Sriram Iyengar

420 total citations
21 papers, 232 citations indexed

About

Sriram Iyengar is a scholar working on General Health Professions, Sociology and Political Science and Applied Psychology. According to data from OpenAlex, Sriram Iyengar has authored 21 papers receiving a total of 232 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in General Health Professions, 6 papers in Sociology and Political Science and 6 papers in Applied Psychology. Recurrent topics in Sriram Iyengar's work include Digital Mental Health Interventions (5 papers), Mobile Health and mHealth Applications (5 papers) and Impact of Technology on Adolescents (3 papers). Sriram Iyengar is often cited by papers focused on Digital Mental Health Interventions (5 papers), Mobile Health and mHealth Applications (5 papers) and Impact of Technology on Adolescents (3 papers). Sriram Iyengar collaborates with scholars based in United States, Brazil and United Kingdom. Sriram Iyengar's co-authors include Frederick A. Moore, Rosemary A. Kozar, David Mercer, James Suliburk, Mary F. McGuire, Ernest A. Gonzalez, Bruce A. McKinley, Sahiti Myneni, Amy Franklin and Jing Wang and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of the American College of Surgeons and Journal of the Association for Information Systems.

In The Last Decade

Sriram Iyengar

18 papers receiving 222 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Sriram Iyengar United States 7 58 45 44 36 33 21 232
Chelsea E. Canan United States 13 73 1.3× 72 1.6× 85 1.9× 27 0.8× 25 0.8× 23 409
Char Leung Australia 8 18 0.3× 54 1.2× 22 0.5× 24 0.7× 8 0.2× 23 433
Jen Birstler United States 13 59 1.0× 47 1.0× 52 1.2× 8 0.2× 13 0.4× 37 328
Muhammad Saqib Pakistan 9 45 0.8× 37 0.8× 55 1.3× 21 0.6× 13 0.4× 27 339
Thomas F. Osborne United States 11 56 1.0× 48 1.1× 30 0.7× 17 0.5× 5 0.2× 44 406
Dianne de Korte‐de Boer Netherlands 8 43 0.7× 15 0.3× 61 1.4× 11 0.3× 19 0.6× 23 262
Jihane Hajj United States 9 27 0.5× 82 1.8× 36 0.8× 37 1.0× 2 0.1× 17 279
M.D.P. Arias Lopez Argentina 6 91 1.6× 34 0.8× 29 0.7× 8 0.2× 12 0.4× 10 234
Lorenzo Blandi Italy 8 32 0.6× 27 0.6× 35 0.8× 21 0.6× 20 0.6× 21 277
Cvetan Trpkov Canada 6 130 2.2× 24 0.5× 23 0.5× 5 0.1× 12 0.4× 12 308

Countries citing papers authored by Sriram Iyengar

Since Specialization
Citations

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

Fields of papers citing papers by Sriram Iyengar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sriram Iyengar

This figure shows the co-authorship network connecting the top 25 collaborators of Sriram Iyengar. A scholar is included among the top collaborators of Sriram Iyengar 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 Sriram Iyengar. Sriram Iyengar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Iyengar, Sriram, et al.. (2024). Resilience Informatics: Role of Informatics in Enabling and Promoting Public Health Resilience to Pandemics, Climate Change, and Other Stressors. SHILAP Revista de lepidopterología. 13. e54687–e54687. 1 indexed citations
2.
Basu, Arindam, M. Ito, Craig Kuziemsky, et al.. (2023). Telehealth as a Component of One Health: a Position Paper. Yearbook of Medical Informatics. 32(1). 19–26.
3.
Benton, Ryan, et al.. (2022). The Intersection of Persuasive System Design and Personalization in Mobile Health: Statistical Evaluation. JMIR mhealth and uhealth. 10(9). e40576–e40576. 6 indexed citations
4.
Ernst, Kacey C., et al.. (2022). Design and implementation of a health messaging protocol employed for use within a COVID-19 health dissemination platform. Frontiers in Public Health. 10. 942795–942795. 1 indexed citations
5.
Patel, Vimla L., et al.. (2021). Information processing by community health nurses using mobile health (mHealth) tools for early identification of suicide and depression risks in Fiji Islands. BMJ Health & Care Informatics. 28(1). e100342–e100342. 4 indexed citations
6.
Basu, Arindam, Craig Kuziemsky, Najeeb Al-Shorbaji, et al.. (2021). Telehealth and the COVID-19 Pandemic: International Perspectives and a Health Systems Framework for Telehealth Implementation to Support Critical Response. Yearbook of Medical Informatics. 30(1). 126–133. 28 indexed citations
7.
Wang, Jing, et al.. (2020). Incorporating Behavioral Trigger Messages Into a Mobile Health App for Chronic Disease Management: Randomized Clinical Feasibility Trial in Diabetes. JMIR mhealth and uhealth. 8(3). e15927–e15927. 31 indexed citations
8.
Iyengar, Sriram, et al.. (2020). Extensive Review of Persuasive System Design Categories and Principles: Behavioral Obesity Interventions. Journal of Medical Systems. 44(7). 128–128. 8 indexed citations
9.
Rains, Stephen A., et al.. (2020). Community-Level Health Promotion during a Pandemic: Key Considerations for Health Communication. Health Communication. 35(14). 1747–1749. 10 indexed citations
10.
11.
Raschke, Robert, et al.. (2020). A Bayesian Analysis of Strategies to Rule Out Coronavirus Disease 2019 (COVID-19) Using Reverse Transcriptase–Polymerase Chain Reaction. Archives of Pathology & Laboratory Medicine. 144(8). 915–916. 6 indexed citations
12.
Oinas‐Kukkonen, Harri, et al.. (2017). Formative Evaluation to Determine Facilitators and Barriers to Nurse-driven Implementation: Designing an Inpatient mHealth Intervention to Support Smoking Cessation. Journal of the Association for Information Systems. 2 indexed citations
13.
14.
Sasso, Grace Teresinha Marcon Dal, et al.. (2015). Mobile Virtual Learning Object for the Assessment of Acute Pain as a Learning Tool to Assess Acute Pain in Nursing: An Analysis of the Mental Workload. JMIR Medical Education. 1(2). e15–e15. 5 indexed citations
15.
Chomutare, Taridzo, et al.. (2014). Persuasive attributes of medication adherence interventions for older adults: A systematic review. Technology and Health Care. 22(2). 189–198. 5 indexed citations
16.
Joshi, Ashish, et al.. (2011). Evaluation of a tele-education programme in Brazil. Journal of Telemedicine and Telecare. 17(7). 341–345. 11 indexed citations
17.
Minard, Charles G., et al.. (2010). The Integrated Medical Model. NASA Technical Reports Server (NASA). 5 indexed citations
18.
Gonzalez, Ernest A., Mary F. McGuire, James Suliburk, et al.. (2009). Early Cytokine Production Risk Stratifies Trauma Patients for Multiple Organ Failure. Journal of the American College of Surgeons. 209(3). 320–331. 97 indexed citations
19.
Minard, Charles G., et al.. (2009). The Integrated Medical Model: A Risk Assessment and Decision Support Tool for Space Flight Medical Systems. NASA Technical Reports Server (NASA).
20.
McGuire, Mary F., et al.. (2008). Cytokine profiling: A tool for predicting early MOF in trauma patients. Journal of the American College of Surgeons. 207(3). S41–S41. 1 indexed citations

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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