much.

Close to practice

Gee and Cooke’s [ 26 ] ‘Close to Practice’ principle covers themes such as keeping research relevant to health care and informing day-to-day practice The current programme tried to be inclusive of all professional types (i.e. being close to practice); however, as identified in the engaging with teaching sessions theme, some language barriers were highlighted by staff from social care backgrounds who felt excluded due to the clinical/academic language used to deliver the training session – which may have obscured the relevance of the content for this group of learners. Still, the way the STARS programme supports this principle is evident in the content, which addresses both the main strands of the UK and English health policy, driving increased health and care involved in research:

the routine use of research findings in day to day practice;

increased involvement in research activity within the health service.

(referred to by Wakefield et al. [ 13 ] as ‘using research’ and ‘doing research’). The findings of the current evaluation demonstrated that participants’ reasons for booking onto the programme usually included one or both elements. Participants’ motivations also mirrored those found by Dimova et al. [ 15 ], presenting expectations that the STARS content supported both individual career development and organisational objectives such as high-quality patient care. In line with Ariely et al. [ 27 ] and Abramovich and McBride [ 28 ] booking but not attending the current training sessions was an indication toward the perceived low value of the training considering it was completely free for the staff. As the training is free to attend for the staff & managers with no direct impact on teams’ budgets, the priority to attend was given to paid trainings over STARS, sometimes.

Support infrastructure

Gee and Cooke’s [ 26 ] ‘Developing a support infrastructure’ principle covers ‘building additional resources and/or processes into the Trust’s organizational system to enable the smooth and effective running of research projects and for research capacity building’. The findings from the current evaluation, particularly under the ‘Promoting a research-active environment’ them, also showed how a wide-ranging in-house research skills training programme open to all staff can help build resources and processes within a healthcare provider that can support greater research activity.

In terms of processes, distinctive features of this training programme were that it was delivered in-house and entirely online. While the move to online training was necessitated by the pandemic (COVID-19), the evaluation showed that online training has the potential to become the delivery method of choice, particularly for in-house training for organisations covering a wide geographical area. Evaluations comparing online synchronous learning to traditional face-to-face learning have generally shown that (though with certain limitations) online approaches can be effective (George et al. [ 29 ], found this was the case for post registration medical education). In line with previous research, the current evaluation has also shown that an online-only training programme has challenges but can have a positive impact on applying research skills and developing confidence among healthcare staff [ 29 , 30 ].

Participants’ feedback identified the importance yet challenge of incorporating interactivity into online training [ 31 , 32 , 33 ]. Feedback on the length of the teaching sessions demonstrated that long sessions (in this case two hours or longer) could reduce engagement [ 33 , 34 ].

The literature on barriers to health and social care staff carrying out either or both of these activities (research finding use or research activity) identified four main barriers:

lack of time and/or resources;

lack of organisational or management support in other ways;

lack of skills, knowledge, and confidence to undertake research or put evidence into practice and.

lack of opportunities to develop these skills.

The first two of these are linked to infrastructure, resources and processes. The findings of the STARS evaluation showed mixed evidence in this respect. On one hand, the evaluation echoed previous research [ 7 , 8 ] that lack of time or staffing pressures was a major barrier to healthcare staff gaining research skills. Lack of protected time for research activities remains an important barrier to embedding a research-active environment into an organisation. As suggested by King et al. [ 11 ] the current evaluation was also conducted keeping in mind the long-term impacts on the organisational level. The STARS evaluation found the issue of management support, also identified previously [ 8 ], and affected both attendance and opportunities to put skills learnt into practice. On the other hand, the evaluation produced at least one positive example of a manager supporting an attendee in putting skills learnt into practice, resulting in changes in practice.

Research skills and confidence in the workforce

Gee and Cooke’s [ 26 ] ‘skills’ principle covers the provision of training and development opportunities to enable the health and care workforce to develop the skills and confidence to both ‘use’ and ‘do’ research. This principle speaks to the second theme of ‘Relevance and impact of training’ and matches the third and fourth barriers to doing and using research from the research literature mentioned above. This evaluation focused on how the STARS training programme addressed this principle and these barriers.

In terms of the provision of opportunities, the analysis of benefits reported by participants suggest that taking part in the programme contributed to improved skills and confidence in both the ‘using’ and ‘doing’ areas. Comments from the interviews also showed how the STARS programme had addressed the barrier of a lack of opportunities to develop these skills, with two (social care) participants commenting that STARS represented an opportunity not traditionally available to staff from their sector. This helps address one of Wakefield et al’s [ 13 ] recommendations about access to research training opportunities.

Previous research [ 8 , 10 , 13 ] showed that a lack of research skills, confidence and opportunities to gain them were issues associated with non-medical staff groups, particularly nurses, AHPs and social workers. However, the opportunity to gain knowledge and new skills through STARS was valued and staff had plans of using them in the future, echoing the results reported by Bullock et al. [ 35 ] The analysis of demographic data for the STARS programme was based on broad nationally defined staff categories (United Kingdom Electronic Staff Record (ESR) categories – see ‘A Guide to the Staff Group, Job Role and Area of Work classifications used in ESR’); it was difficult to separate, for example, social workers from other staff categories who usually have higher degrees, a high level of research skills, confidence and knowledge. However, the high level of take-up from nursing and midwifery and AHPs suggest that the STARS programme had been of interest to staff groups that previous research had identified as lacking skills, confidence and training opportunities to make evidence-based practice and research activity part of their working culture.

Comments received in the STARS evaluation raised the dilemma of whether it was possible to make content available and relevant to groups of participants with very different professional backgrounds and levels of research knowledge and experience; or whether attempting to achieve this meant the course content did not meet any group’s needs well. The evaluation found both positives and negatives in this respect – gains from sharing the training with colleagues from very different areas and perspectives versus content failing to suit the needs of the participants, very different prior research and professional knowledge and so inhibiting learning in some cases. Previous research was found, evaluating multidisciplinary training provisions that either spanned a range of professional groups working in the same area or students at a similar stage of education studying in different subject areas [ 7 , 9 , 10 , 12 ]. However, no previous research was found evaluating training programmes that matched the STARS participants’ mix of both professional backgrounds and work areas (spanning a range of inpatient and community health and social care settings as well as support services).

Strengths and limitations

The current evaluation contains both quantitative and qualitative primary data from engagers and non-engagers in a novel research education and training programme for a broad range of health and social care professionals. Qualitative methods were designed to be flexible and pragmatic to capture views from busy health and social practitioners; however, emailed responses did not support in-depth exploration. As the interviewer was also a staff member of the same organisation there might have been some undisclosed responses. Findings report key the components of training that worked/did not work; this information could eventually be used to improve future training in this setting and others. As the participants of the STARS programme and current evaluation are located within a health and social care NHS trust in England, the conclusions are relevant to similar settings only. However, findings seem relevant to non-UK health and social care workers. For example, Withington et al. described how their targeted training and mentoring model enhanced research capacity among social workers [ 19 ] Also similar to finding in STARS collaborative approaches have also been discussed as essential by Nystrom et al., in in health and social care context in Sweden to ensure support, trust and understanding among those working in healthcare system [ 36 ]. Despite this limitation, the findings highlight how a research training programme can be tailored around the needs of staff and run virtually during a pandemic.

This evaluation covered a 12-month period in which the STARS programme was rolled out for the first time at MPFT. Findings demonstrate the positive impact that access to free, high-quality, online research education can have in terms of enhancing research awareness and confidence across a diverse range of professional types; some of whom reported unequal access to such training in the past (e.g., social care, nursing and midwifery). Service-level barriers remain that a novel training programme cannot address (e.g., competing burden of clinical roles). It is too early to assess longer-term outcomes relating to the fourth level of Kirkpatrick’s framework (performance) or research culture at an organisation-level; further follow-up research is needed. The STARS programme demonstrates what strong collaboration between NHS and academic institutions can produce and provides a training model that can be adopted and adapted elsewhere to nurture research-active environments and promote research capacity building within and beyond the UK.

Availability of data and materials

The anonymised quantitative raw data from evaluation registers and qualitative data from interviews is available on reasonable requests. The corresponding and first author, GT, should be contacted if someone wants to request the data from this study.

Austin A. What does the new clinical research vision mean for NHS patients and health professionals? England.nhs.uk/blog. 2021. Available at: https://www.england.nhs.uk/blog/what-does-the-new-clinical-research-vision-mean-for-nhs-patients-and-health-professionals/#:~:text=Research%20is%20beneficial%20to%20people,faster%20returns%20to%20everyday%20life . Accessed 18 Feb 2022.

Policy paper. UK Govt. Saving and improving lives: the future of UK Clinical Research Delivery, United Kingdom. 2021. Available at: https://www.gov.uk/government/publications/the-future-of-uk-clinical-research-delivery/saving-and-improving-lives-the-future-of-uk-clinical-research-delivery . Accessed Jan 2022.

National Health Service Making research matter: Chief Nursing Officer for England’s strategic plan for research. Available online at https://www.england.nhs.uk/wp-content/uploads/2021/11/B0880-cno-for-englands-strategic-plan-fo-research.pdf . 2021. Accessed 22 Apr 2022.

Royal College of Physicians. Delivering research for all: expectations and aspirations for the NHS in England (policy statement). Available at Delivering research for all: expectations and aspirations for the NHS in England | RCP London. 2019. Accessed 22 Apr 2022.

Barouki R, Kogevinas M, Audouze K, et al. The COVID-19 pandemic and global environmental change: emerging research needs. Environ Int. 2021;146: 106272.

Article   CAS   PubMed   Google Scholar  

Cooke J, Gardois P, Booth A. Uncovering the mechanisms of research capacity development in health and social care: a realist synthesis. Health Res Policy Syst. 2018;16(1):93.

Article   PubMed   PubMed Central   Google Scholar  

Mustafa K, Murray CC, Nicklin E, et al. Understanding barriers for research involvement among paediatric trainees: a mixed methods study. BMC Med Educ. 2018;18:165.

Fry M, Attawet J. Nursing and midwifery use, perceptions and barriers to evidence-based practice: a cross-sectional survey. Int J Evid Based Healthcare. 2018;16(1):47–54. https://doi.org/10.1097/XEB.0000000000000117 . (Accessed 14 Mar 2022).

Article   Google Scholar  

Barratt H, Fulop NJ. Building capacity to use and undertake research in health organisations: a survey of training needs and priorities among staff. BMJ Open. 2016;6: e012557.

Maben J, King A. Engaging NHS staff in research. BMJ. 2019;365:l4040. https://doi.org/10.1136/bmj.l4040 . (Accessed 22 Apr 2022).

Article   PubMed   Google Scholar  

King O, West E, Lee S, Glenister K, Quilliam C, Wong Shee A, Beks H. Research education and training for nurses and allied health professionals: a systematic scoping review. BMC Med Educ. 2022;22(1):1–55.

Burkinshaw P, Bryant LD, Magee C, et al. Ten years of NIHR research training: perceptions of the programmes: a qualitative interview study. BMJ Open. 2022;12:e046410. https://doi.org/10.1136/bmjopen-2020-046410 . (Accessed 22 Apr 2022).

Wakefield J, Lavender S, Nixon K, et al. Social work and social care: mapping workforce engagement, relevance, experience and interest in research. Br J Social Work. 2021;00:1–21.

Google Scholar  

What is social work/ social care? TCSW. Available: http://www.tcsw.org.uk/what-is-social-work-social-care/ . Sited on: 2 Jan 2024.

Dimova S, Prideaux R, Ball S, et al. Enabling NHS staff to contribute to research. Cambridge: RAND Europe; 2018.

Gilbert A, Steel J, Rachel D, Jaggi A. Identifying barriers and facilitators to engaging in clinical research within an NHS Therapies Department: results of a listening exercise. Physiotherapy. 2016;102:e179.

Jowett SM, Macleod J, Wilson S, Hobbs FD. Research in primary care: extent of involvement and perceived determinants among practitioners from one English region. Br J Gen Pract. 2000;50(454):387–9.

CAS   PubMed   PubMed Central   Google Scholar  

Rahman S, Majumder MA, Shaban SF, Rahman N, Ahmed M, Abdulrahman KB, D’souza UJ. Physician participation in clinical research and trials: issues and approaches. Adv Med Educ Pract. 2011;7:85–93.

Withington T, Alcorn N, Maybery D, Goodyear M. Building research capacity in clinical practice for social workers: a training and mentorship approach. Adv Mental Health. 2020;18(1):73–90.

