Explore the vast range of titles available.

In this study, QRMHF-DNK (Quasi Reflection Metropolis Hasting Firefly- Deep Neural Kernel), a hybrid framework is designed to improve fake news detection on benchmark datasets. The framework integrates three main stages: data preprocessing to reduce sampling errors, feature selection using a swarm-based optimization strategy, and classification using a deep neural kernel model. This combination enables effective handling of high-dimensional textual data while accurately identifying informative features for classification. The proposed framework was evaluated on a publicly available Kaggle fake news dataset and compared with existing cooperative and multilingual deep learning methods. Experimental results show that QRMHF-DNK achieves a precision of 0.98 and recall of 0.95, with a sampling error of 0.0671%, indicating that the sampled data closely represents the true class distribution. These results demonstrate the effectiveness of the proposed approach on the evaluated dataset and suggest its potential applicability to fake news detection tasks, while further validation on additional datasets is left for future work.

Background & objectives: COVID-19 pandemic has triggered social stigma towards individuals affected and their families. This study describes the process undertaken for the development and validation of scales to assess stigmatizing attitudes and experiences among COVID-19 and non-COVID-19 participants from the community. Methods: COVID-19 Stigma Scale and Community COVID-19 Stigma Scale constituting 13 and six items, respectively, were developed based on review of literature and news reports, expert committee evaluation and participants' interviews through telephone for a multicentric study in India. For content validity, 61 (30 COVID-19-recovered and 31 non-COVID-19 participants from the community) were recruited. Test-retest reliability of the scales was assessed among 99 participants (41 COVID-19 recovered and 58 non-COVID-19). Participants were administered the scale at two-time points after a gap of 7-12 days. Cronbach's alpha, overall percentage agreement and kappa statistics were used to assess internal consistency and test-retest reliability. Results: Items in the scales were relevant and comprehensible. Both the scales had Cronbach's α above 0.6 indicating moderate-to-good internal consistency. Test-retest reliability assessed using kappa statistics indicated that for the COVID-19 Stigma Scale, seven items had a moderate agreement (0.4-0.6). For the Community COVID-19 Stigma Scale, four items had a moderate agreement. Interpretation & conclusions: Validity and reliability of the two stigma scales indicated that the scales were comprehensible and had moderate internal consistency. These scales could be used to assess COVID-19 stigma and help in the development of appropriate stigma reduction interventions for COVID-19 infected, and mitigation of stigmatizing attitudes in the community.

COVID-19 pandemic has triggered social stigma towards individuals affected and their families. This study describes the process undertaken for the development and validation of scales to assess stigmatizing attitudes and experiences among COVID-19 and non-COVID-19 participants from the community. COVID-19 Stigma Scale and Community COVID-19 Stigma Scale constituting 13 and six items, respectively, were developed based on review of literature and news reports, expert committee evaluation and participants' interviews through telephone for a multicentric study in India. For content validity, 61 (30 COVID-19-recovered and 31 non-COVID-19 participants from the community) were recruited. Test-retest reliability of the scales was assessed among 99 participants (41 COVID-19 recovered and 58 non-COVID-19). Participants were administered the scale at two-time points after a gap of 7-12 days. Cronbach's alpha, overall percentage agreement and kappa statistics were used to assess internal consistency and test-retest reliability. Items in the scales were relevant and comprehensible. Both the scales had Cronbach's α above 0.6 indicating moderate-to-good internal consistency. Test-retest reliability assessed using kappa statistics indicated that for the COVID-19 Stigma Scale, seven items had a moderate agreement (0.4-0.6). For the Community COVID-19 Stigma Scale, four items had a moderate agreement. Validity and reliability of the two stigma scales indicated that the scales were comprehensible and had moderate internal consistency. These scales could be used to assess COVID-19 stigma and help in the development of appropriate stigma reduction interventions for COVID-19 infected, and mitigation of stigmatizing attitudes in the community.

Background/Objectives: Globally, the COVID-19 pandemic and its prevention and control policies have impacted maternal and child health (MCH) services. This study documents the challenges faced by patients in accessing MCH services, and the experiences of health care providers in delivering those services during the COVID-19 outbreak, explicitly focusing on the lockdown period in India. Methods: A cross-sectional study (rapid survey) was conducted in 18 districts from 6 states of India during March to June, 2020. The sample size included 540 MCH patients, 18 gynaecologists, 18 paediatricians, 18 district immunisation officers and 108 frontline health workers. Bivariate analysis and multivariable analysis were used to assess the association between sociodemographic characteristics, and challenges faced by the patients. Results: More than one-third of patients (n = 212; 39%) reported that accessing MCH services was a challenge during the lockdown period, with major challenges being transportation-related difficulties (n = 99; 46%) unavailability of hospital-based services (n = 54; 23%) and interrupted outreach health services (n = 39; 18.4%). The supply-side challenges mainly included lack of infrastructural preparedness for outbreak situations, and a shortage of human resources. Conclusions/Recommendations: A holistic approach is required that focuses on both preparedness and response to the outbreak, as well reassignment and reinforcement of health care professionals to continue catering to and maintaining essential MCH services during the pandemic.