The term NOMOPHOBIA or NO MObile PHone PhoBIA is used to describe a psychological condition when people have a fear of being detached from mobile phone connectivity. The term NOMOPHOBIA is constructed on definitions described in the DSM-IV, it has been labelled as a “phobia for a particular/specific things”. Various psychological factors are involved when a person overuses the mobile phone, e.g., low self-esteem, extrovert personality. The burden of this problem is now increasing globally. Other mental disorders like, social phobia or social anxiety, and panic disorder may also precipitate NOMOPHOBIC symptoms. It is very difficult to differentiate whether the patient become NOMOPHOBIC due to mobile phone addiction or existing anxiety disorders manifest as NOMOPHOBIC symptoms. The signs and symptoms are observed in NOMOPHOBIA cases include- anxiety, respiratory alterations, trembling, perspiration, agitation, disorientation and tachycardia. NOMOPHOBIA may also act as a proxy to other disorders. So, we have to be very judicious regarding its diagnosis. Some mental disorders can precipitate NOMOPHOBIA also and vice versa. The complexity of this condition is very challenging to the patients’ family members as well as for the physicians as NOMOPHOBIA shares common clinical symptoms with other disorders. That's why NOMOPHOBIA should be diagnosed by exclusion. We have to stay in the real world more than virtual world. We have to re-establish the human-human interactions, face to face connections. So, we need to limit our use of mobile phones rather than banning it because we cannot escape the force of technological advancement.

Background: A high burden of non-communicable diseases (NCDs) is contributing to high mortality and morbidity in India. Recent advancements in digital health interventions, including mHealth, eHealth, and telemedicine, have facilitated patient-centered care for NCDs. Objective: This systematic review aims to evaluate the current evidence on digital interventions for people living with NCDs in India and the outcomes of those interventions. Methods: We adopted PRISMA guidelines and systematically reviewed articles from MEDLINE, CINAHL, PsycINFO, ERIC, and Scopus databases with following criteria: journal articles presenting digital intervention(s) used by people with at least one of the NCDs, reporting health outcomes following the intervention, studies conducted in India among Indian population. Results: Among 1669 articles retrieved from multiple sources, only 13 articles met our criteria. Most (n ¼ 7) studies were conducted in southern states of India; eight studies included patients with diabetes, followed by neuropsychiatric disorders and other NCDs. Five studies recruited participants from tertiary hospitals; six interventions used text-messaging for delivering health services, and 10 studies reported randomized controlled trials. All the studies reported positive health outcomes following the intervention, including better self-management, increased patient-provider communication, improved medication adherence, and reduced disease symptoms. Most studies scored moderate to high in quality assessment checklist of Downs and Black. Conclusion: Current evidence suggests a low number of interventions with positive outcomes. Future research should explore avenues of advanced technologies ensuring equitable and sustainable development of digital health interventions for people living with NCDs in India.

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Background Mass vaccination campaigns have significantly reduced the COVID-19 burden. However, vaccine hesitancy has posed significant global concerns. The purpose of this study was to determine the characteristics that influence perceptions of COVID-19 vaccine efficacy, acceptability, hesitancy and decision making to take vaccine among general adult populations in a variety of socioeconomic and cultural contexts. Methods Using a snowball sampling approach, we conducted an online cross-sectional study in 20 countries across four continents from February to May 2021. Results A total of 10,477 participants were included in the analyses with a mean age of 36±14.3 years. The findings revealed the prevalence of perceptions towards COVID-19 vaccine’s effectiveness (78.8%), acceptance (81.8%), hesitancy (47.2%), and drivers of vaccination decision-making (convenience [73.3%], health providers’ advice [81.8%], and costs [57.0%]). The county-wise distribution included effectiveness (67.8–95.9%; 67.8% in Egypt to 95.9% in Malaysia), acceptance (64.7–96.0%; 64.7% in Australia to 96.0% in Malaysia), hesitancy (31.5–86.0%; 31.5% in Egypt to 86.0% in Vietnam), convenience (49.7–95.7%; 49.7% in Austria to 95.7% in Malaysia), advice (66.1–97.3%; 66.1% in Austria to 97.3% in Malaysia), and costs (16.0–91.3%; 16.0% in Vietnam to 91.3% in Malaysia). In multivariable regression analysis, several socio-demographic characteristics were identified as associated factors of outcome variables including, i) vaccine effectiveness: younger age, male, urban residence, higher education, and higher income; ii) acceptance: younger age, male, urban residence, higher education, married, and higher income; and iii) hesitancy: male, higher education, employed, unmarried, and lower income. Likewise, the factors associated with vaccination decision-making including i) convenience: younger age, urban residence, higher education, married, and lower income; ii) advice: younger age, urban residence, higher education, unemployed/student, married, and medium income; and iii) costs: younger age, higher education, unemployed/student, and lower income. Conclusions Most participants believed that vaccination would effectively control and prevent COVID-19, and they would take vaccinations upon availability. Determinant factors found in this study are critical and should be considered as essential elements in developing COVID-19 vaccination campaigns to boost vaccination uptake in the populations.

