Abstract
Background: Inadequate health literacy and low engagement challenge public health education. Digital serious games show potential to enhance health knowledge and attitudes. However, the comparative effectiveness of different game formats is unclear.
Objective: This study aimed to evaluate and compare the effectiveness of different digital serious game formats in improving public health knowledge and attitudes.
Methods: This systematic review and Bayesian network meta-analysis followed PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 guidelines. Seven databases (PubMed, CINAHL, Embase, PsycINFO, Cochrane Library, Scopus, and Web of Science) were searched from January 2000 to October 2025. An updated search in February 2026 identified no additional studies. Eligible studies were randomized controlled trials (RCTs) involving nonprofessional participants comparing digital serious games with traditional or noninteractive education. Standardized mean differences and 95% credible intervals were pooled using Bayesian network models with random effects. Subgroup analyses examined population characteristics, intervention duration, health topic, and delivery format. Risk of bias was assessed using the Cochrane risk-of-bias tool, and evidence certainty was rated using the Grading of Recommendations Assessment, Development and Evaluation.
Results: Forty randomized controlled trials from 19 countries (N=8764 participants) were included. Digital serious games significantly improved knowledge (standardized mean difference 0.66, 95% CI 0.32‐0.99; I²=89.1%) and attitudes (standardized mean difference 0.50, 95% CI 0.27‐0.76; I²=80.7%) compared with traditional education. Multisession interventions showed larger effects than single-session interventions for knowledge (0.76 vs 0.43) and attitudes (0.53 vs 0.30), with greater improvements among adolescents, nonpatient populations, and Asian studies. Network meta-analysis showed low heterogeneity (I²=8% for knowledge; 3% for attitudes). Mobile app–based, computer-offline, and web-based games ranked highest for knowledge; computer-offline, web-based, and virtual reality games ranked highest for attitudes. Evidence certainty was moderate for knowledge and low-to-moderate for attitudes.
Conclusions: Digital serious games improve public health knowledge and attitudes across diverse contexts. Using a Bayesian network meta-analysis of randomized controlled trials, this review compares the relative effectiveness of different game formats. Mobile app–based, computer-offline, and web-based games most improved knowledge; computer-offline, web-based, and virtual reality formats most improved attitudes. Multisession interventions were more effective than single-session ones, particularly for adolescents and nonpatient populations. These findings guide scalable digital health education strategies. Future research requires adequately powered trials, longer follow-up, and standardized frameworks.
Trial Registration: PROSPERO CRD420251056704; https://www.crd.york.ac.uk/PROSPERO/view/CRD420251056704
doi:10.2196/89281
Keywords
Introduction
Inadequate health knowledge and attitudes remain a significant barrier to achieving global health targets [], despite more than a century of organized public health education through mass media campaigns, school-based curricula, and community programs [,]. Health literacy gaps are evident across settings and income levels. In the European Union, 27% to 48% of adults have inadequate health literacy []. In China, only 31.87% of residents were health literate in 2024 [], with substantial disparities by residence and education. In the United States, fewer than one-third of school-aged children met grade-level reading standards, indicating persistent barriers to acquiring and applying health information [,]. These gaps undermine vaccination and screening, compromise chronic disease (CD) management and medication adherence [], and contribute to inequities in health outcomes and avoidable health care costs [,]. Addressing them requires strategies that can sustain engagement, broaden reach, and adapt to rapidly changing information environments.
Traditional public health education has improved awareness and behaviors, but its impact is limited by low long-term engagement, unequal access, and weak adaptability to rapidly changing communication environments [,]. The COVID-19 pandemic magnified these weaknesses, with school closures disrupting learning for more than 1.6 billion learners worldwide and exposing the fragility of knowledge dissemination systems []. This interruption also accelerated the adoption of digital health interventions, which offer scalable, interactive, and adaptable complements to conventional programs, extending reach, promoting equitable access, and strengthening public health knowledge, attitudes, and behaviors [,].
Within digital health interventions, digital serious games have emerged as a promising strategy to address persistent gaps in participation and impact [,]. By combining education with interactive and immersive play, they can sustain engagement and improve knowledge retention, supporting long-term behavioral change [,]. Their formats have progressed from desktop programs to mobile apps and online platforms and now increasingly incorporate virtual reality, augmented reality, artificial intelligence, and wearable devices [-]. This evolution has enabled broad application in public education, including infectious disease preparedness, CD management, and dementia awareness [-]. With their promise of scalability and equitable access [-], digital serious games are increasingly regarded as a complement to conventional approaches and digital tools, with potential to support prevention and health promotion at the population level.
Despite this promise, evidence remains insufficient to guide large-scale implementation. A 2020 scoping review mapped digital serious games for health education across health care providers, patients, and the public, showing expansion beyond disease-specific contexts but without assessing relative effectiveness across formats or populations []. Other reviews have concentrated on single conditions or target groups, such as diabetes [], upper limb rehabilitation [], or vaccination, offering little comparative insight []. Existing meta-analyses are similarly constrained, relying on pairwise comparisons that cannot establish the relative effectiveness of multiple intervention types [,]. For policymakers and educators, the central question is no longer whether digital serious games can work, but rather which formats are most effective, for which populations, and under what circumstances. No systematic evaluation has yet addressed these comparative questions, leaving a critical gap in the evidence needed to inform equitable and scalable public health education strategies.
To our knowledge, this systematic review and Bayesian network meta-analysis is the first to synthesize and compare the effectiveness of different formats of digital serious games in improving public health knowledge and attitudes and to examine how population characteristics, intervention duration, and contextual factors may moderate their impact.
Methods
Information Sources and Search Strategy
For this systematic review and network meta-analysis, we followed PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 and reported the search process in accordance with PRISMA-S (Preferred Reporting Items for Systematic Reviews and Meta-Analyses–Search extension). The completed PRISMA 2020, PRISMA 2020 Expanded, PRISMA-S, and PRISMA for Abstract checklists are provided in . The protocol was registered in PROSPERO (International Prospective Register of Systematic Reviews; CRD420251056704) []. All PRISMA 2020 items were reviewed against the manuscript to ensure complete and transparent reporting. We systematically searched 7 electronic databases (PubMed, CINAHL, Embase, PsycINFO, Cochrane Library, Scopus, and Web of Science) for studies published between January 1, 2000, and October 1, 2025, to identify any newly published studies meeting the eligibility criteria. Search terms combined keywords and Medical Subject Headings terms related to serious games, digital games, video games, public health education, knowledge, attitudes, and diseases. The search strategy was refined in accordance with Chapter 4.4 of the Cochrane Handbook to maximize sensitivity, including the expansion of controlled vocabulary and additional free-text synonyms. An updated search was conducted in February 2026, and no additional eligible studies were identified. Full search strategies for each database are provided in . Reference lists of relevant systematic reviews and meta-analyses were also screened for potentially eligible studies (). Gray literature sources and clinical trial registries were not searched separately.
All records were imported into Covidence (Veritas Health Innovation, Melbourne, Australia) for deduplication, screening, and data management. Two reviewers (DH and DW) independently screened titles, abstracts, and full texts, resolving disagreements by consensus or through consultation with a third reviewer (WM). Study authors were contacted when additional clarification was required.
Eligibility Criteria
Eligibility criteria followed the population, intervention, comparator, outcomes, and study design framework () []. We included randomized controlled trials (RCTs), cluster RCTs, and pilot RCTs of digital serious games designed to improve health-related knowledge or attitudes in nonprofessional populations, including children, adolescents, adults, informal caregivers, patients, and the general public. Interventions were required to be delivered via digital platforms, such as web-based applications, mobile apps, computer software, virtual reality, augmented reality, or robot-assisted systems. Comparators included no intervention, conventional education, or digital nongame tools. The primary outcomes were changes in knowledge or attitudes, assessed using validated instruments when reported.
We excluded studies evaluating nondigital games; interventions targeting clinical treatment, rehabilitation, or professional training; and studies that did not report at least 1 primary outcome. Nonrandomized studies, qualitative research, reviews, commentaries, protocols, and conference abstracts were also excluded.
Data Extraction
A standardized data extraction form was initially developed (DH) and subsequently refined (DH and DW) in accordance with the Cochrane Handbook for Systematic Reviews of Interventions []. The form was pilot-tested on a subset of studies to ensure reliability and reproducibility before full implementation. For each eligible trial, 2 reviewers (DH and DW) independently extracted data and verified the results with a third reviewer (WM). Extracted variables included study characteristics (identifier, year, country, design, and setting); participant characteristics (population group, mean age, sex distribution, sample size, and patient status); intervention details (type of digital serious game, delivery platform, educational content, duration, and follow-up, if reported); comparator details (type and format); and outcome measures (assessment tools, baseline and postintervention scores, and key findings related to knowledge or attitudes).
Outcomes
The primary outcomes were changes in health-related knowledge, including understanding of diseases, prevention, and health promotion, as well as changes in health-related attitudes, beliefs, perceptions, and intentions. Both outcomes were assessed using validated instruments when reported. No secondary outcomes were prespecified.
Bias Risk Assessment
The risk of bias for each included study was assessed using the revised Cochrane risk-of-bias tool for randomized trials tool with the appropriate version applied to individually randomized and cluster-randomized trials []. The tool evaluates potential bias in the following domains: the randomization process, deviations from intended interventions, missing outcome data, measurement of the outcomes, and selection of the reported results. Each trial was independently appraised by 2 reviewers (DH and DW) and categorized as low risk, some concerns, or high risk of bias. Any disagreements were resolved by consensus, with persistent discrepancies adjudicated by a third reviewer (WM).
