Inclusive and Collaborative Exergame for Adults with Intellectual and Developmental Disabilities: Development and Usability Study (Preprint)
Bibliographic record
Abstract
BACKGROUND: People with intellectual and developmental disabilities (IDDs) face difficulties in being included in activities with their peers due to differences in cognitive abilities and social skills. Video games offer a promising medium to support inclusion, physical activity, and social engagement, but current solutions struggle to provide equitable experiences to heterogeneous groups of users, especially in multiplayer real-time contexts. OBJECTIVE: This study aims to co-design and develop an inclusive collaborative real-time multiplayer exergame, assessing its usability, the impact of accessibility features, and players' satisfaction and enjoyment. METHODS: The exergame Elemental was co-designed following the CeHRes (Centre for eHealth and Wellbeing Research) Roadmap, involving clinicians, educators, engineers, and individuals with IDDs. A total of 2 cooperative minigames were developed: Igloo (focused on stimulus collection) and Volcano (focused on enhancing collaboration), playable with 4 different input devices (buttons, tablet, hand-tracking, and full-body tracking). Customizable facilitation options were implemented to adapt gameplay to sensory, cognitive, and motor needs. Young adults with IDDs participated in a 2-phase study testing whether personalized accommodations could eliminate performance disparities: (1) Igloo in homogeneous groups, based on functioning and expected behavior and interaction with stimuli, without facilitations, using all devices to identify optimal input methods, and (2) Volcano in heterogeneous groups using their best-performing devices with individualized facilitations tailored by educators. Data collected included in-game performance (accuracy, reaction time, and collaboration contributions), behavioral observations, and questionnaires on satisfaction and usability from players. Nonparametric analyses were used to assess relationships between disability severity, performance, and the impact of facilitations. RESULTS: A total of 11 individuals (2 male and 9 female; mean age 25.1, SD 4.4 years) with different IDD diagnoses were recruited from an association supporting individuals with cognitive impairments. In the Igloo sessions, performance was negatively correlated with intellectual disability severity (ρ=-0.87, 95% CI -1.00 to -0.56; P<.001) and reaction time was positively correlated (ρ=0.69, 95% CI 0.08-0.94; P=.02). Instead, no significant correlation between performance and intellectual disability severity was observed in the Volcano sessions (ρ=0.24, 95% CI -0.48 to 0.79; P=.48). These results highlight that tailored support (personalized facilitations and best-suited devices) can foster equitable participation even in heterogeneous groups. Behavioral analysis revealed frequent peer collaboration. Participants reported high usability and satisfaction (median 4/5, IQR 0.5). CONCLUSIONS: This study introduces an inherently accessible, co-designed multiplayer exergame. Unlike approaches that adapt games or create separate disability-specific solutions, Elemental was conceived as inclusive from the outset. By demonstrating that personalized features can eliminate performance disparities, this work highlights how inclusive co-design can transform an activity into an inclusive, collaborative, and enjoyable experience for individuals with different abilities and intellectual impairments, supporting the shift from fitting individuals into existing digital spaces to designing environments able to embrace diversity.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".