Automated Author ProfileMishra, Nagendra N.
Atal Bihari Vajpayee Institute of Medical Sciences and Dr. Ram Manohar Lohia Hospital
Mishra, Nagendra N.
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 0.9 (sum of 1 dataset Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Objective: To assess the effect of experienced stigma on depth of multidimensional poverty of persons with severe mental illness (PSMI) in Delhi, India, controlling for gender, age and caste. Design: Matching case (hospital)–control (population) study. Setting: University Hospital (cases) and National Capital Region (controls), India. Participants: A case–control study was conducted from November 2011 to June 2012. 647 cases diagnosed with schizophrenia or affective disorders were recruited and 647 individuals of same age, sex and location of residence were matched as controls at a ratio of 1:2:1. Individuals who refused consent or provided incomplete interview were excluded. Main outcome measures: Higher risk of poverty due to stigma among PSMI. Results: 38.5% of PSMI compared with 22.2% of controls were found poor on six dimensions or more. The difference in multidimensional poverty index was 69% between groups with employment and income of the main contributors. Multidimensional poverty was strongly associated with stigma (OR 2.60, 95% CI 1.27 to 5.31), scheduled castes/scheduled tribes/other backward castes (2.39, 1.39 to 4.08), mental illness (2.07, 1.25 to 3.41) and female gender (1.87, 1.36 to 2.58). A significant interaction between stigma, mental illness and gender or caste indicates female PSMI or PSMI from ‘lower castes’ were more likely to be poor due to stigma than male controls (p<0.001) or controls from other castes (p<0.001). Conclusions: Public stigma and multidimensional poverty linked to SMI are pervasive and intertwined. In particular for low caste and women, it is a strong predictor of poverty. Exclusion from employment linked to negative attitudes and lack of income are the highest contributors to multidimensional poverty, increasing the burden for the family. Mental health professionals need to be aware of and address these issues.
Authors
- Trani, Jean-Francois ;
- Bakhshi, Parul ;
- Kuhlberg, Jill ;
- Venkataraman, Sreelatha S. ;
- Venkataraman, Hemalatha ;
- Mishra, Nagendra N. ;
- Groce, Nora E. ;
- Jadhav, Sushrut ;
- Deshpande, Smita