Statistical Analysis
Pairwise Meta-Analysis
Pairwise meta-analyses were first performed to estimate pooled effects. For each study, mean values and SDs of intervention and control groups were extracted. When SDs were not directly reported, they were imputed from SEs, P values, t values, or 95% CIs. Studies without sufficient information for conversion were excluded from quantitative pooling.
Given the expected heterogeneity across populations, interventions, and outcome measures, pooled standardized mean differences (SMDs) with 95% CIs were calculated using a random-effects model with Hartung-Knapp adjustment to provide more robust variance estimation under conditions of limited study numbers and substantial between-study variability [].
Between-study heterogeneity was assessed using Cochran Q test and quantified using the I² statistic []. Robustness of pooled estimates in the pairwise meta-analyses was evaluated through sensitivity analyses, including sequential exclusion of individual studies, application of fixed-effect models, and removal of trials at high risk of bias. Prespecified subgroup analyses explored potential sources of heterogeneity, stratified by population group, patient status, health topic, duration, publication decade, geographical region, and sex distribution ().
Bayesian Network Meta-Analysis
Bayesian network meta-analysis was conducted using random-effects models implemented via Markov chain Monte Carlo simulation []. Although the included studies differed in populations, health topics, and intervention formats, all interventions were digital serious games targeting health knowledge or attitudes, supporting the conceptual comparability required for network meta-analysis. The analysis followed a predefined 8-step network meta-analysis workflow, including network construction, Bayesian model estimation, convergence diagnostics, inconsistency assessment, treatment ranking, estimation of relative treatment effects, calculation of prediction intervals, and robustness analysis. Analyses were performed in R software (version 4.5.2; R Foundation for Statistical Computing) using the gemtc and netmeta packages. Four Markov chains were run in parallel with different initial values, each with 5000 burn-in iterations followed by 20,000 sampling iterations. Convergence was assessed using trace plots and the Gelman-Rubin diagnostic, with a potential scale reduction factor below 1.05 indicating adequate convergence. Noninformative priors were specified for treatment effects, and vague priors were applied to the between-study heterogeneity parameter to minimize prior influence on the model estimates. Model fit was evaluated using the deviance information criterion [].
Pooled SMDs with corresponding 95% credible intervals (CrIs) were generated for all intervention comparisons. Prediction intervals were additionally calculated to reflect the expected range of effects in future studies. Local inconsistency was assessed using the node-splitting method [], and global inconsistency was evaluated by comparing the deviance information criterion between the consistency model and the unrelated mean effects model. Between-study heterogeneity was accommodated using the random-effects model and quantified using the between-study variance parameter and overall network I². Relative treatment rankings were estimated using the surface under the cumulative ranking curve (SUCRA), mean ranks, and rank probabilities. Sensitivity analyses were conducted by applying alternative prior distributions for the heterogeneity parameter to assess the robustness of the model estimates. Complete R scripts for both pairwise and network meta-analyses are provided in .
Evaluation of Publication Bias
Publication bias and small-study effects were assessed using the Egger regression test (P<.10) and comparison-adjusted funnel plots within the network meta-analysis framework. Interpretation of funnel plot asymmetry was undertaken cautiously, as between-study variability and model complexity may contribute to apparent asymmetry, independent of publication bias.
Certainty of Evidence
The certainty of the evidence was appraised using the GRADE (Grading of Recommendations, Assessment, Development, and Evaluation) framework, following the GRADE Working Group’s guidance. Certainty was evaluated across the domains of study design, risk of bias, inconsistency, indirectness, imprecision, and potential publication bias []. All included randomized trials, including pilot and cluster trials, were initially rated as high-certainty evidence. Downgrading was applied when serious limitations were identified, including high risk of bias, substantial unexplained heterogeneity, indirectness of the evidence in relation to the review question, imprecision of effect estimates, or potential publication bias, in accordance with GRADE guidance []. Potential publication bias was also assessed. Final ratings were categorized as high, moderate, low, or very low certainty.
Results
Study Selection
The database search yielded 9269 records, and a further 47 records were identified through reference searches of relevant systematic reviews and meta-analyses. After the removal of 5352 duplicates, 3917 records were screened by title and abstract (). Of these, 3816 records were excluded, and 1 report could not be retrieved because the full text was unavailable. A total of 88 full-text articles were assessed for eligibility, of which 48 were excluded for reasons summarized in . In total, 40 studies were included in the systematic review and 30 in the Bayesian network meta-analysis ().
Study Characteristics
A total of 40 RCTs published between 2000 and 2025 were included (). Research output increased markedly after 2020, with 5 (12.5%) studies published before 2010 [-,], 10 (22.5%) between 2010 and 2019 [-,-], and 25 (62.5%) since 2020 [-,-]. Studies were conducted across 19 countries, most frequently in the United States (n=13, 32.5%) [-,,,,,,,,,], followed by China (n=4, 10%) [,,,], Iran (n=4, 10%) [,,,], and the Netherlands (n=3, 7.5%) [,,]. All studies adopted a randomized controlled design, including 10 (25%) pilot trials and 5 (12.5%) cluster trials.
The design and characteristics of digital serious games are summarized in . Interventions evolved with technological development. Early studies used computer-offline serious games (n=7, 17.5%) [,-,,] and video-based serious games (n=6, 15%) [,,,,,]. Later studies adopted computer or web-based online games (n=8, 20%) [,,,,,,,] and mobile-app games (n=13, 32.5%) [,-,-,,,,,,]. Since 2020, immersive formats such as virtual-reality serious games (n=3, 7.5%) [,,] and augmented-reality serious games (n=2, 5%) [,] have become more common, and robot-assisted serious games (n=1, 2.5%) [] were included from 2017. Three games, Watch, Discover, Think, and Act [,], Re-Mission [,], and Dental Detective [,], were each evaluated in 2 trials due to updated versions or applications in different populations. All iterations were therefore included in the synthesis.
A total of 8764 participants were included (intervention =4374; control =4390). Twelve studies (30%) targeted children, 11 (27.5%) adolescents, 11 (27.5%) adults, and 6 (15%) mixed populations (eg, children and adolescents or adolescents and adults). Thirteen studies (32.5%) included more women than men, 9 (n=9, 22.5%) were gender-balanced, and 18 (45%) included a higher proportion of men.
The most frequent educational topics were CD education (n=8, 20%), cancer education (n=6, 15%), sexual and reproductive health education (n=6, 15%), and nutrition and healthy lifestyle education (n=6, 15%). Other topics included vaccination and infectious-disease prevention (n=4, 10%), oral health education (n=4, 10%), medication and antimicrobial-resistance education (n=3, 7.5%), and psychological and developmental health education (n=3, 7.5%).
Among the 40 studies, 35 (87.5%) reported knowledge outcomes, of which 28 (80%) showed significant improvement and 7 (20%) found no between-group difference [,,,,,,]. A total of 22 (55%) studies assessed attitude outcomes, with 15 (68.2%) showing positive changes and 7 (31.8%) showing no improvement [,,,,,,]. A total of 30 (75%) studies were included in the Bayesian network meta-analysis [-,], including those reporting knowledge outcomes (n=27, 67.5%) [-,-,-,,] and attitude outcomes (n=16, 40%) [,,-,-,,,-].
