# Introducing CRIS—A unified framework for systematic literature searches across disciplines

## TL;DR

This paper introduces CRIS, a framework for improving literature searches in cross-disciplinary research by enhancing sensitivity and robustness.

## Contribution

The novel contribution is a unified framework for cross-disciplinary literature searches that integrates shared thesaurus and iterative methods.

## Key findings

- The CRIS framework significantly improves the sensitivity and robustness of literature searches.
- An example combining User Experience and Game Design with Human Movement Science demonstrates the framework's effectiveness.
- CRIS outperforms discipline-specific and expert overlap approaches in cross-disciplinary contexts.

## Abstract

Cross-disciplinary research approaches have become more necessary in light of the increasing global and societal challenges. As different forms of collaboration emerge, cross-disciplinary systematic reviews that integrate these approaches are increasingly recognized as crucial. A key part of these reviews is conducting a valid and thorough literature search. To comprehend the state of knowledge, integrating diverse findings and ensuring that the literature search captures relevant studies from all viewpoints, including their combinations and collaborations, is important.

This article presents a framework for conducting cross-disciplinary literature searches that adhere to established best-practice guidelines and reporting standards. The framework seeks to include research across all forms of collaboration across disciplines, including multidisciplinary, interdisciplinary, and transdisciplinary. The objective is to enhance the sensitivity and robustness of literature searches in cross-disciplinary research contexts.

We developed a framework that integrates a pre-process into the search to support cross-disciplinary literature searches. Additionally, we derived a procedure from specific concepts, including the use of shared thesaurus, focus, and iterative approach, which are applied throughout the various stages of the process. To demonstrate the value of the cross-disciplinary literature search (CRIS) framework, we performed an example search that combines User Experience and Game Design with Human Movement Science. We conducted three literature searches and compared our framework with discipline-specific and an expert overlap perspectives.

By applying our CRIS framework, we observed significant improvements in sensitivity and robustness compared to the other searches, illustrating the framework's effectiveness in cross-disciplinary research settings.

Through our example, which combines User Experience and Game Design with Human Movement Science, we show that our framework substantially enhances the quality of literature searches, underscoring its potential for advancing cross-disciplinary research.