We conducted a comprehensive literature search, utilizing various databases and search terms. PubMed, EMBASE, International Journal of Serious Games, Cochrane Library, and Google Scholar were searched for peer-reviewed research, while OpenAlex, GreyNet, and IEEE Xplore were searched for gray literature known to index technical reports, conference proceedings, and non-peer-reviewed research relevant to gamification. Our search strategy included Medical Subject Headings and keywords such as “gamification,” “videogame,” “healthcare worker,” and “healthcare professional” to ensure the inclusion of all relevant studies from both peer-reviewed and gray literature. We employed Boolean operators like “OR” and “AND,” along with truncation (*), to account for variation in word endings, such as gamif* for gamification or gamified. An expert librarian supported this rigorous search to ensure the inclusion of all relevant studies. The detailed search strategy is available in Multimedia Appendix 2. After an initial screening based on titles and abstracts, we conducted a second screening on the full text retrieved by 2 authors (BP and HAS) through Rayyan [50], with a third author (AB) consulted in case of disagreement. The weighted kappa coefficient of Cohen was calculated to assess the degree of agreement between the 2 reviewers, and it was applied as suggested by Landis and Koch [51]. Additionally, we conducted a supplementary manual search through the reference lists of the included studies.

The SPIDER (Sample, Phenomenon of Interest, Design, Evaluation, and Research) framework [52] determined the inclusion and exclusion criteria as outlined in Table 2.

Only interventions involving GDTs for daily health care tasks were selected for inclusion, provided they featured at least 1 gamification element. For this review, HCWs were defined broadly to include not only clinical staff but also volunteers, data clerks, and health administrators who used GDTs in their daily tasks, for example, by entering clinical data into databases within a health care setting. Studies in which gamification elements were not implemented within ICT (eg, board games) were omitted, as well as studies in which GDTs were primarily aimed at training, education, and self-care disease management, or not related to health care.

In our study, we considered studies published between January 2010 and January 2024, as the term gamification gained widespread recognition after 2010 [10-12], and to capture the progression of digital health since the release of the “Principles for Digital Development“ [53]. Additionally, studies of all designs (eg, qualitative, quantitative, and mixed methods studies) published in English, French, Spanish, or Italian were included.

One author (BP) conducted independent data extraction using a spreadsheet prepared by consensus by the reviewers using Microsoft Excel [54], subsequently revised by 2 authors (AB and HAS). For each included study, we extracted information on the year of publication, country of implementation, study objective, design, data collection method, target population, sample size, type of digital intervention, application context, gamification elements used, and main findings.

Two authors (BP and AB) conducted the quality assessment. A third author (HAS) was consulted in case of disagreement. The quality assessment was based on the method outlined by Sardi et al [11], which involved utilizing a set of five closed-ended questions to assess the relevance and quality of the publication: (1) whether the paper provides a detailed description of the game elements employed, (2) if the study presented empirical results, (3) if the benefits and (4) limitations of gamification were explicitly addressed, and (5) the relevance of the source where the study was published investigated through Scimago Journal & Country Rank [55]. The score assigned to each study could range from 0 (lowest) to 6 (highest). Based on the average score, the studies were classified into 3 categories: high (5 or above), average (below 5 and above or equal to 3), and poor (below 3).

The quality assessment checklist and results are given in Multimedia Appendix 3. To assess the degree of agreement between the raters, a weighted kappa coefficient of Cohen was calculated.

Given the heterogeneity of the studies, we employed a narrative approach to summarize the findings and address our research question. As GDTs have been integrated into various digital health interventions, a classification based on the different working contexts and the professional background of health staff was deemed most suitable for conceptualizing and describing their application. This format also aligns with the notion that digital tools should be designed according to the profiles of their users, as stated by the “Principles for Digital Development” [53]. We, therefore, classified users into three main categories: (1) community health care workers (CHWs), frontline workers engaging with communities outside of health facilities; (2) HCWs working in primary health care (PHC); and (3) HCWs working in secondary health facilities, such as hospitals. Finally, as suggested by several authors [11,16,40,56-59], we summarized the benefits of the GDTs on the HCWs as follows: increased engagement, enhanced motivation, task completion and behavior change, and heightened healthy competition.

