The Impact of Active Augmented Reality Games on Physical Activity and Cognition Among Older Adults: Feasibility Study
Notice bibliographique
Résumé
Background: Physical activity (PA) enhances physical health as well as cognitive and brain health, yet motivating older adults to initiate and sustain PA remains challenging, a difficulty exacerbated by the COVID-19 pandemic. Active augmented reality (AAR) games, integrating digital gameplay with real-world physical movement, provide an enjoyable and accessible means for PA promotion among older adults in independent living environments, mitigating barriers such as poor weather and unfavorable neighborhood environments. However, limited research has explored the feasibility and impact of AAR interventions in this population. Objective: This feasibility study examines the acceptability, safety, and preliminary effects of AAR games to enhance PA levels and cognitive functions among older adults, as well as their user experiences. We also examined the practicality of home-based AAR gameplay using minimal equipment and constrained physical space. Methods: Sixteen independent-living older adults aged 65-85 years (mean 74.6, SD 3.73) participated in a single-session AAR intervention using the Active Arcade game set by playing four 10-minute AAR games. PA levels were assessed using ActiGraph wGT3x-bt accelerometers and Polar H10 heart rate monitors. Cognitive function was evaluated pre- and post-gameplay using NIH Toolbox's visual reasoning test and Flanker inhibitory control and attention tests. Surveys of PA intention and motivation as well as the gaming experience questionnaire, along with semistructured interviews, were conducted afterwards, providing both quantitative and qualitative insights into the feasibility and appeal of AAR gameplay from the target population. Results: All participants completed the study protocol without adverse events, demonstrating high feasibility and acceptability. Participants engaged in moderate-to-vigorous PA during 20%-30% of the gameplay, as measured by accelerometers and heart rate monitors. Of the 16 participants, 7 were taking beta blockers. The mean values of average %HRMax suggest that those not on beta blockers generally met the moderate-intensity threshold, whereas those on beta blockers tended to fall slightly below it. Cognitive assessments revealed significant improvements in visual reasoning postintervention, with the effect sustained after adjustment for age and education (P=.03), suggesting potential cognitive benefits from a single bout of AAR gameplay. Survey responses indicated high levels of PA intention (mean 4.15/5, SD 0.59), motivation (mean 5.67/7, SD 1.24), high positive affect (mean 4.35/5, SD 0.80), and low negative affect (mean 1.30/5, SD 0.46) associated with AAR gameplay. Around 75% of gameplay occurred within a 4×4 ft area (mean 29.77/40 min, SD 2.46), indicating suitability for home environments. Thematically analyzed interview feedback emphasized participants' enjoyment, ease of use, desire for progressive difficulty, and the need to cater to diverse physical abilities and individual preferences. Conclusions: AAR games are a feasible, accessible, and enjoyable alternative for PA and cognitive engagement among older adults. Future research should investigate the long-term effects, sustainability, and broader applicability of AAR interventions to fully realize their potential in aging populations.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».