This study shows how nudge theory-based interventions, when combined with consultation, can significantly improve the awareness, knowledge, attitude, and practices of diabetes patients in Sikkim. These results indicate that such interventions can act as an effective approach to improve diabetes self-care attitude and patient’s health behaviour.

Often, Individuals try to choose the best feasible option but sometimes, they don’t succeed in doing so. They make mistakes. Also, the market exchange makes psychological factors cease to matter but many psychological factors matter even for the markets. In contrast to the traditional assumption of neoclassical economics that individuals are rational Homooeconomici, that always seek to maximize their utility and follow their “true” preferences, research in behavioural economics has demonstrated that people’s judgments and decisions are often subject to systematic biases and heuristics, and are strongly dependent on the context of the decision.

Eliminating the need for manual meal announcement, the proposed algorithm overcomes a key barrier to fully automated glucose management, reducing patient burden while maintaining reliable detection performance even in unstructured, free-living conditions. These results support the integration of the algorithm into DSSs for PBH and other populations, where timely and accurate meal detection is critical.

It is a statement of basic ethical principles and guidelines that should assist in resolving the ethical problems that surround the conduct of research with ...

This article addresses a critical gap in artificial intelligence development by advocating for the integration of behavioral science into AI research and deployment. The author argues that while technical expertise dominates the field, a deeper understanding of human behavior, psychology, and decision-making is essential for creating AI systems that effectively interact with and serve human users. By incorporating behavioral science principles, AI developers can better anticipate how people will actually use these technologies, identify potential biases, and design more ethical and effective solutions. This interdisciplinary approach would enhance AI's practical applicability and trustworthiness in real-world contexts.

Continuous lactate monitoring represents an emerging frontier in metabolic health assessment, building upon the success of continuous glucose monitoring systems. While lactate has traditionally been measured only through blood samples in clinical settings, advancing wearable sensor technology now enables real-time tracking of lactate levels in interstitial fluid. Unlike glucose monitoring alone, continuous lactate measurement offers valuable insights into energy production and utilization during exercise, stress, illness, and recovery phases. As biotechnology companies and research institutions develop increasingly reliable biosensor systems, this complementary monitoring approach promises to provide a more comprehensive understanding of metabolic health. Though still in development stages, early evidence suggests these minimally invasive sensors can accurately track lactate fluctuations throughout the day, potentially revolutionizing how clinicians and patients manage metabolic conditions.

Integration of social media (SM) with mobile health (mHealth) platforms presents significant potential to address the persistent challenge of disengagement in digital health interventions among young people. However, empirical evidence supporting this combined approach remains limited, as SM and mHealth are often examined in isolation. This systematic review aimed to identify and synthesise the determinants influencing the participation in SM and mHealth interventions for behaviour change among young people aged 14 to 35 years.

Health app onboarding differs fundamentally from fintech onboarding in one critical way: trust. In fintech, users trust the platform (bank, payment app) and your job is to minimize friction. In health, users are skeptical. They're sharing intimate medical information and betting their health on your platform's ability to connect them with qualified doctors.This means health app onboarding must build trust early. Users need to see that you have real doctors, that their data is secure, and that they'll get a response quickly. Before they'll fill a health profile, they need confidence the system works.

Gamification has done some remarkable things. It taught hundreds of millions of people a second language (or at least to feel guilty about not practicing one). It made saving money feel like leveling up a character. It turned going to the gym into a competitive sport, complete with leaderboards and achievement badges. It has, arguably, made a lot of people brush their teeth longer than they otherwise would.So why, after more than a decade of serious investment and serious effort, do health apps still struggle to move the needle on the things that actually matter?

CGM technology allows patients and doctors to focus on "Time in Range"the percentage of the day spent within the target glucose window. Users are looking for ...

Nutrition-tracking apps like MyFitnessPal and Noom employ gamification features—colored indicators, achievement badges, and streak notifications—to encourage user engagement and habit formation. While these tools offer legitimate benefits for managing chronic conditions like diabetes and heart disease, and many users find them motivating, researchers caution that gamification may pose risks for vulnerable populations. Psychologist Isabella Anderberg warns that calorie tracking can reinforce disordered eating patterns and body dysmorphia in susceptible individuals. Health professionals recognize the apps' value as meal-planning resources, yet experts recommend a cautious approach, acknowledging that not all users experience harm but certain factors increase vulnerability to negative outcomes.

Nudge theory, which employs subtle design changes to encourage behavioral shifts without restricting choice, has gained traction as a potential solution for reducing meat consumption. While research demonstrates that nudges can modestly decrease meat intake, significant caveats exist regarding their long-term effectiveness. Despite environmental, ethical, and health concerns associated with meat production, traditional interventions have failed to substantially increase vegetarian and vegan adoption rates over decades. The article explores whether nudges represent a viable pathway to dietary transformation or merely offer a superficial shortcut to meaningful change, suggesting that their actual impact may be more limited than media coverage implies.

