Divya Madhusudhan
- Clinical Psychology top 5%
- General Health Professions top 10%
- Experimental and Cognitive Psychology top 10%
- Social Psychology top 10%
- Public Health, Environmental and Occupational Health
- Co-authors
- Dena M BravataKevin CokleySharon A. WattsHeather HaggTheodore BellKamlesh D. PatelJohn WrightChaitanya G. Joshi
- Topics
- COVID-19 and Mental Health (3 papers)Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes (3 papers)Perfectionism, Procrastination, Anxiety Studies (3 papers)
- Journals
- SHILAP Revista de lepidopterologíaJournal of General Internal MedicineJournal of Occupational and Environmental Medicine
- Partner nations
- United StatesIndiaCzechia
In The Last Decade
Divya Madhusudhan
12 papers receiving 405 citations
Hit Papers
Peers
Comparison fields: 5 of 72
- Clinical Psychology 303
- General Health Professions 118
- Experimental and Cognitive Psychology 100
- Social Psychology 91
- Public Health, Environmental and Occupational Health 75
Countries citing papers authored by Divya Madhusudhan
This map shows the geographic impact of Divya Madhusudhan'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 Divya Madhusudhan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Divya Madhusudhan more than expected).
Fields of papers citing papers by Divya Madhusudhan
This network shows the impact of papers produced by Divya Madhusudhan. 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 Divya Madhusudhan. The network helps show where Divya Madhusudhan may publish in the future.
Co-authorship network of co-authors of Divya Madhusudhan
This figure shows the co-authorship network connecting the top 25 collaborators of Divya Madhusudhan. A scholar is included among the top collaborators of Divya Madhusudhan 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 Divya Madhusudhan. Divya Madhusudhan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 13 | |
| 4 | 2 | |
| 5 | 1 | |
| 6 | 1 | |
| 7 | 32 | |
| 8 | 2 | |
| 9 | 2 | |
| 10 | 2 | |
| 11 | 35 | |
| 12 | Prevalence, Predictors, and Treatment of Impostor Syndrome: a Systematic Reviewbreakdown → | 327 |
| 13 | 1 |
About Divya Madhusudhan
Divya Madhusudhan is a scholar working on Clinical Psychology, Experimental and Cognitive Psychology and Applied Psychology, having authored 13 papers that have together received 420 indexed citations. Recurring topics across this work include COVID-19 and Mental Health (3 papers), Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes (3 papers) and Perfectionism, Procrastination, Anxiety Studies (3 papers). The work is most often cited by research in Clinical Psychology (303 citations), Experimental and Cognitive Psychology (100 citations) and Gender Studies (50 citations). Divya Madhusudhan has collaborated with scholars based in United States, India and Czechia. Frequent co-authors include Dena M Bravata, Kevin Cokley, Sharon A. Watts, Heather Hagg, Theodore Bell, Kamlesh D. Patel, John Wright, Chaitanya G. Joshi, Kashyap K. Bhatt and Christopher Whaley. Their work appears in journals such as SHILAP Revista de lepidopterología, Journal of General Internal Medicine and Journal of Occupational and Environmental Medicine.
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.