The Success of Serious Games and Gamified Systems in HIV Prevention and Care: Scoping Review
Bibliographic record
Abstract
BACKGROUND: AIDS, which is caused by HIV, has long been one of the most significant global public health issues. Since the beginning of the HIV epidemic, various types of nonelectronic communication tools have been commonly used in HIV/AIDS prevention and care, but studies that apply the potential of electronic games are still limited. OBJECTIVE: We aimed to identify, compare, and describe serious games and gamified systems currently used in HIV/AIDS prevention and care that were studied over a specific period of time. METHODS: A scoping review was conducted into serious games and gamified systems used in HIV prevention and care in various well-known digital libraries from January 2010 to July 2021. RESULTS: After identifying research papers and completing the article selection process, 49 of the 496 publications met the inclusion criteria and were examined. A total of 32 articles described 22 different serious games, while 17 articles described 13 gamified systems for HIV prevention and care. CONCLUSIONS: Most of the studies described in the publications were conducted in the United States, while only a few studies were performed in sub-Saharan African countries, which have the highest global HIV/AIDS infection rates. Regarding the development platform, the vast majority of HIV/AIDS gaming systems were typically deployed on mobile devices. This study demonstrates the effectiveness of using serious games and gamified systems. Both can improve the efficacy of HIV/AIDS prevention strategies, particularly those that encourage behavior change.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".