(B-118) Bibliometric Analysis of Global Research Trends and Themes in ADHD

Background: Understanding research trends and themes in Attention-Deficit/Hyperactivity Disorder (ADHD) is crucial for identifying key topics and emerging areas in the field. Despite the growing body of ADHD research, comprehensive bibliometric analyses of global trends remain limited.

Objectives: To examine research trends and themes in ADHD and analyze keyword changes over time using bibliometric analysis.

Methods: We conducted a bibliometric analysis of ADHD-related publications from 2010 to 2024 using the Web of Science database, with 'ADHD' as the primary keyword to identify relevant articles. To analyze changes in research domains and identify the emergence of key topics over time, the study period was divided into three intervals: Period 1 (2010–2014), Period 2 (2015–2019), and Period 3 (2020–2024). After extracting bibliographic data, keyword standardization was applied by normalizing identical terms with variations in abbreviations, plural forms, and spacing to ensure consistency and accuracy. Keyword co-occurrence analysis using author keywords was performed to construct a network and identify thematic clusters. The co-occurrence network graph used different colors to represent thematic clusters, with nodes and lines illustrating the topic coverage of each cluster. Node size reflects keyword frequency, while lines indicate relationships among keywords. To identify dominant research themes in each period, a minimum keyword occurrence threshold of 50 was applied. Data processing, network construction, and visualization were performed using VOSviewer software.

Results: A total of 32,790 ADHD-related articles were analyzed. Keyword co-occurrence analysis revealed thematic shifts across the three periods, with keywords forming between seven and nine clusters in each period. In Period 1, research primarily focused on executive function and neuroimaging, comorbidities such as autism spectrum disorder, and pharmacological treatments, particularly the use of methylphenidate. In Period 2, research on adult ADHD increased and was accompanied by the emergence of meta-analytic methodologies. Moreover, the keyword 'sex differences' appeared for the first time during this period and remained a focus in Period 3. In Period 3, research applying machine learning and examining ADHD in the context of the COVID-19 pandemic emerged. Across all study periods, ‘children’ and ‘adolescent’ remained key research terms.

Conclusions: Bibliometric analysis enhances understanding of the evolution of ADHD research by identifying major themes and emerging topics. Future ADHD research is expected to focus on sex differences, explore environmental factors influencing ADHD, and increasingly incorporate artificial intelligence.