Papanicolas I, Mossialos E, Gundersen A, Woskie L, Jha AK. Performance of UK National Health Service compared with other high-income countries: observational study. BMJ. 2019;367:6326.

Kirkpatrick DL. Evaluating training programs. Mumbai: Tata McGraw-Hill Education; 1998.

Braun V, Clarke V. Using thematic analysis in psychology. Qual Res Psychol Taylor Francis Online. 2006;3(2):77–101.

Hawkins JE. The practical utility and suitability of email interviews in qualitative research. Qualitative Rep. 2018;23(2):493.

Amri M, Angelakis C, Logan D. Utilizing asynchronous email interviews for health research: overview of benefits and drawbacks. BMC Res Notes. 2021;14(1):1–5.

Kirkpatrick JD, Kirkpatrick WK. Kirkpatrick’s four levels of training evaluation. Association for Talent Development; 2016.

Gee M, Cooke J. How do NHS organisations plan research capacity development? Strategies, strengths, and opportunities for improvement. BMC Health Serv Res. 2018;18(1):1–1.

Ariely D, Loewenstein G, Prelec D. Tom Sawyer and the construction of value. J Econ Behav Organ. 2006;60(1):1–10.

Abramovich S, McBride M. Open education resources and perceptions of financial value. Internet Higher Educ. 2018;39:33–8.

George PP, Zhabenko O, Kyaw BM, et al. Online digital education for post registration training of medical doctors: systematic review by the Digital Health Education Collaboration. J Med Internet Res. 2019;21(2): e13269.

Newport L, Roberts D. Developing online training in wound care. Br J Nurs. 2021;30(12):37–8.

Bączek M, Zagańczyk-Bączek M, Szpringer M, et al. Students’ perception of online learning during the COVID-19 pandemic: a survey study of polish medical students. Medicine. 2021;100(7):e24821.

Clayton KE, Blumberg FC, Anthony JA. Linkages between course status, perceived course value, and students’ preference for traditional versus non-traditional learning environments. Comput Educ. 2018;125:175–81.

Gegenfurtner A, Schmidt-Hertha B, Lewis P. Digital technologies in training and adult education. Int J Train Dev. 2020;24(1):1–4.

Odayappan A, Venkatesh R, Tammineni R, et al. Perspectives of physicians regarding the role of webinars on medical education during the COVID-19 pandemic. Indian J Ophthalmol. 2021;69(5):1251.

Bullock A, Morris ZS, Atwell C. Collaboration between health services managers and researchers: making a difference? J Health Serv Res Policy. 2012;17(2):2–10.

Nyström ME, Karltun J, Keller C, Andersson Gäre B. Collaborative and partnership research for improvement of health and social services: researcher’s experiences from 20 projects. Health Res Policy Syst. 2018;16(1):1–7.

Department of Health. UK policy framework for health and social care research. 2017. Available at: https://www.healthandcareresearch.gov.wales/uploads/Policy%20%26%20Strategy/Research%20Governance/uk-policy-framework-health-social-care-research.pdf . Accessed Feb 2023.

Holm S. Declaration of Helsinki. Int Encyclopedia Ethics. 2013;1:1–4.

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Acknowledgements

The authors acknowledge and sincerely thank the members of the STARS working group for their contributions in delivering the project.

The authors thank CRN I&I strategic funding programme for funding the STARS program.

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Author GT conducted data collection and analysis with support from authors DD-O, EB and TK, author CC supported with literature for background and discussion and all authors were involved in the original conception of the idea and read and approved the final manuscript.

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This study was classified through the Health Research Authority (HRA) automated systems as not requiring ethical approval, as per the UK Policy Framework for Health and Social Care Research28 [ 37 ]. The study was reviewed by the Research and Innovation department form the authors’ organisation (MPFT) prior to being placed on the local evaluation register (ref: e2021-10) and it followed GDPR principles with regard to data management and was conducted in compliance with the Declaration of Helsinki29 [ 38 ]. A written informed consent was obtained from all participants before participation in the study. All prospective participants received information about the study and were asked to return a signed copy of the consent form via email. Additionally, at the start of each interview, participants were asked to confirm verbally that they consented to take part; this was audio recorded, as were the interviews. The author is happy to share the consent forms if needed but those would need to redact to maintain anonymity.

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Tajuria, G., Dobel-Ober, D., Bradley, E. et al. Evaluating the impact of the supporting the advancement of research skills (STARS) programme on research knowledge, engagement and capacity-building in a health and social care organisation in England. BMC Med Educ 24 , 126 (2024). https://doi.org/10.1186/s12909-024-05059-0

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A list of figures and tables compiles all of the figures and tables that you used in your thesis or dissertation and displays them with the page number where they can be found.

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A dissertation prospectus or proposal describes what or who you plan to research for your dissertation. It delves into why, when, where, and how you will do your research, as well as helps you choose a type of research to pursue. You should also determine whether you plan to pursue qualitative or quantitative methods and what your research design will look like.

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The conclusion of your thesis or dissertation shouldn’t take up more than 5–7% of your overall word count.

For a stronger dissertation conclusion , avoid including:

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A thesis or dissertation outline is one of the most critical first steps in your writing process. It helps you to lay out and organize your ideas and can provide you with a roadmap for deciding what kind of research you’d like to undertake.

Generally, an outline contains information on the different sections included in your thesis or dissertation , such as:

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A glossary is a collection of words pertaining to a specific topic. In your thesis or dissertation, it’s a list of all terms you used that may not immediately be obvious to your reader. In contrast, an index is a list of the contents of your work organized by page number.

The title page of your thesis or dissertation goes first, before all other content or lists that you may choose to include.

The title page of your thesis or dissertation should include your name, department, institution, degree program, and submission date.

Glossaries are not mandatory, but if you use a lot of technical or field-specific terms, it may improve readability to add one to your thesis or dissertation. Your educational institution may also require them, so be sure to check their specific guidelines.

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  • Methodology
  • Open access
  • Published: 20 March 2017

Getting started with tables

  • Hazel Inskip   ORCID: orcid.org/0000-0001-8897-1749 1 ,
  • Georgia Ntani 1 ,
  • Leo Westbury 1 ,
  • Chiara Di Gravio 1 ,
  • Stefania D’Angelo 1 ,
  • Camille Parsons 1 &
  • Janis Baird 1  

Archives of Public Health volume  75 , Article number:  14 ( 2017 ) Cite this article

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Tables are often overlooked by many readers of papers who tend to focus on the text. Good tables tell much of the story of a paper and give a richer insight into the details of the study participants and the main research findings. Being confident in reading tables and constructing clear tables are important skills for researchers to master.

Common forms of tables were considered, along with the standard statistics used in them. Papers in the Archives of Public Health published during 2015 and 2016 were hand-searched for examples to illustrate the points being made. Presentation of graphs and figures were not considered as they are outside the scope of the paper.

Basic statistical concepts are outlined to aid understanding of each of the tables presented. The first table in many papers gives an overview of the study population and its characteristics, usually giving numbers and percentages of the study population in different categories (e.g. by sex, educational attainment, smoking status) and summaries of measured characteristics (continuous variables) of the participants (e.g. age, height, body mass index). Tables giving the results of the analyses follow; these often include summaries of characteristics in different groups of participants, as well as relationships between the outcome under study and the exposure of interest. For continuous outcome data, results are often expressed as differences between means, or regression or correlation coefficients. Ratio/relative measures (e.g. relative risks, odds ratios) are usually used for binary outcome measures that take one of two values for each study participants (e.g. dead versus alive, obese versus non-obese). Tables come in many forms, but various standard types are described here.

Clear tables provide much of the important detail in a paper and researchers are encouraged to read and construct them with care.

Peer Review reports

Tables are an important component of any research paper. Yet, anecdotally, many people say that they find tables difficult to understand so focus only on the text when reading a paper. However, tables provide a much richer sense of a study population and the results than can be described in the text. The tables and text complement each other in that the text outlines the main findings, while the detail is contained in the tables; the text should refer to each table at the appropriate place(s) in the paper. We aim to give some insights into reading tables for those who find them challenging, and to assist those preparing tables in deciding what they need to put into them. Producing clear, informative tables increases the likelihood of papers being published and read. Good graphs and figures can often provide a more accessible presentation of study findings than tables. They can add to the understanding of the findings considerably, but they can rarely contain as much detail as a table. Choosing when to present a graph or figure and when to present a table needs careful consideration but this article focuses only on the presentation of tables.

We provide a general description of tables and statistics commonly used when presenting data, followed by specific examples. No two papers will present the tables in the same way, so we can only give some general insights. The statistical approaches are described briefly but cannot be explained fully; the reader is referred to various books on the topic [ 1 – 6 ].

Presentation of tables

The title (or legend) of a table should enable the reader to understand its content, so a clear, concise description of the contents of the table is required. The specific details needed for the title will vary according to the type of table. For example, titles for tables of characteristics should give details of the study population being summarised and indicate whether separate columns are presented for particular characteristics, such as sex. For tables of main findings, the title should include the details of the type of statistics presented or the analytical method. Ideally the table title should enable the table to be examined and understood without reference to the rest of the article, and so information on study, time and place needs to be included. Footnotes may be required to amplify particular points, but should be kept to a minimum. Often they will be used to explain abbreviations or symbols used in the table or to list confounding factors for which adjustment has been made in the analysis.

Clear headings for rows and columns are also required and the format of the table needs careful consideration, not least in regard to the appropriateness and number of rows and columns included within the table. Generally it is better to present tables with more rows than columns; it is usually easier to read down a table than across it, and page sizes currently in use are longer than they are wide. Very large tables can be hard to absorb and make the reader’s work more onerous, but can be useful for those who require extra detail. Getting the balance right needs care.

Types of tables

Many research articles present a summary of the characteristics of the study population in the first table. The purpose of these tables is to provide information on the key characteristics of the study participants, and allow the reader to assess the generalisability of the findings. Typically, age and sex will be presented along with various characteristics pertinent to the study in question, for example smoking prevalence, socio-economic position, educational attainment, height, and body mass index. A single summary column may be presented or perhaps more than one column split according to major characteristics such as sex (i.e. separate columns for males and females) or, for trials, the intervention and control groups.

Subsequent tables generally present details of the associations identified in the main analyses. Sometimes these include results that are unadjusted or ‘crude’ (i.e. don’t take account of other variables that might influence the association) often followed by results from adjusted models taking account of other factors.

Other types of tables occur in some papers. For example, systematic review papers contain tables giving the inclusion and exclusion criteria for the review as well as tables that summarise the characteristics and results of each study included in the review; such tables can be extremely large if the review covers many studies. Qualitative studies often provide tables describing the characteristics of the study participants in a more narrative format than is used for quantitative studies. This paper however, focuses on tables that present numerical data.

Statistics commonly presented in tables

The main summary statistics provided within a table depend on the type of outcome under investigation in the study. If the variable is continuous (i.e. can take any numerical value, between a minimum and a maximum, such as blood pressure, height, birth weight), then means and standard deviations (SD) tend to be given when the distribution is symmetrical, and particularly when it follows the classical bell shaped curve known as a Normal or Gaussian distribution (see Fig.  1a ). The mean is the usual arithmetic average and the SD is an indication of the spread of the values. Roughly speaking, the SD is about a quarter of the difference between the largest and the smallest value excluding 5% of values at the extreme ends. So, if the mean is 100 and the SD is 20 we would expect 95% of the values in our data to be between about 60 (i.e. 100–2×20) and 140 (100 + 2×40).

Distribution of heights and weights of young women from the Southampton Women’s Survey [ 7 ]. a Shows the height distribution, which is symmetrical and generally follows a standard normal distribution, while b shows weight, which is skewed to the right

The median and inter-quartile range (IQR) are usually provided when the data are not symmetrical as in Fig.  1b , which gives an example of data that are skewed, such that if the values are plotted in a histogram there are many values at one end of the distribution but fewer at the other end [ 7 ]. If all the values of the variable were listed in order, the median would be the middle value and the IQR would be the values a quarter and three-quarters of the way through the list. Sometimes the lower value of the IQR is labelled Q1 (quartile 1), the median is Q2, and the upper value is Q3. For categorical variables, frequencies and percentages are used.

Common statistics for associations between continuous outcomes include differences in means, regression coefficients and correlation coefficients. For these statistics, values of zero indicate no association between the exposure and outcome of interest. A correlation coefficient of 0 indicates no association, while a value of 1 or −1 would indicate perfect positive or negative correlation; values outside the range −1 to 1 are not possible. Regression coefficients can take any positive or negative value depending on the units of measurement of the exposure and outcome.

