Dynamiek in beeld

Application to be used in a clinical setting to understand empathy. The application allows clinician to conduct a survey and immediately visualize the results. No data is stored in the RShiny server.

Usage

The app runs online at https://utrecht-university.shinyapps.io/empathy-viz/.

The app has three parts:

Input

Background information of the participant including gender, age and survey code are provided in this section.

Questionnaire

Questionnaire starts with a basic description of the survey, followed by six question, each with three subquestions.

At the end of the questionnaire, the results of the survey can be downloaded.

Visualization

Start with selecting the datasource. There is possibility to visualize the current survey or upload existing results saved in .csv format.

Visualization is available in three styles:

Adapting the survey with new questions

If you would like to modify the app and run locally, please follow the following steps:

Set up survey

• data/introduction.csv - Text in the introduction page, explaining the survey to the participant
• data/vignettes.csv - ID of the questions, title, description, and attached figure (to be displayed in the left)
• `data/relationships.csv - Each vignette is described for two more types of relationships, i.e. stranger and foe.
• data/RadioMatrixFrame.csv - Scales associated (see image above)
• data/ending.csv - Text in the last page
• data/guideline_vis.csv - A short explanation of how to use visualization

Run code

• Clone repository OR download repository (Code --> Download as ZIP)
• Start RStudio and navigate to the folder
• Click on run app

Built with

• shiny1.7.1

Contributing

Contributions are what make the open source community an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

Please refer to the CONTRIBUTING file for more information on issues and pull requests.

License

The code in this project is released under MIT license.

Contact

Dynamiek in Beeld is project by Dr. Minet de Wied. The technical implementation is provided by the ODISSEI Social Data Science (SoDa) team.

Do you have questions, suggestions, or remarks on the technical implementation? File an issue in the issue tracker or feel free to contact Javier Garcia-Bernardo (:bird: @jgarciab) or Parisa Zahedi

Project Link: https://github.com/sodascience/empathy-viz