Creation and validation of a roadside rescue skills scale for training pre-hospital medical teams: the RoadRes-Q scale
Notice bibliographique
Résumé
BACKGROUND: Road traffic injuries are the leading cause of death among young people worldwide. While advances in vehicle safety have reduced some of the risks, the speed and quality of pre-hospital care are critical to prevent fatalities. In France, patients are cared for by medical teams and firefighters who must work together as closely as possible to ensure the best possible survival rate. However, there is a lack of standardised scales to assess the performance of these multidisciplinary teams. This study aimed to create and validate a roadside rescue skills assessment scale, the RoadRes-Q scale, for healthcare teams. METHODS: We used a two-round Delphi method to develop the RoadRes-Q scale. A panel of 9 international roadside rescue experts, including 7 firefighters and 2 engineers in road rescue equipment, agreed to participate. The scale covers five key areas: healthcare provider protection, site securing, vehicle securing, first aid delivery, and patient extrication. The final version was tested during two one-day simulation-based training sessions, each involving 22 participants: 6 healthcare staff, 14 firefighters, and 2 simulated victims. Assessors completed the scale during and after each scenario, focusing on internal consistency and inter-observer reliability. RESULTS: The RoadRes-Q scale consists of 60 items. Internal consistency was excellent (Cronbach's alpha of 0.86), indicating that items were non-redundant and consistently measured the required competencies. However, inter-observer reliability was low (intra-class correlation coefficient of 0.48), suggesting variability between assessors. Satisfaction among participants to the simulation-based training courses was high, and their knowledge increased. CONCLUSIONS: The RoadRes-Q scale proved to be a valid and reliable scale for evaluating both technical and non-technical skills. While internal consistency was strong, improvements are needed in inter-observer reliability. Structured training for assessors and video-based assessments could enhance reproducibility. The RoadRes-Q scale has the potential for assessing the quality and safety of care provided by healthcare teams in roadside rescue situations. REGISTRATION: As the study did not involve interventional research or patient participation, ethics committee approval was not required, but it received approval from the scientific referents of the Faculty of Medicine of Poitiers, and participants provided informed consent for using their anonymised data.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».