For binary outcome measures that only take two possible values (e.g. diseased versus not, dead versus alive, obese versus not obese) the results are commonly presented in the form of relative measures. These include any measure with the word ‘relative’ or ‘ratio’ in their name, such as odds ratios, relative risks, prevalence ratios, incidence rate ratios and hazard ratios. All are interpreted in much the same way: values above 1 indicate an elevated risk of the outcome associated with the exposure under study, whereas below 1 implies a protective effect. No association between the outcome and exposure is apparent if the ratio is 1.

Typically in results tables, 95% confidence intervals (95% CIs) and/or p -values will be presented. A 95% CI around a result indicates that, in the absence of bias, there is a 95% probability that the interval includes the true value of the result in the wider population from which the study participants were drawn. It also gives an indication of how precisely the study team has been able to estimate the result (whether it is a regression coefficient, a ratio/relative measure or any of the summary measures mentioned above). The wider the 95% CI, the less precise is our estimate of the result. Wide 95% CIs tend to arise from small studies and hence the drive for larger studies to give greater precision and certainty about the findings.

If a 95% CI around a result for a continuous variable (difference in means, regression or correlation coefficient) includes 0 then it is unlikely that there is a real association between exposure and outcome whereas, for a binary outcome, a real association is unlikely if the 95% CI around a relative measure, such as a hazard or odds ratio, includes 1.

The p -value is the probability that the finding we have observed could have occurred by chance, and therefore there is no identifiable association between the exposure of interest and the outcome measure in the wider population. If the p -value is very small, then we are more convinced that we have found an association that is not explained by chance (though it may be due to bias or confounding in our study). Traditionally a p -value of less than 0.05 (sometimes expressed as 5%) has been considered as ‘statistically significant’ but this is an arbitrary value and the smaller the p -value the less likely the result is simply due to chance [ 8 ].

Frequently, data within tables are presented with 95% CIs but without p -values or vice versa. If the 95% CI includes 0 (for a continuous outcome measure) or 1 (for a binary outcome), then generally the p -value will be greater than 0.05, whereas if it does not include 0 or 1 respectively, then the p -value will be less than 0.05 [ 9 ]. Generally, 95% CIs are more informative than p -values; providing both may affect the readability of a table and so preference should generally be given to 95% CIs. Sometimes, rather than giving exact p-values, they are indicated by symbols that are explained in a footnote; commonly one star (*) indicates p  < 0.05, two stars (**) indicates p  < 0.01.

Results in tables can only be interpreted if the units of measurement are clearly given. For example, mean or median age could be in days, weeks, months or years if infants and children are being considered, and 365, 52, 12 or 1 for a mean age of 1 year could all be presented, as long the unit of measurement is provided. Standard deviations should be quoted in the same units as the mean to which they refer. Relative measures, such as odds ratios, and correlation coefficients do not have units of measurement, but for regression coefficients the unit of measurement of the outcome variable is required, and also of the exposure variable if it is continuous.

The examples are all drawn from recent articles in Archives of Public Health. They were chosen to represent a variety of types of tables seen in research publications.

Tables of characteristics

The table of characteristics in Table  1 is from a study assessing knowledge and practice in relation to tuberculosis control among in Ethiopian health workers [ 10 ]. The authors have presented the characteristics of the health workers who participated in the study. Summary statistics are based on categories of the characteristics, so numbers (frequencies) in each category and the percentages of the total study population within each category are presented for each characteristic. From this, the reader can see that:

the study population is quite young, as only around 10% are more than 40 years old;

the majority are female;

more than half are nurses;

about half were educated to degree level or above.

The table of characteristics in Table  2 is from a study of the relationship between distorted body image and lifestyle in adolescents in Japan [ 11 ]. Here the presentation is split into separate columns for boys and girls. The first four characteristics are continuous variables, not split into categories but, instead, presented as means, with the SDs given in brackets. The three characteristics in the lower part of the table are categorical variables and, similar to Table  1 , the frequency/numbers and percentages in each category are presented. The p -values indicate that boys and girls differ on some of the characteristics, notably height, self-perceived weight status and body image perception.

In Table  3 , considerable detail is given for continuous variables in the table. This comes from an article describing the relationship between mid-upper-arm circumference (MUAC) and weight changes in young children admitted to hospital with severe acute malnutrition from three countries [ 12 ]. For each country, the categorical characteristic of sex is presented as in the previous two examples, but more detail is given for the continuous variables of age, MUAC and height. The mean is provided as in Table  2 , though without a standard deviation, but we are also given the minimum value, the 25th percentile (labelled Q1 – for quartile 1), the median (the middle value), the 75th percentile (labelled Q2, here though correctly it should be Q3 – see above) and the maximum value. The table shows:

Ethiopian children in this study were older and taller than those from the other two countries but their MUAC measurements tended to be smaller;

in Bangladesh, disproportionally more females than males were admitted for treatment compared with the other two countries.

It is unusual to present as much detail on continuous characteristics as is given in Table  3 . Usually, for each characteristic, either (a) mean and SD or (b) median and IQR would be given, but not both.

Tables of results – summary findings

Many results tables are simple summaries and look similar to tables presenting characteristics, as described above. Sometimes the initial table of characteristics includes some basic comparisons that indicate the main results of the study. Table  4 shows part of a large table of characteristics for a study of risk factors for acute lower respiratory infections (ALRI) among young children in Rwanda [ 13 ]. In addition to presenting the numbers of children in each category of a variety of characteristics, it also shows the percentage in each category among those who suffered ALRI in the previous two weeks, and provides p- values for the differences between the categories among those who did and did not suffer from ALRI. Thus only 2.9% of older children (24–59 months) within the study suffered from ALRI, compared with about 5% in the two youngest categories. The p -value of 0.001, well below 0.05, indicates that this difference is statistically significant. The other finding of some interest is that children who took vitamin A supplements appeared to be less likely to suffer from ALRI than those who did not, but the p -value of 0.04 is close to 0.05 so not as remarkable a finding as for the difference between the age groups.

Table  5 shows a summary table of average life expectancy in British Columbia by socioeconomic status [ 14 ]. The average life expectancy at birth and the associated 95% CIs are given according to level of socio-economic status for the total population (column 1), followed by males and females separately. The study is large so the 95% CIs are quite narrow, and the table indicates that there are considerable differences in life expectancy between the three socioeconomic groups, with the lowest category having the poorest life expectancy. The gap in life expectancy between the lowest and highest category is more than three years, as shown in the final row.

Tables of results – continuous outcomes

Continuous outcome measures can be analysed in a variety of ways, depending on the purpose of the study and whether the measure of the exposure is continuous, categorical or binary.

Table  6 shows an example of correlation coefficients indicating the degree of association between the exposure of interest (cognitive test scores) and the outcome measure (academic performance) [ 15 ]. No confidence intervals are presented, but the results show that almost all the particular cognitive test scores are statistically significantly associated ( p -value < 0.05) with the two measures of academic performance. Note that this table is an example of where a footnote is used to give information about the p-values. Not surprisingly, all the correlations are positive; one would expect that as cognitive score increase so too would academic performance. The numbers labelled “N” give the number of children who contributed data to each correlation coefficient.

Table  7 is quite a complex table, but one that bears examination. It presents regression coefficients from an analysis of pregnancy exposure to nitrogen dioxide (NO 2 ) and birth weight of the baby in a large study of four areas in Norway; more than 17,000 women-baby pairs contributed to the complete crude analysis [ 16 ]. Regression coefficients are presented and labelled “Beta”, the usual name for such coefficients, though the Greek letter β, B or b are sometimes used. They are interpreted as follows: for one unit increase in the exposure variable then the outcome measure increases by the amount of the regression coefficient. Regression coefficients of zero indicate no association. In this table, the Beta in the top left of the table indicates that as NO 2 exposure of the mother increases by 1 unit (a ‘unit’ in this analysis is 10 μg/m 3 , see the footnote in the table, which gives the units of measurement used for the regression coefficients: grams per 10 μg/m 3 NO 2 ) then the birth weight of her baby decreases (because the Beta is negative) by 37.9 g. The 95% CI does not include zero and the p -value is small (<0.001) implying that the association is not due solely to chance.

However, reading across the columns of the table gives a different story. The successive sets of columns include adjustment for increasing numbers of factors that might affect the association. While model 1 still indicates a negative association between NO 2 and birth weight that is highly significant ( p  < 0.001), models 2 and 3 do not. Inclusion of adjustment for parity or area and maternal weight has reduced the association such that the Betas have shrunk in magnitude to be closer to 0, with 95% CIs including 0 and p -values >0.05.

The table has multiple rows, with each one providing information on a different subset of the data, so the numbers in the analyses are all smaller than in the first row. The second row restricts the analysis to women who did not move address during pregnancy, an important consideration in estimating NO 2 exposure from home addresses. The third row restricts the analysis to those whose gestational age was based on the last menstrual period. These second two rows present ‘sensitivity analyses’, performed to check that the results were not due to potential biases resulting from women moving house or having uncertain gestational ages. The remaining rows in the table present stratified analyses, with results given for each category of various variables of interest, namely geographical area, maternal smoking, parity, baby’s sex, mother’s educational level and season of birth. Only one row of this table has a statistically significant result for models 2 and 3, namely babies born in spring, but this finding is not discussed in the paper. Note the gap in the table in the model 2 column as it is not possible to adjust for area (one of the adjustment factors in model 2) when the analysis is being presented for each area separately.

Tables of results – binary outcomes

Table  8 presents results from a study assessing whether children’s eating styles are associated with having a waist-hip ratio greater or equal to 0.5 (the latter being the outcome variable expressed in binary form – ≥0.5 versus <0.5) [ 17 ]. Results for boys and girls are presented separately, along with the number of children in each of the eating style categories. The main results are presented as crude and adjusted odds ratios (ORs). The adjusted ORs take account of age, exercise, skipping breakfast and having a snack after dinner, all of these being variables thought to affect the association between eating style and waist-hip ratio. Looking at the crude OR column, the value of 2.04 in the first row indicates that, among boys, those who report eating quickly have around twice the odds of having a high waist-hip ratio than those who do not eat quickly (not eating quickly is the baseline category, with an odds ratio given as 1.00). The 95% CI for the crude OR for eating quickly is 1.31 – 3.18. This interval does not include 1, indicating that the elevated OR for eating quickly is unlikely to be a chance finding and that there is a 95% probability that the range of 1.31 – 3.18 includes the true OR. The p -value is 0.002, considerably smaller than 0.05, indicating that this finding is ‘statistically significant’. The other ORs can be considered in the same way, but note that, for both boys and girls, the ORs for eating until full are greater than 1 but their 95% CIs include 1 and the p- values are considerably greater than 0.05, so not ‘statistically significant’, indicating chance findings.

The final columns present the ORs after adjustment for various additional factors, along with their 95% CIs and p -values. The ORs given here differ little from the crude ORs in the table, indicating that the adjustment has not had much effect, so the conclusions from examining the crude ORs are unaltered. It thus appears that eating quickly is strongly associated with a greater waist-hip ratio, but that eating until full is not.

Summary tables of characteristics describe the study population and set the study in context. The main findings can be presented in different ways and choice of presentation is determined by the nature of the variables under study. Scrutiny of tables allows the reader to acquire much more information about the study and a richer insight than if the text only is examined. Constructing clear tables that communicate the nature of the study population and the key results is important in the preparation of papers; good tables can assist the reader enormously as well as increasing the chance of the paper being published.

Abbreviations

Acute lower respiratory infections

Confidence interval

Mid-upper-arm circumference

  • Inter-quartile range

Nitrogen dioxide

Quartile 1 (25th percentile)

Quartile 2 (50th percentile = median)

Quartile 3 (75th percentile)

  • Standard deviation

Peacock J, Peacock P. Oxford Handbook of Medical Statistics. Oxford: Oxford University Press; 2010.

Book   Google Scholar  

Bland M. An Introduction to Medical Statistics. 4th ed. Oxford: Oxford University Press; 2015.

Google Scholar  

Kirkwood BR, Sterne JAC. Essential Medical Statistics. 2nd ed. Oxford: Wiley; 2003.

Altman DG. Practical statistics for medical research. London: Chapman & Hall; 1991.

Everitt BS, Palmer C. Encyclopaedic Companion to Medical Statistics. 2nd ed. Chichester: Wiley; 2010.

Armitage P, Berry G, Matthews JNS. Statistical Methods in Medical Research. 4th ed. Oxford: Wiley; 2001.

