Top Articles (Article-Level Metrics)

 
 
Rank Article Tweets Tweets per MonthA
Tweets Influence FactorB
Twimpact Factor (tw7)C Twindex7D
 
31
Assessing the Applicability of E-Therapies for Depression, Anxiety, and Other Mood Disorders Among Lesbians and Gay Men: Analysis of 24 Web- and Mobile Phone-Based Self-Help Interventions
Tomas Rozbroj, Anthony Lyons, Marian Pitts, Anne Mitchell, Helen Christensen
J Med Internet Res 2014;16(7):e166
(Jul 3, 2014)
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41 14.28 0.00 18 95
 
 
32
Norwegian General Practitioners’ Perspectives on Implementation of a Guided Web-Based Cognitive Behavioral Therapy for Depression: A Qualitative Study
Maja Wilhelmsen, Ragnhild Sørensen Høifødt, Nils Kolstrup, Knut Waterloo, Martin Eisemann, Richard Chenhall, Mette Bech Risør
J Med Internet Res 2014;16(9):e208
(Sep 10, 2014)
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8 12.40 0.00 8 50
 
 
33
The Behavioral Intervention Technology Model: An Integrated Conceptual and Technological Framework for eHealth and mHealth Interventions
David C Mohr, Stephen M Schueller, Enid Montague, Michelle Nicole Burns, Parisa Rashidi
J Med Internet Res 2014;16(6):e146
(Jun 5, 2014)
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46 12.19 0.00 35 95
 
 
34
Do Cancer Patients Tweet? Examining the Twitter Use of Cancer Patients in Japan
Atsushi Tsuya, Yuya Sugawara, Atsushi Tanaka, Hiroto Narimatsu
J Med Internet Res 2014;16(5):e137
(May 27, 2014)
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48 11.81 0.00 36 100
 
 
35
Mapping Physician Twitter Networks: Describing How They Work as a First Step in Understanding Connectivity, Information Flow, and Message Diffusion
Ranit Mishori, Lisa Oberoi Singh, Brendan Levy, Calvin Newport
J Med Internet Res 2014;16(4):e107
(Apr 14, 2014)
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63 11.56 0.00 41 95
 
 
36
Characterizing the Followers and Tweets of a Marijuana-Focused Twitter Handle
Patricia Cavazos-Rehg, Melissa Krauss, Richard Grucza, Laura Bierut
J Med Internet Res 2014;16(6):e157
(Jun 27, 2014)
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32 10.44 0.00 28 100
 
 
37
Purple: A Modular System for Developing and Deploying Behavioral Intervention Technologies
Stephen M Schueller, Mark Begale, Frank J Penedo, David C Mohr
J Med Internet Res 2014;16(7):e181
(Jul 30, 2014)
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19 9.50 0.00 16 90
 
 
38
The Role of Facebook in Crush the Crave, a Mobile- and Social Media-Based Smoking Cessation Intervention: Qualitative Framework Analysis of Posts
Laura Louise Struik, Neill Bruce Baskerville
J Med Internet Res 2014;16(7):e170
(Jul 11, 2014)
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22 8.42 0.00 21 95
 
 
39
Online Social Networks That Connect Users to Physical Activity Partners: A Review and Descriptive Analysis
Atul Nakhasi, Album Xiaotian Shen, Ralph Joseph Passarella, Lawrence J Appel, Cheryl AM Anderson
J Med Internet Res 2014;16(6):e153
(Jun 16, 2014)
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28 8.19 0.00 18 95
 
 
40
Wikis and Collaborative Writing Applications in Health Care: A Scoping Review
Patrick M Archambault, Tom H van de Belt, Francisco J Grajales III, Marjan J Faber, Craig E Kuziemsky, Susie Gagnon, Andrea Bilodeau, Simon Rioux, Willianne LDM Nelen, Marie-Pierre Gagnon, Alexis F Turgeon, Karine Aubin, Irving Gold, Julien Poitras, Gunther Eysenbach, Jan AM Kremer, France Légaré
J Med Internet Res 2013;15(10):e210
(Oct 8, 2013)
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46 7.67 0.00 75 100
 
 
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Total Tweets
 
Tweets per Month
 
Tweets Influence Factor
 
Twimpact Factor (TWIF) tw7
 
Twindex7

A Tweets per month statistic may be artifically inflated for newly published articles

B Tweets Influence Factor (TIF): number of tweets x avg. influence of tweeters (influence is determined by how often all tweets of that person are retweeted by others)

C Twimpact Factor (TWIF) tw7: Number of mentionings in tweets (tweetations) within first 7 days after article publication (Eysenbach 2011)

D Twindex7 (Eysenbach 2011): Rank percentile of this article when its twimpact factor (tw7) is compared to 19 previously published articles. Range 0-100, with higher scores reflecting higher impact on Twitter. Articles with a Twindex greater than 75 have a 75% chance of being highly cited (top quartile by citation), articles with a Twindex less than 75 have a 7% chance to be highly cited.