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Record W7034044263

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

2023· dissertation· en· W7034044263 on OpenAlexaff

Bibliographic record

VenueUWSpace (University of Waterloo) · 2023
Typedissertation
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Technological Innovation
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsFormative assessmentDementiaLived experiencePharmacyExperiential learningSerious gamePopularityTransparency (behavior)Qualitative research
DOInot available

Abstract

fetched live from 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.393
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.054
GPT teacher head0.251
Teacher spread0.198 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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