Inskip HM, Godfrey KM, Robinson SM, Law CM, Barker DJ, Cooper C. SWS Study Group: Cohort profile: The Southampton Women's Survey. Int J Epidemiol. 2006;35:42–8.

Article   PubMed   Google Scholar  

Sterne JA, Davey Smith G. Sifting the evidence-what's wrong with significance tests? BMJ. 2001;322:226–31.

Article   CAS   PubMed   PubMed Central   Google Scholar  

Davies HTO, Crombie IK. What are confidence intervals and p-values? http://www.bandolier.org.uk/painres/download/whatis/What_are_Conf_Inter.pdf. or https://grunigen.lib.uci.edu/sites/all/docs/gml/what_are_conf_inter.pdf . Accessed 27 Jan 2017.

Demissie Gizaw G, Aderaw Alemu Z, Kibret KT. Assessment of knowledge and practice of health workers towards tuberculosis infection control and associated factors in public health facilities of Addis Ababa, Ethiopia: A cross-sectional study. Arch Public Health. 2015;73:1–9.

Article   Google Scholar  

Shirasawa T, Ochiai H, Nanri H, Nishimura R, Ohtsu T, Hoshino H, Tajima N, Kokaze A. The relationship between distorted body image and lifestyle among Japanese adolescents: a population-based study. Arch Public Health. 2015;73:1–7.

Binns P, Dale N, Hoq M, Banda C, Myatt M. Relationship between mid upper arm circumference and weight changes in children aged 6–59 months. Arch Public Health. 2015;73:1–10.

Harerimana J-M, Nyirazinyoye L, Thomson DR, Ntaganira J. Social, economic and environmental risk factors for acute lower respiratory infections among children under five years of age in Rwanda. Arch Public Health. 2016;74:1–7.

Zhang LR, Rasali D. Life expectancy ranking of Canadians among the populations in selected OECD countries and its disparities among British Columbians. Arch Public Health. 2015;73:1–10.

Haile D, Nigatu D, Gashaw K, Demelash H. Height for age z score and cognitive function are associated with Academic performance among school children aged 8–11 years old. Arch Public Health. 2016;74:1–7.

Panasevich S, Håberg SE, Aamodt G, London SJ, Stigum H, Nystad W, Nafstad P. Association between pregnancy exposure to air pollution and birth weight in selected areas of Norway. Arch Public Health. 2016;74:1–9.

Ochiai H, Shirasawa T, Nanri H, Nishimura R, Matoba M, Hoshino H, Kokaze A. Eating quickly is associated with waist-to-height ratio among Japanese adolescents: a cross-sectional survey. Arch Public Health. 2016;74:1–7.

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Acknowledgement

Not applicable.

The work was funded by the UK Medical Research Council which funds the work of the MRC Lifecourse Epidemiology Unit where the authors work. The funding body had no role in the design and conduct of the work, or in the writing the manuscript.

Availability of data and materials

Data sharing is not applicable to this article as no datasets were generated or analysed during the current study.

Authors’ contributions

HI conceived the idea for the paper in discussion with JB. HI wrote the first draft and all other authors commented on successive versions and contributed ideas to improve content, clarity and flow of the paper. All authors read and approved the final manuscript.

Competing interests

The authors declare that they have no competing interests.

Consent for publication

Ethics approval and consent to participate, author information, authors and affiliations.

MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton General Hospital, Southampton, SO16 6YD, UK

Hazel Inskip, Georgia Ntani, Leo Westbury, Chiara Di Gravio, Stefania D’Angelo, Camille Parsons & Janis Baird

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Analyzing Reddit Forums Specific to Abortion That Yield Diverse Dialogues Pertaining to Medical Information Seeking and Personal Worldviews: Data Mining and Natural Language Processing Comparative Study

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Original Paper

  • Danny Valdez, PhD   ; 
  • Lucrecia Mena-Meléndez, PhD   ; 
  • Brandon L Crawford, PhD   ; 
  • Kristen N Jozkowski, PhD  

Department of Applied Health Science, Indiana University School of Public Health, Bloomington, IN, United States

Corresponding Author:

Danny Valdez, PhD

Department of Applied Health Science

Indiana University School of Public Health

1025 E 7th Street

Bloomington, IN, 47403

United States

Phone: 1 8128038955

Email: [email protected]

Background: Attitudes toward abortion have historically been characterized via dichotomized labels, yet research suggests that these labels do not appropriately encapsulate beliefs on abortion. Rather, contexts, circumstances, and lived experiences often shape views on abortion into more nuanced and complex perspectives. Qualitative data have also been shown to underpin belief systems regarding abortion. Social media, as a form of qualitative data, could reveal how attitudes toward abortion are communicated publicly in web-based spaces. Furthermore, in some cases, social media can also be leveraged to seek health information.

Objective: This study applies natural language processing and social media mining to analyze Reddit (Reddit, Inc) forums specific to abortion, including r/Abortion (the largest subreddit about abortion) and r/AbortionDebate (a subreddit designed to discuss and debate worldviews on abortion). Our analytical pipeline intends to identify potential themes within the data and the affect from each post.

Methods: We applied a neural network–based topic modeling pipeline (BERTopic) to uncover themes in the r/Abortion (n=2151) and r/AbortionDebate (n=2815) subreddits. After deriving the optimal number of topics per subreddit using an iterative coherence score calculation, we performed a sentiment analysis using the Valence Aware Dictionary and Sentiment Reasoner to assess positive, neutral, and negative affect and an emotion analysis using the Text2Emotion lexicon to identify potential emotionality per post. Differences in affect and emotion by subreddit were compared.

Results: The iterative coherence score calculation revealed 10 topics for both r/Abortion (coherence=0.42) and r/AbortionDebate (coherence=0.35). Topics in the r/Abortion subreddit primarily centered on information sharing or offering a source of social support; in contrast, topics in the r/AbortionDebate subreddit centered on contextualizing shifting or evolving views on abortion across various ethical, moral, and legal domains. The average compound Valence Aware Dictionary and Sentiment Reasoner scores for the r/Abortion and r/AbortionDebate subreddits were 0.01 (SD 0.44) and −0.06 (SD 0.41), respectively. Emotionality scores were consistent across the r/Abortion and r/AbortionDebate subreddits; however, r/Abortion had a marginally higher average fear score of 0.36 (SD 0.39).

Conclusions: Our findings suggest that people posting on abortion forums on Reddit are willing to share their beliefs, which manifested in diverse ways, such as sharing abortion stories including how their worldview changed, which critiques the value of dichotomized abortion identity labels, and information seeking. Notably, the style of discourse varied significantly by subreddit. r/Abortion was principally leveraged as an information and outreach source; r/AbortionDebate largely centered on debating across various legal, ethical, and moral abortion domains. Collectively, our findings suggest that abortion remains an opaque yet politically charged issue for people and that social media can be leveraged to understand views and circumstances surrounding abortion.

Introduction

Although the abortion debate is often framed along strict proabortion or antiabortion stances (eg, prochoice versus prolife—terms common in the United States, Ireland, and other English-speaking countries; pro-elección versus provida and pro-aborto versus anti-aborto —terms used in Mexico, Argentina, and other Spanish-speaking countries), actual abortion beliefs are complex, contextual, and at times contradictory [ 1 - 4 ]. Notably, despite media characterizations of these 2 oppositional perspectives—for people ascribing to either proabortion or prochoice labels (ie, broad abortion support) or antiabortion or prolife labels (ie, broad abortion opposition)—there exist circumstances in which people’s views diverge from the dichotomy [ 5 ]. These circumstances include, for example, the gestation period of pregnancy [ 6 ], the context for seeking abortion [ 7 ], and whether people consider abortion as a legal versus moral issue [ 8 ]. In addition, attitudes toward abortion also vary across some demographic characteristics such as age, educational attainment, political affiliation, and race or ethnicity of a person or groups of people participating in a survey [ 1 , 9 , 10 ].

Beyond context-specific or cultural considerations that may predict complex abortion views, personal accounts, narratives, and discussions about abortion may similarly reveal the extent to which abortion views depart from a support or opposition dichotomy, including extreme abortion circumstances or personal experience with an abortion. Evidence suggests that these considerations are not ethnocentric but shared globally. Research comparing abortion beliefs between English-speaking US residents and Spanish-speaking US residents of diverse nations of origin demonstrates that clear general differences exist in abortion beliefs. Following investigations of the abovementioned considerations, we suggest that further research may yield more precise insights into evolving views on abortion [ 11 ].

Contextual, contradictory, and, in some cases, changing beliefs on abortion make it difficult to accurately assess global and US abortion climates beyond rote and dichotomized categories [ 12 ]. However, evidence strongly suggests the US and global populations hold views that depart from these 2 categories, reflecting abortion attitude complexity [ 1 , 10 ]. Although survey data have quantitatively supported the idea of abortion attitude complexity—qualitative data, broadly defined as any type of open-ended text, audio, visual, or language data, may add additional nuance to suggest where and how complexity may emerge. For example, interviews about abortion reveal specific circumstances that contribute to variability in people’s views on abortion [ 4 ] or reveal how current events and news cycles, in turn, shape social beliefs and attitudes [ 13 ]. Qualitative data can also inform how people contextualize assistance-related resources such as those found on social media.

Social media posts, as a novel form of qualitative data, may similarly reveal how people view abortion and the associated complexity of belief systems at a population-level scale. Notably, the inescapable role of social media in the public lexicon has evolved over time into an outlet for community building and information dissemination that can connect users over shared interests disregarding location [ 14 ]. For example, the Pew Research Center contends that more than three-quarters of the US adult population regularly use at least 1 social media platform [ 15 ], and half of all the users have actively maintained at least 1 account for more than a decade. Because social media data are part of the public domain, longitudinal tracking of such data can represent an open-access running diary of thoughts, perspectives, and affective indicators—particularly for issues deemed controversial or contentious, including COVID-19 vaccination status, marriage equality, transgender sports bans, and abortion [ 16 , 17 ]. Furthermore, social media data are also global, implying that shared languages, regardless of geographic constraint, can contribute to discourses about abortion and associated beliefs therein.

Research has documented that people use social media to share their opinions and views and engage in debates on various topics, as well as to seek help and information and solicit personal advice that pertains to their situation or to something they are going through in life [ 18 - 20 ]. These web-based interactions vary widely across social media platforms and topics but may include discussions about substance use disorders [ 21 ], mental health [ 22 ], sexual assault [ 23 ], and managing HIV treatment [ 24 ], among a wide range of other topics. Furthermore, some more limited research has explored social media users’ engagement and interactions as part of sharing personal experiences, soliciting help, and requesting information pertaining to abortion. This research has focused particularly on assessing how social media users rely on each other to discuss cost-related barriers to abortion care [ 25 ], to discuss decision-making processes regarding abortion methods [ 26 ], and to seek support to make abortion decisions when they may lack familial and medical support otherwise [ 27 ].

Reddit (Reddit, Inc) is a social networking website, which is defined by its structure that allows users to subscribe to forums on diverse topics, both controversial and noncontroversial. Their approach to topic discussion is distinct from other social media platforms in that users can opt into conversations with variably different foci depending on needs and interests. For example, previous research has demonstrated that Reddit can serve as a social connection metric, information-sharing tool, and outreach resource [ 28 ] for controversial or contentious social topics, including sexual assault [ 29 ], abortion [ 30 ], and addiction and recovery [ 21 ]. For most, Reddit forums are a source of information on these topics. However, many of these same topics, particularly those with political contexts, can also be discussed on different Reddit forums in more social commentary or debate-style perspectives. Abortion is one example of a contentious social topic with ranging subreddits pertaining to different aspects of abortion, including as a social connection and information-sharing tool and debate platform.

Analyzing different facets of the same topic through various subreddits could yield nuanced aspects regarding crucial health topics unique from other quantitative and qualitative abortion research. Notably, as of December 2022, Reddit was the 20th most accessed website globally (sixth in the United States), and 50% of all Reddit users reside in the United States, with Canada, Australia, and the United Kingdom comprising approximately 20% of the total Reddit users. Reddit data can principally serve as a window into views on abortion in the United States; however, because not all English language data originate in the United States, it is also possible to observe abortion attitude complexity in a more Westernized, but global context or global reactions to news related to abortion in the United States.

