Background: Increasing smartphone use has led to the introduction of smartphone addiction as a behavioral addiction with detrimental effects on health. This phenomenon has not been widely studied in the Indian context. This study assessed the rate of smartphone addiction in a sample of medical students, with a focus on its correlation with sleep quality and stress levels. Methods: A cross-sectional study was conducted between November 2016 and January 2017 in 195 medical students. Their smartphone use, level of smartphone addiction, sleep quality, and perceived stress levels were measured using the Smartphone Addiction Scale-Short Version (SAS-SV), the Pittsburgh Sleep Quality Index (PSQI), and the Perceived Stress Scale (PSS-10), respectively. Results: Of the 195 students, 90 (46.15%) had smartphone addiction as per the scale. A self-reported feeling of having smartphone addiction, use of the smartphone right before sleeping, PSS scores, and PSQI scores were found to be significantly associated with the SAS-SV scores. Significant positive correlations were observed between the SAS-SV and PSS-10 scores, and the SAS-SV and PSQI scores. Conclusions: There is a high magnitude of smartphone addiction in medical students of a college in Western Maharashtra. The significant association of this addiction with poorer sleep quality and higher perceived stress is a cause for concern. The high self-awareness among students about having smartphone addiction is promising. However, further studies are required to determine whether this self-awareness leads to treatment seeking. Further studies are required to explore our finding of the association of smartphone addiction with using the smartphone before sleeping.
Background Rural India has a severe shortage of human resources for health (HRH). The National Rural Health Mission (NRHM) deploys HRH in the rural public health system to tackle shortages. Sanctioning under NRHM does not account for workload resulting in inadequate and inequitable HRH allocation. The Workforce Indicators of Staffing Needs (WISN) approach can identify shortages and inform appropriate sanctioning norms. India currently lacks nationally relevant WISN estimates. We used existing data and modelling techniques to synthesize such estimates. Methods We conducted a retrospective analysis of existing survey data for 93 facilities from 5 states over 8 years to create WISN calculations for HRH cadres at primary and community health centres (PHCs and CHCs) in rural areas. We modelled nationally representative average WISN-based requirements for specialist doctors at CHCs, general doctors and nurses at PHCs and CHCs. For 2019, we calculated national and state-level overall and per-centre WISN differences and ratios to depict shortage and workload pressure. We checked correlations between WISN ratios for cadres at a given centre-type to assess joint workload pressure. We evaluated the gaps between WISN-based requirements and sanctioned posts to investigate suboptimal sanctioning through concordance analysis and difference comparisons. Results In 2019, at the national-level, WISN differences depicted workforce shortages for all considered HRH cadres. WISN ratios showed that nurses at PHCs and CHCs, and all specialist doctors at CHCs had very high workload pressure. States with more workload on PHC-doctors also had more workload on PHC-nurses depicting an augmenting or compounding effect on workload pressure across cadres. A similar result was seen for CHC-specialist pairs—physicians and surgeons, physicians and paediatricians, and paediatricians and obstetricians–gynaecologists. We found poor concordance between current sanctioning norms and WISN-based requirements with all cadres facing under-sanctioning. We also present across-state variations in workforce problems, workload pressure and sanctioning problems. Conclusion We demonstrate the use of WISN calculations based on available data and modelling techniques for national-level estimation. Our findings suggest prioritising nurses and specialists in the rural public health system and updating the existing sanctioning norms based on workload assessments. Workload-based rural HRH deployment can ensure adequate availability and optimal distribution.
