Is Digital Social Work a Cohesive Body of Knowledge? A Bibliometric Review

Background Integrating digital technologies into social work practice has become increasingly significant, with new developments occurring in the artificial intelligence (AI) era, reshaping service delivery and interdisciplinary collaboration. This bibliometric-systematic review examines the scope and evolution of digital technologies in social work. This is a review that examines the body of knowledge as a whole, rather than focusing on the effectiveness of individual interventions. Specifically, the study addresses the following research questions: Which articles, journals, countries, and authors hold the most significant influence in the field? What research trends in this domain have been explored in the past decade? To what extent is digital social work a cohesive body of knowledge? What are the future directions for research in digital social work? Methods The study employed a bibliometric approach and analysed 767 articles from the Web of Science's Social Work category. It used CiteSpace for network analysis and visualisation. Results The findings reveal ten major research clusters, including foundational themes like the social worker–client relationship and emerging areas such as AI and telehealth. Implication The review highlights the potential for continuity and cohesiveness within the field while also identifying structural hurdles, the need for enhanced theorisation, the strategic importance of innovation, and the value of fostering cross-regional collaborations.

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Publication Details

Journal
Journal of Social Work
Published
2026-04-22
DOI
https://doi.org/10.1177/14680173261441079
Primary Topic
Social Work Education and Practice
Type
article
Field-Weighted Citation Impact
0.00

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article

Is Digital Social Work a Cohesive Body of Knowledge? A Bibliometric Review

Ashari Fitra Rachmannullah, Chitat Chan, Afifah Nurrosyidah
Journal of Social Work
Social Work Education and Practice
article

Is Digital Social Work a Cohesive Body of Knowledge? A Bibliometric Review

Ashari Fitra Rachmannullah, Chitat Chan, Afifah Nurrosyidah
article en

Abstract

Background Integrating digital technologies into social work practice has become increasingly significant, with new developments occurring in the artificial intelligence (AI) era, reshaping service delivery and interdisciplinary collaboration. This bibliometric-systematic review examines the scope and evolution of digital technologies in social work. This is a review that examines the body of knowledge as a whole, rather than focusing on the effectiveness of individual interventions. Specifically, the study addresses the following research questions: Which articles, journals, countries, and authors hold the most significant influence in the field? What research trends in this domain have been explored in the past decade? To what extent is digital social work a cohesive body of knowledge? What are the future directions for research in digital social work? Methods The study employed a bibliometric approach and analysed 767 articles from the Web of Science's Social Work category. It used CiteSpace for network analysis and visualisation. Results The findings reveal ten major research clusters, including foundational themes like the social worker–client relationship and emerging areas such as AI and telehealth. Implication The review highlights the potential for continuity and cohesiveness within the field while also identifying structural hurdles, the need for enhanced theorisation, the strategic importance of innovation, and the value of fostering cross-regional collaborations.

Journal of Social Work
Hong Kong Baptist University (HK), Universiti Malaysia Terengganu (MY), National Cheng Kung University (TW)
Hong Kong Baptist University
Industry, innovation and infrastructure
Openalex Percentile: Top 4%
Social Work Education and Practice
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Is Digital Social Work a Cohesive Body of Knowledge? A Bibliometric Review — Ashari Fitra Rachmannullah, Chitat Chan, et al. · Journal of Social Work (2026) | TGRS Research Map | TGRS