This scoping review examines gamification-based interventions designed to enhance treatment adherence and self-management in children with chronic diseases, with particular focus on thalassemia applications. Conducted using Joanna Briggs Institute methodology and PRISMA-ScR guidelines, the study systematically searched five major databases from 2016 to 2026, ultimately analyzing sixteen studies involving pediatric chronic disease patients. The research addresses a critical gap in pediatric healthcare, as chronic disease management in children presents significant challenges to physical, psychological, and social well-being. Gamification represents an innovative approach to improving patient engagement and health behaviors, yet its implementation in thalassemia treatment remains underutilized. This comprehensive analysis identifies key findings and implications for developing gamified interventions specifically tailored to support children requiring lifelong treatment protocols.

Duolingo has revolutionized language learning through sophisticated gamification strategies that combine behavioral psychology with artificial intelligence. With over 100 million monthly active users, the platform drives industry-leading retention by embedding habit-loop mechanics that transform education into engaging gameplay. Key features including AI-enhanced streaks, competitive leaderboards, and theme-based lessons have dramatically improved user engagement, reducing churn from 47% in 2020 to 28% in core markets. This engagement-focused approach has resulted in a 36% year-over-year increase in daily active users as of 2025 and a tenfold growth in daily active users since 2019. Duolingo's success demonstrates how integrating game mechanics with personalized learning pathways creates a sustainable model for user retention and motivation in educational technology.

Health apps face significant retention challenges, with Day 30 retention averaging 15-25% and dropping to 6-10% by Day 90. The most successful applications achieve 40%+ Day 30 retention by facilitating genuine behavior change rather than relying on superficial engagement tactics. The critical differentiator is providing users with measurable health outcomes and progress feedback, establishing a clear action-to-result feedback loop that sustains motivation. Health behavior change is inherently difficult as users typically download apps during high-motivation periods but abandon them when motivation wanes or results remain invisible. Effective retention requires designing features that support continued engagement during low-motivation phases. Drawing from BJ Fogg's Tiny Habits framework, successful health apps implement minimal daily actions—such as five-second metric logging—anchored to existing routines with immediate rewards. Product teams should prioritize designing quick daily habit loops under 60 seconds, featuring trigger notifications, tiny actions, and immediate gratification through visual feedback and progress tracking.

Sensor-Wide Association Studies (SWAS) represent a methodological framework adapted from genomic association studies to the realm of digital medicine. This approach systematically scans high-dimensional, longitudinal data generated by wearables, smartphones, and connected devices against predefined clinical phenotypes. By establishing minimal standards, transparent feature documentation, and appropriate statistical controls, SWAS aims to facilitate reproducible digital epidemiology and personalized medicine. The framework addresses common pitfalls in analyzing sensor data while maintaining ethical considerations, enabling researchers to identify meaningful associations between continuous multimodal signals and health outcomes in a structured, hypothesis-generating manner.

Real-time data analytics significantly enhance patient medication adherence by enabling early risk detection and timely intervention. With approximately 50% of patients not following prescribed medication regimens, organizations require live monitoring signals and automated alert systems to drive better outcomes. Research demonstrates that refreshing adherence models every 15 minutes improves compliance by 5% across large patient populations. Effective implementation requires connecting real-time data to specific adherence goals, leveraging direct behavioral signals from smart devices like pill bottles and blister packs, and establishing clear trigger rules tailored to individual patient journeys. By identifying risk patterns early—whether related to medication refills, side effects, or pre-operative readiness—healthcare systems can route timely interventions to appropriate personnel, ultimately transforming data insights into actionable outcomes that prevent treatment discontinuation and improve patient health.

This research examines how different disclosure messages influence the effectiveness of behavioral nudges. The study investigates whether transparency about nudge mechanisms affects behavioral outcomes and consumer responses. By analyzing various disclosure approaches, the research contributes to understanding the tension between nudge effectiveness and informed consumer choice. The findings have important implications for policymakers and organizations seeking to implement ethical nudging strategies while maintaining public trust and transparency in behavioral interventions.

Healthcare traditionally focuses on episodic clinical encounters, neglecting the 8,759 hours annually where daily behaviors fundamentally shape health outcomes. This paper proposes the Personal Care Utility, a foundational infrastructure layer addressing this gap by continuously monitoring personal health signals and translating them into actionable guidance. The architecture employs a Personicle to organize data into meaningful life events, estimates dynamic health states against individual baselines, and routes recommendations through an orchestrator that separates clinical logic from behavioral strategy and communication. Demonstrated through Type 2 Diabetes management, PCU integrates continuous glucose monitoring, activity, medication, and stress data to generate context-appropriate interventions. By treating personalization as an architectural property rather than a messaging overlay, this framework provides real-time guidance while maintaining safety through evidence-grounded clinical decision-making, with applicability across chronic conditions and implications for governance of always-on health systems.

This evidence gap map systematically identifies and synthesizes research on digital health interventions designed to enhance health outcomes across populations. The study catalogs existing evidence, highlighting areas with robust empirical support and significant research gaps within the digital health landscape. By mapping the distribution of studies across intervention types, health conditions, and populations, the research provides critical insights for researchers, policymakers, and practitioners seeking to prioritize future investigations. The findings inform strategic resource allocation and guide the development of evidence-based digital health solutions, ultimately supporting improved health delivery and population health management in an increasingly digital healthcare environment.