BACKGROUND: Digital technology and gamified apps can be useful in the health care context. Gamification uses technology to influence users\' actions and motivations through experiences that resemble games. Patient adherence to the enhanced recovery after surgery (ERAS) program is crucial for achieving early recovery after surgery and continuous monitoring is essential for obtaining good results.
OBJECTIVE: This study aimed to describe the development and validation of a mobile app for enhanced recovery after surgery (MobERAS), a gamified mobile health app for telemonitoring patients in the postoperative period based on the ERAS program, and to evaluate its functionality and usability and the experience of patients, health care professionals, and computer professionals with its use.
METHODS: We developed MobERAS for postoperative telemonitoring, with active participation of patients in the process, and offering availability of real-time information for the health team. The app development process included idealization, interdisciplinary team formation, potential needs assessment, and product deployment. Usability tests were conducted throughout the development process with improvements, technical adjustments, and updates. After finalization, comprehensive verification tests were performed. The parameters evaluated are those that can influence the length of hospital stay, such as nausea, vomiting, pain scales, return to normal gastrointestinal function, and thromboembolic events. MobERAS was designed to be downloaded by users on their phones, tablets, or other mobile devices and to provide postoperative data. The app has a GPS that monitors the patient\'s walking time and distance and is connected to a virtual database that stores the collected data.
RESULTS: Women undergoing medium and major gynecologic oncologic surgeries were included. We included 65 patients with an average age of 53.2 (SD 7.4, range 18-85) years. The time of use ranged from 23.4 to 70 hours (mean 45.1, SD 19.2 hours). Regarding adherence to the use of MobERAS, the mean fill rate was 56.3% (SD 12.1%, range 41.7%-100%), and ambulation data were obtained for 60 (92.3%) of the 65 patients. The researcher had access to the data filled out by the patients in real time. There was good acceptance of the use of MobERAS by the patients, with good evaluation of the app\'s usability. MobERAS was easy to use and considered attractive because of its gamified design. The app was rated as good or very good in all items by health care professionals (n=20) and professionals specializing in technological innovation (n=10).
CONCLUSIONS: MobERAS is easy to use, safe, well accepted by patients, and well evaluated by experts. It can be of great use in clinical surgical practice and an important tool for greater engagement of patients and health care professionals with the ERAS program.

BACKGROUND:  Major bile duct injuries during laparoscopic cholecystectomy (LC), often stemming from errors in surgical judgment and visual misperception of critical anatomy, significantly impact morbidity, mortality, disability, and health care costs.
OBJECTIVE:  To enhance safe LC learning, we developed an educational mobile game, LapBot Safe Chole, which uses an artificial intelligence (AI) model to provide real-time coaching and feedback, improving intraoperative decision-making.
METHODS:  LapBot Safe Chole offers a free, accessible simulated learning experience with real-time AI feedback. Players engage with intraoperative LC scenarios (short video clips) and identify ideal dissection zones. After the response, users receive an accuracy score from a validated AI algorithm. The game consists of 5 levels of increasing difficulty based on the Parkland grading scale for cholecystitis.
RESULTS:  Beta testing (n=29) showed score improvements with each round, with attendings and senior trainees achieving top scores faster than junior residents. Learning curves and progression distinguished candidates, with a significant association between user level and scores (P=.003). Players found LapBot enjoyable and educational.
CONCLUSIONS:  LapBot Safe Chole effectively integrates safe LC principles into a fun, accessible, and educational game using AI-generated feedback. Initial beta testing supports the validity of the assessment scores and suggests high adoption and engagement potential among surgical trainees.

