Maria Han

900 citations
35 papers · 518 · 1 hit paper · h-index 10

Impact in

Papers in

Maria Han

31 papers receiving 506 citations

Hit Papers

Behavioural nudges increase COVID-19 vaccinations 2021 · 271 citations
2710+1+3Years since publication50100150200250

Peers

Maria Han
Comparison fields: 5 of 98
  • Health 199
  • Modeling and Simulation 79
  • Applied Psychology 34
  • General Decision Sciences 9
  • General Health Professions 105
Replace Lily Roh with:
Lily Roh United States
Naveen Raja United States
Jurriaan Oudhoff Netherlands
Monica L. Kasting United States
Sarah Eitze Germany
Xuan Zhu United States
Florian Schneider Switzerland
Kalahn Taylor‐Clark United States
Basmattee Boodram United States
Niels Michalski Germany
Maria Han relative to Lily Roh United States Lily Roh's profile →
Citations per field
00.5×
Lily Roh · 1×
Citations per year

Countries citing papers authored by Maria Han

Since Specialization
Citations

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

Fields of papers citing papers by Maria Han

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Maria Han, 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 Maria Han Line = papers co-authored together Maria Han links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Behavioural nudges increase COVID-19 vaccinations
Hit paper breakdown →
2021271
2 202228
3 202226
4 202121
5 202220
6 202020
7 201920
8 202116
9 202213
10 202311
11 20059
12 20157
13 20226
14 20166
15 20245
16 20235
17 20215
18 20234
19 20234
20 20214

About Maria Han

Maria Han is a scholar working on Molecular Biology, General Health Professions, Oncology, Public Health, Environmental and Occupational Health and Health, having authored 35 papers that have together received 518 indexed citations. Recurring topics across this work include Vaccine Coverage and Hesitancy (5 papers), Telemedicine and Telehealth Implementation (4 papers), Patient Satisfaction in Healthcare (4 papers), Extracellular vesicles in disease (4 papers), Behavioral Health and Interventions (3 papers), Colorectal Cancer Screening and Detection (3 papers), Global Cancer Incidence and Screening (3 papers) and Food Security and Health in Diverse Populations (2 papers). The work is most often cited by research in Health (199 citations), Modeling and Simulation (79 citations), Applied Psychology (34 citations), General Decision Sciences (9 citations) and General Health Professions (105 citations). Maria Han has collaborated with scholars based in United States, Germany and Denmark. Frequent co-authors include Sitaram Vangala, Daniel M. Croymans, Hengchen Dai, Lily Roh, Naveen Raja, Silvia Saccardo, Michael Sloyan, Catherine A. Sarkisian, Alejandra Casillas and Michael Ong. Their work appears in journals such as Journal of General Internal Medicine, Scientific Reports, Telemedicine Journal and e-Health, Journal of Thoracic Oncology and Vaccine.

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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