Increased engagement refers to HCWs’ higher involvement and commitment to their tasks, leading to improved performance and better patient care [11,56-58]. Enhanced motivation means a stronger drive to perform duties effectively, resulting in higher job satisfaction and productivity [11,16,56-58]. Task completion involves the consistent and timely fulfillment of assigned duties based on a behavior change [56,59]. Healthy competition is a positive rivalry that encourages staff to excel, share best practices, and support each other’s growth, enhancing overall care quality [40].

A total of 5844 records were identified through a comprehensive search of multiple databases. After removing 554 duplicates, 5290 studies were screened by title and abstract. Of these, 4784 were excluded for not meeting the study objectives, primarily because they did not address gamification. An additional 195 studies were excluded for not focusing on health care, and 29 were removed based on publication type (eg, editorial or commentary). Subsequently, 506 studies were sought for retrieval. Of these, 6 could not be accessed as full text and were therefore excluded. The final 500 studies underwent a second screening. At this stage, 488 were excluded: 195 focused on patient-centered intervention rather than HCWs, 158 did not incorporate gamified components, 89 described gamified tools solely for training and educational purposes, 29 included gamification elements not integrated into a digital platform, and 17 involved GDTs not intended for use by HCWs. Finally, based on the eligibility criteria, 12 studies were selected for the final review, comprising 9 studies that had been peer-reviewed and 3 Congress proceedings.

The interrater reliability for selecting the included studies, measured using Cohen’s weighted kappa coefficient [51], was 0.72, suggesting a substantial agreement between raters. The PRISMA flow diagram of the study selection process is presented in Figure 1.

The average quality score of the selected studies, based on the assessment method proposed by Sardi et al [11], was 3.4, with scores ranging from 1 (minimum) to 5 (maximum). A total of 5 studies were classified as high quality, 4 as average quality, and 3 as poor quality. Most of the studies (n=10, 83.3%) lacked a discussion concerning the limitations of the GDTs, and many (n=5, 41.7%) did not discuss any benefit. A total of 8 studies (66.7%) were published or presented in recognized journals or Congresses. The Cohen weighted kappa coefficient among the raters was very good: 0.83 [51].

Of the 12 included studies, 9 (75%) were peer-reviewed in scientific journals, while the remaining 3 (25%) were sourced from gray literature (Congress proceedings). A total of 6 (50%) studies originated from high-income countries (HICs): Canada [60], Australia [61], the United States [62-64], and Portugal [65]; 6 (50%) from low- and middle-income countries (LMICs): Nigeria [66], India [67], Pakistan [68], Kenya [69], and Ethiopia [70]. One study was a multi-country intervention carried out in Bangladesh, Burkina Faso, and Ecuador. A total of 3 interventions focus on CHWs’ use of GDTs, 3 are implemented in PHC settings, and 6 in hospitals. The majority of the studies was published before 2020 (n=10, 83.3%). The most common study design was quasi-experimental (n=5, 41.7%), followed by qualitative studies (n=2, 16.7%). Of the remaining 5 studies, 1 was a cross-sectional study, 1 a case study, 1 an interventional pilot study, 1 a diagnostic accuracy study, and 1 an observational study. The characteristics of each study are presented in Table 3.

These 12 studies address a variety of health topics, including compliance with hand hygiene [63,65], mother and childcare [67,70], health-related data collection [64,69], surgical antibiotic prophylaxis (SAP) [66], Integrated Community Case Management (iCCM) [71], and Expanded Programme on Immunization (EPI) implementation [68], sepsis diagnosis and therapy [60], atrial fibrillation (AF) screening [61], and central line-associated bloodstream infections prevention [62]. Table 3 presents a comprehensive overview of the included studies.

