Background: Keeping track of the developments in a scientific field can be challenging. Techniques for automated content analysis represent a promising approach for getting insight into large text corpora. Topic modeling, in particular, is gaining in popularity in scientometrics. A topic-guided and user-friendly interface for databases of scientific literature can open publication trends to a broader audience with various user scenarios. Aim: The goal of this project was to develop a user-friendly web-based application for exploring and analyzing research topics in Psychology. Method: A standardized vocabulary of keywords in PSYNDEX - the database of psychological literature from the
German-speaking countries - was the input for topic modeling based on latent Dirichlet allocation. A total of 329,240 documents published between 1980 and 2017 were included. Results: The final model comprised 213 topics. The app features different views for exploring the topics: "popular topics," "hot topics," "cold topics," and an overview of "all topics." Each topic entry has a search button that forwards a search query to PSYNDEX for literature relevant to this topic. Conclusions: Initial user experiences confirm the app's ease of use. Future developments are discussed. A demo version of the app can be accessed for free via https://abitter.shinyapps.io/psychtopics/.