# Visualization of Age Distributions as Elements of Medical Data-Stories

arXiv: https://arxiv.org/abs/2409.17854 · HTML: https://mlsanity.com/paper/2409.17854/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 2 of its 63 references that are in the map.
- First posted on arXiv 26 Sep 2024.

## Builds on (most cited first, 2 of 2)

- [Towards Understanding How Readers Integrate Charts and Captions: A Case Study with Line Charts](https://mlsanity.com/paper/2101.08235/) (2021)
- [Narrative Visualization to Communicate Neurological Diseases](https://mlsanity.com/paper/2212.10121/) (2022)

## Abstract (arXiv)

In various fields, including medicine, age distributions are crucial. Despite widespread media coverage of health topics, there remains a need to enhance health communication. Narrative medical visualization is promising for improving information comprehension and retention. This study explores the most effective ways to present age distributions of diseases through narrative visualizations. We conducted a thorough analysis of existing visualizations, held workshops with a broad audience, and reviewed relevant literature. From this, we identified design choices focusing on comprehension, aesthetics, engagement, and memorability. We specifically tested three pictogram variants: pictograms as bars, stacked pictograms, and annotations. After evaluating 18 visualizations with 72 participants and three expert reviews, we determined that annotations were most effective for comprehension and aesthetics. However, traditional bar charts were preferred for engagement, and other variants were more memorable. The study provides a set of design recommendations based on these insights.