The use of digital screens, including television, computers, mobile phones, and smart devices, can be associated with a wide range of health outcomes. During the COVID-19 pandemic, different population groups may have been adapted to varying levels of screen time, which may have profound implications on their health and wellbeing. The available evidence suggests that screen time is associated with obesity, hypertension, type 2 diabetes, myopia, depression, sleep disorders, and many other noncommunicable diseases. This elevated burden of diseases is prevalent among individuals who have sedentary lifestyles and other unhealthy behaviors that are likely to increase during quarantine or isolation due to COVID-19. As several empirical studies have reported a rising trend of screen time during this pandemic, it is critical to assess the adverse health outcomes that may appear as its long-term consequences globally. Researchers and practitioners need to revisit the available guidelines and incorporate evidence-based interventions for preventing unhealthy screen time among the affected individuals. Such interventions may address not only unhealthy screen use behavior but also promote active lifestyles that may improve health across populations during and after this pandemic.

Due to the restrictions imposed to contain the coronavirus disease 2019 (COVID-19) pandemic, different population groups have adapted to varying screen time levels, which may have profound implications on their physical and mental wellbeing. Several empirical studies included in this review reported a sudden upward change in screen time across different population groups. A higher number of people with increased screen time compared to their pre-pandemic state and prolonged duration of total screen time substantiates such assertions. The available evidence suggests that screen time is associated with obesity, hypertension, type 2 diabetes, myopia, depression, sleep disorders, and several non-communicable diseases. This elevated burden of diseases is more prevalent among individuals who have sedentary lifestyles and other unhealthy behaviors that are likely to increase during quarantine or isolation due to COVID-19. Hence, it is critical to assess the adverse health outcomes that may appear as long-term consequences of such behavior. Researchers and practitioners need to revisit the available guidelines and incorporate evidence-based interventions for preventing unhealthy screen time among the affected individuals. Such interventions may address harmful behaviors associated with screen time and promote active lifestyles that may improve health across populations during and after this pandemic.

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Blockchain technology is a decentralized system of recording data and performing transactions which is increasingly being used across many industries, including healthcare. It has several unique features like the validation of transaction processes, prevention of systems failure from any single point of transaction, and approval of data sharing with optimal security, to name a few. At the hospital level, blockchain technologies are used in the electronic medical records systems, insurance claims, billing management, and so on. Moreover, this technology is helpful to manage logistic and human resources to achieve the quality of care in learning health systems. In many countries, blockchain is being used to promote patient-centered care by sharing patient data for remote monitoring and management. Furthermore, blockchain technology has the potential to strengthen disease surveillance systems in cases of disease outbreaks resulting in local and global health emergencies. In such conditions, blockchain can be used to identify health security concerns, analyze preventive measures, and facilitate decision-making processes to act rapidly and effectively. Despite its limitations, research, and practice based on blockchain technology have shown promises to strengthen health systems around the world with a potential to reduce the global burden of diseases, mortality, morbidity, and economic costs.