A bibliometric analysis of mental health help-seeking intervention from 2014 to 2024

The global escalation of mental health challenges necessitates a robust systematic evaluation of help-seeking interventions. While individual empirical studies abound, a comprehensive evaluation of the global knowledge structure, thematic evolution, and research landscape remains limited. This study mapped the development and knowledge structure of mental health help-seeking intervention research from 2014 to 2024. Bibliographic data were retrieved from the Web of Science Core Collection (SCI-Expanded and SSCI) and analysed using VOSviewer and the bibliometrix R package. After eligibility screening and manual relevance checking, 95 peer-reviewed experimental and quasi-experimental studies were included. Performance analysis, keyword co-occurrence analysis, and thematic mapping were conducted. Performance analysis revealed a substantial increase in publications after 2020, with research output concentrated in Western high-income countries, particularly the United States, Australia, and the United Kingdom, while institutional collaboration remained relatively fragmented. Thematic analysis identified help-seeking, stigma, mental health literacy, depression, adolescents, and intervention as prominent and interconnected areas of research. The thematic map further showed that stigma, mental health literacy, and adolescent-focused research were highly relevant but varied in their degree of development, while digital, early-intervention, and several population-specific topics remained comparatively peripheral or less developed within the thematic structure. Overall, the findings indicate an expanding but geographically uneven evidence base, with Asian and low- and middle-income settings comparatively underrepresented in the WoS-indexed literature. Future research should strengthen culturally responsive intervention development, broaden representation across diverse settings, and examine how interventions translate into sustained help-seeking behaviour and real-world implementation.