| Study and outcome | Study design | Country | Population | Age (y), mean (SD) | Female, % | Patient status | Intervention | Comparator | Sample size (IG/CG) | Health topic | Duration | Baseline | Key findings |
| Aljafari et al [], 2017 | |||||||||||||
| RCT | United Kingdom | Children | 6.5 (1.55) | 45 | Patient | CF | FE | 55/54 | OH | Single session | IG 56.0 (9.6); CG 53.4 (10.6) | Knowledge increased in both groups, with no significant differences observed between them | |
| NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | No significant changes were observed in perceived susceptibility or perceived importance | |
| Aljafari et al [], 2022 | |||||||||||||
| RCT | Jordan | Children | 6.5 (0.5) | 48 | Nonpatient | CF | NI | 144/139 | OH | Single session | IG 56.5 (5.9); CG 57.2 (4.9) | Knowledge improved in the intervention group, but no significant difference was found between groups at follow-up | |
| NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | Attitudes, intentions, and self-efficacy improved in the IG and were sustained for 6 mo, with no significant change in HIV testing uptake | |
| Bartholomew et al [], 2000 | |||||||||||||
| Pilot RCT | United States | Children | IG 9.8 (2.1); CG 9.5 (1.9) | 35 | Patient | CF | NI | 29/25 | CD | Multiple sessions | IG 76.1 (12.8); CG 78.4 (14.5) | Knowledge and self-management behaviors significantly improved in the IG compared with controls, with greater gains observed in younger children | |
| NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | The intervention reduced emergency visits and hospitalizations among participants with moderate-to-severe asthma | |
| Beale et al [], 2007 | |||||||||||||
| RCT | United States | Adolescents | IG 15.79 (2.62); CG 16.0 (2.89) | 32 | Patient | VI | AC | 191/169 | Cancer | Multiple sessions | IG 59.31 (16.9); CG 59.73 (15.6) | Knowledge increased in both groups, with the Re-Mission game showing greater gains than the CG | |
| Beaujean et al [], 2016 | |||||||||||||
| Cluster RCT | Netherlands | Children | NA | 50 | Nonpatient | CO | NI | 199/372 | ID | Single session | NA | Knowledge improved across all groups, with no significant differences between the game, leaflet, and CGs | |
| Bloomfield et al [], 2025 | |||||||||||||
| Cluster RCT | Australia | Adolescents | NA | 50 | Nonpatient | AP | FE | 442/346 | ID | Single session | NA | Knowledge gains in the IG were maintained at 3- and 6-mo follow-up, while the CG remained stable | |
| Boomer et al [], 2024 | |||||||||||||
| RCT | United States | Adolescents | 15.4 (1.2) | 48 | Nonpatient | CO | OT | 145/142 | SRH | Multiple sessions | NA | Knowledge increased in the IG compared with controls and was sustained over 12 months | |
| Carcioppolo et al [], 2022 | |||||||||||||
| RCT | United States | Adults | 47.3 (17.6) | 53 | Nonpatient | CO | NI | 100/102 | Cancer | Single session | IG 6.75 (2.6); CG 6.13 (2.2) | The game improved melanoma identification compared with the CG | |
| NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | IG 5.89 (1.0); CG 5.65 (1.1) | The game enhanced self-efficacy and promoted more positive prevention attitudes | |
| Espinosa-Curiel et al [], 2022 | |||||||||||||
| Pilot RCT | Mexico | Children | 9.9 (0.8) | 59 | Nonpatient | VI | FE | 15/12 | NHL | Multiple sessions | IG 5.7 (2.4); CG 4.08 (1.6) | The game improved children’s knowledge of physical activity compared with controls | |
| NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | IG 3.07 (0.8); CG 2.3 (1.4) | Attitudes toward sexual health improved, particularly among boys and younger adolescents | |
| Fadda et al [], 2017 | |||||||||||||
| RCT | Italy | Adults | 34.2 (4.7) | 94.60 | Nonpatient | AP | NI | 48/44 | Vaccination | Multiple sessions | 10.3 (2.1) | Knowledge scores increased significantly in the gamified app group compared with the CG | |
| NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | 3.4 (0.6) | Vaccination intention and decision confidence improved in the gamified app group, with no significant change in vaccination attitude or recommendation intention | |
| Fiellin et al [], 2017 | |||||||||||||
| RCT | United States | Adolescent | 12.5 (1.1) | 50 | Nonpatient | VI | AC | 166/165 | SRH | Multiple sessions | NA | Knowledge improved in the IG, including greater awareness of menstrual hygiene management and contraceptive methods | |
| Froome et al [], 2020 | |||||||||||||
| Pilot RCT | Canada | Children | 9.0 (0.8) | 38 | Nonpatient | AP | NI | 39/34 | NHL | Multiple sessions | IG 10.3 (2.9); CG 10.2 (3.1) | Knowledge scores increased significantly in the IG compared with controls, with notable gains in fruits, protein, and whole grains knowledge | |
| Ghadam et al [], 2023 | |||||||||||||
| RCT | Iran | Adolescents | 14.2 (0.7) | 100 | Nonpatient | AP | TE | 80/80 | NHL | Multiple sessions | IG 47.9 (9.9); CG 46.6 (7.8) | Knowledge scores increased significantly in the IG compared with controls | |
| NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | IG 60.0 (6.7); CG 57.6 (12.9) | Attitude scores were higher in the IG compared with the CG | |
| Goodman et al [], 2024 | |||||||||||||
| Pilot RCT | United States | Children | 10.9 (2.9) | 50 | Patient | AR | VE | 26/27 | CD | Single session | IG 9.4 (3.1); CG 9.1 (3.0) | Knowledge increased in both groups, with no significant difference between game and video education | |
| Haruna et al [], 2018 | |||||||||||||
| Cluster RCT | Malaysia | Children and adolescents | 13.6 (1.1) | 50 | Nonpatient | CF | TE | 40/40 | SRH | Multiple sessions | IG 62.5 (12.3); CG 55.4 (11.8) | Knowledge scores were significantly higher in the game-based group compared with traditional education | |
| NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | Attitude, motivation, and engagement were higher in the game-based learning group than in the CG | |
| Henkemans et al [], 2017 | |||||||||||||
| Pilot RCT | Netherlands | Children | 10.5 (2.0) | 50 | Patient | RB | TA | 14/13 | CD | Multiple sessions | IG 17.2 (4.1); CG 13.5 (3.8) | Knowledge scores increased significantly in the robot-assisted game group compared with controls | |
| NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | Autonomy, competence, relatedness, motivation, and engagement were higher in the robot-assisted group than in the CG | |
| Huang et al [], 2025 | |||||||||||||
| RCT | China | Adults | 63.5 (11.7) | 24.5 | Patient | AP | FE | 51/51 | CD | Multiple sessions | IG 6.14 (1.8); CG 7.06 (1.8) | Knowledge scores improved significantly in the IG compared with the CG at post test | |
| Huang et al [], 2024 | |||||||||||||
| RCT | Singapore | Adults | 36.7 (10.4) | 57 | Nonpatient | AP | NI | 90/90 | MAR | Single session | IG 8.5 (1.6); CG 8.3 (1.7) | Knowledge scores were higher in the app-based serious game group compared with the CG | |
| Joubert et al [], 2016 | |||||||||||||
| Pilot RCT | France | Adolescents | 15.5 (1.5) | 48 | Patient | CO | TA | 37/34 | CD | Multiple sessions | IG 64.8 (12.3); CG 63.7 (11.9) | Diabetes-related knowledge increased significantly in the IG compared with controls | |
| NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | IG 58.6 (14.1); CG 59.4 (13.7) | Positive trends were observed in self-management attitudes and behaviors, though less pronounced than knowledge gains | |
| Kato et al [], 2008 | |||||||||||||
| RCT | United States | Adolescents and adults | NA | 32.3 | Patient | VI | NI | 164/148 | Cancer | Multiple sessions | IG 0.59 (0.2); CG 0.63 (0.2) | Cancer-related knowledge improved significantly in the IG compared with the CG | |
| Khalil et al [], 2016 | |||||||||||||
| RCT | United States | Adolescents | NA | 50 | Nonpatient | VI | EM | 166/50 | Cancer | Single session | 2.92 (1.2) | Participants in the IG reported higher perceived susceptibility to cancer than controls, and the effect was sustained for 20 d | |
| Koohmareh et al [], 2021 | |||||||||||||
| RCT | Iran | Adults | IG 52.6 ( 8.4); CG 53.3 (7.9) | 56.7 | Patient | AP | EM | 30/30 | NHL | Multiple sessions | IG 7.27 (2.6); CG 7.47 (2.4) | Knowledge increased significantly in the IG compared with the CG | |
| Koniou et al [], 2025 | |||||||||||||
| RCT | Greece | Adults | 20.8 (2.5) | 70.8 | Nonpatient | VR | NI | 51/51 | PDH | Single session | IG 36.92 (3.2); CG 33.14 (3.1) | Knowledge scores improved significantly in the VR group compared with the CG | |
| NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | IG 77.18 (6.2); CG 71.29 (6.0) | Attitudes toward autism improved significantly in the VR group compared with controls | |
| Kumar et al [], 2004 | |||||||||||||
| Pilot RCT | United States | Children and adolescents | 13.6 (2.5) | 45 | Patient | CF | NI | 19/21 | CD | Multiple sessions | NA | Knowledge scores increased significantly in IG compared with CG | |
| Kumar RS et al [], 2022 | |||||||||||||
| RCT | India | Adolescents | 13.62 (1.37) | 42 | Nonpatient | VI | TE | 48/42 | OH | Single session | IG 7.29 (1.7); CG 7.30 (1.3) | Knowledge increased significantly in the IG compared with traditional education | |
| Liu et al [], 2024 | |||||||||||||
| Pilot RCT | China | Children | 7.09 (0.9) | 38.9 | Nonpatient | AR | WN | 18/18 | Cancer | Multiple sessions | IG 6.17 (2.3); CG 6.56 (2.1) | Knowledge improved significantly in the IG compared with controls | |
| NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | IG 4.98 (0.6); CG 4.95 (0.6) | Attitudes improved significantly in the IG compared with controls | |
| Mack et al [], 2020 | |||||||||||||
| Cluster RCT | Germany | Children | 10.5 (0.5) | 50 | Nonpatient | CO | TE | 172/144 | NHL | Multiple sessions | IG 20.77 (4.2); CG 20.28 (3.8) | Knowledge improved significantly in the IG compared with controls after the intervention | |
| Maddison et al [], 2022 | |||||||||||||
| Pilot RCT | New Zealand | Children and adolescents | 11.2 (1.8) | 70 | Patient | AP | WN | 15/8 | CD | Multiple sessions | IG 4.6 (6.6); CG 5.8 (2.6) | No significant group differences were found; the intervention was perceived as engaging, but effects were not sustained | |
| Maganty et al [], 2018 | |||||||||||||
| Pilot RCT | United States | Adults | 59.1 (15.5) | NA | Nonpatient | CO | NI | 20/20 | Cancer | Single session | IG 2.3 (1.1); CG 2.2 (1.0) | Confidence in melanoma recognition improved significantly in the game group compared with no intervention | |
| Nazmi et al [], 2025 | |||||||||||||
| RCT | Iran | Adolescents | 12.77 (0.5) | 100 | Nonpatient | CO | NI | 45/45 | PDH | Multiple sessions | IG 5.11 (1.3); CG 5.22 (1.0) | Knowledge scores increased significantly in the IG compared with controls | |
| NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | IG 61.9 (7.3); CG 57.6 (6.3) | Practice scores improved significantly in the IG compared with the CG | |
| Nowak et al [], 2020 | |||||||||||||
| RCT | United States | Adults | NA | NA | Nonpatient | VR | NI | 81/81 | Vaccination | Single session | NA | The VR intervention enhanced vaccine confidence, beliefs about community immunity, and vaccination intention compared with the CG | |
| Pouls et al [], 2022 | |||||||||||||
