🩺 Dashboard for Breast Cancer Screening in Australia (Reactive on Demand)
This Shiny web application allows users to explore breast cancer screening data for Australian women. It uses observer-based logic, meaning updates occur only after users trigger an action, such as clicking a button.
This project is part of a broader effort to translate public health screening data into actionable insights. It demonstrates best practices in using R Shiny for health surveillance, offering visual tools to support policy development and outreach strategies.
📘 App Behavior & Architecture
This app uses observeEvent() to control reactivity. Changes to filters (e.g. age group or state) do not instantly update the outputs. Instead, results appear after the user explicitly clicks a “Show Results” or similar button.
| Shiny Feature | Role |
|---|---|
observeEvent() |
Triggers server actions on button click |
eventReactive() |
Reactive expressions tied to events |
actionButton() |
Manual trigger for output updates |
renderPlotly() / renderDT() |
Controlled output rendering |
✅ Advantages
- Reduces unnecessary computation
- Allows the user to finalize multiple input choices before updating
- Preferred for slower connections or complex datasets
⚠️ Disadvantages
- Less fluid interaction for exploratory tasks
- Requires an extra click for every update
🔗 Try the App
🗂️ Project Summary
This application emphasizes deliberate, user-controlled interaction, making it well-suited for presentations or analytical reporting. It is especially helpful when data loads are heavy or precise comparisons are required.
Source code: GitHub – Breast Cancer Screening Shiny App