The most common gamification elements integrated into the GDTs were the use of feedback (n=9, 75%), use of competition (n=6, 50%), leaderboards/dashboards/scoreboards (n=6, 50%), badges (n=3, 25%), and time pressure elements (n=3, 25%). A total of 3 (25%) digital interventions [67,69,71] incorporated a single gamification element, whereas most (n=9, 75%) integrated at least 2. Table 4 presents a summary of the elements of gamification adopted in these studies.

We identified 3 studies [67,69,71] that involved CHWs using GDTs, all conducted in LMICs.

One intervention in Kenya focuses on improving data collection by introducing a custom-made GDT device with intuitive input mechanisms like sliders and dials, complemented by visual aids and sensory feedback (eg, when collecting height data, the device featured images of a tall individual at the top and a shorter individual at the bottom of a height slider). This approach was reported to enhance CHWs’ engagement, but it does not present any evidence of increased effectiveness in data collection [69].

In India, a quasi-experimental study evaluated an intervention with a smartphone app for health activists and a web interface for PHC staff to improve maternal and childcare. The app used time pressure as a gamification element, turning text red for overdue tasks to prompt faster completion. The intervention increased home-based newborn care from 10% to 56%, exclusive breastfeeding from 23% to 44%, care-seeking for maternal and neonatal complications from 57% to 77% and 27% to 78%, respectively, and pneumonia care from 24% to 41%. The time pressure likely improved task completion, though the study did not quantify its specific impact [67].

MEDSINC, a mobile health platform, integrates Integrated Community Case Management guidelines to support CHWs in the clinical assessment, triage, and treatment of children aged between 2 months and 6 years. This tool includes demonstrations and animated graphics interchange formats to enhance data collection quality and accuracy. Children’s clinical assessments by CHWs using MEDSINC showed a specificity correlation of 84%-99% with local health care experts, and their triage recommendations were highly correlated [71]. The tool received positive feedback for its user-friendliness, educational value, and enhancement of job performance, showing that gamified data visualization can motivate data collection.

A total of 3 interventions evaluated GDTs in PHC: two in LMICs and one in an HIC [61,68,70].

An observational study in Ethiopia [70] evaluated an Open Data Kit platform for maternal and childcare case management. The tool included an analytic dashboard and a scorecard to monitor key performance indicators. The intervention was well-received by HCWs, who quickly adapted to smartphones and required minimal technical support. However, while visualizing progress appeared to motivate HCWs’ performance, the study did not establish a causal link between the heightened motivation and the overall impact of the intervention.

In Pakistan, an app was developed to monitor routine immunization by recording and uploading data, synchronizing profiles with central databases, and managing vaccine inventories [68]. The tool used real-time data to monitor vaccinations, track incomplete cases, plan outreach, adjust micro plans, and allocate fuel allowances. It demonstrated greater accuracy than manual data entry and used gamification to highlight top performers (leaderboard), reward high achievers, and foster healthy competition. Also, individual vaccine performance feedback increased vaccinators’ engagement.

A qualitative study investigated the use of an eHealth tool within an atrial fibrillation screening program in PHC in Australia [61]. The app extracted EMR data to provide real-time screening prompts and treatment recommendations. Additionally, a smartphone electrocardiograph tool was used for diagnosis. The app generated stroke risk scores and treatment advice, with monthly individual de-identified data reports for quality improvement. These reports included screening rates, new diagnoses, and treatment adherence. HCWs appreciated the eHealth tools, and regular feedback was beneficial for quality improvement, increased the proportion of eligible people to be screened for atrial fibrillation, and maintained motivation. Moreover, the feedback encouraged app usage by fostering healthy competition.

A total of 6 interventions were carried out in hospital care, 5 [60,62,63,65,66] focusing on reducing health care–associated infections by increasing adherence to guidelines and procedures, and 1 study [64] was carried out on patient flow management.

Two interventions [63,65] incorporated gamification elements to improve hand hygiene in intensive care units. In the United States, a multifaceted strategy included hand washing automated monitoring machines, communication, and leadership initiatives [63]. Key features included hospital-wide competitions, public compliance postings, and electronic point-of-care performance reporting. This approach led to a 75% increase in hand hygiene solution dispensing, a 96% improvement in hand hygiene compliance, and an 11% reduction in health care–associated infections, demonstrating that individual feedback and team competition can significantly impact health outcomes.

