Maya Sahu
Impact in
- Applied Psychology top 10%
- Digital Mental Health Interventions
- Clinical Psychology top 10%
- COVID-19 and Mental Health
- Resilience and Mental Health
Papers in
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- Family Caregiving in Mental Illness 4
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- Mental Health Treatment and Access 5
- Co-authors
- Manoj Kumar Sharma (7 shared papers)Sailaxmi Gandhi (13 shared papers)Ripudaman Singh (1 shared paper)Nitin Anand (4 shared papers)Tamar Rodney (2 shared papers)Paulomi M. Sudhir (1 shared paper)Aarti Jagannathan (1 shared paper)Meeka Khanna (1 shared paper)
- Journals
- Asian Journal of Psychiatry (2 papers)Current Opinion in Psychiatry (1 paper)PLoS ONE (1 paper)Cyberpsychology Behavior and Social Networking (1 paper)International Journal of Social Psychiatry (1 paper)
- Partner nations
- IndiaUnited StatesIran
In The Last Decade
Maya Sahu
22 papers receiving 365 citations
Peers
Comparison fields: 5 of 65
- Applied Psychology 40
- Clinical Psychology 99
- Sociology and Political Science 186
- Education 60
- Social Psychology 38
Countries citing papers authored by Maya Sahu
This map shows the geographic impact of Maya Sahu'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 Maya Sahu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maya Sahu more than expected).
Fields of papers citing papers by Maya Sahu
This network shows the impact of papers produced by Maya Sahu. 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 Maya Sahu. The network helps show where Maya Sahu may publish in the future.
Co-authors
The 20 scholars most cited alongside Maya Sahu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 127 | |
| 2 | 2020 | 66 | |
| 3 | 2020 | 48 | |
| 4 | 2021 | 38 | |
| 5 | 2021 | 22 | |
| 6 | 2019 | 20 | |
| 7 | 2020 | 13 | |
| 8 | 2019 | 10 | |
| 9 | 2019 | 9 | |
| 10 | 2022 | 6 | |
| 11 | 2019 | 4 | |
| 12 | 2020 | 3 | |
| 13 | 2020 | 3 | |
| 14 | 2022 | 2 | |
| 15 | 2019 | 2 | |
| 16 | 2023 | 1 | |
| 17 | 2020 | 1 | |
| 18 | 2025 | 1 | |
| 19 | 2021 | 1 | |
| 20 | 2017 | 1 |
About Maya Sahu
Maya Sahu is a scholar working on Clinical Psychology, Social Psychology, Sociology and Political Science, Applied Psychology and General Health Professions, having authored 23 papers that have together received 380 indexed citations. Recurring topics across this work include Impact of Technology on Adolescents (5 papers), Mental Health Treatment and Access (5 papers), Family Caregiving in Mental Illness (4 papers), Digital Games and Media (3 papers), Mental Health and Patient Involvement (2 papers), Educational Games and Gamification (2 papers), Schizophrenia research and treatment (2 papers) and Digital Mental Health Interventions (2 papers). The work is most often cited by research in Applied Psychology (40 citations), Clinical Psychology (99 citations), Sociology and Political Science (186 citations), Education (60 citations) and Social Psychology (38 citations). Maya Sahu has collaborated with scholars based in India, United States and Iran. Frequent co-authors include Manoj Kumar Sharma, Sailaxmi Gandhi, Ripudaman Singh, Nitin Anand, Tamar Rodney, Paulomi M. Sudhir, Aarti Jagannathan, Meeka Khanna, Rajesh Kumar and Thanapal Sivakumar. Their work appears in journals such as Asian Journal of Psychiatry, Current Opinion in Psychiatry, PLoS ONE, Cyberpsychology Behavior and Social Networking and International Journal of Social Psychiatry.
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.