Fred Raab

1.7k total citations · 1 hit paper
9 papers, 1.2k citations indexed

About

Fred Raab is a scholar working on General Health Professions, Clinical Psychology and Public Health, Environmental and Occupational Health. According to data from OpenAlex, Fred Raab has authored 9 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in General Health Professions, 4 papers in Clinical Psychology and 3 papers in Public Health, Environmental and Occupational Health. Recurrent topics in Fred Raab's work include Mobile Health and mHealth Applications (7 papers), Eating Disorders and Behaviors (4 papers) and Obesity, Physical Activity, Diet (3 papers). Fred Raab is often cited by papers focused on Mobile Health and mHealth Applications (7 papers), Eating Disorders and Behaviors (4 papers) and Obesity, Physical Activity, Diet (3 papers). Fred Raab collaborates with scholars based in United States. Fred Raab's co-authors include Kevin Patrick, William G. Griswold, Gregory J. Norman, Stephen Intille, Lindsay Dillon, Cheryl L. Rock, Marc A. Adams, Timothy Sohn, Michael Gottschalk and Karen J. Calfas and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS Medicine and American Journal of Preventive Medicine.

In The Last Decade

Fred Raab

9 papers receiving 1.2k citations

Hit Papers

A Text Message–Based Intervention for Weight Loss: Random... 2009 2026 2014 2020 2009 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Fred Raab United States 9 843 353 337 166 159 9 1.2k
Nicol Nijland Netherlands 10 1.1k 1.3× 450 1.3× 367 1.1× 105 0.6× 77 0.5× 19 1.8k
Oksana Zelenko Australia 10 1.2k 1.4× 688 1.9× 216 0.6× 75 0.5× 116 0.7× 21 1.9k
Huong Ly Tong Australia 15 630 0.7× 672 1.9× 189 0.6× 109 0.7× 222 1.4× 21 1.6k
Madhavan Mani Australia 2 1.2k 1.4× 801 2.3× 208 0.6× 85 0.5× 123 0.8× 6 1.8k
Marco Bardus Lebanon 14 617 0.7× 269 0.8× 154 0.5× 46 0.3× 126 0.8× 37 934
Dallas Swendeman United States 11 600 0.7× 241 0.7× 177 0.5× 54 0.3× 70 0.4× 25 1.0k
Enid Dorey New Zealand 12 493 0.6× 327 0.9× 236 0.7× 35 0.2× 188 1.2× 14 967
Rajani S. Sadasivam United States 19 660 0.8× 348 1.0× 188 0.6× 37 0.2× 331 2.1× 91 1.3k
Silje C Wangberg Norway 18 797 0.9× 347 1.0× 202 0.6× 30 0.2× 155 1.0× 31 1.4k
Santosh Krishna United States 9 953 1.1× 260 0.7× 174 0.5× 31 0.2× 135 0.8× 15 1.4k

Countries citing papers authored by Fred Raab

Since Specialization
Citations

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

Fields of papers citing papers by Fred Raab

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fred Raab

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

All Works

9 of 9 papers shown
1.
Godino, Job, Natalie M. Golaszewski, Gregory J. Norman, et al.. (2019). Text messaging and brief phone calls for weight loss in overweight and obese English- and Spanish-speaking adults: A 1-year, parallel-group, randomized controlled trial. PLoS Medicine. 16(9). e1002917–e1002917. 30 indexed citations
2.
Kolodziejczyk, Julia K., Gregory J. Norman, Lindsay Dillon, et al.. (2013). Feasibility and Effectiveness of an Automated Bilingual Text Message Intervention for Weight Loss: Pilot Study. SHILAP Revista de lepidopterología. 2(2). e48–e48. 19 indexed citations
3.
Patrick, Kevin, Gregory J. Norman, Evelyn P. Davila, et al.. (2013). Outcomes of a 12-Month Technology-Based Intervention to Promote Weight Loss in Adolescents at Risk for Type 2 Diabetes. Journal of Diabetes Science and Technology. 7(3). 759–770. 71 indexed citations
4.
Patrick, Kevin, Karen Basen‐Engquist, Wendy Demark‐Wahnefried, et al.. (2010). CYberinfrastructure for COmparative effectiveness REsearch (CYCORE): improving data from cancer clinical trials. Translational Behavioral Medicine. 1(1). 83–88. 12 indexed citations
5.
Patrick, Kevin, Fred Raab, Marc A. Adams, et al.. (2009). A Text Message–Based Intervention for Weight Loss: Randomized Controlled Trial. Journal of Medical Internet Research. 11(1). e1–e1. 541 indexed citations breakdown →
6.
Patrick, Kevin, William G. Griswold, Fred Raab, & Stephen Intille. (2008). Health and the Mobile Phone. American Journal of Preventive Medicine. 35(2). 177–181. 329 indexed citations
7.
Raab, Fred, et al.. (2007). Usability and Feasibility of PmEB: A Mobile Phone Application for Monitoring Real Time Caloric Balance. Mobile Networks and Applications. 12(2-3). 173–184. 199 indexed citations
9.
Tsai, Chris, et al.. (2006). PmEB. 1013–1018. 36 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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