| RCT | Netherlands | Adults | 61.2 (11.3) | 73 | Patient | AP | TA | 110/111 | MAR | Multiple sessions | IG 5.0 (5.1); CG 5.8 (4.3) | No significant differences were found in medication beliefs or adherence between intervention and CGs | |
| Raj et al [], 2025 | |||||||||||||
| RCT | India | Adolescents | 16.7(0.1) | 100 | Nonpatient | AP | NI | 769/928 | SRH | Multiple sessions | NA | Knowledge improved significantly in the IG compared with the CG | |
| Shegog et al [], 2001 | |||||||||||||
| RCT | United States | Children | 10.9 (1.1) | 34 | Patient | CF | NI | 38/33 | CD | Single session | IG 18.6 (6.5); CG 15.7 (5.8) | The IG showed greater improvement in asthma self-management knowledge compared with the CG | |
| NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | IG 53.4 (9.7); CG 51.6 (9.9) | The IG demonstrated higher self-efficacy and more positive attributions regarding asthma management than the CG | |
| Tan et al [], 2022 | |||||||||||||
| RCT | Singapore | Adults | 35.7 (9.6) | 59.6 | Nonpatient | CO | WN | 178/196 | Vaccination | Single session | IG 10.0 (2.3); CG 10.0 (2.3) | Knowledge scores increased in both groups, with no significant difference between them | |
| NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | IG 12.5 (1.2); CG 12.3 (1.5) | Attitude scores increased in both groups, with no significant difference between them | |
| Tang et al [], 2022 | |||||||||||||
| RCT | China | Adolescents | 13.5 (0.6) | 50 | Nonpatient | AP | TE | 50/46 | SRH | Single session | IG 11.2 (3.4); CG 10.9 (3.2) | Knowledge scores increased significantly in the IG compared with controls | |
| NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | The intervention group showed more positive attitudes toward HIV prevention than the CG | |
| Vandeweerdt et al [], 2022 | |||||||||||||
| RCT | Belgium | Adults | NA | NA | Nonpatient | VR | WN | 208/208 | Vaccination | Single session | NA | Knowledge and perceived health awareness improved significantly in the IG compared with the CG | |
| Wang et al [], 2025 | |||||||||||||
| Cluster RCT | China | Children | NA | 48 | Nonpatient | CF | NI | 40/39 | NHL | Multiple sessions | IG 8.93 (2.4); CG 8.38 (2.1) | The intervention enhanced vaccination intention and collective responsibility compared with text-based education | |
| Whiteley et al [], 2018 | |||||||||||||
| RCT | United States | Adolescents and adults | 22.4 (2.5) | 21.3 | Patient | AP | NI | 32/29 | SRH | Multiple sessions | IG 2.44 (1.2); CG 3.00 (1.0) | The IG showed improvements in HIV knowledge, but the difference was not significant | |
| NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | IG 17.94 (4.0); CG 18.21 (5.5) | The IG reported slightly higher self-efficacy for ART use compared with the CG, but the difference was not significant | |
| Zolfaghari et al [], 2021 | |||||||||||||
| RCT | Iran | Adolescents and adults | 36.4 (4.7) | 100 | Nonpatient | AP | WN | 46/47 | OH | Multiple sessions | IG 11.3 (1.9); CG 10.5 (2.1) | The IG had higher knowledge scores than the CG at posttest and 3-month follow-up | |
aIG: intervention group.
bCG: control group.
cRCT: randomized controlled trial.
dCF: computer offline serious games delivered via PC, tablet, or DVD.
eFE: face-to-face education.
fOH: oral health.
gNA: not available.
hNI: no intervention.
iCD: chronic diseases.
jVI: video-based serious games.
kAC: active control (non–health-related video game).
lCO: computer or web-based online serious games.
mID: infectious diseases.
nAP: mobile app serious games.
oOT: other serious games.
pSRH: sexual and reproductive health.
qNHL: nutrition and healthy lifestyle.
rTE: traditional classroom or lecture-based education.
sAR: augmented reality serious games.
tVE: educational videos without gamified elements.
uRB: robot-assisted serious games.
vMAR: medication and antimicrobial resistance.
wTA: treatment as usual.
xEM: educational materials (leaflets, booklets, or pamphlets).
yVR: virtual reality serious games.
zPDH: psychological and developmental health.
aaWN: web-based nongame education.
abART: antiretroviral therapy.
Risk-of-Bias Results
Among the 40 included RCTs, methodological quality was generally moderate to high (). For the 35 individually randomized trials, low risk of bias was most frequently observed in the randomization process (25/35, 71.4%), deviations from intended interventions (31/35, 88.6%), and measurement of outcomes (33/35, 94.3%). “Some concerns” were mainly identified in the selection of reported results (14/35, 40%) and overall bias judgment (24/35, 68.6%), mainly due to the absence of preregistered protocols or incomplete reporting of secondary outcomes. One trial was rated as high risk of bias in the domain of deviations from intended interventions because participants and facilitators were not blinded during gameplay [], and another trial was judged as high risk for the same reason, with substantial researcher involvement potentially influencing participant responses []. No other study was rated as high risk in any domain. Among the 5 cluster-randomized trials, methodological quality was similarly high; all studies were rated as low risk for the randomization process and missing outcome data, with only minor concerns regarding the selection of the reported result. Taken together, 31.4% (11/35) of studies were judged as low risk, 68.6% (24/35) as having some concerns, and none as high risk.
Results of the Meta-Analyses
Across the 40 included studies, 27 reported data on knowledge outcomes, and 16 on attitude outcomes [-], with 21 trials contributing to both outcome categories. Compared with controls, digital serious games significantly improved public health knowledge (SMD=0.66; 95% CI 0.32‐0.99; P<.001; I²=89.1%) and showed a moderate positive effect on health attitudes (SMD=0.50; 95% CI 0.27‐0.76; P<.001; I²=80.7%) (). Considerable heterogeneity was observed across studies (knowledge: Q=239.23; P<.001; attitude: Q=77.75; P<.001). Funnel plots showed mild asymmetry for both outcomes (). Egger’s regression test indicated potential small-study effects for knowledge (P=.006) but not for attitude (P=.05).
The overall certainty of evidence, assessed using the GRADE framework, was moderate for both knowledge and attitude outcomes. Although substantial heterogeneity was present, the direction of effects remained consistent across studies, and subgroup analyses explained much of the observed variation by intervention duration, population type, and health topic. Minor methodological concerns related to randomization, allocation concealment, and small-study effects contributed to downgrading from high to moderate certainty. Indirectness and imprecision did not materially affect the certainty ratings, as all included trials directly addressed the review question and yielded precise pooled estimates ().
Subgroup and Moderator Analyses
Subgroup analyses were undertaken to explore potential sources of heterogeneity across intervention duration, study region, patient status, health topic, publication year, population type, and sex. Across both knowledge and attitude outcomes, multisession interventions consistently yielded larger effects than single-session exposure (knowledge: χ²1=4.04; P=.04; attitude: χ²1=4.97; P=.03), indicating that repeated game participation reinforced learning and attitude internalization. Effect sizes were also greater among nonpatient populations than among patients (knowledge: χ²1=7.13; P=.008; attitude: χ²1=9.97; P=.002), suggesting that individuals without disease burden may be more receptive to health information. Considerable variation was observed across health topics (knowledge: χ²6=120.32; P<.001; attitude: χ²6=176.14; P<.001), with cancer- and CD-focused games achieving the highest impact, whereas effects were smaller for vaccination and oral health education. Regional differences were modest but favored studies conducted in Asia (χ²4=10.18; P=.04). Publication year, age group, and sex composition did not consistently influence effect estimates ().
Bayesian Network Meta-Analysis
The knowledge network comprised 14 interventions, including 7 types of digital serious games and 7 traditional or nongame comparators, forming 26 direct comparisons and 5 closed loops (). Between-study heterogeneity in the network meta-analysis was low (τ=2.75; 95% CrI 1.58‐4.69; τ²=7.57; network I²=8%). Digital serious games produced the greatest improvements in knowledge outcomes (). Mobile app–based games showed significantly higher effects than traditional education (mean difference 5.46; 95% CrI 2.00‐9.39), treatment as usual (4.87; 95% CrI 1.06‐9.37), and no intervention (2.82; 95% CrI 0.09‐5.79). Computer-offline and web-based serious games also achieved superior gains compared with traditional education (4.87; 95% CrI 0.65‐7.95 and 4.12; 95% CrI 0.79‐6.05, respectively), whereas robot-assisted, virtual reality, and video-based games showed weaker comparative effects. Bayesian ranking analyses indicated that mobile app–based, computer-offline, and web-based serious games consistently ranked highest for improving knowledge outcomes (). Prediction intervals were calculated to reflect the expected range of treatment effects in future studies (). No significant inconsistency between direct and indirect evidence was detected in node-splitting analyses (all P>.05; ), and the consistency and unrelated mean effects models showed nearly identical model fit (Deviance Information Criterion; DIC=109.899 vs 109.894; ΔDIC=0.005). Sensitivity analyses using alternative prior distributions produced nearly identical SUCRA values and treatment rankings, indicating robust results ().
The attitude network comprised 11 interventions, including 6 types of digital serious games and 5 traditional or nongame comparators, forming 16 direct comparisons and 3 closed loops (). Between-study heterogeneity in the network meta-analysis was low (τ=3.19; 95% CrI 1.42‐6.53; τ²=10.20; network I²=3%). Digital serious games produced greater improvements in health attitudes compared with traditional or nongame education (). Computer-offline, web-based, and virtual reality serious games showed the largest improvements in attitude outcomes compared with traditional education (13.28; 95% CrI 3.30‐22.92; 11.30; 95% CrI 1.53‐21.00; and 11.61; 95% CrI 1.33‐21.74, respectively), whereas video-based, face-to-face, and no-intervention conditions showed weaker or inconsistent effects. Bayesian ranking analyses indicated that computer-offline, web-based, and virtual reality serious games ranked highest for improving health attitudes (). Prediction intervals were calculated to reflect the expected range of treatment effects in future studies (). No significant inconsistency between direct and indirect evidence was detected in node-splitting analyses (all P>.05; ), and the consistency and unrelated mean effects models showed similar model fit (DIC=58.47 vs 60.12; ΔDIC=1.65). Sensitivity analyses using alternative prior distributions produced nearly identical SUCRA values and treatment rankings, indicating that the results were robust ().
