Nisha Mehta
- Social Psychology top 1%
- Clinical Psychology top 2%
- General Health Professions top 2%
- Infectious Diseases top 5%
- Health top 5%
- Co-authors
- Graham ThornicroftDiana RoseLars GoerigkMirja KoschorkeClaire L. O’ReillySarah ClémentClaire HendersonRahul Shidhaye
- Topics
- Advanced Chemical Physics Studies (8 papers)Machine Learning in Materials Science (7 papers)Child Welfare and Adoption (6 papers)
- Partner nations
- United KingdomUnited StatesIsrael
In The Last Decade
Nisha Mehta
40 papers receiving 2.2k citations
Hit Papers
Peers
Comparison fields: 5 of 157
- Social Psychology 802
- Clinical Psychology 750
- General Health Professions 470
- Infectious Diseases 377
- Health 214
Countries citing papers authored by Nisha Mehta
This map shows the geographic impact of Nisha Mehta's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Nisha Mehta with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nisha Mehta more than expected).
Fields of papers citing papers by Nisha Mehta
This network shows the impact of papers produced by Nisha Mehta. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Nisha Mehta. The network helps show where Nisha Mehta may publish in the future.
Co-authorship network of co-authors of Nisha Mehta
This figure shows the co-authorship network connecting the top 25 collaborators of Nisha Mehta. A scholar is included among the top collaborators of Nisha Mehta based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Nisha Mehta. Nisha Mehta is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 6 | |
| 2 | 27 | |
| 3 | 4 | |
| 4 | 52 | |
| 5 | 1 | |
| 6 | Risk prediction of covid-19 related death and hospital admission in adults after covid-19 vaccination: national prospective cohort studybreakdown → | 196 |
| 7 | 29 | |
| 8 | 7 | |
| 9 | 0 | |
| 10 | 112 | |
| 11 | Evidence for effective interventions to reduce mental-health-related stigma and discriminationbreakdown → | 841 |
| 12 | 27 | |
| 13 | 85 | |
| 14 | 31 | |
| 15 | 14 | |
| 16 | 43 | |
| 17 | 10 | |
| 18 | 143 | |
| 19 | 20 | |
| 20 | 17 |
About Nisha Mehta
Nisha Mehta is a scholar working on Health, Safety Research and Physical and Theoretical Chemistry, having authored 41 papers that have together received 2.3k indexed citations. Recurring topics across this work include Advanced Chemical Physics Studies (8 papers), Machine Learning in Materials Science (7 papers) and Child Welfare and Adoption (6 papers). The work is most often cited by research in Social Psychology (802 citations), Clinical Psychology (750 citations) and Health (214 citations). Nisha Mehta has collaborated with scholars based in United Kingdom, United States and Israel. Frequent co-authors include Graham Thornicroft, Diana Rose, Lars Goerigk, Mirja Koschorke, Claire L. O’Reilly, Sarah Clément, Claire Henderson, Rahul Shidhaye, Sara Evans‐Lacko and Jonathan S. Nguyen‐Van‐Tam. Their work appears in journals such as The Lancet, Clinical Infectious Diseases and The Journal of Comparative Neurology.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.