Top Articles (Article-Level Metrics)

 
 
Rank Article Tweets Tweets per MonthA
Tweets
Influence
Factor
B
Twimpact Factor (tw7)C Twindex7D
 
51
The 1% Rule in Four Digital Health Social Networks: An Observational Study
Trevor van Mierlo
J Med Internet Res 2014;16(2):e33
(Feb 4, 2014)
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1 1.00 0.00 118 100
 
 
52
Collaborative Biomedicine in the Age of Big Data: The Case of Cancer
Abdul R Shaikh, Atul J Butte, Sheri D Schully, William S Dalton, Muin J Khoury, Bradford W Hesse
J Med Internet Res 2014;16(4):e101
(Apr 7, 2014)
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1 1.00 0.00 38 95
 
 
53
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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1 1.00 0.00 36 100
 
 
54
Real-Time Sharing and Expression of Migraine Headache Suffering on Twitter: A Cross-Sectional Infodemiology Study
Thiago D Nascimento, Marcos F DosSantos, Theodora Danciu, Misty DeBoer, Hendrik van Holsbeeck, Sarah R Lucas, Christine Aiello, Leen Khatib, MaryCatherine A Bender, UMSoD (Under)Graduate Class Of 2014, Jon-Kar Zubieta, Alexandre F DaSilva
J Med Internet Res 2014;16(4):e96
(Apr 3, 2014)
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1 1.00 0.00 18 100
 
 
55
Health Care Professionals’ Beliefs About Using Wiki-Based Reminders to Promote Best Practices in Trauma Care
Patrick Michel Archambault, Andrea Bilodeau, Marie-Pierre Gagnon, Karine Aubin, André Lavoie, Jean Lapointe, Julien Poitras, Sylvain Croteau, Martin Pham-Dinh, France Légaré
J Med Internet Res 2012;14(2):e49
(Apr 19, 2012)
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1 1.00 0.00 19 75
 
 
56
Effects of Functional Interactivity on Patients’ Knowledge, Empowerment, and Health Outcomes: An Experimental Model-Driven Evaluation of a Web-Based Intervention
Luca Camerini, Peter Johannes Schulz
J Med Internet Res 2012;14(4):e105
(Jul 18, 2012)
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1 1.00 0.00 15 70
 
 
57
On Supplementing “Foot in the Door” Incentives for eHealth Program Engagement
Marc Steven Mitchell, Guy E Faulkner
J Med Internet Res 2014;16(7):e179
(Jul 25, 2014)
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1 1.00 0.00 5 55
 
 
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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.