Discussion
Principal Findings
In this systematic review and Bayesian network meta-analysis of 40 RCTs involving 8764 participants, digital serious games were associated with improvements in public health knowledge and attitudes compared with traditional or noninteractive education. Greater effects were observed with multisession interventions. Subgroup analyses indicated stronger responses among adolescents and nonpatient populations, particularly in studies conducted in Asia and in interventions addressing psychological or developmental health topics. Network meta-analysis further demonstrated differences across delivery formats: mobile app–based games ranked highest for knowledge outcomes, whereas computer-offline and web-based formats showed greater relative effectiveness for attitude change, while video-based and traditional education formats consistently ranked lower. By integrating pairwise and network meta-analysis within a cross-disease framework, this study enables comparative evaluation across formats and population contexts, addressing limitations of prior reviews restricted to single conditions or pairwise comparisons [-].
Despite substantial heterogeneity observed in the pairwise meta-analysis, sensitivity analyses confirmed the stability of pooled estimates, indicating that the variability primarily reflects contextual and population-level differences rather than methodological bias. Differences across health topics highlight the influence of content relevance and narrative structure in shaping learning outcomes. Interventions targeting psychological or developmental health often incorporate self-management scenarios and emotionally salient components that may enhance perceived relevance and retention []. The advantage of repeated exposure is consistent with reinforcement and memory consolidation processes, whereas single-session interventions may offer insufficient opportunities for feedback and integration. Larger improvements among nonpatient populations may relate to lower baseline knowledge and reduced ceiling effects []. The heterogeneity observed, therefore, reflects meaningful contextual differentiation rather than instability of effect estimates.
These findings should also be interpreted considering methodological factors, including the risk of bias and the certainty of evidence. Risk-of-bias assessment using the revised Cochrane risk-of-bias tool for randomized trial tool indicated that several studies had methodological limitations that may have influenced effect estimates. The overall certainty of evidence assessed using the GRADE framework was rated as moderate for knowledge outcomes and low-to-moderate for attitudes. In addition, while CIs represent the average effect across studies, prediction intervals reflect the potential variation in effects across different implementation settings, indicating that intervention effects may vary depending on population characteristics and context.
Beyond these methodological considerations, the findings also suggest several interpretive mechanisms underlying the educational effects of serious games. Although the network meta-analysis suggested relatively consistent comparative effects across formats, the pooled estimates and ranking probabilities should still be interpreted with caution because the included studies varied in populations, health topics, and intervention characteristics. From a structural perspective, the network findings further suggest that the educational impact of serious games may operate along complementary cognitive and affective pathways. Interventions incorporating adaptive feedback, progressive challenge, and opportunities for repeated engagement are more likely to activate sustained cognitive processing, thereby facilitating the consolidation and integration of information []. In contrast, formats characterized by low interactivity and fixed content delivery may limit learner control and cognitive activation []. With respect to attitudinal outcomes, narrative-driven and role-playing designs appear more conducive to attitude change through mechanisms of perspective-taking and emotional engagement [], while immersive simulations may intensify affective involvement through first-person experiential framing. Together, these findings indicate that knowledge gains are primarily supported by cognitive reinforcement processes, whereas attitudinal change is more closely linked to emotional immersion and social resonance. The integration of both pathways may, therefore, strengthen the overall educational impact of serious games in public health contexts.
Importantly, the relative balance between cognitive structure and experiential immersion is not only a theoretical distinction but also a practical one. Designs that prioritize deep affective engagement often require greater technological resources and infrastructural investment, whereas cognitively structured, feedback-oriented formats may be more feasible for large-scale dissemination []. This interplay between experiential intensity and implementation feasibility becomes particularly salient in population-level public health education [].
Consistent with this structural tension, the network analysis highlights trade-offs between experiential depth and scalability. Virtual-reality and robot-assisted formats may achieve high experiential fidelity yet face barriers related to cost and accessibility, while mobile and web-based interventions enable broader reach, albeit sometimes with reduced experiential richness []. These findings suggest that innovation should not focus solely on increasing technical sophistication but rather on developing adaptive architectures capable of preserving feedback, learner autonomy, and emotional resonance across diverse delivery contexts [,]. Achieving equilibrium between structural fidelity and affective relevance may be essential for translating short-term knowledge improvements into sustained behavioral and attitudinal change in population health education.
Implications for Practice and Research
Evidence from this review suggests that digital serious games can extend the reach of public health education in settings where conventional programs face limitations in coverage or engagement. The consistent advantages of mobile and web-based formats over resource-intensive technologies indicate that scalability depends more on accessibility and design efficiency than on technical sophistication [,]. In practice, prioritizing adaptive, feedback-driven mobile platforms may yield greater population impact than investing in high-fidelity but low-reach systems, such as virtual reality or robotics [,]. At the same time, stronger effects observed among adolescents and women highlight both the potential for targeted implementation and the need to address equity gaps among patients and older adults who demonstrate lower engagement. Inclusive design, tailored difficulty adjustment, and integration within existing community or school-based programs may help reduce digital exclusion and sustain long-term participation [,].
Beyond implementation considerations, the current evidence base remains fragmented, with substantial variation in populations, intervention formats, and outcome measures. Most randomized trials are small and exploratory, often limited to school-aged or student samples. Future research should prioritize adequately powered trials involving adult and older populations and incorporate medium- and long-term follow-up to determine whether gains in knowledge and attitudes translate into sustained behavioral change [].
A structured implementation framework is also needed to define minimal effective exposure, establish evaluation benchmarks, and clarify ethical standards for educational gaming [,]. Standardization represents a critical next step. Although thematic diversity in public health education is expected, a unified evaluation framework should be developed to assess usability, implementation quality, and core design attributes—such as interactivity, feedback mechanisms, immersion, and accessibility—using validated instruments [,]. Establishing shared data infrastructures that systematically document intervention characteristics, engagement metrics, and outcome measures would further enhance comparability and enable cumulative synthesis across studies. Strengthening these methodological and infrastructural foundations will be essential for advancing serious game research from isolated trials toward a coherent and reproducible scientific field.
Limitations
The interpretation of this synthesis should take into account the methodological and conceptual variability among the included trials, which likely contributed to the substantial heterogeneity observed in the pairwise meta-analysis. Health education topics, measurement instruments, and feedback structures differed widely, complicating direct comparison of effect sizes across studies []. Although subgroup analyses identified several sources of heterogeneity, the diversity in outcome definitions and analytical strategies inevitably limited the precision of pooled estimates.
In several recent studies, particularly those published after 2020, technological advancements have led serious games, such as Food Adventure Quest and Amoo, to evolve beyond stand-alone formats, increasingly integrating complementary educational components, such as video segments and classroom instruction [,]. Although this convergence complicates the identification of the game’s independent effects, it reflects the growing trend toward multimodal approaches in health education. It indicates that serious games are becoming embedded components of broader digital learning ecosystems that combine interactive games, web-based modules, and instructor-led components.
Reporting transparency also varied across studies. Protocol preregistration and complete reporting of secondary outcomes were often absent, resulting in the overall methodological quality being rated as moderate, despite generally low risks of bias in randomization, intervention delivery, and outcome measurement []. These limitations indicate that the main threat to internal validity stems from incomplete documentation rather than flawed trial conduct, underscoring the need for preregistered protocols and comprehensive reporting standards in future evaluations of serious games.
Conclusions
This systematic review and Bayesian network meta-analysis of RCTs provides a comprehensive evaluation of the educational impact of digital serious games in public health. Unlike earlier reviews that focused on individual interventions or specific health topics, this study compares multiple digital serious game formats within a unified analytical framework. Across 40 trials, mobile-, computer-, and web-based formats generally produced the greatest improvements in knowledge outcomes, while computer-, web-, and virtual reality–based formats showed stronger effects for attitude change. Multisession interventions sustained learning and attitudinal change more effectively than single-session exposure, highlighting the importance of reinforcement and continued engagement. The overall certainty of evidence was moderate, reflecting methodological heterogeneity across trials. These findings contribute comparative evidence to the field of digital health education and offer practical guidance for selecting scalable serious game interventions in real-world public health programs. Strengthening implementation strategies, standardizing outcome evaluation, and extending trials to underrepresented adult and older populations are important next steps.
Acknowledgments
We would like to thank Professor Wendy Moyle for funding support of this study. In addition, we thank all corresponding authors of the included studies for providing additional data and clarifications. The first author, DH, acknowledges the China Scholarship Council for scholarship support during this research. No generative AI tools were used to generate scientific content, analyses, results, or interpretations.
Funding
This study was funded by consultancy research funds awarded to Professor Wendy Moyle, Griffith University.
Data Availability
All extracted data and analytical codes used in this study are available from the corresponding author upon reasonable request. Unpublished data obtained from individual researchers will be shared only with their explicit permission.
Conflicts of Interest
None declared.
Multimedia Appendix 1
Full electronic search strategies for all databases used in this systematic review, including PubMed, CINAHL, Embase, APA PsycINFO, Cochrane CENTRAL, Scopus, and Web of Science.
DOCX File, 31 KBMultimedia Appendix 2
Detailed eligibility criteria for study inclusion and exclusion in this systematic review, including population, intervention, comparator, outcomes, study design, language, and publication type.
