Visualization of Age Distributions as Elements of Medical Data-Stories
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arXiv
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| Hauptverfasser: | , , |
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| _version_ | 1866916411929001984 |
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| author | Dowlatabadi, Sophia Preim, Bernhard Meuschke, Monique |
| author_facet | Dowlatabadi, Sophia Preim, Bernhard Meuschke, Monique |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_17854 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Visualization of Age Distributions as Elements of Medical Data-Stories Dowlatabadi, Sophia Preim, Bernhard Meuschke, Monique Human-Computer Interaction Computer Vision and Pattern Recognition Graphics 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. |
| title | Visualization of Age Distributions as Elements of Medical Data-Stories |
| topic | Human-Computer Interaction Computer Vision and Pattern Recognition Graphics |
| url | https://arxiv.org/abs/2409.17854 |