A similar intervention in Portugal used an automated monitoring system based on indoor location detection to assess nurses’ proximity to patients and handwashing habits. Initial trials faced accuracy issues, preventing a full evaluation of the gamification elements. However, the intervention aimed to provide real-time feedback through dashboards, email notifications, and competitions with avatars and leaderboards, with its impact on hand hygiene compliance still under evaluation [65].

To prevent nosocomial infections, another study evaluated the use of the CLABSI (Central Line-Associated Bloodstream Infections) app to engage nurses in preventing infections caused by central catheters in intensive care units through a quasi-experimental design [62]. This app allowed nurses to monitor protocol compliance and compare their performance against benchmarks and their units. Over 12 months, the intervention group showed a 48% decline in CLABSI rates compared to the previous year, while the control group showed no significant change. The app included gamification elements such as leaderboards, social networking, points, team competitions, awards, and prizes. A total of 3 competitions were held during the study period. Self-assessment completions were significantly higher, with a median of 43 self-assessments per unit per month versus two in non-contest months. Nurse engagement with the app was also 10 times higher during contest months.

Prevention was at the core of another study conducted in Nigeria, aiming to change surgeons’ behavior regarding SAP [66]. A virtual mentor provided real-time feedback on surgical risk, antibiotic choice, and therapy duration. A WhatsApp group supported app usage, and 321 surgeries were recorded. The study found that 12% (n=37) of surgeons adjusted their decisions to align with guidelines, and 10% (n=33) changed their antibiotic prophylaxis decisions. Gamification elements such as challenges and digital badges increased engagement, though the app’s lack of EMR integration limited its effectiveness.

In 2015, Canada launched a 150-day campaign to enhance sepsis treatment in emergency departments using a gamification approach to increase the adoption of sepsis protocol [60]. Clinicians organized themselves as teams, and clinical data from sepsis patients were collected online, via the app, or on paper and reviewed for protocol adherence. The campaign featured a countdown clock, a daily tally of saved lives, awards, and a feedback module. Positive extrinsic motivators, such as feedback and rewards, along with intrinsic motivators, including mastery, autonomy, relatedness, and purpose, were incorporated into this life-saving campaign, which showed a reduction in severe sepsis mortality from 21% to 6%. The healthy competition among clinicians was crucial to the campaign’s success.

Lastly, 1 US-based intervention was not strictly connected to clinical care but focused on patient flow management. A radiology department implemented a tailored dashboard to address patient data collection delays. This application calculated delays using daily EMR data and displayed real-time, color-coded dashboards to alert staff. A quasi-experimental study showed that the intervention reduced patient delays over 60 minutes by 27%, with time pressure as the gamification element [64].

The primary purpose of this review was to collate existing evidence on how incorporating GDTs into the daily workflow of HCWs affects their behavior and performance in health-related tasks. Of the 12 reviewed studies, 5 [60,62,66,68,69] reported that integrating different game elements such as challenges, prizes, badges, feedback, leaderboards, social networks, competition, and time pressure helps to enhance HCWs’ engagement; 3 [60,61,71] emphasized the role of gamification in increasing motivation; 3 [62,66,67] promoted task completion and behavior change; and 4 [60,61,63,68] boosted healthy competition among users.

The reviewed studies suggested that GDTs can improve hand hygiene compliance, sick child assessment, maternal and child health care, sepsis management and control, and CLABSI rates. However, we observed significant heterogeneity across the interventions, due to differences in health care settings, the purposes of the digital tools, and user characteristics. These differences make it challenging to identify a consistent impact of GDTs. Furthermore, gamification was rarely the primary focus of the research, as most studies prioritized a comprehensive evaluation of the broader ICT strategy. As a result, isolating the specific effects of gamification from the overall digital intervention remains difficult, limiting the ability to establish clear causal links.

