Video-based examination of patients with shoulder pain: a scoping review.

BACKGROUND

Virtual healthcare has developed rapidly and become an important part of medical care. Shoulder complaints are a common reason for seeking care and require thorough examination. Studies indicate that musculoskeletal examinations can be performed via video with good validity, but the evidence is limited. There is a need to explore, identify and map current research on the topic. The aim of this scoping review was to map and compile the existing literature on real-time video-based examination of the shoulder, to identify knowledge gaps in this area, and to describe procedures used in shoulder examinations.

METHODS

A literature search was conducted in November 2024 on PubMed, CINAHL and Scopus, and updated in June 2026. Grey literature was excluded. Selection of literature was performed independently by two authors. Conduct and reporting of the review followed established guidance for scoping reviews.

RESULTS

Twenty articles were included in the review. Seven were designed as guidelines, 12 were validity or reliability studies, and one article was a case report. A result was compiled that describes the different parts of a video-based examination of the shoulder. The result also includes a description of investigated validity and reliability for individual examination components, and overall clinical assessment and diagnosis.

CONCLUSIONS

This scoping review identified multiple studies outlining examination components and practical procedures for video-based assessment of the shoulder, suggesting the usefulness of this mode. Nevertheless, more research is necessary to establish a robust evidence base. Further research is needed to determine best practices and the appropriate role of video-based shoulder examination in musculoskeletal care. .

CLINICAL TRIAL REGISTRATION: Not applicable. This study is not a clinical trial.

CLINICAL TRIAL NUMBER: Not applicable. The scoping review was preregistered on 8 Nov 2024 on Open Science Framework Registry (Identifier: https://doi.org/10.17605/OSF.IO/B4C8S ).