BACKGROUND Rural India has a severe shortage of human resources for health (HRH). The National Rural Health Mission (NRHM) deploys HRH in the rural public health system to tackle shortages. Sanctioning under NRHM does not account for workload resulting in inadequate and inequitable HRH allocation. The Workforce Indicators of Staffing Needs (WISN) approach can identify shortages and inform appropriate sanctioning norms. India currently lacks nationally-relevant WISN estimates. We used existing data and modelling techniques to synthesize such estimates. METHODS We conducted a retrospective analysis of existing survey data for 93 facilities from 5 states over 8 years to create WISN calculations for HRH cadres at primary and community health centres (PHCs and CHCs) in rural areas. We modelled nationally-representative average WISN-based requirements for specialist doctors at CHCs, general doctors and nurses at PHCs and CHCs. For 2019, we calculated national and state-level overall and per-centre WISN differences and ratios to depict shortage and workload pressure. We checked correlations between WISN ratios for cadres at a given centre-type to assess joint workload pressure. We evaluated the gaps between WISN-based requirements and sanctioned posts to investigate suboptimal sanctioning through concordance analysis and difference comparisons. RESULTS In 2019, at the national-level, WISN differences depicted workforce shortages for all considered HRH cadres. WISN ratios showed that nurses at PHCs and CHCs, and all specialist doctors at CHCs had very high workload pressure. States with more workload on PHC-doctors also had more workload on PHC-nurses depicting an augmenting or compounding effect on workload pressure across cadres. A similar result was seen for CHC-specialist pairs - physicians and surgeons, physicians and paediatricians, and paediatricians and obstetricians-gynaecologists. We found poor concordance between current sanctioning norms and WISN-based requirements with all cadres facing under-sanctioning. We also present across-state variations in workforce problems, workload pressure and sanctioning problems. CONCLUSION We demonstrate the use of WISN calculations based on available data and modelling techniques for national-level estimation. Our findings suggest prioritising nurses and specialists in the rural public health system and updating the existing sanctioning norms based on workload assessments. Workload-based rural HRH deployment can ensure adequate availability and optimal distribution.
In the ongoing COVID-19 pandemic, countries across the globe undertook several stringent movement restrictions to prevent the virus spread. In April 2020, around 3.9 billion people in 90 countries were contained in their homes. Discourse on the ethical questions raised by such restrictions while historically rich is absent when it comes to pragmatic policy considerations by the decision-makers. Drawing from the existing literature, we present a unified ethical principles–pragmatic considerations–policy indicators framework flexibly applicable across different countries and contexts to assess the ethical soundness of movement-restricting policies. Our framework consolidates 11 unique but related ethical principles (harm, justifiability, proportionality, least restrictive means, utility efficiency, reciprocity, transparency, relevance, equity, accountability, and cost and feasibility). We mapped each ethical principle to answerable questions or pragmatic considerations to subsequently generate 34 policy indicators. These policy indicators can help policymakers and health practitioners to decide the ethically substantiated initiation of movement restrictions, monitor progress and systematically evaluate the imposed restrictions. As an example, we applied the framework to evaluate the first two phases of the largest lockdown (March–May 2020) implemented nationwide in India for its adherence to ethical principles. The policy indicators revealed ethical lapses in proportionality, utility efficiency and accountability for India’s lockdown that should be focused on in subsequent restrictions. The framework possesses value towards ensuring that movement-restrictive public health interventions across different parts of the world in the ongoing pandemic and possible future outbreaks are ethically sound.
BACKGROUND Screen use time has increased in the past decade owing to the increased availability and accessibility of electronic devices and the internet. Several studies have shown an association between increased screen use time and mental health issues like anxiety and depression. However, screen use is vital to modern life. It thus becomes pertinent to establish thresholds for screen use time to protect one’s mental well-being. OBJECTIVE We aim to measure the self-reported screen use times and patterns in young adults (18-24 years) in India, study the hypothesis that increased screen use time is associated with poorer mental well-being, and establish thresholds for ‘safe’ screen exposure time. METHODS This protocol describes a cross-sectional study of a pan-India online convenience sample of young adults that have access to digital devices with a screen and a minimum of secondary school education. Participants will be recruited through a network of collaborators via social media while data will be collected through Google forms. Socio-demographic details will be collected through a questionnaire designed by the authors; screen use time and patterns will be assessed using an adaptation of the screen time questionnaire to include data on different applications and websites used on electronic devices; while mental health parameters will be gauged using the Warwick-Edinburgh mental well-being scale, Generalized Anxiety Disorder (GAD)-7, Perceived Stress Scale (PSS)-10, and Patient Health Questionnaire (PHQ)-9. To quantify the association between the screen use time with mental health, a Bayesian multivariate multiple regression analysis will be performed which models the possibility of multiple alternative hypotheses while accounting for relevant socio-demographic covariables. RESULTS We have designed the questionnaire (survey instrument) and have received feedback from domain experts. We have not yet initiated the data collection and the results obtained will be updated accordingly. CONCLUSIONS This study could help better understand the role of screen time use on mental health, and determine the healthy levels of use in India, where the largest young adult population resides.
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