DOCX File, 13 KBMultimedia Appendix 3
Subgroup classification and coding schema used for subgroup analyses in this systematic review.
DOCX File, 13 KBMultimedia Appendix 4
R scripts used to conduct the pairwise meta-analysis and Bayesian network meta-analysis, including data preparation, model fitting, subgroup analyses, and sensitivity analyses.
DOCX File, 16 KBMultimedia Appendix 5
Detailed characteristics of the included studies, including study design, sample size, population characteristics, intervention features, and outcome measures.
DOCX File, 40 KBMultimedia Appendix 6
Design features and characteristics of the digital serious games included in this review, including developers, interaction mechanisms, and educational purposes.
DOCX File, 27 KBMultimedia Appendix 7
Risk of bias assessment for included trials, including individually randomized trials and cluster randomized trials.
DOCX File, 142 KBMultimedia Appendix 8
Funnel plots assessing potential publication bias for knowledge and attitude outcomes across the included studies.
DOCX File, 28 KBMultimedia Appendix 9
Grading of Recommendations Assessment, Development and Evaluation summarizing the certainty of evidence for knowledge and attitude outcomes across the included studies.
DOCX File, 14 KBMultimedia Appendix 10
Forest plots of subgroup analyses for knowledge and attitude outcomes across 7 moderators, including intervention duration, study region, and population characteristics.
DOCX File, 784 KBMultimedia Appendix 11
Forest plots of the Bayesian network meta-analysis for knowledge and attitude outcomes showing pooled mean differences with 95% credible intervals.
PDF File, 26 KBMultimedia Appendix 12
Node-splitting analyses assessing inconsistency between direct and indirect evidence in the network meta-analysis for knowledge and attitude outcomes.
PDF File, 40 KBMultimedia Appendix 13
Comparison of surface under the cumulative ranking curve values and treatment rankings under uniform and half-normal prior distributions for knowledge and attitude outcomes.
DOCX File, 19 KBChecklist 1
PRISMA reporting checklists used in this review, including the PRISMA 2020 checklist, PRISMA 2020 expanded checklist, PRISMA 2020 for abstracts checklist, and PRISMA-S checklist.
PDF File, 845 KBReferences
- A global health strategy for 2025–2028: advancing equity and resilience in a turbulent world (fourteenth general programme of work). World Health Organization; 2025. URL: https://iris.who.int/server/api/core/bitstreams/46cc7cac-e35e-451b-808e-1f0e4ad5f68c/content [Accessed 2026-04-01]
- Fazel M, Hoagwood K, Stephan S, Ford T. Mental health interventions in schools 1: mental health interventions in schools in high-income countries. Lancet Psychiatry. Oct 2014;1(5):377-387. [CrossRef] [Medline]
- Dodd S, Widnall E, Russell AE, et al. School-based peer education interventions to improve health: a global systematic review of effectiveness. BMC Public Health. Dec 2, 2022;22(1):2247. [CrossRef] [Medline]
- Baccolini V, Rosso A, Di Paolo C, et al. What is the prevalence of low health literacy in European Union member states? A systematic review and meta-analysis. J Gen Intern Med. Mar 2021;36(3):753-761. [CrossRef] [Medline]
- China achieves 31.87% health literacy rate in 2024. The State Council of the People’s Republic of China. 2025. URL: https://english.www.gov.cn/archive/statistics/202501/10/content_WS6780e424c6d0868f4e8eeae6.html [Accessed 2025-09-29]
- Yu YS, Altares A, Leib A, et al. Sociodemographic disparities in health literacy among American adults: a national survey study. Prev Med Rep. Sep 2025;57:103179. [CrossRef] [Medline]
- O’Neill G. Global health literacy: Delaware and beyond! Dela J Public Health. Apr 2025;11(1):24-25. [CrossRef] [Medline]
- van der Gaag M, Heijmans M, Spoiala C, Rademakers J. The importance of health literacy for self-management: a scoping review of reviews. Chronic Illn. Jun 2022;18(2):234-254. [CrossRef] [Medline]
- Magnani JW, Mujahid MS, Aronow HD, et al. Health literacy and cardiovascular disease: fundamental relevance to primary and secondary prevention: a scientific statement from the American Heart Association. Circulation. Jul 10, 2018;138(2):e48-e74. [CrossRef] [Medline]
- Vasileia E, Koulierakis G, Fouskas T, Liarigkovinou A. Health literacy and acceptance of COVID-19 preventive measures and vaccination in the European Union: a scoping review. Health Lit Res Pract. Jan 2025;9(1):e46-e55. [CrossRef] [Medline]
- St Leger L. Schools, health literacy and public health: possibilities and challenges. Health Promot Int. Jun 2001;16(2):197-205. [CrossRef] [Medline]
- Zhao T, Deng W, Yang Y, Jin Y, Xu F. Enhancing student satisfaction through open collaborative practical teaching reforms in public health education: a comparative study. Front Public Health. 2025;13:1546962. [CrossRef] [Medline]
- Education: from COVID-19 school closures to recovery. UNESCO. URL: https://www.unesco.org/en/covid-19/education-response [Accessed 2025-09-29]
- Dettori M, Castiglia P. COVID-19 and digital health: evolution, perspectives and opportunities. Int J Environ Res Public Health. Jul 12, 2022;19(14):8519. [CrossRef] [Medline]
- Getachew E, Adebeta T, Muzazu SGY, et al. Digital health in the era of COVID-19: reshaping the next generation of healthcare. Front Public Health. 2023;11:942703. [CrossRef] [Medline]
- Kermavnar T, Visch VT, Desmet PMA. Games in times of a pandemic: structured overview of COVID-19 serious games. JMIR Serious Games. Mar 7, 2023;11:e41766. [CrossRef] [Medline]
- DeSmet A, Thompson D, Baranowski T, Palmeira A, Verloigne M, De Bourdeaudhuij I. Is participatory design associated with the effectiveness of serious digital games for healthy lifestyle promotion? A meta-analysis. J Med Internet Res. Apr 29, 2016;18(4):e94. [CrossRef] [Medline]
- Xu M, Luo Y, Zhang Y, Xia R, Qian H, Zou X. Game-based learning in medical education. Front Public Health. 2023;11:1113682. [CrossRef] [Medline]
- Alencar NES, Pinto MAO, Leite NT, Silva C. Serious games for sex education of adolescents and youth: integrative literature review. Cien Saude Colet. Aug 2022;27(8):3129-3138. [CrossRef] [Medline]
- Abd-Alrazaq A, Abuelezz I, Hassan A, et al. Artificial intelligence-driven serious games in health care: scoping review. JMIR Serious Games. Nov 29, 2022;10(4):e39840. [CrossRef] [Medline]
- Checa D, Miguel-Alonso I, Bustillo A. Immersive virtual-reality computer-assembly serious game to enhance autonomous learning. Virtual Real. Dec 23, 2021:1-18. [CrossRef] [Medline]
- Buffel C, van Aalst J, Bangels AM, et al. A web-based serious game for health to reduce perioperative anxiety and pain in children (CliniPup): pilot randomized controlled trial. JMIR Serious Games. Jun 1, 2019;7(2):e12431. [CrossRef] [Medline]
- Dietvorst E, Aukes MA, Legerstee JS, et al. A smartphone serious game for adolescents (Grow It! app): development, feasibility, and acceptance study. JMIR Form Res. Mar 3, 2022;6(3):e29832. [CrossRef] [Medline]
- Aster A, Scheithauer S, Middeke AC, et al. Use of a serious game to teach infectious disease management in medical school: effectiveness and transfer to a clinical examination. Front Med. 2022;9:863764. [CrossRef]
- Thomas TH, Sivakumar V, Babichenko D, Grieve VLB, Klem ML. Mapping behavioral health serious game interventions for adults with chronic illness: scoping review. JMIR Serious Games. Jul 30, 2020;8(3):e18687. [CrossRef] [Medline]
- Craig S, Stark P, Wilson CB, Carter G, Clarke S, Mitchell G. Evaluation of a dementia awareness game for undergraduate nursing students in Northern Ireland: a pre-/post-test study. BMC Nurs. May 22, 2023;22(1):177. [CrossRef] [Medline]
- Wang Y, Wang Z, Liu G, et al. Application of serious games in health care: scoping review and bibliometric analysis. Front Public Health. 2022;10:896974. [CrossRef]
- Haoran G, Bazakidi E, Zary N. Serious games in health professions education: review of trends and learning efficacy. Yearb Med Inform. Aug 2019;28(1):240-248. [CrossRef] [Medline]
- Suppan M, Stuby L, Harbarth S, et al. Nationwide deployment of a serious game designed to improve COVID-19 infection prevention practices in Switzerland: prospective web-based study. JMIR Serious Games. Nov 25, 2021;9(4):e33003. [CrossRef] [Medline]
- Sharifzadeh N, Kharrazi H, Nazari E, et al. Health education serious games targeting health care providers, patients, and public health users: scoping review. JMIR Serious Games. Mar 5, 2020;8(1):e13459. [CrossRef] [Medline]
- Nørlev J, Sondrup K, Derosche C, Hejlesen O, Hangaard S. Game mechanisms in serious games that teach children with type 1 diabetes how to self-manage: a systematic scoping review. J Diabetes Sci Technol. Sep 2022;16(5):1253-1269. [CrossRef] [Medline]
