Nontabular Material - Tables, Figures, and Multimedia

AMA Manual of Style - Stacy L. Christiansen, Cheryl Iverson 2020

Nontabular Material
Tables, Figures, and Multimedia

Nontabular material does not contain cells of individual data. Usually it is set off from the text by a box, rules, shading, or other elements. Sometimes the box or sidebar is cited in the text (following the citation rules for tables) and other times it is not. Any references that appear in nontabular material should also appear in the reference list and be numbered in order of their appearance (see, Tables, Figures, and Multimedia, Tables, Table Components, Footnotes).

4.3.1 Boxes.

A textual table or box contains words, phrases, or sentences, often in list form. Boxes are used to emphasize key points, summarize information, and/or reduce the narrative text (Box 4.3-1).

Box 4.3-1. Box or Textual Table of Content Set Off From the Text Box 2. Features of Irritable Bowel Syndrome

Typical features

Loose/frequent stools



Abdominal cramping

Abdominal discomfort

Symptom brought on by food intake/specific food sensitivities

Symptoms dynamic over time (change in pain location, change in stool pattern)

Concerning features for organic disease

Symptom onset after age 50 y

Severe or progressively worsening symptoms

Unexplained weight loss

Nocturnal diarrhea

Family history of organic gastroenterological diseases, including colon cancer, celiac disease, or inflammatory bowel disease

Rectal bleeding or melena

Unexplained iron-deficiency anemia

In this example, the box provides information in a list-type format, which allows for easier reading than the same content in prose form.

4.3.2 Sidebars.

Sidebars typically contain supplementary information, including related topics or lists of sources for further reading (Box 4.3-2 and Box 4.3-3). They are often not called out in the text (eg, “Box 1”) but instead are placed within the article in a logical place for best comprehension.

Box 4.3-2. Sidebar From a News Story on Antibiotic-Resistant Bacteria

Antibiotic-Resistant Bacteria Posing the Greatest Threats

At least 2 million people each year become infected with bacteria that are resistant to antibiotics, and at least 23 000 people die as a direct result. Additional patients die of conditions complicated by antibiotic-resistant infection, according to a 2013 report from the Centers for Disease Control and Prevention (CDC).

The CDC report classifies Clostridioides difficile (formerly Clostridium difficile), carbapenem-resistant Enterobacteriaceae, and drug-resistant Neisseria gonorrhoeae as urgent threats. Methicillin-resistant Staphylococcus aureus, vancomycin-resistant Enterococcus, and 10 others are classified as serious threats. Vancomycin-resistant S aureus, erythromycin-resistant Group A Streptococcus, and clindamycin-resistant Group B Streptococcus are concerning threats.

Box 4.3-3. Sidebar of Sources for Further Reading

Related guidelines and other resources

Chaikof EL, Brewster DC, Dalman RL, et al. The care of patients with abdominal aortic aneurysm: the Society for Vascular Surgery practice guidelines. J Vasc Surg. 2009;50:S2-S49

Mastracci TM, Cinà CS. Screening for abdominal aortic aneurysm in Canada: review and position statement of the Canadian Society for Vascular Surgery. J Vasc Surg. 2007;45(6):1268-1276

Moll FL, Powell JT, Fraedrich G, et al. Management of abdominal aortic aneurysms: clinical practice guidelines of the European Society for Vascular Surgery. Eur J Vasc Endovasc Surg. 2011;41(suppl 1):S1-S58

Principal Authors: Stacy Christiansen, MA, and Connie Manno, ELS


Thanks to the following for reviewing this chapter and providing important comments: Hope Lafferty, AM, ELS, Hope Lafferty Communications, Marfa, Texas; Trevor Lane, MA, DPhil, Edanz Group, Fukuoka, Japan; Thomas A. Lang, MA, Tom Lang Communications, Kirkland, Washington; Chris Meyer, JAMA Network; Joseph Clayton Mills, MA, Neuroscience Publications, Barrow Neurological Institute, Phoenix, Arizona; David Schriger, MD, MPH, JAMA, and David Geffen School of Medicine at UCLA, Los Angeles, California.


1.Lang T. How to Report Statistics in Medicine: Annotated Guidelines for Authors, Editors, and Reviewers. 2nd ed. American College of Physicians; 2006.

2.Geller SE, Adams MG, Carnes M. Adherence to federal guidelines for reporting of sex and race/ethnicity in clinical trials. J Womens Health (Larchmt). 2006;15(10):1123-1131. doi:10.1089/jwh.2006.15.1123

3.The Chicago Manual of Style. 17th ed. University of Chicago Press; 2017.

4.Council of Science Editors. Scientific Style and Format: The CSE Manual for Authors, Editors, and Publishers. 8th ed. University of Chicago Press/Council of Science Editors; 2014.

5.Recommended Practices for Online Supplemental Journal Article Materials. National Information Standards Organization; 2013. NISO RP-15-2013. Accessed June 20, 2019.