In other contexts, literature is rich with contributions from authors who highlighted the positive effect of gamification on education and learning [44,72,73], as well as health and wellness [45]. However, to the best of our knowledge, this review is the first to explore the integration of GDTs into the daily workflows of HCWs.

The reviewed studies offer several important insights. Evidence from HICs suggests that GDTs are most effective when integrated into a broader organizational framework that includes workflow reorganization and improved intra-team communication. Additionally, the integration of EMRs plays a key role by enabling real-time access to patient data, thereby facilitating more effective performance feedback and the delivery of timely clinical prompts. However, these structural elements require continuous attention to ensure seamless integration and to maximize the impact of GDTs, particularly when they are strategically incorporated into comprehensive public health initiatives.

On the other hand, for HCWs with limited digital literacy, particularly in LMICs, the reviewed studies suggest that a simple and engaging user interface plays a particularly important role in facilitating adoption and sustained use. Many CHWs may face challenges navigating complex systems, making it essential for the interface to be intuitive, visually appealing, and engaging. Poorly designed or overly complicated interfaces can act as significant barriers to adoption and may ultimately undermine the effectiveness of the intervention.

Among the 12 studies reviewed, only 2 [65,69] explicitly addressed the challenges associated with integrating gamification elements into broader ICT interventions. One study noted that incorporating gamification elements, which are visual and acoustic, into a digital data collection tool can drain the device’s power rapidly, potentially reducing its appeal [69]. Another study in Portugal found that requiring HCWs to engage with gamification elements like badges, virtual goods, and content unlocking outside working hours decreased their enthusiasm [65]. The same study suffered significant setbacks due to technological issues, which hampered an evaluation of the benefits of gamification.

The difficulties encountered in these studies exemplify the importance of careful design in GDTs: a technologically flawed product can compromise all the benefits of gamification, and a solution not designed with users in mind can lead to resistance from them. Researchers and developers must ensure that the gamification elements are relevant and engaging for diverse user groups, as many factors can influence attitudes toward GDTs, including age, education level, work experience, culture, and computer skills [74]. Although gamification design is fundamentally user-centered [33], none of the interventions reviewed mentioned involving users in the design process.

In this review, among the various gamification elements utilized and embedded in digital health interventions, feedback emerged as the most commonly used component. This is consistent with previous reviews on the use of gamification in other domains [11,75]. Sardi et al [11] and Edwards et al [75] reported that feedback was used in over 90% (n=60) of the studies they reviewed on eHealth and health promotion, respectively. The present review also highlights that performance feedback enhances HCWs’ experience and engagement in their tasks, leading to behavioral change [40,75].

Competition emerged as the second most utilized element of gamification in 50% (n=6) of the included interventions, corroborating findings from a previous systematic review on gamification for health profession education [18]. Dashboards, leaderboards, and scoreboards were the most commonly used elements to convey feedback and foster competition. However, the use of external rewards, such as feedback, competitions, and leaderboards, to motivate HCWs can present several important limitations, as suggested by several studies. Although such incentives may be effective in generating short-term engagement, they risk becoming repetitive or losing their appeal over time. More critically, they may fail to foster sustained engagement or promote intrinsic motivation, which are essential for long-term behavioral change and integration into routine practice [11,12,28,76]. These extrinsic motivators are highly effective at attracting initial participation, but they might not support enduring involvement as well as intrinsic motivators. Therefore, in the design of GDTs, striking a balance between extrinsic and intrinsic motivations is pivotal to maintaining engagement and fostering meaningful participation [28]. Regrettably, none of the studies analyzed in this review investigate the long-term impact of gamification or identify which specific gamification elements are most effective compared to others, limiting our ability to draw conclusions about the sustained benefits and potential limitations of GDTs.

