Effectiveness of Exergaming in Improving Cognitive and Physical Function in People With Mild Cognitive Impairment or Dementia: Systematic Review
Bibliographic record
Abstract
BACKGROUND: Individuals with mild cognitive impairment and dementia have impaired physical and cognitive functions, leading to a reduced quality of life compared with those without such impairment. Exergaming, which is defined as a combination of exercise and gaming, is an innovative, fun, and relatively safe way to exercise in a virtual reality or gaming environment. Therefore, exergaming may help people living with mild cognitive impairment or dementia to overcome obstacles that they may experience regarding regular exercise and activities. OBJECTIVE: The aim of this systematic review was to review studies on exergaming interventions administered to elderly individuals with mild cognitive impairment and dementia, and to summarize the results related to physical and cognitive functions such as balance, gait, executive function, and episodic memory. METHODS: We searched Cochrane Central Register of Controlled Trials (CENTRAL), Medline, Embase, PsycINFO, Amed, and Nursing Database for articles published from the inception of the respective databases to January 2019. We included all clinical trials of exergaming interventions in individuals with mild cognitive impairment and dementia for review. The risk of bias was independently evaluated by two reviewers using the Cochrane Collaboration and Risk of Bias in Non-randomized Studies of Interventions tools. RESULTS: Ten studies involving 702 participants were included for review. There was consistent evidence from 7 studies with a low risk of bias showing statistically significant effects of exergaming on cognitive functioning in people with mild cognitive impairment and dementia. With respect to physical function, 3 of 5 full-scale studies found positive results, and the intensity of most games was classified as moderate. CONCLUSIONS: Overall, exergaming is an innovative tool for improving physical and cognitive function in people with mild cognitive impairment or dementia, although there is high heterogeneity among studies in terms of the duration, frequency, and gaming platform used. The quality of the included articles was moderate to high. More high-quality studies with more accurate outcome indicators are needed for further exploration and validation of the benefits of exergaming for this population.
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 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 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".