Notice bibliographique
Résumé
Each year, 10-20% of newborns (about 13-26 million babies) worldwide will need help to breathe at birth. Helping babies breathe is the cornerstone of neonatal resuscitation. Healthcare providers (HCPs) must perform many tasks quickly and correctly to help babies breathe and prevent irreversible organ injury or death. However even with their help, one million of these babies will die. Medical errors by HCPs remain common and are responsible for 60% of this mortality. To address this staggering gap, guidelines recommend frequent simulation training. Simulation training prepares HCPs to deliver high-quality care while maintaining patient safety. Therefore, to be certified as a neonatal resuscitation provider, HCPs must complete the simulation-based Neonatal Resuscitation Program course once every two years. However, HCPs’ knowledge and skills decrease significantly over time, as early as three months after training. More frequent training is needed but is often prohibitively resource intensive, requiring significant financial and personnel investment. Traditional simulation requires learners to coordinate time away from the clinic to practice under the supervision of a trained instructor and operations specialist, in a lab outfitted with expensive manikins and equipment to mimic the delivery room. Therefore, most HCPs are unable to access adequate training to safely provide care for their newborn patients. Simulation-based serious games may offer a solution to improve access to training. Serious games use elements like competition and emotional design to teach knowledge or skills. This thesis examines the simulation-based serious game RETAIN (REsuscitation TrAINing for healthcare professionals, Retain Labs Medical Inc., Edmonton, Canada) which fits this description. In the RETAIN board game and digital game, learners undergo neonatal resuscitation scenarios to practice their knowledge, communication, and decision-making skills while stabilizing a simulated newborn in distress. The main goal of this research project was to investigate the educational outcomes of using the RETAIN simulators for training and assessment of experienced neonatal resuscitation providers from a level-three perinatal center in Edmonton, Canada. I hypothesized that i) the board game could be used as a summative assessment of HCPs’ knowledge, and ii) training with the digital game would improve HCPs’ short- and long-term knowledge retention, maintenance, and transfer. In the first study to assess summative assessment with the board game, I measured HCPs’ performance on an open-answer written test, compared to their performance on the board game. In the second study to assess longitudinal knowledge with the digital game, I measured participants’ incoming knowledge with a pre-test simulation scenario. Next, participants underwent two training scenarios with the digital simulator to practice their neonatal resuscitation knowledge. I then measured participants’ knowledge improvement by administering a post-test immediately after training, long-term knowledge retention by repeating the post-test 2 months after training, and knowledge transfer by administering a novel assessment scenario and medium, 5 months after training. Across the two studies, I quantitatively and qualitatively measured participants’ mindset, habits, and attitudes towards RETAIN, technology, board games, and other educational media with post-session surveys. The results showed that participants performed better on the board game than on the open-answer test, especially if they reported having more experience with board games overall. The board game also allowed for deeper probing of HCPs’ knowledge, like explaining ventilation corrective steps, compared to the written test. In the second study, I observed a significant improvement in participants’ performance immediately after training, which was maintained 2 months later. I also observed successful knowledge transfer, with participants’ best performance demonstrated on this assessment. Overall, participants reported positive attitudes towards RETAIN, technology, and growth mindset. Negative feedback was clustered around usability issues with the digital game. I concluded that the RETAIN simulators supported successful educational outcomes for experienced neonatal resuscitation providers. The board game functioned as an enjoyable and clinically relevant summative assessment, and the digital game facilitated knowledge improvement, retention, and transfer over time. HCPs also expressed positive attitudes towards the simulators, indicating their receptiveness towards these media for continuing healthcare education. Simulation-based serious games are well-positioned to address challenges of traditional simulation training, including improving access to training for urban and rural providers; or facilitating distanced learning during the current pandemic and beyond. Further research is needed to understand how training may ultimately lead to better care and improve health outcomes for our smallest patients.
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 | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,020 | 0,005 |
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 ».