Furthermore, although gamification is no longer a new concept in ICT, none of the studies reviewed addressed potential ethical issues. Although gamification is generally well received by HCWs, gamification may lead to unintended consequences, including addiction, cheating, or compromised data quality, especially when points, badges, or leaderboards overshadow the intended purpose [77,78]. For example, rewarding speed over accuracy may result in errors. Competition, one of the most common gamification elements adopted, fosters a spirit of healthy competition among HCWs [79]. However, it also carries the risk of demoralizing workers due to feelings of irrelevance and oppression by other users and of moving the focus excessively on measurable outcomes rather than quality [77]. To mitigate this, competition should promote teamwork through group-based formats rather than individual performance. Additionally, gamification raises ethical concerns related to user autonomy and consent [74].

Despite ethical considerations being increasingly recognized in ICTs [80], the ethical discourse within the gamification field remains underdeveloped [80-82]. Authors like Kim and Werbach [80] urge caution to avoid manipulative or harmful design practices.

This study has 2 main strengths. First, by examining the current literature and available tools, we provided an initial overview of the potential effects of integrating gamified digital tools into the daily tasks of HCWs. Second, by conducting a scoping review to map the literature broadly, we have paved the way for future work to identify and select key outcomes for systematic reviews and meta-analyses in this domain more easily.

Our review also has certain limitations. First, it was challenging to identify studies that applied gamification to the daily tasks of HCWs, as many studies do not mention gamification explicitly. To locate potential studies, we thoroughly examined the methodologies and ICT interventions to pinpoint elements of gamification accurately. Second, most interventions researched and included in our review were pilots or case studies, characterized by small sample sizes and brief follow-ups. As a result, these studies have several limitations in evaluating long-term benefits that can affect their reliability and generalizability. Third, many studies do not rigorously describe or assess changes in motivation, behavior, or health outcomes. Fourth, given our goal to capture all relevant evidence and examples, we included a broad range of study designs, as is typical in a scoping review. Due to the rapid growth in digital health, prioritizing evidence based on quality criteria to capture scientifically based findings is challenging. Therefore, we applied the criteria developed by Sardi et al [11] to assess publications focusing on GDTs, ensuring the inclusion of evidence obtained through the most scientifically sound methodologies. Fifth, although our search was not limited to English, we were unable to find evidence in Spanish, French, or Italian. Lastly, only 1 author performed the data extraction, which may have introduced errors or biases. However, to ensure the accuracy of data extraction, all authors discussed which information should be extracted before the extraction process began. Subsequently, 2 authors carefully reviewed the extracted data to verify their accuracy.

Our study highlighted that no study to date has directly compared gamified digital tools with their nongamified counterparts to assess their impact on HCWs’ daily tasks. Future research would benefit from adopting a 3-arm study design to better isolate the effects of gamification: (1) a control group without any digital tool, (2) a group using a nongamified digital tool, and (3) a group using a gamified digital tool. Furthermore, studies should incorporate longer follow-up periods and larger sample sizes to overcome the evident limitations identified in this scoping review, namely small sample sizes, lack of comparative groups, and short study durations. Extended follow-ups and broader participant inclusion would not only strengthen the robustness of findings but also allow the detection of potential tool misuse and ethical breaches that may emerge over time. Such an approach would enable a more comprehensive evaluation of whether gamification truly adds value beyond the use of digital tools alone and whether its effects are sustainable and ethically sound.

The integration of GDTs into the daily workflows of HCWs holds significant potential to enhance engagement, motivation, and overall performance across a range of health-related tasks. However, this area remains largely underexplored, with limited empirical evidence to support its systematic implementation. This gap needs more robust comparative studies to provide precise insights into the benefits and limitations of GDTs.

Therefore, due to the limited evidence base, gamification remains less developed than other components of digital health programming, such as scalability, interoperability, or digital health landscape assessment, which are often supported by established frameworks and tools. Currently, there are no formal guidelines or standardized frameworks to assist developers and policymakers in effectively integrating GDTs into broader digital strategies.

Additionally, the lack of such guidance raises the risk of ethical misuse, such as manipulation, coercion, or unintended negative effects. Therefore, clear design principles and ethical safeguards are necessary to ensure that gamification boosts engagement without harming professional integrity or user autonomy.