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Accepted for/Published in: JMIR Research Protocols

Date Submitted: Aug 16, 2022
Date Accepted: Oct 28, 2022

The final, peer-reviewed published version of this preprint can be found here:

Identification of Clinical Measures to Use in a Virtual Concussion Assessment: Protocol for a Mixed Methods Study

Barnes K, Sveistrup H, Bayley M, Egan M, Rathbone M, Taljaard M, Marshall S

Identification of Clinical Measures to Use in a Virtual Concussion Assessment: Protocol for a Mixed Methods Study

JMIR Res Protoc 2022;11(12):e40446

DOI: 10.2196/40446

PMID: 36548031

PMCID: 9816949

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Identification of Clinical Measures to Use in a Virtual Concussion Assessment: Protocol for a Mixed-Methods Study

  • Keely Barnes; 
  • Heidi Sveistrup; 
  • Mark Bayley; 
  • Mary Egan; 
  • Michel Rathbone; 
  • Monica Taljaard; 
  • Shawn Marshall

ABSTRACT

Background:

Workplace concussions can have a significant impact on workers. The impact of concussion symptoms combined with challenges associated with clinical environments that are loud, bright and busy, create barriers to conducting effective in-person assessments. While the opportunity for remote care in rural communities has long been recognized, the COVID-19 pandemic has catalyzed the transition to virtual assessments and care into the mainstream. With this rapid shift, many clinicians have been completing remote assessments. However, the approaches and measures used in these assessments have not yet been standardized. Furthermore, the psychometric properties of the assessments when completed remotely using videoconference have not yet been documented.

Objective:

Through this mixed-methods study, we aim: 1) To identify which concussion assessment measures clinicians are currently using in-person and are most relevant to five physical domains: neurological examination (cranial nerve, coordination, motor, sensory), cervical spine, vestibular, oculomotor, and effort assessment; 2) To document the psychometric properties of the measures identified; 3) To identify measures that appear feasible in a virtual context; and 4) To identify practical and technical barriers/challenges, facilitators and benefits to conducting or engaging in virtual concussion assessments.

Methods:

This study will follow a sequential mixed methods design using a survey and Delphi approach, working groups with expert clinicians, and focus groups with experienced clinicians and people living with concussions. Our target sample sizes are 50 clinicians for the Delphi surveys, 4 clinician-participants for the working group, and 5-7 participants for each focus group (roughly 6-10 total groups being planned with at least two groups consisting of people living with concussions). The results from this study will inform the decision regarding which measures to include in a virtual assessment toolkit, to be tested in a future planned prospective evaluation study.

Results:

The study is expected to be completed by December 2022.

Conclusions:

This mixed-methods study will document the clinical measures that are currently used in-person and identify those that are most relevant to assessing the physical domains impacted by concussions. Potential feasibility of using these measures in a virtual context will be explored.


 Citation

Please cite as:

Barnes K, Sveistrup H, Bayley M, Egan M, Rathbone M, Taljaard M, Marshall S

Identification of Clinical Measures to Use in a Virtual Concussion Assessment: Protocol for a Mixed Methods Study

JMIR Res Protoc 2022;11(12):e40446

DOI: 10.2196/40446

PMID: 36548031

PMCID: 9816949

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