Division of Restorative Dentistry and Periodontology, Dublin Dental University Hospital, Trinity College Dublin, Dublin 2, Ireland.
BMC Oral Health. 2023 Apr 24;23(1):238. doi: 10.1186/s12903-023-02895-2.
A working knowledge of data analytics is becoming increasingly important in the digital health era. Interactive dashboards are a useful, accessible format for presenting and disseminating health-related information to a wide audience. However, many oral health researchers receive minimal data visualisation and programming skills.
The objective of this protocols paper is to demonstrate the development of an analytical, interactive dashboard, using oral health-related data from multiple national cohort surveys.
The flexdashboard package was used within the R Studio framework to create the structure-elements of the dashboard and interactivity was added with the Shiny package. Data sources derived from the national longitudinal study of children in Ireland and the national children's food survey. Variables for input were selected based on their known associations with oral health. The data were aggregated using tidyverse packages such as dplyr and summarised using ggplot2 and kableExtra with specific functions created to generate bar-plots and tables.
The dashboard layout is structured by the YAML (YAML Ain't Markup Language) metadata in the R Markdown document and the syntax from Flexdashboard. Survey type, wave of survey and variable selector were set as filter options. Shiny's render functions were used to change input to automatically render code and update output. The deployed dashboard is openly accessible at https://dduh.shinyapps.io/dduh/ . Examples of how to interact with the dashboard for selected oral health variables are illustrated.
Visualisation of national child cohort data in an interactive dashboard allows viewers to dynamically explore oral health data without requiring multiple plots and tables and sharing of extensive documentation. Dashboard development requires minimal non-standard R coding and can be quickly created with open-source software.
在数字健康时代,数据分析的基本知识变得越来越重要。交互式仪表板是向广大受众展示和传播健康相关信息的有用且易于访问的格式。然而,许多口腔健康研究人员接受的数据分析和编程技能很少。
本方案论文的目的是展示如何使用来自多个国家队列研究的口腔健康相关数据开发分析性交互式仪表板。
使用 R Studio 框架中的 flexdashboard 包来创建仪表板的结构元素,并使用 Shiny 包添加交互性。数据源来自爱尔兰国家儿童纵向研究和国家儿童食品调查。根据已知与口腔健康相关的变量选择输入变量。使用 tidyverse 包(如 dplyr)对数据进行聚合,并使用 ggplot2 和 kableExtra 进行汇总,同时创建特定函数生成条形图和表格。
仪表板布局由 R Markdown 文档中的 YAML(YAML 不是标记语言)元数据和 Flexdashboard 的语法结构。调查类型、调查波次和变量选择器被设置为筛选选项。使用 Shiny 的 render 函数来更改输入,以自动呈现代码并更新输出。部署的仪表板可在 https://dduh.shinyapps.io/dduh/ 公开访问。演示了如何针对选定的口腔健康变量与仪表板进行交互的示例。
在交互式仪表板中可视化国家儿童队列数据可使查看者无需多个图表和表格以及共享大量文档,即可动态探索口腔健康数据。仪表板开发只需要很少的非标准 R 编码,并且可以使用开源软件快速创建。