Visualizing medicine: The case for implementing graphical abstracts in clinical reporting

Table 1 Comparison of graphical abstract creation tools

Software	Free version	Paid pricing	Ease of use	Scientific focus	Key strengths	Key limitations
Canva	Yes	$12.99/month (Pro)	Very easy	No	Large template library, beginner-friendly	Lacks scientific icons, watermark on free plan
BioRender	Yes	$9/month (Academic Basic), $35/month (premium)	Easy	Yes	Extensive scientific icon library, designed for life sciences	Watermark in free version, limited export
Inkscape	Yes	Free	Moderate	No	Powerful vector design tool, open-source	Steeper learning curve, no scientific templates
Adobe Illustrator	No	$20.99/month (Academic)	Difficult	No	Professional-quality designs, unmatched customization	Expensive, requires design experience
Microsoft PowerPoint	No	Part of Office 365 ($69.99/year)	Very easy	No	Widely used, familiar interface	Limited graphic design capabilities
Mind the Graph	Yes	Starts at $5/month	Easy	Yes	Affordable, designed for researchers	Limited icon library compared to BioRender
GIMP	Yes	Free	Difficult	No	Free, full-featured image editor	More suited for image editing than vector-based abstracts
Smart Servier Medical Art	Yes	Free	Very easy	Yes	Free, high-quality medical and biological illustrations	Limited customization options

Table 2 Challenges and recommendations for graphical abstracts

Challenge	Description	Consequences	Recommendation
Risk of oversimplification	Simplifying complex data may omit important details, such as variability and methodological context	Leads to misinterpretation or misconceptions about the research findings	Balance clarity and completeness; ensure crucial points like statistical variability are included
Skill gap in graphic design	Researchers often lack necessary skills in visual hierarchy, data representation, and design software	Poorly designed abstracts diminish the clarity and impact of the research	Provide targeted training in design software (e.g., Adobe Illustrator, BioRender) and basic design principles through online courses or workshops
Lack of standardized guidelines	No universal standards for GAs exist, leading to inconsistencies in format and content across journals	Inconsistent formatting complicates peer review and interpretation, affecting reproducibility	Develop universal guidelines with input from researchers and designers, covering balance of text and imagery, and necessary methodological details
Complexity of visual data representation	Visualizing certain data types (e.g., statistical results, methodological details) can be difficult without loss of context	Inappropriate visual choices may obscure key findings, confusing readers	Provide journals with examples of best practices for different types of data and create discipline-specific templates for GAs
Time and resource constraints	Creating high-quality GAs can be time-consuming and may require resources not available to all researchers	Researchers might rush through or avoid creating GAs, reducing their potential benefits	Journals could offer simplified design tools and templates, while institutions provide resources or personnel trained in graphic design to assist researchers
Subjectivity in visual design	Lack of clear guidelines can lead to subjective design choices that are inconsistent between researchers or disciplines	Reduces clarity and uniformity, complicating interpretation across publications	Journals should include specific visual design elements (font types, color palettes) in their guidelines to ensure uniformity

GA: Graphical abstract.