Barriers and Facilitators Associated With Remote Concussion Physical Assessments From the Perspectives of Clinicians and People Living With Workplace Concussions: Focus Group Study
Bibliographic record
Abstract
BACKGROUND: Evaluating the clinical status of concussions using virtual platforms has become increasingly common. While virtual approaches to care are useful, there is limited information regarding the barriers and facilitators associated with a virtual concussion assessment. OBJECTIVE: This study aims to identify the barriers and facilitators associated with engaging in virtual concussion assessments from the perspective of people living with workplace concussions; identify the barriers and facilitators to completing virtual concussion assessments from the perspectives of clinicians; and identify the clinical measures related to 4 clinical domains that would be most appropriate in virtual practice: general neurological examination and vestibular, oculomotor, and cervical spine assessment. We also evaluated effort. METHODS: Separate online focus groups were conducted with expert concussion clinicians and people living with workplace concussions. A moderator led the focus groups using a semistructured interview guide that targeted a discussion of participants' experiences with virtual assessments. The discussions were recorded, transcribed, and analyzed by 2 reviewers using content analysis. Barriers and facilitators associated with completing the physical concussion examination were categorized based on the domain of the concussion examination and more general barriers and facilitators. Clinician-selected measures believed to work best in a virtual practice were described using frequency counts. RESULTS: A total of 4 focus groups with 15 people living with workplace concussions and 3 focus groups with 14 clinicians were completed using Microsoft Teams. Barriers were identified, such as triggering of symptoms associated with completing an assessment over video (mentioned 13/162 (8%) and 9/201 (4%) of the time for patient and clinician participants, respectively); challenges with location and setup (mentioned 16/162 (10%) of the time for patient participants); communication (mentioned 34/162 (21%) and 9/201 (4%) of the time for patient and clinician participants, respectively); and safety concerns (mentioned 11/162 (7%) of the time for patient and 15/201 (7%) for clinician participants). Facilitators were identified, such as having access to support (mentioned 42/154 (27%) and 21/151 (14%) of the time for patient and clinician participants, respectively); implementing symptom management strategies throughout the assessment (mentioned 11/154 (7%) of the time for patient participants); and having access to resources (mentioned 25/151 (17%) of the time for clinician participants). From the perspective of the clinician participants included in this study, the clinical measures recommended most for a virtual practice were finger to nose testing; balance testing; the Vestibular/Ocular Motor Screening tool; saccades; and cervical spine range of motion within their respective domains (ie, neurological examination, vestibular, oculomotor, and cervical spine assessment). CONCLUSIONS: Virtual assessments appear to be useful for both people living with workplace concussions and clinicians. While barriers were identified, such as challenges associated with exposure to screens, virtual assessments have benefits such as improved access to care. The clinician-selected measures that were considered best in a virtual practice will be investigated in an upcoming evaluative study. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/40446.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".