Exploring Fragmentation in Emerging Fields of Research

Psychotherapy researchers have emphasized the importance of a paradigm shift towards translational psychological treatment. However, the publication landscape on this topic is uncharted. This makes it difficult to assess the state of translational psychotherapy research. Hence, we developed a workflow that leverages natural language processing and machine learning to find relevant studies. Based on this, we bibliometrically analyzed 7,146 publications to provide insights for the integration and development of the research field. Specifically, citation and network analyses were performed to examine the strengths and weaknesses of the research field. Five main findings emerged: 1. Machine learning proved valuable in finding eligible publications and generating an open dataset. 2. Regarding basic psychological subfields, translation comes primarily from physiological psychology/neuroscience, with a focus on fear, posttraumatic stress, and anxiety. 3. Translational research is characterized by international collaborations. 4. It has an impact within and beyond academia. 5. The lack of standardized terminology might threaten scientific progress. To foster a paradigm shift towards translational psychological treatment, a consistent terminology would greatly facilitate its development and dissemination.