- Koutsiana E, Ladakis I, Fotopoulos D, Chytas A, Kilintzis V, Chouvarda I. Serious gaming technology in upper extremity rehabilitation: scoping review. JMIR Serious Games. Dec 11, 2020;8(4):e19071. [CrossRef] [Medline]
- Ohannessian R, Yaghobian S, Verger P, Vanhems P. A systematic review of serious video games used for vaccination. Vaccine (Auckl). Aug 2016;34(38):4478-4483. [CrossRef]
- Tavares N. The use and impact of game-based learning on the learning experience and knowledge retention of nursing undergraduate students: a systematic literature review. Nurse Educ Today. Oct 2022;117:105484. [CrossRef] [Medline]
- Moschonis G, Siopis G, Jung J, et al. Effectiveness, reach, uptake, and feasibility of digital health interventions for adults with type 2 diabetes: a systematic review and meta-analysis of randomised controlled trials. Lancet Digit Health. Mar 2023;5(3):e125-e143. [CrossRef] [Medline]
- Page MJ, McKenzie JE, Bossuyt PM, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. Mar 29, 2021;372:n71. [CrossRef] [Medline]
- Schardt C, Adams MB, Owens T, Keitz S, Fontelo P. Utilization of the PICO framework to improve searching PubMed for clinical questions. BMC Med Inform Decis Mak. Jun 15, 2007;7(1):16. [CrossRef] [Medline]
- Higgins JP, Thomas J, Chandler J, et al. Cochrane Handbook for Systematic Reviews of Interventions. 2nd ed. Wiley; 2019. URL: https://onlinelibrary.wiley.com/doi/book/10.1002/9781119536604 [Accessed 2026-04-01]
- Sterne JAC, Savović J, Page MJ, et al. RoB 2: a revised tool for assessing risk of bias in randomised trials. BMJ. Aug 28, 2019;366:l4898. [CrossRef] [Medline]
- Furukawa TA, Barbui C, Cipriani A, Brambilla P, Watanabe N. Imputing missing standard deviations in meta-analyses can provide accurate results. J Clin Epidemiol. Jan 2006;59(1):7-10. [CrossRef] [Medline]
- Higgins JPT, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. BMJ. Sep 6, 2003;327(7414):557-560. [CrossRef] [Medline]
- Efthimiou O, Rücker G, Schwarzer G, Higgins JPT, Egger M, Salanti G. Network meta-analysis of rare events using the Mantel-Haenszel method. Stat Med. Jul 20, 2019;38(16):2992-3012. [CrossRef] [Medline]
- Neupane B, Richer D, Bonner AJ, Kibret T, Beyene J. Network meta-analysis using R: a review of currently available automated packages. PLoS ONE. 2014;9(12):e115065. [CrossRef] [Medline]
- Higgins JPT, Jackson D, Barrett JK, Lu G, Ades AE, White IR. Consistency and inconsistency in network meta-analysis: concepts and models for multi-arm studies. Res Synth Methods. Jun 2012;3(2):98-110. [CrossRef] [Medline]
- Guyatt G, Oxman AD, Akl EA, et al. GRADE guidelines: 1. Introduction-GRADE evidence profiles and summary of findings tables. J Clin Epidemiol. Apr 2011;64(4):383-394. [CrossRef] [Medline]
- Guyatt GH, Oxman AD, Kunz R, et al. GRADE guidelines: 7. Rating the quality of evidence--inconsistency. J Clin Epidemiol. Dec 2011;64(12):1294-1302. [CrossRef] [Medline]
- Shegog R, Bartholomew LK, Parcel GS, Sockrider MM, Mâsse L, Abramson SL. Impact of a computer-assisted education program on factors related to asthma self-management behavior. J Am Med Inform Assoc. 2001;8(1):49-61. [CrossRef] [Medline]
- Kato PM, Cole SW, Bradlyn AS, Pollock BH. A video game improves behavioral outcomes in adolescents and young adults with cancer: a randomized trial. Pediatrics. Aug 2008;122(2):e305-e317. [CrossRef] [Medline]
- Kumar VS, Wentzell KJ, Mikkelsen T, Pentland A, Laffel LM. The DAILY (Daily Automated Intensive Log for Youth) trial: a wireless, portable system to improve adherence and glycemic control in youth with diabetes. Diabetes Technol Ther. Aug 2004;6(4):445-453. [CrossRef] [Medline]
- Bartholomew LK, Gold RS, Parcel GS, et al. Watch, discover, think, and act: evaluation of computer-assisted instruction to improve asthma self-management in inner-city children. Patient Educ Couns. Feb 2000;39(2-3):269-280. [CrossRef] [Medline]
- Aljafari A, Gallagher JE, Hosey MT. Can oral health education be delivered to high-caries-risk children and their parents using a computer game? - a randomised controlled trial. Int J Paediatr Dent. Nov 2017;27(6):476-485. [CrossRef] [Medline]
- Haruna H, Hu X, Chu SKW, Mellecker RR, Gabriel G, Ndekao PS. Improving sexual health education programs for adolescent students through game-based learning and gamification. Int J Environ Res Public Health. Sep 17, 2018;15(9):2027. [CrossRef] [Medline]
- Henkemans OAB, Bierman BPB, Janssen J, et al. Design and evaluation of a personal robot playing a self-management education game with children with diabetes type 1. Int J Hum Comput Stud. Oct 2017;106:63-76. [CrossRef]
- Whiteley L, Brown LK, Mena L, Craker L, Arnold T. Enhancing health among youth living with HIV using an iPhone game. AIDS Care. 2018;30(sup4):21-33. [CrossRef] [Medline]
- Joubert M, Armand C, Morera J, Tokayeva L, Guillaume A, Reznik Y. Impact of a serious videogame designed for flexible insulin therapy on the knowledge and behaviors of children with type 1 diabetes: the LUDIDIAB pilot study. Diabetes Technol Ther. Feb 2016;18(2):52-58. [CrossRef] [Medline]
- Maganty N, Ilyas M, Zhang N, Sharma A. Online, game-based education for melanoma recognition: a pilot study. Patient Educ Couns. Apr 2018;101(4):738-742. [CrossRef] [Medline]
- Fadda M, Galimberti E, Fiordelli M, Romanò L, Zanetti A, Schulz PJ. Effectiveness of a smartphone app to increase parents’ knowledge and empowerment in the MMR vaccination decision: a randomized controlled trial. Hum Vaccin Immunother. Nov 2, 2017;13(11):2512-2521. [CrossRef] [Medline]
- Zolfaghari M, Shirmohammadi M, Shahhosseini H, Mokhtaran M, Mohebbi SZ. Development and evaluation of a gamified smart phone mobile health application for oral health promotion in early childhood: a randomized controlled trial. BMC Oral Health. Jan 7, 2021;21(1):18. [CrossRef] [Medline]
- Froome HM, Townson C, Rhodes S, et al. The effectiveness of the foodbot factory mobile serious game on increasing nutrition knowledge in children. Nutrients. Nov 6, 2020;12(11):3413. [CrossRef] [Medline]
- Goodman K, Arriaga RI, Korman R, et al. Pediatric emergency department-based asthma education tools and parent/child asthma knowledge. Allergy Asthma Clin Immunol. Mar 25, 2024;20(1):24. [CrossRef] [Medline]
- K RSK, Deshpande AP, Ankola AV, et al. Effectiveness of a visual interactive game on oral hygiene knowledge, practices, and clinical parameters among adolescents: a randomized controlled trial. Children (Basel). Nov 26, 2022;9(12):1828. [CrossRef] [Medline]
- Koohmareh Z, Karandish M, Hadianfard AM. Effect of implementing a mobile game on improving dietary information in diabetic patients. Med J Islam Repub Iran. 2021;35:68. [CrossRef] [Medline]
- Pouls BPH, Bekker CL, Gundogan F, et al. Gaming for adherence to medication using eHealth in rheumatoid arthritis (GAMER) study: a randomised controlled trial. RMD Open. Nov 2022;8(2):e002616. [CrossRef] [Medline]
- Tang J, Zheng Y, Zhang D, et al. Evaluation of an AIDS educational mobile game (AIDS Fighter · Health Defense) for young students to improve AIDS-related knowledge, stigma, and attitude linked to high-risk behaviors in China: randomized controlled trial. JMIR Serious Games. Jan 24, 2022;10(1):e32400. [CrossRef] [Medline]
- Carcioppolo N, Kim S, Sanchez M, et al. Evaluating a game-based randomized experiment to increase melanoma identification among adults living in the U.S. Soc Sci Med. Oct 2022;310:115281. [CrossRef] [Medline]
- Espinosa-Curiel IE, Pozas-Bogarin EE, Hernández-Arvizu M, et al. HelperFriend, a serious game for promoting healthy lifestyle behaviors in children: design and pilot study. JMIR Serious Games. May 6, 2022;10(2):e33412. [CrossRef] [Medline]
- Ghadam OS, Sohrabi Z, Mehrabi M, et al. Evaluating the effect of digital game-based nutrition education on anemia indicators in adolescent girls: a randomized clinical trial. Food Sci Nutr. Feb 2023;11(2):863-871. [CrossRef] [Medline]
- Huang X, Jiang Z, Dai Y, et al. Effect of gamification on improved adherence to inhaled medications in chronic obstructive pulmonary disease: randomized controlled trial. J Med Internet Res. May 14, 2025;27:e65309. [CrossRef] [Medline]
- Koniou I, Douard E, Lanovaz MJ. Brief report: virtual reality to raise awareness about autism. J Autism Dev Disord. Sep 2025;55(9):3378-3386. [CrossRef] [Medline]
- Liu B, Wan X, Li X, Zhu D, Liu Z. An augmented reality serious game for children’s optical science education: randomized controlled trial. JMIR Serious Games. Feb 1, 2024;12:e47807-e47807. [CrossRef] [Medline]
- Mack I, Reiband N, Etges C, et al. The kids obesity prevention program: cluster randomized controlled trial to evaluate a serious game for the prevention and treatment of childhood obesity. J Med Internet Res. Apr 24, 2020;22(4):e15725. [CrossRef] [Medline]
