Investigation of Study Procedures to Estimate Sensitivity and Reliability of a Virtual Physical Assessment Developed for Workplace Concussions: a Feasibility Study (Preprint)
Bibliographic record
Abstract
BACKGROUND Virtual approaches to workplace concussion assessment have demonstrated value to end users. The feasibility of administering physical concussion assessment measures in a virtual context has been minimally explored and there is limited information on important psychometric properties of physical assessment measures used in virtual contexts. OBJECTIVE The objectives of this feasibility study were to: determine recruitment capability for a future larger-scale study aimed at determining sensitivity and reliability of the virtual assessment, time required to complete study assessments, acceptability of virtual assessment to people with brain injuries and clinicians, and to document preliminary results of sensitivity of the virtual assessment when compared to the in-person assessment and to estimate the preliminary inter-rater and intra-rater reliability of the virtual assessments to inform procedures of a future larger-scale study that is adequately powered to reliably estimate these parameters of interest. METHODS People living with acquired brain injury attended two assessments (one in-person and one virtual) in a randomized order. The measures administered in these assessments included: the finger-to-nose test, balance testing, the Vestibular/Ocular Motor Screening (VOMS) tool including documentation of change in symptoms and distance for near point convergence (NPC), saccades, cervical spine range of motion, and evaluation of effort. Both assessments occurred at the Ottawa Hospital Rehabilitation Centre. After the assessments, a clinician different from the person who completed the original assessments then viewed and documented findings independently on the recordings of the virtual assessment. The same second clinician viewed the recording again approximately one month following initial observation. RESULTS Rate of recruitment was 61% of people approached, with a total of 20 patient-participants included in the feasibility study. Three clinicians participated as assessors. Length of time required to complete the in-person and virtual assessment procedures averaged nine and 13 minutes, respectively. The majority of clinician and patient-participants agreed or strongly agreed that they were confident in the findings on both in-person and virtual assessments. Feedback obtained revolved around technology (e.g. screen size), lighting, and fatigue of participants in the second assessment. Preliminary estimates of sensitivity of the virtual assessment ranged from poor (finger-to-nose testing: 0.0) to excellent (NPC: 1.0). Preliminary estimates of reliability of the virtual assessment ranged from poor (balance testing, saccades, and range of motion: Kappa=0.38-0.49) to excellent (VOMS change in symptoms: Kappa=1.0). CONCLUSIONS The results of this feasibility study indicate that our study procedures are feasible and acceptable to participants. Certain measures show promising psychometric properties (reliability and sensitivity); however, wide confidence intervals due to the small sample size limit the ability to draw definitive conclusions. A planned follow-up study will expand on this work and include a sufficiently large sample to estimate these important properties with acceptable precision. INTERNATIONAL REGISTERED REPORT RR2-10.2196/preprints.57663
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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 | 0.461 | 0.585 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".