BACKGROUND: Machine learning (ML) models can yield faster and more accurate medical diagnoses; however, developing ML models is limited by a lack of high-quality labeled training data. Crowdsourced labeling is a potential solution but can be constrained by concerns about label quality.
OBJECTIVE: This study aims to examine whether a gamified crowdsourcing platform with continuous performance assessment, user feedback, and performance-based incentives could produce expert-quality labels on medical imaging data.
METHODS: In this diagnostic comparison study, 2384 lung ultrasound clips were retrospectively collected from 203 emergency department patients. A total of 6 lung ultrasound experts classified 393 of these clips as having no B-lines, one or more discrete B-lines, or confluent B-lines to create 2 sets of reference standard data sets (195 training clips and 198 test clips). Sets were respectively used to (1) train users on a gamified crowdsourcing platform and (2) compare the concordance of the resulting crowd labels to the concordance of individual experts to reference standards. Crowd opinions were sourced from DiagnosUs (Centaur Labs) iOS app users over 8 days, filtered based on past performance, aggregated using majority rule, and analyzed for label concordance compared with a hold-out test set of expert-labeled clips. The primary outcome was comparing the labeling concordance of collated crowd opinions to trained experts in classifying B-lines on lung ultrasound clips.
RESULTS: Our clinical data set included patients with a mean age of 60.0 (SD 19.0) years; 105 (51.7%) patients were female and 114 (56.1%) patients were White. Over the 195 training clips, the expert-consensus label distribution was 114 (58%) no B-lines, 56 (29%) discrete B-lines, and 25 (13%) confluent B-lines. Over the 198 test clips, expert-consensus label distribution was 138 (70%) no B-lines, 36 (18%) discrete B-lines, and 24 (12%) confluent B-lines. In total, 99,238 opinions were collected from 426 unique users. On a test set of 198 clips, the mean labeling concordance of individual experts relative to the reference standard was 85.0% (SE 2.0), compared with 87.9% crowdsourced label concordance (P=.15). When individual experts\' opinions were compared with reference standard labels created by majority vote excluding their own opinion, crowd concordance was higher than the mean concordance of individual experts to reference standards (87.4% vs 80.8%, SE 1.6 for expert concordance; P<.001). Clips with discrete B-lines had the most disagreement from both the crowd consensus and individual experts with the expert consensus. Using randomly sampled subsets of crowd opinions, 7 quality-filtered opinions were sufficient to achieve near the maximum crowd concordance.
CONCLUSIONS: Crowdsourced labels for B-line classification on lung ultrasound clips via a gamified approach achieved expert-level accuracy. This suggests a strategic role for gamified crowdsourcing in efficiently generating labeled image data sets for training ML systems.

BACKGROUND: Evidence supports the effectiveness of serious games in health education, but little is known about their effects on the psychosocial well-being of children in the general population.
OBJECTIVE: This study aimed to investigate the potential of a mobile game-based safety education program in improving children\'s safety and psychosocial outcomes.
METHODS: Safe City is a mobile roleplaying game specifically designed to educate children in Hong Kong about safety. This randomized controlled trial included 340 children in grades 4 through 6. Intervention arm participants (n=170) were instructed to play the Safe City mobile game for 4 weeks, whereas control arm participants (n=170) received a safety booklet. All participants completed a survey on safety knowledge and behaviors and psychosocial problems at baseline (T1), 1 month postintervention (T2), and 3 months postintervention (T3). Cumulative game scores and mini-game performance were analyzed as a proxy for the extent of exposure to the game. Outcome data were analyzed using 2-sample 2-tailed t tests to compare mean change from T1 to T2 and to T3 for intervention versus control arm participants. The association of game use with outcome changes postintervention was analyzed using generalized additive models.
RESULTS: No significant differences were found in mean changes between the intervention and control arms. However, use analyses showed that higher game scores were associated with improvements in safe behavior (P=.03) and internalizing problems (P=.01) at T3. Matching and Spot the Danger mini-game performance significantly predicted improvements in safety knowledge at T2 and T3.
CONCLUSIONS: Analysis of use has shown that playing the Safe City mobile game can result in significant improvements in safety knowledge and reductions in unsafe behavior and internalizing problems. These findings provide evidence for the positive impact of serious games on psychological and social well-being, highlighting the potential of technology-driven interventions to assist children in learning about safety and preventing injuries.
BACKGROUND: ClinicalTrials.org NCT04096196; https://clinicaltrials.gov/show/NCT04096196.
UNASSIGNED: RR2-10.2196/17756.

OBJECTIVE: Gamification broadly refers to the use of game design elements in non-game contexts with the goal of promoting users\' engagement. Gamification strategies appear as an advantageous tool to increase the motivation and involvement of users. The purpose of this systematic review is to identify studies using gamification strategies in distinct intervention contexts and to describe their impact in each type of intervention. Thus, the focus is on the construct (gamification) rather than on a particular area or population.
RESULTS: To achieve this goal, Scopus, IEEE, Web of Science, MEDLINE, ERIC, and PsycINFO databases will be used to gather data for the systematic review. Both the research and report of results will be based on Cochrane\'s recommendations and PRISMA guidelines. Data, including the assessment on the quality of the articles, will be conducted by two members of the team independently. Findings will be reported narratively. The ethical approval is not required as the research does not involve data collection. Findings will be submitted to a peer-review journal and the results will be presented on international congresses. Future reviews could consider investigating particular areas of intervention in which gamification strategies are being employed. Trial registration Systematic Review Registration: PROSPERO CRD42017070508.