- Maddison R, Baghaei N, Calder A, et al. Feasibility of using games to improve healthy lifestyle knowledge in youth aged 9-16 years at risk for type 2 diabetes: pilot randomized controlled trial. JMIR Form Res. Jun 17, 2022;6(6):e33089. [CrossRef] [Medline]
- Nazmi S, Omrani A, Behmanesh F, Nikbakht HA, Mehrabi M, Hamzehpour R. Improving pubertal health education for adolescent girls through a gamified learning approach. J Pediatr Adolesc Gynecol. Jun 2025;38(3):320-327. [CrossRef] [Medline]
- Nowak GJ, Evans NJ, Wojdynski BW, et al. Using immersive virtual reality to improve the beliefs and intentions of influenza vaccine avoidant 18-to-49-year-olds: considerations, effects, and lessons learned. Vaccine (Auckl). Jan 29, 2020;38(5):1225-1233. [CrossRef] [Medline]
- Tan A, Koh E, Sankari U, Tang J, Goh CK, Tan NC. Effects of a serious game on knowledge, attitude and practice in vector control and dengue prevention among adults in primary care: a randomised controlled trial. Digit Health. 2022;8:20552076221129099. [CrossRef] [Medline]
- Beale IL, Kato PM, Marin-Bowling VM, Guthrie N, Cole SW. Improvement in cancer-related knowledge following use of a psychoeducational video game for adolescents and young adults with cancer. J Adolesc Health. Sep 2007;41(3):263-270. [CrossRef] [Medline]
- Beaujean D, Gassner F, Wong A, Steenbergen JE, Crutzen R, Ruwaard D. Education on tick bite and Lyme borreliosis prevention, aimed at schoolchildren in the Netherlands: comparing the effects of an online educational video game versus a leaflet or no intervention. BMC Public Health. Nov 16, 2016;16(1):1163. [CrossRef] [Medline]
- Khalil GE, Beale IL, Chen M, Prokhorov AV. A video game promoting cancer risk perception and information seeking behavior among young-adult college students: a randomized controlled trial. JMIR Serious Games. Jul 28, 2016;4(2):e13. [CrossRef] [Medline]
- Fiellin LE, Hieftje KD, Pendergrass TM, et al. Video game intervention for sexual risk reduction in minority adolescents: randomized controlled trial. J Med Internet Res. Sep 18, 2017;19(9):e314. [CrossRef] [Medline]
- Aljafari A, ElKarmi R, Nasser O, Atef A, Hosey MT. A video-game-based oral health intervention in primary schools-a randomised controlled trial. Dent J (Basel). May 19, 2022;10(5):90. [CrossRef] [Medline]
- Huang Z, Ow JT, Tang WE, Chow A. An evidence-based serious game app for public education on antibiotic use and resistance: randomized controlled trial. JMIR Serious Games. Sep 5, 2024;12:e59848. [CrossRef] [Medline]
- Bloomfield L, Boston J, Masek M, Andrew L, Barwood D, Devine A. Evaluating the efficacy of a serious game to deliver health education about invasive meningococcal disease: clustered randomized controlled equivalence trial. JMIR Serious Games. Feb 11, 2025;13:e60755. [CrossRef] [Medline]
- Boomer TP, Larkin K, Duncan LR, Fernandes CSF, Fiellin LE. A serious video game targeting HIV testing and counseling: a randomized controlled trial. J Adolesc Health. Feb 2024;74(2):252-259. [CrossRef] [Medline]
- Raj A, Shankar L, Dixit A, et al. Enhancing reproductive health among adolescent girls in India: results of an individualized RCT to study the efficacy of the Go Nisha Go Mobile Game. Reprod Health. Apr 7, 2025;22(1):48. [CrossRef] [Medline]
- Wang R, Yao J, Leong C, Moltchanova E, Hoermann S. Promoting learning about nutrition and healthy eating behaviors in Chinese children through an alternate reality game: a pilot study. Nutrients. Mar 30, 2025;17(7):1219. [CrossRef]
- Vandeweerdt C, Luong T, Atchapero M, et al. Virtual reality reduces COVID-19 vaccine hesitancy in the wild: a randomized trial. Sci Rep. Mar 17, 2022;12(1):4593. [CrossRef] [Medline]
- Charlier N, Zupancic N, Fieuws S, Denhaerynck K, Zaman B, Moons P. Serious games for improving knowledge and self-management in young people with chronic conditions: a systematic review and meta-analysis. J Am Med Inform Assoc. Jan 2016;23(1):230-239. [CrossRef] [Medline]
- DeSmet A, Shegog R, Van Ryckeghem D, Crombez G, De Bourdeaudhuij I. A systematic review and meta-analysis of interventions for sexual health promotion involving serious digital games. Games Health J. Apr 2015;4(2):78-90. [CrossRef] [Medline]
- Lau HM, Smit JH, Fleming TM, Riper H. Serious games for mental health: are they accessible, feasible, and effective? A systematic review and meta-analysis. Front Psychiatry. 2017;7:209. [CrossRef] [Medline]
- Andrew L, Barwood D, Boston J, Masek M, Bloomfield L, Devine A. Serious games for health promotion in adolescents – a systematic scoping review. Educ Inf Technol. May 2023;28(5):5519-5550. [CrossRef]
- Dudai Y, Karni A, Born J. The consolidation and transformation of memory. Neuron. Oct 7, 2015;88(1):20-32. [CrossRef] [Medline]
- Mullins JK, Sabherwal R. Gamification: a cognitive-emotional view. J Bus Res. Jan 2020;106:304-314. [CrossRef]
- Maxim RI, Arnedo-Moreno J. Identifying key principles and commonalities in digital serious game design frameworks: scoping review. JMIR Serious Games. Mar 5, 2025;13:e54075. [CrossRef] [Medline]
- Liao X, Noor NFM. Design components of serious game based on flow theories. Adv Educ Technol Psychol. 2025;9(3):67-80. [CrossRef]
- Gómez-León MI. Serious games to support emotional regulation strategies in educational intervention programs with children and adolescents. Systematic review and meta-analysis. Heliyon. Feb 2025;11(4):e42712. [CrossRef] [Medline]
- David OA, Magurean S, Tomoiagă C. Do improvements in therapeutic game-based skills transfer to real life improvements in children’s emotion-regulation abilities and mental health? A pilot study that offers preliminary validity of the REThink in-game performance scoring. Front Psychiatry. 2022;13:828481. [CrossRef] [Medline]
- Kai L, Tan WH, Saari EM. Dimensions of interactive pervasive game design: systematic review. JMIR Serious Games. Aug 22, 2023;11:e42878. [CrossRef] [Medline]
- Alexiou A, Schippers MC, Oshri I, Angelopoulos S. Narrative and aesthetics as antecedents of perceived learning in serious games. Inf Technol People. Dec 19, 2022;35(8):142-161. [CrossRef]
- Martin F, Dennen VP, Bonk CJ. A synthesis of systematic review research on emerging learning environments and technologies. Educ Technol Res Dev. 2020;68(4):1613-1633. [CrossRef] [Medline]
- Zhang X, Lai E. A web-based gaming approach to decrease HIV-related stigma: game development and mixed methods evaluation. JMIR Serious Games. Dec 15, 2022;10(4):e37219. [CrossRef] [Medline]
- Bunt L, Greeff J, Taylor E. Enhancing serious game design: expert-reviewed, stakeholder-centered framework. JMIR Serious Games. May 31, 2024;12:e48099. [CrossRef] [Medline]
- Aster A, Laupichler MC, Zimmer S, Raupach T. Game design elements of serious games in the education of medical and healthcare professions: a mixed-methods systematic review of underlying theories and teaching effectiveness. Adv Health Sci Educ Theory Pract. Nov 2024;29(5):1825-1848. [CrossRef] [Medline]
- Kwak M, Kim BJ, Chung JB. Serious game development for public health: participatory design approach to COVID-19 quarantine policy education. JMIR Serious Games. Oct 15, 2024;12:e54968. [CrossRef] [Medline]
- Epstein DS, Zemski A, Enticott J, Barton C. Tabletop board game elements and gamification interventions for health behavior change: realist review and proposal of a game design framework. JMIR Serious Games. Mar 31, 2021;9(1):e23302. [CrossRef] [Medline]
- Pistono A, dos Santos AMP, Baptista RJV, Mamede HS. Framework for adaptive serious games. Comp Applic In Engineering. Jul 2024;32(4):e22731. [CrossRef]
- Eysenbach G, CONSORT-EHEALTH Group. CONSORT-EHEALTH: improving and standardizing evaluation reports of web-based and mobile health interventions. J Med Internet Res. Dec 31, 2011;13(4):e126. [CrossRef] [Medline]
Abbreviations
| CD: chronic diseases |
| CrI: credible interval |
| GRADE: Grading of Recommendations Assessment, Development and Evaluation |
| PRISMA: Preferred Reporting Items for Systematic Reviews and Meta-Analyses |
| PRISMA-S: Preferred Reporting Items for Systematic Reviews and Meta-Analyses–Search extension |
| RCT: randomized controlled trial |
| SMD: standardized mean difference |
| SUCRA: surface under the cumulative ranking curve |
Edited by Stefano Brini; submitted 09.Dec.2025; peer-reviewed by Guotuan Wang, Shuo Xiong; final revised version received 17.Mar.2026; accepted 17.Mar.2026; published 24.Apr.2026.
Copyright© Di Huang, Dongjun Wu, Rene Hexel, Christine Brown-Wilson, Jing Zhou, Wendy Moyle. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 24.Apr.2026.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research (ISSN 1438-8871), is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.