Jay Siwek

2.3k total citations · 1 hit paper
8 papers, 1.4k citations indexed

About

Jay Siwek is a scholar working on Economics and Econometrics, General Health Professions and Public Health, Environmental and Occupational Health. According to data from OpenAlex, Jay Siwek has authored 8 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Economics and Econometrics, 2 papers in General Health Professions and 2 papers in Public Health, Environmental and Occupational Health. Recurrent topics in Jay Siwek's work include Meta-analysis and systematic reviews (2 papers), Health Systems, Economic Evaluations, Quality of Life (2 papers) and Health and Medical Research Impacts (2 papers). Jay Siwek is often cited by papers focused on Meta-analysis and systematic reviews (2 papers), Health Systems, Economic Evaluations, Quality of Life (2 papers) and Health and Medical Research Impacts (2 papers). Jay Siwek collaborates with scholars based in United States. Jay Siwek's co-authors include Bernard Ewigman, Jeffrey Susman, Marjorie A. Bowman, Barry D. Weiss, Mark H. Ebell, Steven H. Woolf, David C. Slawson, Allen F. Shaughnessy, Margaret L. Gourlay and Adriane Fugh‐Berman and has published in prestigious journals such as Academic Medicine, The Journal of the American Board of Family Medicine and PubMed.

In The Last Decade

Jay Siwek

7 papers receiving 1.3k citations

Hit Papers

Strength of Recommendation Taxonomy (SORT): A Patient-Cen... 2004 2026 2011 2018 2004 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jay Siwek United States 6 284 253 229 193 190 8 1.4k
Adèle Weston Australia 22 288 1.0× 159 0.6× 179 0.8× 191 1.0× 242 1.3× 30 1.7k
Christiane Ruffieux Switzerland 24 302 1.1× 254 1.0× 157 0.7× 186 1.0× 200 1.1× 58 2.2k
John Miller United States 7 275 1.0× 247 1.0× 146 0.6× 39 0.2× 112 0.6× 15 1.4k
Stephen Rice United Kingdom 23 635 2.2× 203 0.8× 169 0.7× 85 0.4× 297 1.6× 75 2.3k
Salvador Pita‐Fernández Spain 25 439 1.5× 148 0.6× 254 1.1× 128 0.7× 240 1.3× 108 2.3k
Pablo Alonso Coello Spain 7 199 0.7× 320 1.3× 217 0.9× 45 0.2× 132 0.7× 13 1.1k
Suzie Cro United Kingdom 28 840 3.0× 139 0.5× 91 0.4× 371 1.9× 112 0.6× 85 2.2k
Katrina Sullivan Canada 21 393 1.4× 191 0.8× 255 1.1× 87 0.5× 138 0.7× 43 1.8k
María José Martínez‐Zapata Spain 29 842 3.0× 279 1.1× 142 0.6× 104 0.5× 82 0.4× 87 2.4k
Safia Qureshi United Kingdom 8 620 2.2× 658 2.6× 364 1.6× 75 0.4× 467 2.5× 10 3.2k

Countries citing papers authored by Jay Siwek

Since Specialization
Citations

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

Fields of papers citing papers by Jay Siwek

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jay Siwek

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

All Works

8 of 8 papers shown
1.
Siwek, Jay. (2016). Screening for Ovarian Cancer-More Hype Than Hope?. PubMed. 93(11). 906–906.
2.
Fugh‐Berman, Adriane, et al.. (2011). Closing the Door on Pharma? A National Survey of Family Medicine Residencies Regarding Industry Interactions. Academic Medicine. 86(5). 649–654. 11 indexed citations
3.
Ebell, Mark H., Jay Siwek, Barry D. Weiss, et al.. (2004). Strength of Recommendation Taxonomy (SORT): A Patient-Centered Approach to Grading Evidence in the Medical Literature. The Journal of the American Board of Family Medicine. 17(1). 59–67. 897 indexed citations breakdown →
4.
Ebell, Mark H., Jay Siwek, Barry D. Weiss, et al.. (2004). Simplifying the language of evidence to improve patient care: Strength of recommendation taxonomy (SORT): a patient-centered approach to grading evidence in medical literature.. PubMed. 53(2). 111–20. 59 indexed citations
5.
Ebell, Mark H., Jay Siwek, Barry D. Weiss, et al.. (2004). Strength of recommendation taxonomy (SORT): a patient-centered approach to grading evidence in the medical literature.. PubMed. 69(3). 548–56. 358 indexed citations
6.
Siwek, Jay, Margaret L. Gourlay, David C. Slawson, & Allen F. Shaughnessy. (2002). How to write an evidence-based clinical review article.. PubMed. 65(2). 251–8. 99 indexed citations
7.
Siwek, Jay. (1997). Reading and evaluating clinical review articles.. PubMed. 55(6). 2064, 2069–70, 2072. 2 indexed citations
8.
Siwek, Jay. (1985). House calls: current status and rationale.. PubMed. 31(4). 169–74. 17 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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