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Record W4285329744 · doi:10.2196/35202

The Effectiveness of Serious Games in Improving Memory Among Older Adults With Cognitive Impairment: Systematic Review and Meta-analysis

2022· review· en· W4285329744 on OpenAlexvenueno aff
Alaa Abd‐Alrazaq, Dari Alhuwail, Eiman Al-Jafar, Arfan Ahmed, Farag Shuweihdi, Shuja Reagu, Mowafa Househ

Bibliographic record

VenueJMIR Serious Games · 2022
Typereview
Languageen
FieldPsychology
TopicAging and Gerontology Research
Canadian institutionsnot available
Fundersnot available
KeywordsMeta-analysisRandomized controlled trialCognitionStrictly standardized mean differenceVerbal memoryPsychological interventionData extractionSystematic reviewMemory impairmentCritical appraisalCognitive impairmentPsychologyMedicineMEDLINEClinical psychologyPsychiatryInternal medicineAlternative medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Memory, one of the main cognitive functions, is known to decline with age. Serious games have been used for improving memory in older adults. The effectiveness of serious games in improving memory has been assessed by many studies. To draw definitive conclusions about the effectiveness of serious games, the findings of these studies need to be pooled and aggregated. OBJECTIVE: This study aimed to assess the effectiveness of serious games in improving memory in older adults with cognitive impairment. METHODS: A systematic review of randomized controlled trials was carried out. The search sources included 8 databases, the reference lists of the included studies and relevant reviews, and the studies that cited the included studies. In total, 2 reviewers (AA and MH) independently carried out the study selection, data extraction, risk of bias assessment, and quality of evidence appraisal. Extracted data were synthesized using a narrative approach and a statistical approach (ie, multilevel meta-analysis), as appropriate. RESULTS: Of the 618 citations retrieved, 18 (2.9%) met the eligibility criteria for this review. Of these 18 studies, 15 (83%) randomized controlled trials were included in 10 multilevel meta-analyses. We found that serious games were more effective than no or passive interventions in improving nonverbal memory (P=.02; standardized mean difference [SMD]=0.46, 95% CI 0.09-0.83) and working memory (P=.04; SMD=0.31, 95% CI 0.01-0.60) but not verbal memory (P=.13; SMD=0.39, 95% CI -0.11 to 0.89). The review also showed that serious games were more effective than conventional exercises in improving verbal memory (P=.003; SMD=0.46, 95% CI 0.16-0.77) but not nonverbal memory (P=.30; SMD=-0.19, 95% CI -0.54 to 0.17) or working memory (P=.99; SMD=0.00, 95% CI -0.45 to 0.45). Serious games were as effective as conventional cognitive activities in improving verbal memory (P=.14; SMD=0.66, 95% CI -0.21 to 1.54), nonverbal memory (P=.94; SMD=-0.01, 95% CI -0.32 to 0.30), and working memory (P=.08; SMD=0.37, 95% CI -0.05 to 0.78) among older adults with cognitive impairment. Finally, the effect of adaptive serious games on working memory was comparable with that of nonadaptive serious games (P=.08; SMD=0.18, 95% CI -0.02 to 0.37). CONCLUSIONS: Serious games have the potential to improve verbal, nonverbal, and working memory in older adults with cognitive impairment. However, our findings should be interpreted cautiously given that most meta-analyses were based on a few studies (≤3) and judged to have a low quality of evidence. Therefore, serious games should be offered as a supplement to existing proven and safe interventions rather than as a complete substitute until further, more robust evidence is available. Future studies should investigate the short- and long-term effects of serious games on memory and other cognitive abilities among people of different age groups with or without cognitive impairment.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.748
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0090.002
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.030
GPT teacher head0.368
Teacher spread0.338 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations45
Published2022
Admission routes1
Has abstractyes

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