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Record W4406225604 · doi:10.1002/alz.094290

People with dementia as exercise video game testers: Gathering end‐user perspectives

2024· article· en· W4406225604 on OpenAlexaffabout
Erica Dove, Rosalie H. Wang, Kara K. Patterson, Arlene Astell

Bibliographic record

VenueAlzheimer s & Dementia · 2024
Typearticle
Languageen
FieldPsychology
TopicEducational Games and Gamification
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDementiaVideo gameEnd userComputer scienceMultimediaPsychologyApplied psychologyHuman–computer interactionInternet privacyWorld Wide WebMedicine

Abstract

fetched live from OpenAlex

Abstract Background Commercially available exercise video games (‘exergames') can be used by people with dementia with the right (human) prompting and support. However, more information is needed about what makes these systems and games technologically accessible for this population, considering their cognitive difficulties. This study explores what works and doesn’t work for people with dementia when introducing new exergame systems and games to broaden opportunities for physical activity. Methods Thirty‐two people living with dementia (mean Montreal Cognitive Assessment score: 12.75/30) were recruited from four community‐based adult day programs in Canada. Participants were recruited as ‘game testers' once weekly for six weeks at each day program. Participants with dementia tried different exergame systems (e.g., Xbox Kinect, Nintendo Switch) and games (e.g., darts, boxing, dancing, etc.). Concurrently, gameplay video recordings and feedback via the talk‐aloud protocol and audio‐recorded post‐game group debriefs were collected. Data were analyzed descriptively and are currently undergoing analysis using behavioural coding software to examine in‐game prompts and player movements. Results In total, 292 gameplay turns occurred across the sessions. Some participants declined to play certain games after watching their peers experience accessibility challenges. Common reasons for ending a turn (beyond completing the game objective) included boredom, frustration, confusion, fatigue, and soreness. Systems with handheld controllers (e.g., Nintendo Wii) were less accessible for participants than gesture‐based controls due to the need to push buttons and attend to the controller while simultaneously performing physical motions. Additionally, games requiring multiple coordinated movements and those not accommodating additional age‐related impairments (e.g., range of motion impairments, mobility devices) were not widely accessible to this diverse group of participants. Conclusions This study highlights the importance of involving people living with dementia in game development. The findings reveal which elements of current exergames make them accessible or inaccessible for people living with dementia. These findings can help design new exergames to increase access to physical activity for people with dementia. The findings will also interest dementia service providers who want to use exergames to increase physical activity for people with 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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.020
GPT teacher head0.302
Teacher spread0.283 · 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 source (direct Gemma or distilled Codex), 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
Published2024
Admission routes2
Has abstractyes

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