Effectiveness of Serious Games for Improving Executive Functions Among Older Adults With Cognitive Impairment: Systematic Review and Meta-analysis (Preprint).. [DOI: 10.2196/preprints.36123]

Artificial Intelligence-Driven Serious Games in Health Care: Scoping Review

BACKGROUND

Artificial intelligence (AI)-driven serious games have been used in health care to offer a customizable and immersive experience. Summarizing the features of the current AI-driven serious games is very important to explore how they have been developed and used and their current state to plan on how to leverage them in the current and future health care needs.

OBJECTIVE

This study aimed to explore the features of AI-driven serious games in health care as reported by previous research.

METHODS

We conducted a scoping review to achieve the abovementioned objective. The most popular databases in the information technology and health fields (ie, MEDLINE, PsycInfo, Embase, CINAHL, IEEE Xplore, ACM Digital Library, and Google Scholar) were searched using keywords related to serious games and AI. Two reviewers independently performed the study selection process. Three reviewers independently extracted data from the included studies. A narrative approach was used for data synthesis.

RESULTS

The search process returned 1470 records. Of these 1470 records, 46 (31.29%) met all eligibility criteria. A total of 64 different serious games were found in the included studies. Motor impairment was the most common health condition targeted by these serious games. Serious games were used for rehabilitation in most of the studies. The most common genres of serious games were role-playing games, puzzle games, and platform games. Unity was the most prominent game engine used to develop serious games. PCs were the most common platform used to play serious games. The most common algorithm used in the included studies was support vector machine. The most common purposes of AI were the detection of disease and the evaluation of user performance. The size of the data set ranged from 36 to 795,600. The most common validation techniques used in the included studies were k-fold cross-validation and training-test split validation. Accuracy was the most commonly used metric for evaluating the performance of AI models.

CONCLUSIONS

The last decade witnessed an increase in the development of AI-driven serious games for health care purposes, targeting various health conditions, and leveraging multiple AI algorithms; this rising trend is expected to continue for years to come. Although the evidence uncovered in this study shows promising applications of AI-driven serious games, larger and more rigorous, diverse, and robust studies may be needed to examine the efficacy and effectiveness of AI-driven serious games in different populations with different health conditions.

Artificial Intelligence-Driven Serious Games in Healthcare: A Scoping Review (Preprint).. [DOI: 10.2196/preprints.39840] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

BACKGROUND

Artificial Intelligence (AI)-driven serious games have been used in healthcare to offer a customizable and immersive experience. Summarizing the features of the current AI-driven serious games is very important to explore how they have been developed and used and their current state in order to plan on how to leverage them in the current and future healthcare needs.

OBJECTIVE

The current study aimed to explore the features of AI-driven serious games in healthcare as reported by previous research.

METHODS

We carried out a scoping review to achieve the above-mentioned objective. The most popular databases in information technology and health fields (e.g., MEDLINE and IEEE Xplore) were searched using keywords related to serious games and AI. These terms were selected based on the target intervention (i.e., AI) and the target disease (i.e., COVID-19). Two reviewers independently performed the study selection process. Three reviewers independently used Microsoft Excel to extract data from the included studies. A narrative approach was used for data synthesis.

RESULTS

The search process returned 1470 records. Of these records, 46 met all eligibility criteria. 60 different serious games were found in the included studies. Motor impairment was the most common health condition targeted by these serious games. Serious games in most of the studies were used for rehabilitation. The serious games in the majority of the included studies can be played by only single player. Most serious games were played on standalone devices (offline games). The most common genres of serious games were role-playing games, puzzle games, and platformer games. Unity was the most prominent game engine used to develop serious games. Personal computers (PCs) were the most common platforms used to play serious games. The most common algorithms used in the included studies were Support Vector Machine (SVM), Convolutional Neural Network (CNN), Artificial Neural Networks (ANN), and Random Forest (RF). The most common purposes of AI were the detection of disease and the evaluation of user's performance. The dataset size ranged from 36 to 795,600, with an average of about 52,124. The most common validation techniques used in the included studies were K-fold cross-validation and training test split validation. Accuracy was the most commonly used metric to evaluate the performance of AI models.

