Jordan Rivera
Impact in
- Applied Psychology top 10%
- Digital Mental Health Interventions
- General Health Professions top 5%
- Mobile Health and mHealth Applications
Papers in
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- Soft Robotics and Applications 3
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- Mobile Health and mHealth Applications 2
- Co-authors
- Jennifer Stinson (4 shared papers)Chitra Lalloo (3 shared papers)Arnav Agarwal (2 shared papers)Lindsay Jibb (1 shared paper)Amy C. McPherson (2 shared papers)Michael James Coons (2 shared papers)Catherine S. Birken (2 shared papers)Jill Hamilton (2 shared papers)
- Journals
- JMIR mhealth and uhealth (2 papers)Clinical Journal of Pain (1 paper)Journal of Mechanisms and Robotics (1 paper)JMIR Formative Research (1 paper)
- Partner nations
- United StatesCanada
In The Last Decade
Jordan Rivera
8 papers receiving 448 citations
Peers
Comparison fields: 5 of 70
- Applied Psychology 59
- General Health Professions 138
- Anesthesiology and Pain Medicine 21
- Pediatrics, Perinatology and Child Health 65
- Family Practice 3
Countries citing papers authored by Jordan Rivera
This map shows the geographic impact of Jordan Rivera'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 Jordan Rivera with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jordan Rivera more than expected).
Fields of papers citing papers by Jordan Rivera
This network shows the impact of papers produced by Jordan Rivera. 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 Jordan Rivera. The network helps show where Jordan Rivera may publish in the future.
Co-authors
The 17 scholars most cited alongside Jordan Rivera, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 191 | |
| 2 | 2016 | 121 | |
| 3 | 2017 | 69 | |
| 4 | 2018 | 31 | |
| 5 | 2014 | 25 | |
| 6 | 2014 | 16 | |
| 7 | 2014 | 1 | |
| 8 | 2024 | 1 |
About Jordan Rivera
Jordan Rivera is a scholar working on Biomedical Engineering, General Health Professions, Control and Systems Engineering, Mechanical Engineering and Neuropsychology and Physiological Psychology, having authored 8 papers that have together received 455 indexed citations. Recurring topics across this work include Soft Robotics and Applications (3 papers), Modular Robots and Swarm Intelligence (2 papers), Mobile Health and mHealth Applications (2 papers), Art Therapy and Mental Health (1 paper), Urban Green Space and Health (1 paper), Robotic Mechanisms and Dynamics (1 paper), Aging and Gerontology Research (1 paper) and Robot Manipulation and Learning (1 paper). The work is most often cited by research in Applied Psychology (59 citations), General Health Professions (138 citations), Anesthesiology and Pain Medicine (21 citations), Pediatrics, Perinatology and Child Health (65 citations) and Family Practice (3 citations). Jordan Rivera has collaborated with scholars based in United States and Canada. Frequent co-authors include Jennifer Stinson, Chitra Lalloo, Arnav Agarwal, Lindsay Jibb, Amy C. McPherson, Michael James Coons, Catherine S. Birken, Jill Hamilton, Fiona Campbell and Kathryn A. Birnie. Their work appears in journals such as JMIR mhealth and uhealth, Clinical Journal of Pain, Journal of Mechanisms and Robotics 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.