Introduction: Post-stroke movement disorders are common, especially upper limb dysfunction, which seriously affects the physical and mental health of stroke patients. With the continuous development of intelligent technology, robot-assisted therapy has become a research hotspot in the upper limb rehabilitation of stroke patients in recent years. Many scholars have also integrated robot-assisted therapy with other interventions to improve rehabilitation outcomes. However, there is a lack of research to determine which auxiliary intervention is the best. Therefore, this protocol aims to guide the development of a network meta-analysis, which helps determine the most suitable auxiliary interventions for robot-assisted therapy.
Methods and analysis: Published randomized controlled trials will be included if robot-assisted therapy or robot-assisted therapy associated with other different interventions was applied in stroke patients with upper limb dysfunction in the experimental group and usual rehabilitation treatment and care was applied in the control group. CINAHL, PubMed, Web of Science, MEDLINE, Embase, CNKI, and Wanfang electronic databases will be searched. Studies should be published between January 1, 2013, and December 31, 2023. Two reviewers will independently select studies and extra data, and assess the quality of the included studies. The risk of bias will be evaluated based on the Cochrane Collaboration's risk of bias tool. The evidence quality will be measured according to the Grading of Recommendations Assessment, Development and Evaluation. A network meta-analysis will be conducted by using STATA version 15.0 and R version 4.1.3. The probabilities of rehabilitation interventions will be ranked according to the surface under the cumulative ranking curve.
Ethics and dissemination: Ethical approval is not needed for reviewing published studies. The results will be submitted to a journal.
Trial registration: PROSPERO registration number: CRD42023486570.
Copyright: © 2025 Liu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.