DscoreApp: A Shiny Web Application for the Computation of the Implicit Association Test D-Score

Area of Science:

• Psychological assessment
• Computational psychology
• Data science in social sciences

Background:

• Existing methods for calculating the Implicit Association Test (IAT) D-score often require programming skills, specific software licenses, or are tied to particular experimental setups.
• These limitations hinder accessibility and reproducibility for researchers without extensive technical expertise.

Purpose of the Study:

• To introduce DscoreApp, a user-friendly, open-source web application developed using the R Shiny package.
• To provide a flexible and accessible tool for computing the IAT D-score, accommodating various algorithms and data cleaning criteria.

Main Methods:

• Development of an interactive web application (DscoreApp) utilizing the R Shiny package.
• Implementation of multiple D-score computation algorithms and customizable data cleaning options.
• Integration of immediate visualization of results through interactive graphs and descriptive statistics.

Main Results:

• DscoreApp successfully computes IAT D-scores with user-defined parameters and cleaning criteria.
• The application provides immediate, easy-to-read interactive graphs and descriptive statistics for visualized results.
• Downloadable outputs include graphical representations, D-score datasets, and participant performance metrics.

Conclusions:

• DscoreApp significantly lowers the barrier to entry for accurate IAT D-score computation.
• The tool enhances data exploration and understanding by allowing users to visualize the impact of different settings.
• This open-source application promotes wider adoption and standardized D-score calculation in psychological research.