Background: Exercise and physical activity are key components of treatment for chronic respiratory diseases. However, the level of physical activity and adherence to exercise programs are low in people with these diseases. Active video games (AVGs) may provide a more engaging alternative to traditional forms of exercise.
Objective: This review examines the effectiveness of game-based interventions on physiological outcome measures, as well as adherence and enjoyment in subjects with chronic respiratory diseases.
Methods: A systematic search of the literature was conducted, with full texts and abstracts included where they involved an AVG intervention for participants diagnosed with respiratory conditions. A narrative synthesis of included studies was performed. Additionally, meta-analysis comparing AVGs with traditional exercise was undertaken for 4 outcome measures: mean heart rate (HR) during exercise, peripheral blood oxygen saturation (SO) during exercise, dyspnea induced by the exercise, and enjoyment of the exercise.
Results: A total of 13 full-text papers corresponding to 12 studies were included in the review. Interventions predominantly used games released for the Nintendo Wii (8 studies) and Microsoft Xbox Kinect (3 studies). There were 5 studies that examined the acute effects of a single session of AVGs and 7 studies that examined the long-term effects after multiple sessions of AVGs. Trials conducted over more than 1 session varied in duration between 3 and 12 weeks. In these, AVG interventions were associated with either similar or slightly greater improvements in outcomes such as exercise capacity when compared with a traditional exercise control, and they also generally demonstrated improvements over baseline or nonintervention comparators. There were a few studies of unsupervised AVG interventions, but the reported adherence was high and maintained throughout the intervention period. Additionally, AVGs were generally reported to be well liked and considered feasible by participants. For outcome measures measured during a single exercise session, there was no significant difference between an AVG and traditional exercise for HR (mean difference 1.44 beats per minute, 95% CI -14.31 to 17.18), SO (mean difference 1.12 percentage points, 95% CI -1.91 to 4.16), and dyspnea (mean difference 0.43 Borg units, 95% CI -0.79 to 1.66), but AVGs were significantly more enjoyable than traditional exercise (Hedges g standardized mean difference 1.36, 95% CI 0.04-2.68).
Conclusions: This review provides evidence that AVG interventions, undertaken for several weeks, can provide similar or greater improvements in exercise capacity and other outcomes as traditional exercise. Within a single session of cardiovascular exercise, an AVG can evoke similar physiological responses as traditional exercise modalities but is more enjoyable to subjects with chronic respiratory diseases. However, there is very limited evidence for adherence and effectiveness in long-term unsupervised trials, which should be the focus of future research.
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http://dx.doi.org/10.2196/10116 | DOI Listing |
JAMA Netw Open
January 2025
National-Local Joint Engineering Research Center of Rehabilitation Medicine Technology, Fujian University of Traditional Chinese Medicine, Fuzhou, Fujian, China.
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View Article and Find Full Text PDFEur Heart J
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Heart, Exercise and Research Trials (HEART) Lab, St. Vincent's Institute of Medical Research, Melbourne, Australia.
There should be no assumption that an athlete is immune to coronary artery disease (CAD), even when traditional cardiovascular (CV) risk factors appear well-managed. Excelling in certain aspects of health does not equate to total CV protection. Recent data from cardiac imaging studies have raised the possibility that long-term, high-volume, high-intensity endurance exercise is associated with coronary atherosclerosis.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Exercise Science, Syracuse University, 150 Crouse Dr, Syracuse, NY, 13244, USA.
Analyzing video footage of falls in older adults has emerged as an alternative to traditional lab studies. However, this approach is limited by the labor-intensive process of manually labeling body parts. To address this limitation, we aimed to validate the use of the AI-based pose estimation algorithm (OpenPose) in assessing the hip impact velocity and acceleration of video-captured falls.
View Article and Find Full Text PDFClin Exp Pharmacol Physiol
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School of Physical Education, Hangzhou Normal University, Hangzhou, China.
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View Article and Find Full Text PDFJ Sports Med Phys Fitness
January 2025
School of Medicine, Department of Medical Humanities, Chung Shan Medical University, Taichung, Taiwan.
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