Seas the day: Co‐designing immersive virtual reality exergames with exercise professionals and people living with dementia
Bibliographic record
Abstract
BACKGROUND: Physical activity (PA) is associated with physical and cognitive benefits among people living with dementia or mild cognitive impairment (PLWD/MCI) and is a meaningful activity that can improve their confidence in everyday life. Exercising in virtual reality environments (VR Exergame) is becoming an increasingly feasible and enjoyable way to promote PA and well-being in PLWD/MCI. Although co-design can significantly improve the design of technology, it is rarely done with PLWD/MCI. This study uses participatory design methods and collaborative approaches to involve key stakeholders to develop and test a VR Exergame "Seas the Day", a novel solution targeting PLWD/MCI well-being. METHODS: A multi-stage, user-centered co-design approach was used to custom-build VR Exergames tailored to the unique needs and abilities of PLWD/MCI based on a first generation of the prototype that was previously developed and tested with PLWD/MCI. This paper describes the next iteration of the prototype. Processes included concept ideation and brainstorming activities, iterative prototyping, and playtesting/input/feedback sessions with key stakeholders (PLWD/MCI, exercise professionals, engineers, VR game designers, content developers). RESULTS: The multidisciplinary and collaborative design process occurred over 15 months (overlapping with COVID-19 pandemic) with 7 PLWD/MCI (6 females; M=81.3 years) and 9 exercise professionals (7 females; M=38.1 years) to date. The game was designed to target movements identified by exercise professionals and researchers (aerobic exercises, range of motion, seated-balance, quick response to stimuli) and is structured in three exercise stages (warm-up, conditioning, cool-down). To ensure safety of participants while using VR headsets, only seated upper-limb exercises were targeted. Stakeholder feedback regarding game mechanics, aesthetics, and visual/auditory cues were gathered during brainstorming and playtesting sessions and implemented into specific game-related scenarios (tai-chi, rowing, fishing). CONCLUSION: We presented the process, outcomes, and challenges of adopting a participatory/collaborative approach with multiple stakeholder groups to co-design VR Exergames tailored to PLWD/MCI. Next steps will include a mixed-method evaluation of the VR Exergames among community-dwelling older adults and PLWD/MCI in retirement communities and long-term care to evaluate: i) feasibility and acceptability of use, ii) game user experience, iii) barriers/facilitators to uptake of VR Exergames; and iv) inform/validate VR Exergames gameplay metrics reflective of cognitive and motor performance.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".