Top Articles (Article-Level Metrics)

 
 
Rank Article Tweets Tweets per MonthA
Tweets Influence FactorB
Twimpact Factor (tw7)C Twindex7D
 
401
Patient-reported Outcomes as a Source of Evidence in Off-Label Prescribing: Analysis of Data From PatientsLikeMe
Jeana Frost, Sally Okun, Timothy Vaughan, James Heywood, Paul Wicks
J Med Internet Res 2011;13(1):e6
(Jan 21, 2011)
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2 0.17 6.00 24 90
 
 
402
Reliability of Health Information on the Internet: An Examination of Experts' Ratings
Mark Craigie, Brian Loader, Roger Burrows, Steven Muncer
J Med Internet Res 2002;4(1):e2
(Jan 17, 2002)
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2 0.17 8.00 0 0
 
 
403
Seeking Support on Facebook: A Content Analysis of Breast Cancer Groups
Jacqueline L Bender, Maria-Carolina Jimenez-Marroquin, Alejandro R Jadad
J Med Internet Res 2011;13(1):e16
(Feb 4, 2011)
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2 0.17 0.00 25 80
 
 
404
Mobile Phone Applications for the Care and Prevention of HIV and Other Sexually Transmitted Diseases: A Review
Kathryn E Muessig, Emily C Pike, Sara LeGrand, Lisa B Hightow-Weidman
J Med Internet Res 2013;15(1):e1
(Jan 4, 2013)
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2 0.17 2.00 20 80
 
 
405
Smartphone Versus Pen-and-Paper Data Collection of Infant Feeding Practices in Rural China
Shuyi Zhang, Qiong Wu, Michelle HMMT van Velthoven, Li Chen, Josip Car, Igor Rudan, Yanfeng Zhang, Ye Li, Robert W Scherpbier
J Med Internet Res 2012;14(5):e119
(Sep 18, 2012)
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2 0.17 0.00 15 60
 
 
406
Versatile, Immersive, Creative and Dynamic Virtual 3-D Healthcare Learning Environments: A Review of the Literature
Margaret Hansen
J Med Internet Res 2008;10(3):e26
(Sep 1, 2008)
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2 0.17 1.00 2 75
 
 
407
The Law of Attrition Revisited
Helen Christensen, Andrew Mackinnon
J Med Internet Res 2006;8(3):e20
(Sep 29, 2006)
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2 0.17 1.00 0 0
 
 
408
Benefits of Peer Support in Online Japanese Breast Cancer Communities: Differences Between Lurkers and Posters
Yoko Setoyama, Yoshihiko Yamazaki, Kazuhiro Namayama
J Med Internet Res 2011;13(4):e122
(Dec 29, 2011)
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2 0.17 1.00 32 90
 
 
409
The Role of Engagement in a Tailored Web-Based Smoking Cessation Program: Randomized Controlled Trial
Victor Strecher, Jennifer McClure, Gwen Alexander, Bibhas Chakraborty, Vijay Nair, Janine Konkel, Sarah Greene, Mick Couper, Carola Carlier, Cheryl Wiese, Roderick Little, Cynthia Pomerleau, Ovide Pomerleau
J Med Internet Res 2008;10(5):e36
(Nov 4, 2008)
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2 0.17 0.00 0 0
 
 
410
Claiming Positive Results From Negative Trials: A Cause for Concern in Randomized Controlled Trial Research - Author's Reply
Reid Hester, William Campbell, Kathryn Lenberg, Harold Delaney
J Med Internet Res 2013;15(8):e180
(Aug 19, 2013)
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1 0.12 1.00 1 20
 
 
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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.