Application of Commonly Used Physical Tests in a Virtual Environment in Patients With Concussion to Patients With Various Types and Severities of Acquired Brain Injury: Prospective Cohort Method Comparison Study
Notice bibliographique
Résumé
Background: People who sustain a concussion and live in remote areas can experience challenges in accessing specialized assessments. In these cases, virtual approaches to assessment are of value. There is limited information on important psychometric properties of physical assessment measures used to evaluate people postconcussion virtually. Objective: The aims of this method-comparison psychometric study were to determine (1) inter- and intrarater reliability of a battery of concussion physical tests administered virtually in people with brain injury and (2) sensitivity and specificity of the virtual battery when compared to the in-person assessment. Methods: A total of 60 people living with acquired brain injuries attended an in-person and virtual assessment at the Ottawa Hospital Rehabilitation Centre. The order of the assessments, in-person and virtual, was randomized. The following physical measures were administered in-person and virtually: finger-to-nose test, vestibular ocular motor screening (VOMS), static balance testing (double leg, single leg, and tandem), saccades, cervical spine range of motion, and evaluation of effort. The virtual assessment was recorded, and a second clinician viewed and independently documented findings from the recordings twice at 1-month intervals. Results: The mean age of the participants was 45.65 (SD 16.50) years. The sensitivity metrics ranged from moderate (60%, 95% CI 30-86) to excellent (100%, 95% CI 71-100) for saccades and cervical spine right lateral flexion, respectively. Specificity ranged from 75%, 95% CI 35-95 to 100%, 95% CI 91-100 for left single leg stance eyes closed and left finger-to-nose testing, respectively. The interrater reliability ranged from poor for cervical spine extension (Cohen κ=0.20, 95% CI -0.07 to 0.47) to excellent for VOMS change in symptoms (Cohen κ=0.93, 95% CI 0.83-1). The intrarater reliability ranged from poor for cervical spine extension (Cohen κ=0.31, 95% CI 0.04-0.58) to excellent for the finger-to-nose testing on the right (Cohen κ=0.90, 95% CI 0.71-1). The wide CIs highlight variability in precision and suggest that further research with larger samples is needed before clinical use can be fully standardized. Conclusions: This study provides information on the psychometric properties associated with virtual administration of concussion measures. The VOMS change in symptoms measure appears to have the most promising properties when administered virtually when in-person visits are not possible. This is particularly relevant for patients in rural areas, for those facing access barriers, and in contexts where timely follow-up is challenging. However, caution should be maintained when administering certain concussion measures virtually. The wide CIs for some measures caution against over-reliance on single test findings, and clinicians should consider both the strengths and limitations of virtual delivery. Clinicians are encouraged to make informed decisions about which measures can be effectively used remotely, and which may still require in-person administration to maintain accuracy.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».