Advances in computational data mining have made it feasible to extract, analyze, and interpret these data en masse. This study used natural language processing (NLP) and data mining methods to identify and visualize latent themes across 2 distinct subreddits specific to abortion: r/Abortion and r/AbortionDebate. As a comparative study, we aimed to compare the semantic and content differences across these subreddits to gain a comprehensive social media portrait of abortion dialogue on Reddit. This study was guided by three research questions:

  • What themes emerge in a corpus of Reddit posts in r/Abortion, the largest subreddit dedicated to abortion social support and outreach?
  • What themes emerge in a corpus of Reddit posts in r/AbortionDebate?
  • What do similarities and differences by subreddits implicate regarding social media–derived beliefs and ideologies on abortion?

Data for this study were collected over 5 months (ie, from January 2020 to May 2022) from the social networking website Reddit. Reddit represents an open network of communities where users can engage and connect with others over shared interests, hobbies, or personal experiences. Unlike other popular social media websites used for computational analyses, including X (X Corp, formerly known as Twitter), Reddit is unique in that users can create specific channels to form communities with other interested parties on diverse issues or topics. These channels, otherwise known as subreddits, comprise people with shared identities who find, subscribe to, and post within these channels. For instance, people interested in gaming can join the r/Gaming subreddit and people with depression can join the r/Depression subreddit.

We leveraged the PRAW (Python Reddit Application programming interface Wrapper) [ 31 ], a third-party application programming interface (API), to collect data for this study and specifically to isolate and download content posted into subreddits in English germane to abortion—we queried the API to allocate similar subreddits also spanning abortion-related topics. This query returned 1 additional subreddit: r/AbortionDebate. Given observable differences in framing (ie, people’s abortion experiences vs debates about abortion), we included this subreddit in our study as an additional but mutually distinct unit of analysis; that is, we collected and stored data for r/Abortion and r/AbortionDebate as separate corpora intended for separate analyses. All data collected for this study were in English, which we selected for 2 reasons: first, >70% of all Reddit users originated from English-speaking countries, and second, at the time of data collection, Reddit posts originating in languages other than English were insufficient for analysis. In Spanish, for example, r/Aborto contained only 5 members, with no activity since 2019; similarly, we observed <50 Spanish-language posts in either r/Abortion or r/AbortionDebate.

Once we identified our subreddits of interest, we queried the API to collect new posts and top posts from the r/Abortion and r/AbortionDebate subreddits. After filtering our data for duplicates and accounting for API data scraping limits, our final sample size comprised 4966 posts, divided into 2 corpora: 56.68% (2815/4966) of r/AbortionDebate posts and 43.31% (2151/4966) of r/Abortion posts.

We aimed to use NLP to identify salient categories in the r/Abortion and r/AbortionDebate subreddits. In numerous studies, latent Dirichlet allocation (LDA) topic models have been predominantly used for this purpose. LDA is a well-regarded unsupervised probabilistic model that evaluates word co-occurrence patterns using an iterative Gibbs sampling method [ 32 ]. Although LDA is often considered the gold standard within many academic and professional communities, advancements in NLP, artificial intelligence, and neural networks have introduced innovative topic modeling methods that can more closely approximate the potential meaning in these categories [ 33 ].

For this study, we applied one such advancement, the Bidirectional Encoder Representations from Transformers (BERT) topic modeling tool, BERTopic. BERTopic is an NLP topic modeling approach used to identify latent themes or topics within a collection of interrelated documents [ 34 ]. Unlike LDA, which uses probabilistic modeling to identify latent topics, BERTopic leverages pretrained embeddings from one of many transformer models, a type of neural network architecture in which an input sequence is compared against large-scale language models to calculate embeddings [ 35 ]. Embeddings are used to convert unstructured data, including words and sentences, into fixed-length continuous vectors. These vectors enable mathematical operations to capture semantic meanings, relationships, and other properties related to natural human language.

The vectors calculated using this approach tend to be highly dimensional and difficult to interpret. To reduce dimensionality while maintaining the integrity of our data, we applied a principal component analysis, which is commonly applied in NLP approaches for general dimensionality reduction purposes [ 36 ]. This analysis allowed us to extract and more easily interpret a range of possible clusters or topics in both the r/Abortion and r/AbortionDebate subreddit data. Once we reduced the dimensionality of our vectors, we applied a Hierarchical Density-Based Spatial Clustering of Applications with Noise to identify latent clusters or topics [ 37 ], CountVectorizer to tokenize each topic, and class term frequency–inverse document frequency to extract topic words for each cluster [ 38 ].

Furthermore, to gauge the emotional tone or mood represented in each post from the studied corpora, we applied a Valence Aware Dictionary and Sentiment Reasoner (VADER), a rule-based sentiment analysis tool [ 39 ], and Text2Emotion, a rule-based emotion analysis tool [ 40 ]. VADER sentiment analysis is an algorithm and analysis that examines the polarity of words within each social media post. Posts are fed through a lexicon or web-based dictionary, which is precoded with values for all positive and negative words in the English language. When posts are run through the VADER lexicon, they receive a composite score. Negative VADER values denote lower affect (ie, −0.99 to −0.01), and positive values denote higher affect (ie, 0.01 to 0.99). Although an older tool, VADER is commonly used to assess content affect and emotional affect. In contrast, the Text2Emotion tool for emotion analysis scans each entry for key phrases and terms denoting one of four base emotions: (1) happy, (2) surprise, (3) fear, and (4) sadness. Collectively, these 2 tools can identify potential tonal differences in each post, again implicating the different uses of each subreddit included in the analysis. Both tools have been applied extensively in computational public health studies owing to their ease of access, replicability, and numerous validation studies [ 16 , 21 , 41 , 42 ].

Our workflow is depicted in Figure 1 . First, we queried the Reddit API to archive top and new posts from the r/Abortion and r/AbortionDebate subreddits. Data collected from the r/Abortion and r/AbortionDebate subreddits were saved as separate data files. After removing duplicate and non-English posts in either data file, we applied standard preprocessing steps to remove parts of speech that would detract from the clarity of our models, including articles, prepositions, punctuation, abbreviations, and numbers [ 43 ]. Once the data were cleaned, we tokenized our data at the sentence level before calculating embeddings. Once the data were preprocessed and tokenized, we proceeded with our BERTopic pipeline. First, to calculate embeddings in our data we applied all-MiniLM-L6_v2 [ 44 ], a transformer-based model developed by Microsoft Corp. This model is designed to be a smaller and more efficient transformer model than larger models, including a generative pretrained transformer or T5, which may make it more appropriate for smaller data sets; however, more research is needed to confirm this notion. Once we calculated embeddings for all sentences in each corpus, we applied a principal component analysis to reduce dimensionality in our data, retaining 5 components. We then ran an iterative topic model ranging from 10 to 80 topics and calculated coherence scores [ 45 ] to identify an optimal number of topics, retaining a topic solution with the highest coherence score. For both r/Abortion and r/AbortionDebate, the optimal solution was 10 topics, yielding a respective coherence score of 0.42 and 0.35, which indicates a marginal fit. After we extracted key terms per topic, we applied a sorting function to examine key terms in each entry. Each entry was then classified into one of 10 possible topics in either corpus. We lastly performed a VADER sentiment analysis and Text2Emotion emotion analysis for each entry in both corpora.

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Ethical Considerations

This study involved a secondary analysis of deidentified and anonymized Reddit posts collected between January and May 2022. As this was an observational study with no contact between human subjects and no possible way to trace posts to any individual author, this study was exempt from Institutional Review Board review.

Our study applied computational tools to collect and analyze subreddits specific to abortion. We aimed to examine how abortion was discussed on the social media platform Reddit, both as an information-sharing tool and as a platform for debating worldviews.

What Themes Emerged in a Corpus of Reddit Posts About r/Abortion, the Largest Subreddit Dedicated to Abortion Social Support and Outreach?

Our coherence score analysis indicated a 10-topic solution for the r/Abortion subreddit. Table 1 outlines each topic by keywords, the number of sentences belonging to each topic, and the percentage of each topic relative to the larger corpus. Names for each topic were derived by reviewing a small excerpt of Reddit data that were sorted into one of 10 topics by a sorting function using keywords.

The r/Abortion subreddit analysis revealed numerous ways in which abortion was discussed in a social support context. The most prominent topic of our study, topic 1: sharing support , comprised the bulk of the conversation with >18% total representation. Social support was commonly manifested by people sharing their own experiences with abortion or by friends and family members who may have experienced abortion. This was further evident by multiple topics containing information-sharing content: abortion experience (topics 3, 7, and 10). Beyond social support, several of our topics also appeared to discuss abortion in a neutral and educational information-sharing context: general abortion (topic 5) and general pregnancy (topic 8).

Further review of the topics added context to our findings. Table 2 provides a summary of each topic and the key excerpts that denote additional meaning. As shown in Table 2 , there was little content indicative of debate or questioning one’s position on abortion. Instead, we observed personal experience sharing, including narrative accounts of one’s experience with abortion generally, miscarriage, and medication abortion specifically.

Perhaps one of the most recurring patterns in our data was frank discussions about postabortion feelings in a clinical setting, (“I felt so nauseous in that waiting room, I was not sure I could go through with it”), a postabortion setting (“It took me a few days to finally feel like myself again post-abortion”), or a medication abortion context (“The mifepristone caused some pretty intense clotting after I took the pill”). The medication abortion narratives were sometimes framed as someone explaining their decision (“I chose the pill because where I live you cannot have someone with you when getting an abortion due to COVID-19”).

What Themes Emerged in a Corpus of Reddit Posts in the r/AbortionDebate Subreddit?

Our coherence score analysis indicated a 10-topic solution for the r/AbortionDebate subreddit. Table 3 outlines each topic by keywords, the number of sentences belonging to each topic, and the percentage of each topic relative to the larger corpus. Names for each topic were derived by reviewing a small excerpt of Reddit data that was sorted into one of 10 topics by a sorting function based on keywords.

Unlike the r/Abortion subreddit, which we determined seemed to be used in a social support and information-sharing context, the r/AbortionDebate subreddit comprised conversations dedicated to critically assessing abortion from legal, moral, and ethical perspectives. The topic with the greatest representation was topic 1: Reddit forum rules and regulations . In topic 1, we observed several posts directly from moderators explicitly warning against outright attacks, misinformation, and vitriol targeted at people with opposing views on abortion; this topic was absent completely in the r/Abortion topic model. The second most prominent topic, topic 2: abortion morality , was centered on debating abortion from a moral perspective. The topic with the smallest representation was topic 5, pertaining to general pregnancy . At face value, we did not observe a great overlap in topic content in the r/AbortionDebate subreddit compared with the r/Abortion subreddit. However, we reviewed additional excerpts to ascribe a deeper meaning to these topics to examine precisely how abortion debates manifested on these forums.

Table 4 outlines additional information about each topic, including a summary and key excerpts that implicate deeper meaning. This additional analysis allowed us to examine more precise moral, legal, and ethical arguments pertaining to people’s expressed views on abortion.

For example, we observed that the abortion morality topic typically contained content related to drawing lines about abortion permissibility (“Where do [people] draw the line between acceptable and not acceptable”). This style of discussion was mirrored in conversations about fetal personhood (“Who here honestly believes a zygote is a person with rights?”) and the role spirituality plays in moral arguments about abortion (“But what do Catholics really think on this issue?”). Discussions and arguments about abortion morality were notably similar to the content in topic 3: abortion legality . Content on this topic typically discussed new abortion-related laws, the merits of those laws, and opinions about their relative effectiveness (“Texas passed a very restrictive law and it will serve as a benchmark for other states, watch”). Importantly, and across topics, we observed that people declared their abortion views (“I am pro-choice and I will always be”) and, in some cases, discussed how their abortion views evolved over time (“I am pro-life, but we should be discussing the merits of abortion as a life-saving tool here”). Here, we observed more opinions than the outright support articulated in the r/Abortion subreddit.

What Do Similarities and Differences by Subreddit Implicate About Social Media–Derived Abortion Beliefs and Ideologies?

Figure 2 visually represents data from each subreddit, where dense, overlapping clusters signify similar topics (or higher collinearity) and nonoverlapping circles indicate dissimilar topics (or lower collinearity).

In both the r/Abortion and r/AbortionDebate subreddits, the intertopic distance maps depict mutual exclusivity in general abortion and pregnancy topics, distinguished by basic sharing of language and specific information related to pregnancy and abortion (“Sometimes a pregnancy can end without warning or reason”; “abortion is a women’s health issue”). Beyond these statements, however, other conversations exhibit a richer and more nuanced discourse about abortion, overlapping between topics and offering deeper insights into an individual’s worldview on abortion, and portraying how various co-occurring factors influence one’s beliefs and worldviews (“Laws are one thing but have you considered the humanistic side of it all?”).

