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Item A Framework of Intelligent Mental Health Monitoring in Smart Cities and Societies(IETE J. Res., 2023) Arpita Chakraborty; Jyoti Sekhar Banerjee; Ritam Bhadra; Anik Dutta; Shatabdi Ganguly; Deblina Das; Souvik Kundu; Mufti Mahmud; Gautam SahaIn any smart city and society, the citizens' mental health is one of the utmost concerns. Nowadays, people from different sectors of our community face a severe mental health threat due to the prolonged pandemic of COVID-19. Depression, anxiety, suicidal behaviours, and posttraumatic stress disorder are widespread terms nowadays for students, health care workers, jobless people, etc. And Machine Learning (ML), image processing, expert systems, Internet of Things (IoT) are performing an essential function in the significant acceleration of the automation process within the healthcare industry. Therefore, this article aims to address the problem of preventing mental health disorders by early predicting individuals using the developed web portal Mind Turner; and by integrating the mentioned emerging tools in this way, later chronic mental health disorders can be avoided. We used the Random Forest Classifier to detect stress levels from the Question-Answer-based assessment, and SVM is used to detect facial emotions. Finally, both are combined using Interval Type-2 Fuzzy Logic to predict the probable mental health of a person, i.e. acute depression, moderate depression and not depressed.Item A step closer towards achieving universal health coverage: the role of gender in enrolment in health insurance in India(BMC Health Serv. Res., 2024) Susanne Ziegler; Swati Srivastava; Divya Parmar; Sharmishtha Basu; Nishant Jain; Manuela De AllegriBackgroundThere is limited understanding of how universal health coverage (UHC) schemes such as publicly-funded health insurance (PFHI) benefit women as compared to men. Many of these schemes are gender-neutral in design but given the existing gender inequalities in many societies, their benefits may not be similar for women and men. We contribute to the evidence by conducting a gender analysis of the enrolment of individuals and households in India's national PFHI scheme, Rashtriya Swasthya Bima Yojana (RSBY).MethodsWe used data from a cross-sectional household survey on RSBY eligible families across eight Indian states and studied different outcome variables at both the individual and household levels to compare enrolment among women and men. We applied multivariate logistic regressions and controlled for several demographic and socio-economic characteristics.ResultsAt the individual level, the analysis revealed no substantial differences in enrolment between men and women. Only in one state were women more likely to be enrolled in RSBY than men (AOR: 2.66, 95% CI: 1.32-5.38), and this pattern was linked to their status in the household. At the household level, analyses revealed that female-headed households had a higher likelihood to be enrolled (AOR: 1.36, 95% CI: 1.14-1.62), but not necessarily to have all household members enrolled.ConclusionFindings are surprising in light of India's well-documented gender bias, permeating different aspects of society, and are most likely an indication of success in designing a policy that did not favour participation by men above women, by mandating spouse enrolment and securing enrolment of up to five family members. Higher enrolment rates among female-headed households are also an indication of women's preferences for investments in health, in the context of a conducive policy environment. Further analyses are needed to examine if once enrolled, women also make use of the scheme benefits to the same extent as men do. India is called upon to capitalise on the achievements of RSBY and apply them to newer schemes such as PM-JAY.Item Access and barriers to maternal health program: a community perspective in a tribal area of Odisha, India(Asia Pac. J. Soc. Work Dev., 2023) Ranjit Kumar DehuryThe janani surakhya yojana (JSY), a flagship programme of the national health mission (NHM), was implemented to reduce maternal and neonatal mortality by promoting institutional delivery among marginalised pregnant women in India. This study provides an account of the challenges faced by tribal pregnant women in accessing reproductive health care services. Primary data was collected from various maternal health stakeholders and expectant mothers using qualitative methods. The study adopted data collection methods like focus group discussions (FGDs) and in-depth interviews regarding the programme implementation of JSY at Jaleswar. Secondary data were analysed to understand the effectiveness of government policy in improving maternal health. The study indicates that despite an elaborate programme of action, there is low community perception and trust in bio-medical (mostly) procedures among the tribal population. The government programmes rarely compliment the tribal cultural construction of pregnancy and child birthing with existing medical and professional discourse.