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Enregistrement W7034044263

Serious Games on the Lived Experience of Dementia as Learning Tools in Pharmacy Education

2023· dissertation· en· W7034044263 sur OpenAlexaff

Notice bibliographique

RevueUWSpace (University of Waterloo) · 2023
Typedissertation
Langueen
DomaineEconomics, Econometrics and Finance
ThématiqueEconomic and Technological Innovation
Établissements canadiensUniversity of Waterloo
Organismes subventionnairesnon disponible
Mots-clésFormative assessmentDementiaLived experiencePharmacyExperiential learningSerious gamePopularityTransparency (behavior)Qualitative research
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Dementia is a stigmatized and often ‘invisible’ condition which requires clinicians to have a nuanced understanding of the lived experience to build trust and provide better quality of care. Pharmacists are at the frontline of care for patients who may have dementia and there is a need for effective and engaging learning opportunities to prepare them for caring for patients living with dementia. Serious games have gained popularity for their potential in facilitating safe and engaging learning opportunities. However, there are limited applications of serious games in clinical education on the topic of dementia and little transparency on the development process. The thesis work outlined in this project intends to explore how serious games can best facilitate a learning experience for senior pharmacy students to better their understanding of the lived experience of dementia. The primary objective was to develop a serious game with multi-stakeholder input. The secondary objective was to provide game design recommendations for development of serious games on this topic based on end-user play-testing experiences. During both the development and user-testing, qualitative methods were used to gather thorough feedback and understand individual play experiences, namely semi-structured interviews and the think-aloud protocol. To develop a serious game, the game design framework for medical education was adapted in this project, which involved three stages: preparation and design, development, and formative evaluation. In the first stage, a clinician and a systems design expert were consulted to develop the first prototype. In the development stage, the prototype was reviewed by stakeholders including clinicians, people with lived experiences of dementia or care partners, and serious game researchers through semi-structured interviews, resulting in iterative improvements. Stakeholder feedback culminated in the development of a serious game with the goal of helping pharmacy students better understand the lived experience of dementia, in a digital, non-linear story format. During the final formative evaluation stage of game design, 11 senior pharmacy students, a pharmacy educator, and a social worker with expertise in dementia care tested the game. Their learning and play experiences were gauged through the semi-structured interview and think-aloud protocols. The qualitative data was analyzed using the framework method of analysis. Three factors were necessary for creating an engaging learning experience about dementia for senior pharmacy students. The first was facilitating understanding of dementia through an experiential approach using a realistic environment and authentic storytelling. The second was providing a problem-oriented experience by providing meaningful player interaction opportunities and creative freedom. Finally, novelty in the game format was necessary for an engaging experience. Future directions include recruiting more stakeholders and student participants with experiences relating to dementia, and utilizing these recommendations to improve on the game and assessing its impact on student empathy and confidence in caring for patients who have dementia.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Qualitatif · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,393
Score d'incertitude au seuil0,986

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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.

Tête enseignante Opus0,054
Tête enseignante GPT0,251
Écart entre enseignants0,198 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeQualitatif
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2023
Routes d'admission1
Résumé présentoui

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