We used VADER and Text2Emotion tools to discern affective differences between r/Abortion and r/AbortionDebate subreddits. The r/Abortion subreddit displayed a compound VADER score of 0.10, reflecting overall neutral content, whereas the r/AbortionDebate subreddit displayed a score of −0.06, denoting neutral to slightly negative content. The emotion analysis findings for the r/Abortion subreddit were as follows: happy (mean 0.06, SD 0.19) , angry (mean 0.20, SD 0.31) , surprise (mean 0.12, SD 0.26) , sad (mean 0.20, SD 0.31) , and fear (mean 0.36, SD 0.39) . The emotion analysis findings for r/AbortionDebate subreddit were as follows: happy (mean 0.12, SD 0.27), angry (mean 0.05, SD 0.18), surprise (mean 0.11, SD 0.25), sad (mean 0.22, SD 0.35), fear (mean 0.28, SD 0.35).

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Furthermore, the Text2Emotion variable fear was prominent in r/Abortion, whereas happy was slightly more elevated in r/AbortionDebate. These observed differences are likely attributed to the differing nature and scope of the subreddits. For instance, the manifestation of fear may be more related to personal abortion narratives in r/Abortion, whereas happiness may arise from occasional friendly exchanges of views in r/AbortionDebate.

Despite their different foci, both subreddits contain myriad conversation topics, allowing for civil and enlightening discussions on evolving abortion views and ideologies. The discourse in these forums sometimes hints at the evolution of individual ideologies with time, reflecting the dynamic nature of personal beliefs and the influences shaping them (adapted excerpt: “I guess I just don’t know my views”; excerpt: “My opinion changed over time, growing up in a Christian household I was always against abortion...until I needed one myself”) . This phenomenon underscores the essential role of such platforms in fostering understanding and dialogue on the multifaceted issue of abortion.

Our study leveraged Reddit data as a novel, big data form of qualitative data to examine abortion discourse on r/Abortion and r/AbortionDebate subreddits. We observed several important themes, including evidence of complexity in abortion-related social media posts, which warrant further discussion.

The r/Abortion Subreddit as an Information-Seeking or Information-Sharing Platform for People With Questions About Their Abortion Experiences

Within the r/Abortion subreddit, we noticed posters using this platform to discuss abortion in diverse, sometimes overlapping contexts. However, each topic emerging from r/Abortion typically involved a degree of information sharing, whether through the provision of available resources or sharing personal narratives and experiences with abortion. We primarily observed these types of posts in topic 1: sharing support ; topic 2: postabortion emotions ; topics 3, 7, and 10: abortion experience ; and topic 5: clinical experience . The content within these topics typically involved direct sharing of one’s experiences related to abortion or posing highly specific questions about access (eg, excerpt: “Is abortion legal past 6 weeks gestation in Oklahoma?”) and medication abortion (eg, excerpt: “Abortion is legal here; can I get abortion pills by mail?”). Within the medication abortion topic, the content was both informative and supportive, with some posters sharing their experience in solidarity with others facing a similar choice. Notably, we did not observe any critiques against anyone’s abortion narratives; rather, the tone and structure, as also evident in this study’s VADER and emotion analysis, are largely informative and overall supportive of abortion. Given that the rules and guidelines established this subreddit as a place of nonconfrontational discussion, perhaps people advocating for other reproductive choices may have shared their perspectives in other subreddits, such as those related to adoption.

We acknowledge the possible connection between personal tendencies to share intimate information and the continually evolving role of the internet as a medium for social connection and information acquisition [ 46 ]. Notably, for the past 3 decades, the internet has become the most influential medium for information-seeking globally. The Pew Research Center indicates that approximately 80% of the adult population in the United States regularly use the internet to acquire general information or understand unfamiliar topics [ 47 ]. For example, an individual contemplating an abortion might opt to seek guidance in web-based forums to avoid potential ostracism from friends and family. Similarly, a friend or family member of someone considering an abortion might turn to web-based forums to secure advice or perspectives on assisting their loved one. Discourse on such platforms is crucial, especially when addressing sensitive topics that many may feel uneasy to discuss openly. This emphasizes the significance of the internet as a confidential and reliable resource for information and advice. Importantly, this also supports Reddit as a source of information for people needing abortion-related counseling.

These excerpts, and others in our composite sample, illustrate that social networking websites serve as a potentially crucial source of information for some [ 48 ], offering insights and details that may be otherwise unavailable, including local and state resources for abortion. This finding becomes particularly salient in light of the overturning of Roe v. Wade , which marked the end of federal protections for abortion until viability [ 49 ]. In the wake of this decision, 24 states enacted bans with limited exceptions or additional restrictions on abortion—generally earlier in terms of weeks of gestation than previously occurring under Roe v. Wade [ 50 ]. For those residing in states where abortion transitioned from being broadly legal to almost entirely illegal, web-based resources may have played a pivotal role during instances of unplanned pregnancy, as observed previously [ 51 ]. Further research is imperative to assess the efficacy of Reddit and other social networking sites in offering support and resources on this and other health-related topics. Notably, this subreddit contained little to no expression about personal abortion beliefs and ideologies.

The r/AbortionDebate Subreddit and Discussions of Abortion Identity and Changing Views Over Time

We did not observe much information or support sharing in the r/AbortionDebate subreddit. Rather, content in this subreddit discussed values and beliefs about abortion across many domains, including ethical, moral, legal, and humanistic. In several circumstances, we observed complex and nuanced abortion perspectives that do not correspond neatly to prochoice or prolife frameworks—2 commonly used but contested abortion identity labels used to outline personal abortion beliefs. For example, as many as half of the topics uncovered by r/AbortionDebate contained contradictory expressions regarding abortion and how the abortion debate was framed. These posts were broadly delineated as those deconstructing or debating prochoice and prolife movements and others explaining how circumstances contributed to moral and ethical shifts in abortion views, for example, in the following excerpts: “I was and will always be pro-choice, but my reaction was absolutely not [to abort a fetus with serious birth defects] even though I knew it was the right answer” and “I was pro-life and never thought I’d need Planned Parenthood until I did. My experience changed my opinion of them, but [I still wish] they didn’t primarily exist to perform abortions.” Here, the emphasis is far less on information or support sharing, rather the purpose is to articulate personal views about abortion and defend them accordingly. These findings align with ongoing abortion attitude research citing complex or nuanced abortion views that do not neatly fit into a singular label [ 52 - 54 ].

In addition to discussing and debating abortion values, we observed more combative content in the r/AbortionDebate subreddit. This is likely by design, namely to parse out people seeking information about abortion versus people looking to debate abortion [ 55 ]. Such differences between the r/Abortion and r/AbortionDebate subreddits were particularly evident in our sentiment and emotion analyses. For example, r/AbortionDebate yielded slightly more negative VADER affect scores and decreased emotion analysis scores for fear . We attributed more negative VADER scores to the often contentious exchanges among users (excerpt: “All these pro-choicers in here trying to lump as all as anti-women bigots”). We attributed lower fear scores to the apparent use of r/AbortionDebate as a forum to discuss abortion views and not for sharing information or narrative accounts about abortion. In other words, negative language was reflected via discourse in the r/AbortionDebate subreddit, as opposed to expressing personal fears or concerns about abortion, which may have surfaced more in the r/Abortion subreddit. In this context, the r/AbortionDebate subreddit may be more useful for mining insights into abortion ideologies, particularly when examining precise factors about abortion, including moral and legal arguments, gestational limits, and others. However, to gain insights into how abortion, as a medical procedure, is communicated from a decision-making perspective, r/Abortion may be more informative.

We identified 2 main implications from the content differences observed in r/Abortion and r/AbortionDebate. First, opting for the right Reddit forum is critically important. Reddit’s structure—where users select forums based on interests or needs—is different from other social networking sites. For people looking for ideally accurate, impartial information about abortion, r/Abortion or similar subreddits are suitable. Meanwhile, r/AbortionDebate is better for those wanting to discuss and ponder the ethical aspects of abortion. However, this choice is dependent on knowing how Reddit works. We project that a significant proportion of people may join the wrong forum and get exposed to unintended outcomes and viewpoints owing to a lack of preexisting knowledge about Reddit and its operations. Second, our observations support the idea that Reddit’s higher moderation levels make it a valuable tool for social science research. Historically, Reddit has carried the reputation of fostering trolls and hate speech. However, for health content, subreddits tend to be more effectively moderated by content experts. As evidenced in our data, both subreddits seemed relatively free from hate speech and trolling because of this moderation, which is unique to Reddit compared with other social media platforms. Therefore, Reddit remains a fairly reliable platform for both users and researchers, especially in the wake of recent changes in APIs and data access on other platforms, including X (X Corp, formerly known as Twitter).

Social Media as a Resource and Triangulation Tool to Support Ongoing Quantitative and Qualitative Research on Abortion

Our findings, particularly those critiquing abortion identity labels or people explaining their contextual abortion beliefs, support extant research demonstrating that people’s attitudes toward abortion are complex. Notably, this larger body of research argues that abortion attitudes are not unidimensional or polar but rather vary along legal, moral, social, and other similar domains [ 2 , 3 , 56 , 57 ]. This work is composed of both quantitative (surveys) and qualitative (interviews) data collections, which collectively yield deep insights into social attitude formation in the United States and how beliefs vary based on context and other dimensions. Consistent with these studies, our results support the notion that abortion attitudes and abortion decision-making are not unidimensional but involve multiple co-occurring considerations.

The novel nature of social media as data adds additional validity to previous abortion attitude research. This is particularly salient regarding how our findings triangulate or corroborate previous research on abortion attitude complexity. Notably, by mining Reddit abortion forums, we observed at least two principal uses of these forums: (1) as a space to share narratives and resources about abortion and (2) as a dedicated channel to debate abortion views. For many, Reddit forums could be a place where some people feel comfortable sharing or debating abortion views, although we acknowledge that more research on this area is needed. Furthermore, Reddit offers a somewhat anonymous space where people can gather the information they need about abortion or inform their perspectives on abortion. These shared Reddit perspectives, which are generally top of the mind, spontaneous, and unprompted [ 58 ], may provide a window into collective abortion beliefs that support or refute previous findings from other conventional forms of data collection. Similar uses of social media data, namely to corroborate findings on social issues, including gun control [ 59 ], marriage equality [ 60 ], and vaccination mandates [ 61 ], have been similarly leveraged. Therefore, we argue that social media can be a valuable source of data to help elucidate people’s opinions on relevant social issues.

Furthermore, we argue that national surveys, strategic qualitative interviews, and mass social media scrapes as data sources yield specific outcomes that, when combined, provide a robust and comprehensive portrait of social issues. Survey data, which are strengthened when participants are identified via probability-based sampling protocols [ 62 ], reveal nationwide associations between demographic variables and other variables of interest. Qualitative data can reveal insights into highly specific research questions, for example, whether changing auxiliary verbs leads to diverging responses about abortion beliefs [ 63 ]. Social media data scrapes can offer population-level insights that support or contradict findings from previous studies at the population-level scope and scale [ 41 ]. Our Reddit data support previous findings from surveys and qualitative research, demonstrating how social media data can serve as a triangulation tool. We contend that further strategic applications of social media mining with traditional quantitative and qualitative research can provide highly accurate portrayals of social views in the United States.

Limitations and Future Research

This study has several limitations that we hope to address in future research. First, although Reddit posts can be construed as qualitative data, we did not perform a formal qualitative analysis using these data. Owing to the scope of this study, we instead leveraged NLP algorithms to categorize and visualize all data simultaneously. In the future, researchers could perform detailed qualitative inquiries with these data, which can occur with the entire data set or among one or several clusters depending on the scope and research questions. Second, our study was limited to exploratory analyses. Although more refined algorithms could more effectively annotate and classify our data, we believed that these approaches would better serve as a follow-up to our exploratory approach to mining Reddit data. Future studies should consider using our data for more refined machine learning–driven or artificial intelligence-driven tasks. Finally, our study was limited by its relatively small timeframe (5 months). It is likely that collecting data for an even longer period may have yielded more nuanced findings.

Conclusions

With the decision in Dobbs v. Jackson Women’s Health Organization overturning Roe v. Wade , there is renewed attention to abortion as a contentious political and social issue. Despite abortion being an exceedingly complex topic, political debate and discussions about abortion are generally framed dichotomously as a support or opposition, or prolife or prochoice issue. However, extensive research indicates that public opinion about abortion does not ascribe neatly to that dichotomy and that circumstances beyond a person’s control may lead to shifts in views of abortion over time. Our research corroborates such findings that detail the myriad ways in which abortion attitudes are complex and contextual, beyond simple information-seeking. Furthermore, our findings provide evidence that social media data can be a helpful triangulation tool for public opinion survey research.

