The "science of science" field employs quantitative methods to understand the evolution of scientific fields. This study leverages network science to investigate the multidisciplinarity of psychology and its temporal trends. Psychology's multidisciplinary nature is evident in fields like behavioral economics (combining psychology and economics), evolutionary psychology (psychology and biology), and quantum cognition (psychology and physics). However, a quantitative measure of this multidisciplinarity is lacking. The increasing complexity of scientific problems necessitates more multidisciplinary research. This study aims to quantify psychology's multidisciplinarity, assess its change over time (2008-2018), and provide insights for research administrators and individual researchers. Network science tools are chosen due to their growing use in psychology and the science of science, particularly in analyzing citation patterns to reveal information flow within scientific communities. Two network types are used: citation networks (similar to Price's 1965 work, with nodes representing journals and links representing citations) and co-word networks (nodes as keywords, links as co-occurrence). A longitudinal approach is taken (2008-2018) to track changes in citation patterns and research themes, providing a decade-long perspective encompassing calls for increased interdisciplinary research.

The study draws on existing literature demonstrating psychology's interdisciplinary collaborations, citing examples such as behavioral economics, evolutionary psychology, and quantum cognition. It also references works advocating for increased multidisciplinary research to address complex contemporary issues. The authors highlight the use of network analysis techniques in various fields, referencing Price's seminal work on citation networks and their use in the "science of science." They mention previous studies on citation networks in psychology, emphasizing the longitudinal aspect of the current study to track trends over time. Additionally, the authors acknowledge the use of co-word networks to analyze research trends, citing relevant examples from other disciplines.

The study uses citation and co-word network analyses. For citation networks, data were extracted from the Web of Science's Social Sciences Citation Index database, focusing on articles from journals categorized as "Psychology, Multidisciplinary" from 2008 to 2018. Nodes represented journals, and links represented citations from a multidisciplinary psychology journal article to another journal (multidisciplinary psychology, other psychology subfields, or other disciplines). Gephi software (version 0.9.2) was used for network visualization and analysis. For co-word networks, author-provided keywords from articles within the identified modules of the citation networks were used. Nodes represented keywords, and links represented co-occurrence of keywords. The Louvain method was used for community detection in citation networks to identify modules representing research themes, which were further analyzed using co-word networks. A degree threshold was applied to the co-word networks to highlight the most important research themes. The study considered the number of articles, journals, and citations to quantify the extent of multidisciplinary research in psychology.

The number of articles published in multidisciplinary psychology journals approximately doubled from 2008 to 2018, consistent with the general growth of scientific publications. However, the relative proportion of multidisciplinary psychology research remained stable. The number of journals classified as multidisciplinary psychology increased by approximately 25%, but this increase was slower than the overall growth of scientific journals. Citation analysis revealed a consistent distribution of citations across multidisciplinary psychology journals (25%), other psychology journals (50%), and journals from other disciplines (25%). This distribution remained relatively stable over the years. Community detection in the citation networks (2008 and 2018) identified modules, and co-word network analysis of these modules revealed research themes. Some themes persisted over time (e.g., mental and physical health), while others were more transient. The Q values indicated significant community structure in the 2008 network (Q = 0.32), while the structure was less defined in the 2018 network (Q = 0.20). The co-word networks revealed various research themes for each module in both years, highlighting persistent and evolving research foci.

The consistent proportion of citations across different disciplines (approximately 25% within multidisciplinary psychology, 50% in other psychology areas, and 25% in other disciplines) suggests that multidisciplinary psychology research maintains a strong connection to core psychological principles. The relatively stable multidisciplinarity over time, coupled with the dynamic shifts in research topics, indicates that while the overall extent of multidisciplinary research remains consistent, the specific areas of focus evolve. The observed patterns of persistent and transient research themes suggest the need for strategies that support the continuous development of new multidisciplinary connections, replacing those that become absorbed into mainstream psychology or fade in prominence. The study proposes strategies for research administrators (e.g., recurring short talks across disciplines) and individual researchers (e.g., identifying emerging research gaps) to foster and continually renew multidisciplinary research.

This study provides a quantitative assessment of psychology's multidisciplinarity using network analysis. The findings reveal that the level of multidisciplinarity remained relatively stable, but the specific topics changed over time. This suggests the need for proactive strategies to foster ongoing multidisciplinary collaboration and address emerging societal challenges. Future research could explore more sophisticated network models, consider co-author networks, and analyze longer time spans to further refine our understanding of multidisciplinarity within psychology and other fields.

The study's limitations include the reliance on journal articles and keywords as units of analysis, potentially overlooking other forms of interdisciplinary collaboration. The relatively short time span (10 years) may not capture long-term trends, and the use of relatively simple network measures may not fully exploit the potential of network science. The interpretation of the stable citation proportions remains speculative, lacking definitive causal explanations. The reliance on author-provided keywords introduces potential biases.