CONCLUSIONS

The last decade witnessed an increase in the development of AI-driven serious games for healthcare purposes and targeting various health conditions and leveraging multiple AI algorithms; this rising trend is expected to continue for years to come. While the evidence uncovered in this study shows promising applications of AI-driven serious games, larger and more rigorous, diverse, and robust studies may be needed to examine the efficacy and effectiveness of AI-driven serious games in different populations with different health conditions.

The effectiveness of serious games in improving processing speed among elderly people with cognitive impairment: A systematic review and meta-analysis (Preprint).. [DOI: 10.2196/preprints.36754]

BACKGROUND

Cognitive processing speed is known to decline by age. Processing speed refers to the time that an individual takes from receiving a stimulus to reacting to it. Serious games, which are video games employed for training and educational purposes, have the potential in improving processing speed. Numerous systematic reviews have summarized the evidence about the effectiveness of serious games in improving processing speed, but they are undermined by some limitations.

OBJECTIVE

This study aims to pool the evidence about the effectiveness of serious games in improving processing speed among elderly people with cognitive impairment.

METHODS

A systematic review of randomized controlled trials (RCTs) was undertaken. Two search sources were used in this review: 8 electronic databases as well as backward and forward reference list checking. Two reviewers independently checked the eligibility of the studies, extracted data from the included studies, and appraised the risk of bias and quality of the evidence. Evidence from the included studies was synthesized using a narrative and statistical approach (i.e., meta-analysis), as appropriate.

RESULTS

Out of 548 publications identified, 16 RCTs eventually met all eligibility criteria. Very low-quality evidence from 8 RCTs and 6 RCTs showed no statistically significant effect of serious games on the processing speed as compared with no or passive interventions groups (P=0.77) and conventional exercises (P=0.58), respectively. A subgroup analysis showed that both types of serious games (cognitive training games (P=0.26) and exergames (P=0.88)) are as effective as conventional exercises in improving processing speed.

CONCLUSIONS

There is no superiority of serious games over no or passive interventions and conventional exercises in improving processing speed among older adults with cognitive impairment. Yet, our findings remain inconclusive due to the low quality of the evidence, the small sample size in most included studies, and the paucity of studies included in the meta-analyses. Therefore, until more robust evidence is published, serious games should be offered or used as an adjunct to existing interventions. Further trials should be undertaken to investigate the effect of serious games that target specifically processing speed rather than cognitive abilities in general.

The effectiveness of serious games on the cognitive processing speed among elderly people with cognitive impairment: A systematic review and meta-analysis (Preprint)

Background

Human cognitive processing speed is known to decline with age. Human cognitive processing speed refers to the time that an individual takes from receiving a stimulus to reacting to it. Serious games, which are video games used for training and educational purposes, have the potential to improve processing speed. Numerous systematic reviews have summarized the evidence regarding the effectiveness of serious games in improving processing speed, but they are undermined by some limitations.

Objective

This study aimed to examine the effectiveness of serious games on the cognitive processing speed of an older adult population living with cognitive impairment.

Methods

A systematic review of randomized controlled trials (RCTs) was conducted. Two search sources were used in this review: 8 electronic databases and backward and forward reference list checking. A total of 2 reviewers independently checked the eligibility of the studies, extracted data from the included studies, and appraised the risk of bias and quality of the evidence. Evidence from the included studies was synthesized using a narrative and statistical approach (ie, meta-analysis), as appropriate.

Results

Of the 548 publications identified, 16 (2.9%) RCTs eventually met all eligibility criteria. Very-low-quality evidence from 50% (8/16) and 38% (6/16) of the RCTs showed no statistically significant effect of serious games on processing speed compared with no or passive intervention groups (P=.77) and conventional exercises (P=.58), respectively. A subgroup analysis showed that both types of serious games (cognitive training games: P=.26; exergames: P=.88) were as effective as conventional exercises in improving processing speed.

Conclusions

There is no superiority of serious games over no or passive interventions and conventional exercises in improving processing speed among older adults with cognitive impairment. However, our findings remain inconclusive because of the low quality of the evidence, the small sample size in most of the included studies, and the paucity of studies included in the meta-analyses. Therefore, until more robust evidence is published, serious games should be offered or used as an adjunct to existing interventions. Further trials should be undertaken to investigate the effect of serious games that specifically target processing speed rather than cognitive abilities in general.

Trial Registration

PROSPERO CRD42022301667; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=301667