Data Availability

The data are currently stored in a secure GitHub repository and are available for further analysis upon request.

Conflicts of Interest

None declared.

  • Jozkowski KN, Crawford BL, Hunt ME. Complexity in attitudes toward abortion access: results from two studies. Sex Res Soc Policy. Mar 10, 2018;15(4):464-482. [ CrossRef ]
  • Jozkowski KN, Crawford BL, Turner RC, Lo WJ. Knowledge and sentiments of Roe v. Wade in the wake of justice Kavanaugh’s nomination to the U.S. Supreme Court. Sex Res Soc Policy. May 31, 2019;17(2):285-300. [ CrossRef ]
  • Jozkowski KN, Crawford BL, Willis M. Abortion complexity scores from 1972 to 2018: a cross-sectional time-series analysis using data from the general social survey. Sex Res Soc Policy. Mar 09, 2020;18(1):13-26. [ CrossRef ]
  • Maier JM, Jozkowski KN, Valdez D, Crawford BL, Turner RC, Lo WJ. Applicability of a salient belief elicitation to measure abortion beliefs. Am J Health Behav. Jan 01, 2021;45(1):81-94. [ CrossRef ] [ Medline ]
  • Hans JD, Kimberly C. Abortion attitudes in context: a multidimensional vignette approach. Soc Sci Res. Nov 2014;48:145-156. [ CrossRef ] [ Medline ]
  • Crawford BL, LaRoche KJ, Jozkowski KN. Examining abortion attitudes in the context of gestational age. Soc Sci Q. May 16, 2022;103(4):855-867. [ CrossRef ]
  • Smith TW. An evaluation of Spanish questions on the 2006 general social survey. NORC/University of Chicago. Mar 2007. URL: https:/​/gss.​norc.org/​Documents/​reports/​methodological-reports/​MR109%20An%20Evaluation%20of%20Spanish%​20Questions%20on%20the%202006%20General%20Social%20Survey.​pdf [accessed 2024-01-29]
  • Bowman K, Goldstein S. Attitudes about abortion: a comprehensive review of polls from the 1970s to today. American Enterprise Institute. Nov 2, 2021. URL: https:/​/www.​aei.org/​research-products/​report/​attitudes-about-abortion-a-​comprehensive-review-of-polls-from-the-1970s-to-today/​ [accessed 2022-07-21]
  • Doherty D. What can conjoint experiments tell us about Americans’ abortion attitudes? Am Politics Res. Jan 21, 2022;50(2):147-156. [ CrossRef ]
  • Jelen TG, Wilcox C. Causes and consequences of public attitudes toward abortion: a review and research agenda. Polit Res Q. Jul 02, 2016;56(4):489-500. [ CrossRef ]
  • Buyuker BE, LaRoche KJ, Bueno X, Jozkowski KN, Crawford BL, Turner RC, et al. A mixed-methods approach to understanding the disconnection between perceptions of abortion acceptability and support for Roe v. Wade among US adults. J Health Polit Policy Law. Aug 01, 2023;48(4):649-678. [ CrossRef ] [ Medline ]
  • Friedersdorf C. There are more than two sides to the abortion debate. The Atlantic. Dec 10, 2021. URL: https:/​/www.​theatlantic.com/​ideas/​archive/​2021/​12/​there-are-more-than-two-sides-to-the-abortion-debate/​620978/​ [accessed 2022-05-27]
  • Adamo C, Carpenter J. Sentiment and the belief in fake news during the 2020 presidential primaries. Oxf Open Econ. 2023;2:odad051. [ CrossRef ]
  • Milakovich ME, Wise JM. Internet technology as a global connector. In: Digital Learning. Cheltenham, UK. Edward Elgar Publishing; 2019. [ CrossRef ]
  • Perrin A. Social media usage: 2005-2015. Pew Research Center. Oct 8, 2015. URL: https://www.pewresearch.org/internet/2015/10/08/social-networking-usage-2005-2015/ [accessed 2024-01-29]
  • Bathina KC, Ten Thij M, Valdez D, Rutter LA, Bollen J. Declining well-being during the COVID-19 pandemic reveals US social inequities. PLoS One. Jul 8, 2021;16(7):e0254114. [ https://dx.plos.org/10.1371/journal.pone.0254114 ] [ CrossRef ] [ Medline ]
  • Zafarani R, Abbasi MA, Liu H. Social Media Mining: An Introduction. Cambridge, MA. Cambridge University Press; 2014. URL: http://www.socialmediamining.info/SMM.pdf
  • Jacques L, Valley T, Zhao S, Lands M, Rivera N, Higgins JA. "I'm going to be forced to have a baby": a study of COVID-19 abortion experiences on Reddit. Perspect Sex Reprod Health. Jun 11, 2023;55(2):86-93. [ CrossRef ] [ Medline ]
  • Priya S, Sequeira R, Chandra J, Dandapat SK. Where should one get news updates: Twitter or Reddit. Online Soc Netw Media. Jan 2019;9:17-29. [ CrossRef ]
  • Ong E, Davis L, Sanchez A, Stohl HE, Nelson AL, Robinson N. A review of women’s unanswered questions following miscarriage on different social media platforms [A207]. Obstet Gynecol. May 2022;139:60S. [ CrossRef ]
  • Valdez D, Patterson MS. Computational analyses identify addiction help-seeking behaviors on the social networking website Reddit: insights into online social interactions and addiction support communities. PLOS Digit Health. Nov 2022;1(11):e0000143. [ https://europepmc.org/abstract/MED/36812569 ] [ CrossRef ] [ Medline ]
  • Sit M, Elliott SA, Wright KS, Scott SD, Hartling L. Youth mental health help-seeking information needs and experiences: a thematic analysis of Reddit posts. Youth Soc. Oct 29, 2022;56(1):24-41. [ CrossRef ]
  • Abavi R, Branston A, Mason R, Du Mont J. An exploration of sexual assault survivors' discourse online on help-seeking. Violence Vict. Feb 03, 2020;35(1):126-140. [ CrossRef ]
  • Ayers JW, Zhu Z, Harrigian K, Wightman GP, Dredze M, Strathdee SA, et al. Managing HIV during the COVID-19 pandemic: a study of help-seeking behaviors on a social media forum. AIDS Behav. Jul 21, 2023 (forthcoming). [ CrossRef ] [ Medline ]
  • Higgins J, Lands M, Valley T, Carpenter E, Jacques L. Real-time effects of payer restrictions on reproductive healthcare: a qualitative analysis of cost-related barriers and their consequences among U.S. abortion seekers on Reddit. Int J Environ Res Public Health. Aug 26, 2021;18(17):9013. [ https://www.mdpi.com/resolver?pii=ijerph18179013 ] [ CrossRef ] [ Medline ]
  • Jacques L, Carpenter E, Valley T, Alvarez B, Higgins J. Medication or surgical abortion? An exploratory study of patient decision making on a popular social media platform. Am J Obstet Gynecol. Sep 2021;225(3):344-347. [ https://europepmc.org/abstract/MED/34022196 ] [ CrossRef ] [ Medline ]
  • Richards NK, Masud A, Arocha J. P28 Breaking down abortion barriers: Reddit users’ empowerment in absence of parental and medical support. Contraception. Oct 2020;102(4):286. [ CrossRef ]
  • Sawicki J, Ganzha M, Paprzycki M, Watanobe Y. Reddit CrosspostNet—studying Reddit communities with large-scale Crosspost graph networks. Algorithms. Sep 04, 2023;16(9):424. [ CrossRef ]
  • Lanthier S, Mason R, Logie CH, Myers T, Du Mont J. "Coming out of the closet about sexual assault": intersectional sexual assault stigma and (non) disclosure to formal support providers among survivors using Reddit. Soc Sci Med. Jul 2023;328:115978. [ CrossRef ] [ Medline ]
  • Richards NK, Masud A, Arocha JF. Online abortion empowerment in absence of parental and medical support: a thematic analysis of a reddit community’s contributions to decision-making and access. Research Square. Preprint posted online May 24, 2021. 2024 [ https://www.researchsquare.com/article/rs-523420/v1 ]
  • Madan P. Web scraping Reddit with python: a complete guide with code. GoLogin. Mar 23, 2023. URL: https://gologin.com/blog/web-scraping-reddit [accessed 2023-09-26]
  • Blei DM, Ng AY, Jordan MI. Latent dirichlet allocation. J Mach Learn Res. 2003;3:993-1022. [ CrossRef ]
  • Resnik P, Armstrong W, Claudino L, Nguyen T, Nguyen VA, Boyd-Graber J. Beyond LDA: exploring supervised topic modeling for depression-related language in Twitter. In: Proceedings of the 2nd Workshop on Computational Linguistics and Clinical Psychology: From Linguistic Signal to Clinical Reality. Presented at: 2nd Workshop on Computational Linguistics and Clinical Psychology: From Linguistic Signal to Clinical Reality; June 5, 2015, 2015; Denver, CO. [ CrossRef ]
  • Egger R, Yu J. A topic modeling comparison between LDA, NMF, Top2Vec, and BERTopic to demystify Twitter posts. Front Sociol. May 6, 2022;7:886498. [ https://europepmc.org/abstract/MED/35602001 ] [ CrossRef ] [ Medline ]
  • Wolf T, Debut L, Sanh V, Chaumond J, Delangue C, Moi A, et al. Transformers: state-of-the-art natural language processing. In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations. Presented at: 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations; November 16-20, 2020, 2020; Online. [ CrossRef ]
  • Drikvandi R, Lawal O. Sparse principal component analysis for natural language processing. Ann Data Sci. May 18, 2020;10(1):25-41. [ CrossRef ]
  • Stewart  G, Al-Khassaweneh M. An implementation of the HDBSCAN* clustering algorithm. Appl Sci. Feb 25, 2022;12(5):2405. [ CrossRef ]
  • Kim SW, Gil JM. Research paper classification systems based on TF-IDF and LDA schemes. Hum Cent Comput Inf Sci. Aug 26, 2019;9:30. [ CrossRef ]
  • Hutto C, Gilbert E. VADER: a parsimonious rule-based model for sentiment analysis of social media text. Proc Int AAAI Conf Web Soc Media. May 16, 2014;8(1):216-225. [ https://ojs.aaai.org/index.php/ICWSM/article/view/14550 ] [ CrossRef ]
  • Aslam N, Rustam F, Lee E, Washington PB, Ashraf I. Sentiment analysis and emotion detection on cryptocurrency related tweets using ensemble LSTM-GRU model. IEEE Access. 2022;10:39313-39324. [ https://ieeexplore.ieee.org/abstract/document/9751065/ ] [ CrossRef ]
  • Valdez D, Ten Thij M, Bathina K, Rutter LA, Bollen J. Social media insights into US mental health during the COVID-19 pandemic: longitudinal analysis of Twitter data. J Med Internet Res. Dec 14, 2020;22(12):e21418. [ https://www.jmir.org/2020/12/e21418/ ] [ CrossRef ] [ Medline ]
  • Adarsh R, Patil A, Rayar S, Veena KM. Comparison of VADER and LSTM for sentiment analysis. Int J Recent Technol Eng. Mar 2019;7(6):543. [ https://www.ijrte.org/wp-content/uploads/papers/v7i6s/F03040376S19.pdf ]
  • Nesca M, Katz A, Leung C, Lix L. A scoping review of preprocessing methods for unstructured text data to assess data quality. Int J Popul Data Sci. 2022;7(1) [ CrossRef ]
  • Hertling S, Portisch J, Paulheim H. KERMIT -- a transformer-based approach for knowledge graph matching. arXiv. Preprint posted online April 29, 2022. 2024 [ https://arxiv.org/abs/2204.13931 ] [ CrossRef ]
  • O’Callaghan D, Greene D, Carthy J, Cunningham P. An analysis of the coherence of descriptors in topic modeling. Expert Syst Appl. Aug 2015;42(13):5645-5657. [ CrossRef ]
  • Szymkowiak A, Melović B, Dabić M, Jeganathan K, Kundi GS. Information technology and Gen Z: the role of teachers, the internet, and technology in the education of young people. Technol Soc. May 2021;65:101565. [ CrossRef ]
  • Auxier B, Anderson M. Social media use in 2021. Pew Research Center. Apr 7, 2021. URL: https://www.pewresearch.org/internet/2021/04/07/social-media-use-in-2021/ [accessed 2023-03-20]
  • Frey E, Bonfiglioli C, Brunner M, Frawley J. Parents' use of social media as a health information source for their children: a scoping review. Acad Pediatr. May 2022;22(4):526-539. [ https://linkinghub.elsevier.com/retrieve/pii/S1876-2859(21)00621-5 ] [ CrossRef ] [ Medline ]
  • Crawford BL, Simmons MK, Turner RC, Lo WJ, Jozkowski KN. Perceptions of abortion access across the United States prior to the Dobbs v. Jackson Women's Health Organization decision: results from a national survey. Perspect Sex Reprod Health. Sep 20, 2023;55(3):153-164. [ CrossRef ] [ Medline ]
  • Tracking abortion bans across the country. The New York Times. URL: https://www.nytimes.com/interactive/2022/us/abortion-laws-roe-v-wade.html [accessed 2023-09-26]
  • Reis BY, Brownstein JS. Measuring the impact of health policies using internet search patterns: the case of abortion. BMC Public Health. Aug 25, 2010;10:514. [ https://bmcpublichealth.biomedcentral.com/articles/10.1186/1471-2458-10-514 ] [ CrossRef ] [ Medline ]
  • Kim T, Steinberg JR. Individual changes in abortion knowledge and attitudes. Soc Sci Med. Mar 2023;320:115722. [ CrossRef ] [ Medline ]
  • Bueno X, Asamoah NA, LaRoche KJ, Dennis B, Crawford BL, Turner RC, et al. People's perception of changes in their abortion attitudes over the life course: a mixed methods approach. Adv Life Course Res. Sep 2023;57:100558. [ CrossRef ] [ Medline ]
  • Jozkowski KN, Mena-Meléndez L, Crawford BL, Turner RC. Abortion stigma: attitudes toward abortion responsibility, illegal abortion, and perceived punishments of “illegal abortion”. Psychol Women Q. Jul 04, 2023;47(4):443-461. [ CrossRef ]
  • Shen Q, Rosé CP. A tale of two subreddits: measuring the impacts of quarantines on political engagement on Reddit. Proc IntAAAI Conf Web Soc Media. May 31, 2022;16(1):932-943. [ CrossRef ]
  • Crawford BL, Jozkowski KN, Turner RC, Lo WJ. Examining the relationship between Roe v. Wade knowledge and sentiment across political party and abortion identity. Sex Res Soc Policy. May 28, 2021;19(3):837-848. [ CrossRef ]
  • LaRoche KJ, Jozkowski KN, Crawford BL, Haus KR. Attitudes of US adults toward using telemedicine to prescribe medication abortion during COVID-19: a mixed methods study. Contraception. Jul 2021;104(1):104-110. [ https://europepmc.org/abstract/MED/33848466 ] [ CrossRef ] [ Medline ]
  • Kulkarni V, Kern ML, Stillwell D, Kosinski M, Matz S, Ungar L, et al. Latent human traits in the language of social media: an open-vocabulary approach. PLoS One. Nov 28, 2018;13(11):e0201703. [ https://dx.plos.org/10.1371/journal.pone.0201703 ] [ CrossRef ] [ Medline ]
  • Dowler K. Media influence on attitudes toward guns and gun control. Am J Crim Just. Mar 2002;26(2):235-247. [ CrossRef ]
  • O'Connor C. 'Appeals to nature' in marriage equality debates: a content analysis of newspaper and social media discourse. Br J Soc Psychol. Sep 27, 2017;56(3):493-514. [ CrossRef ] [ Medline ]
  • Chen L, Ling Q, Cao T, Han K. Mislabeled, fragmented, and conspiracy-driven: a content analysis of the social media discourse about the HPV vaccine in China. Asian J Commun. Sep 08, 2020;30(6):450-469. [ CrossRef ]
  • Catania JA, Dolcini MM, Orellana R, Narayanan V. Nonprobability and probability-based sampling strategies in sexual science. J Sex Res. 2015;52(4):396-411. [ CrossRef ] [ Medline ]
  • Maier JM, Jozkowski KN, Montenegro MS, Willis M, Turner RC, Crawford BL, et al. Examining auxiliary verbs in a salient belief elicitation. Health Behav Policy Rev. Jul 2021;8(4):374-393. [ CrossRef ]

