Riyu Pan

9 papers receiving 9.1k citations

Hit Papers

A longitudinal study on the mental health of general population during the COVID-19 epidemic in China 2020 · 1.9k citations
1.9k20202026202220242.0k4.0k6.0k

Peers

Riyu Pan
Comparison fields: 5 of 161
  • Clinical Psychology 7.7k
  • Applied Psychology 1.1k
  • Social Psychology 2.3k
  • Modeling and Simulation 490
  • Experimental and Cognitive Psychology 1.3k
Replace Xiaoyang Wan with:
Xiaoyang Wan Singapore
Linkang Xu Singapore
Yilin Tan China
Gideon James Rubin United Kingdom
Lisa Woodland United Kingdom
Rebecca Webster United Kingdom
Teris Cheung Hong Kong
Daniel Kwasi Ahorsu Hong Kong
Riyu Pan relative to Xiaoyang Wan Singapore Xiaoyang Wan's profile →
Citations per field
00.5×1.5×
Xiaoyang Wan · 1×
Citations per year

Countries citing papers authored by Riyu Pan

Since Specialization
Citations

This map shows the geographic impact of Riyu Pan'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 Riyu Pan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Riyu Pan more than expected).

Fields of papers citing papers by Riyu Pan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Riyu Pan. 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 Riyu Pan. The network helps show where Riyu Pan may publish in the future.

Co-authors

The 25 scholars most cited alongside Riyu Pan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Riyu Pan Line = papers co-authored together Riyu Pan links everyone, so they are left out of the graph.

All Works

10 of 10 papers shown
#Work
1
Immediate Psychological Responses and Associated Factors during the Initial Stage of the 2019 Coronavirus Disease (COVID-19) Epidemic among the General Population in China
Hit paper breakdown →
20207010
2
A longitudinal study on the mental health of general population during the COVID-19 epidemic in China
Hit paper breakdown →
20201924
3 2020257
4 202176
5 202150
6 202149
7 20234
8
A longitudinal study on the mental health of general population during the COVID-19 epidemic in China
20211
9 20211
10 20230

About Riyu Pan

Riyu Pan is a scholar working on Clinical Psychology, Modeling and Simulation, Economics and Econometrics, Social Psychology and Neurology, having authored 10 papers that have together received 9.4k indexed citations. Recurring topics across this work include COVID-19 and Mental Health (7 papers), COVID-19 Pandemic Impacts (5 papers), Psychological Well-being and Life Satisfaction (3 papers), Long-Term Effects of COVID-19 (2 papers), COVID-19 epidemiological studies (1 paper), Heart Rate Variability and Autonomic Control (1 paper), Health disparities and outcomes (1 paper) and Emotional Labor in Professions (1 paper). The work is most often cited by research in Clinical Psychology (7.7k citations), Applied Psychology (1.1k citations), Social Psychology (2.3k citations), Modeling and Simulation (490 citations) and Experimental and Cognitive Psychology (1.3k citations). Riyu Pan has collaborated with scholars based in China, Singapore and Canada. Frequent co-authors include Roger Ho, Linkang Xu, Xiaoyang Wan, Cyrus S. H. Ho, Yilin Tan, Cuiyan Wang, Roger S. McIntyre, Bach Xuan Tran, Vijay K. Sharma and Damian Grabowski. Their work appears in journals such as Frontiers in Psychiatry, Scientific Reports, Brain Behavior and Immunity, International Journal of Environmental Research and Public Health and JMIR Formative Research.

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.

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