6.Best Practices for Publishing Journal Articles. NFAIS website. Approved February 13, 2009. Accessed October 1, 2019.

7.Kosslyn SM. Clear and to the Point. Oxford University Press; 2007.

8.Customize x-axis and y-axis properties. Microsoft Power BI website. Published January 20, 2018. Accessed May 23, 2018.

9.Sullivan L. Survival analysis. Updated June 3, 2016. Accessed June 6, 2018.

10.Clark TG, Bradburn MJ, Love SB, Altman DG. Survival analysis, part I: basic concepts and first analyses. Br J Cancer. 2003;89(2):232-238. doi:10.1038/sj.bjc.6601118

11.Pocock SJ, Clayton TC, Altman DG. Survival plots of time-to-event outcomes in clinical trials: good practice and pitfalls. Lancet. 2002;359(9318):1686-1689.

12.Year 10 interactive maths—second edition: scatterplots. G S Rehill’s Interactive Maths Series website. Accessed May 22, 2018.

13.Haighton J, Haworth A, Wake G. AS Use of Maths—Statistics: Using and Applying Statistics. Nelson Thornes Ltd; 2003:74-76.

14.Peterson SM. CSE GuideLines: Editing Science Graphs. Council of Science Editors; 2000.

15.Tufte ER. The Visual Display of Quantitative Information. 2nd ed. Graphics Press; 2001.

16.Schriger DL, Cooper RJ. Achieving graphical excellence: suggestions and methods for creating high-quality visual displays of experimental data. Ann Emerg Med. 2001;37(1):75-87.

17.Hedeker D. Longitudinal data analysis, including categorical outcomes. Accessed February 12, 2018.

18.Wicklin R. Create spaghetti plots in SAS. Published June 2, 2016. Accessed June 1, 2018.

19.Schriger DL. Graphic portrayal of studies with paired data: a tutorial. Ann Emerg Med. 2018;71(2):239-246. doi:10.1016/j.annemergmed.2017.05.033

20.Schriger DL, Altman DG, Vetter JA, Heafner T, Moher D. Forest plots in reports of systematic reviews: a cross-sectional study reviewing current practice. Int J Epidemiol. 2010;39(2):421-429. doi:10.1093/ije/dyp370

21.Lewis S, Clarke M. Forest plots: trying to see the wood and the trees. BMJ. 2001;322(7300):1479-1480.

22.Sedgwick P. Meta-analyses: how to read a funnel plot. BMJ. 2013;346-f1342. doi:10.1136/bmj.f1342

23.Egger M, Davey Smith G, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical test. BMJ. 1997;315:629. doi:10.1136/bmj.315.7109.6290

24.Equator Network. Accessed June 20, 2019.

25.Ofori-Asenso R, Agyeman AA. Understanding cross over and parallel group studies in drug research. Precis Med. 2015;2:e1046. doi:10.14800/pm.1046

26.Sox HC, Higgins MC, Owens DK. Medical Decision Making. 2nd ed. Wiley-Blackwell; 2013.

27.Hadorn DC. Use of algorithms in clinical guideline development. In: Clinical Practice Guideline Development: Methodology Perspectives. US Agency for Health Care Policy and Research; 1994:93-104.

28.Bennett RL. Appendix A.1: handy reference tables of pedigree nomenclature. In: The Practical Guide to the Genetic Family History. 2nd ed. John Wiley & Sons Inc; 2010:287-289.

29.Wilkinson L, Friendly M. The history of the cluster heat map. Am Stat. 2009;63(2):179-184. doi:10.1198/tas.2009.0033

30.Kaufman L, Rousseeuw PJ. Finding Groups in Data: An Introduction to Cluster Analysis. John Wiley & Sons Inc; 2005.

31.Grant GR, Manduchi E, Stoeckert CJ. Analysis and management of microarray gene expression data. Curr Protoc Mol Biol. 2007;77:chap 19:unit 19.6. doi:10.1002/0471142727.mb1906s77

32.Keast R. How to Measure Progress & Impact: Network Mapping. Presented at: Collective Impact 2014; February 12, 2014; Melbourne, Australia. Accessed May 24, 2018.

33.Pearson H. Image manipulation: CSI: cell biology. Nature. 2005;434(7036):952-953. doi:10.1038/434952a

34.Science instructions: preparing your manuscript and figures. Accessed October 1, 2019.

35.Scientific Illustration Committee of the Council of Biology Editors. Illustrating Science: Standards for Publication. Council of Biology Editors; 1988.

36.Cleveland WS. The Elements of Graphing Data. Rev ed. Hobart Press; 1994.

37.Singer PA, Feinstein AR. Graphical display of categorical data. J Clin Epidemiol. 1993;46(3):231-236. doi:10.1016/0895-4356(93)90070-H

38.Figures. Instructions for Authors. JAMA website. Accessed January 29, 2019.

39.Video. Instructions for Authors. JAMA website. Accessed February 5, 2019.