Abbreviations

Edited by A Mavragani; submitted 18.03.23; peer-reviewed by L Jacques, T Zhang; comments to author 27.07.23; revised version received 27.09.23; accepted 20.12.23; published 14.02.24

©Danny Valdez, Lucrecia Mena-Meléndez, Brandon L Crawford, Kristen N Jozkowski. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 14.02.2024.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.

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  1. Figure and Table Lists

    Example of a list of tables and figures Additional lists to consider In addition to your list of tables and figures, there are a few other lists to consider for your thesis or dissertation. They can be placed in the following order:

  2. Tables in Research Paper

    Definition: In Research Papers, Tables are a way of presenting data and information in a structured format. Tables can be used to summarize large amounts of data or to highlight important findings. They are often used in scientific or technical papers to display experimental results, statistical analyses, or other quantitative information.

  3. List of Tables, List of Figures

    List of Tables, List of Figures If even one numbered table or figure appears in your manuscript, then a List of Tables and/or a List of Figures must be included in your manuscript following the Table of Contents. If both are used, arrange the List of Tables before the List of Figures.

  4. List of Figures and Tables in a Dissertation

    "List of tables and figures is a list containing all the tables and figures that you have used in your dissertation paper. Typically, dissertations don't have many tables and figures unless the research involved is too deep and lengthy."

  5. APA Format for Tables and Figures

    An example of a table formatted according to APA guidelines is shown below. The table above uses only four lines: Those at the top and bottom, and those separating the main data from the column heads and the totals. Create your tables using the tools built into your word processor. In Word, you can use the " Insert table " tool.

  6. Figure & Table Lists

    Dissertation Figure & Table Lists | Word Instructions, Template & Examples Published on 24 May 2022 by Tegan George . Revised on 25 October 2022. A list of figures and tables compiles all of the figures and tables that you used in your thesis or dissertation, along with their corresponding page numbers.

  7. Sample tables

    Sample Tables These sample tables illustrate how to set up tables in APA Style. When possible, use a canonical, or standard, format for a table rather than inventing your own format. The use of standard formats helps readers know where to look for information.

  8. APA Tables and Figures

    Note: This page reflects the latest version of the APA Publication Manual (i.e., APA 7), which released in October 2019. The equivalent resources for the older APA 6 style can be found at this page as well as at this page (our old resources covered the material on this page on two separate pages). The purpose of tables and figures in documents is to enhance your readers' understanding of the ...

  9. List Of Figures And Tables For Your Dissertation

    The list of figures and tables in a research paper, thesis, or dissertation provides a structured overview of graphic elements included in the paper. This list guides readers to find specific graphs, images, tables, or charts effortlessly.

  10. 10.5 List of figures and tables

    Strictly speaking, figures are illustrations, drawings, photographs, graphs, and charts. Tables are rows and columns of words and numbers; they are not considered figures. For longer reports that contain dozens of figures and tables each, create separate lists of figures and tables.

  11. Tables in your dissertation

    Step 1. Decide where to insert a table Step 2. Create your table Example of a table in APA Style Step 3. Assign your table a number and title Step 4. Clarify your table with a note (optional) Step 5. Cite the table within the text Step 1. Decide where to insert a table Where should you add a table?

  12. Tips on effective use of tables and figures in research papers

    Finally, follow the best-practice guidelines outlined in section 3 and review the examples presented in section 4 of this paper to ensure that your tables and figures are well-designed. Table 1: How to choose between tables, figures, and text to present data. Best practices for presentation of tables and figures in scientific papers General ...

  13. How to Write the List of Figures for a Thesis or Dissertation

    Write your list of figures and list of tables immediately after your list of contents. Unless specifically asked by a journal, you should not include a separate list of figures in a manuscript for peer-review. Important Points to Remember

  14. Effective Use of Tables and Figures in Research Papers

    By Enago Academy Dec 4, 2023 3 mins read 🔊 Listen Research papers are often based on copious amounts of data that can be summarized and easily read through tables and graphs. When writing a research paper, it is important for data to be presented to the reader in a visually appealing way.

  15. PDF Student Paper Setup Guide, APA Style 7th Edition

    Indent the first line of every paragraph of text 0.5 in. using the tab key or the paragraph-formatting function of your word-processing program. Page numbers: Put a page number in the top right corner of every page, including the title page or cover page, which is page 1. Student papers do not require a running head on any page.

  16. List of Tables

    Type Page (#), tab once, type Table 1: Title of Table One. If your page number is a single digit, you will need to tab twice so that all table names are aligned. List each table on a new line. If your title is so long it goes onto another line, indent that line to match where all table names start. If you have tables in the appendix, be sure to ...

  17. How to clearly articulate results and construct tables and figures in a

    It will be appropriate to indicate other demographic numerical details in tables or figures. As an example elucidating the abovementioned topics a research paper written by the authors of this review article, and published in the Turkish Journal of Urology in the year 2007 (Türk Üroloji Dergisi 2007;33:18-23) is presented below:

  18. Getting started with tables

    Tables are often overlooked by many readers of papers who tend to focus on the text. Good tables tell much of the story of a paper and give a richer insight into the details of the study participants and the main research findings. Being confident in reading tables and constructing clear tables are important skills for researchers to master.

  19. Five tips for developing useful literature summary tables for writing

    Literature reviews offer a critical synthesis of empirical and theoretical literature to assess the strength of evidence, develop guidelines for practice and policymaking, and identify areas for future research.1 It is often essential and usually the first task in any research endeavour, particularly in masters or doctoral level education. For effective data extraction and rigorous synthesis ...

  20. Figures in Research Paper

    Some common purposes of figures in research papers are: To summarize data: Figures can be used to present data in a concise and easy-to-understand manner. For example, graphs can be used to show trends or patterns in data, while tables can be used to summarize numerical information. To support arguments: Figures can be used to support arguments ...

  21. Table of Contents for Dissertation/ Research Paper & Example

    Our paper writers designed a sample table of contents to illustrate the best practices and various styles in formatting the work. Check our samples to find advanced options for organizing your own list. Example of Table of Contents in Research Paper. As you can see, this contents page includes sections with different levels.

  22. Evaluating the impact of the supporting the advancement of research

    Quantitative findings Attendance. Over the 12-month evaluation period, a total of 18 half-day workshops were delivered, six from the research in clinical practice pathway; four from the research delivery pathway; eight from the research leader pathway (refer to Fig. 1); and 11 seminars to support the development of key skills.In total, 165 (2% of total staff at MPFT) staff members booked one ...

  23. What is a list of figures and tables?

    All level 1 and 2 headings should be included in your table of contents. That means the titles of your chapters and the main sections within them. The contents should also include all appendices and the lists of tables and figures, if applicable, as well as your reference list. Do not include the acknowledgements or abstract in the table of ...

  24. Getting started with tables

    Background Tables are often overlooked by many readers of papers who tend to focus on the text. Good tables tell much of the story of a paper and give a richer insight into the details of the study participants and the main research findings. Being confident in reading tables and constructing clear tables are important skills for researchers to master. Method Common forms of tables were ...

  25. Journal of Medical Internet Research

    Background: Evidence supports the effectiveness of serious games in health education, but little is known about their effects on the psychosocial well-being of children in the general population. Objective: This study aimed to investigate the potential of a mobile game-based safety education program in improving children's safety and psychosocial outcomes.

  26. Journal of Medical Internet Research

    Background: Attitudes toward abortion have historically been characterized via dichotomized labels, yet research suggests that these labels do not appropriately encapsulate beliefs on abortion. Rather, contexts, circumstances, and lived experiences often shape views on abortion into more nuanced and complex perspectives. Qualitative data have also been shown to underpin belief systems ...

  27. Federalist Papers: Primary Documents in American History

    The Federalist, commonly referred to as the Federalist Papers, is a series of 85 essays written by Alexander Hamilton, John Jay, and James Madison between October 1787 and May 1788.The essays were published anonymously, under the pen name "Publius," in various New York state newspapers of the time. The Federalist Papers were written and published to urge New Yorkers to ratify the proposed ...

  28. CBSE Class 10 Practice Papers with Solutions for Board Exam 2024: Best

    The subject-wise practice papers are prepared based on the latest CBSE Class 10 Syllabus. They cover the key concepts and topics carrying high weightage for the board exam. Solutions have been ...