Top Articles (Article-Level Metrics)

 
 
Rank Article Tweets Tweets per MonthA
Tweets Influence FactorB
Twimpact Factor (tw7)C Twindex7D
 
61
Development of a National Agreement on Human Papillomavirus Vaccination in Japan: An Infodemiology Study
Haruka Nakada, Koichiro Yuji, Masaharu Tsubokura, Yukio Ohsawa, Masahiro Kami
J Med Internet Res 2014;16(5):e129
(May 15, 2014)
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1 1.00 0.00 12 65
 
 
62
Supportive Accountability: A Model for Providing Human Support to Enhance Adherence to eHealth Interventions
David Mohr, Pim Cuijpers, Kenneth Lehman
J Med Internet Res 2011;13(1):e30
(Mar 10, 2011)
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1 1.00 0.00 2 0
 
 
63
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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1 1.00 0.00 21 95
 
 
64
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
 
 
65
Understanding the Factors That Influence the Adoption and Meaningful Use of Social Media by Physicians to Share Medical Information
Brian S McGowan, Molly Wasko, Bryan Steven Vartabedian, Robert S Miller, Desirae D Freiherr, Maziar Abdolrasulnia
J Med Internet Res 2012;14(5):e117
(Sep 24, 2012)
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1 1.00 0.00 142 100
 
 
66
Why Business Modeling is Crucial in the Development of eHealth Technologies
Maarten van Limburg, Julia EWC van Gemert-Pijnen, Nicol Nijland, Hans C Ossebaard, Ron MG Hendrix, Erwin R Seydel
J Med Internet Res 2011;13(4):e124
(Dec 28, 2011)
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1 1.00 0.00 27 85
 
 
67
Paging “Dr. Google”: Does Technology Fill the Gap Created by the Prenatal Care Visit Structure? Qualitative Focus Group Study With Pregnant Women
Jennifer L Kraschnewski, Cynthia H Chuang, Erika S Poole, Tamara Peyton, Ian Blubaugh, Jaimey Pauli, Alyssa Feher, Madhu Reddy
J Med Internet Res 2014;16(6):e147
(Jun 3, 2014)
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1 1.00 0.00 10 75
 
 
68
Comparison of Text and Video Computer-Tailored Interventions for Smoking Cessation: Randomized Controlled Trial
Nicola Stanczyk, Catherine Bolman, Mathieu van Adrichem, Math Candel, Jean Muris, Hein de Vries
J Med Internet Res 2014;16(3):e69
(Mar 3, 2014)
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1 1.00 0.00 0 0
 
 
69
Use of Twitter Among Local Health Departments: An Analysis of Information Sharing, Engagement, and Action
Brad L Neiger, Rosemary Thackeray, Scott H Burton, Callie R Thackeray, Jennifer H Reese
J Med Internet Res 2013;15(8):e177
(Aug 19, 2013)
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1 1.00 0.00 40 95
 
 
70
Reducing Suicidal Ideation: Cost-Effectiveness Analysis of a Randomized Controlled Trial of Unguided Web-Based Self-help
Bregje A.J. van Spijker, M. Cristina Majo, Filip Smit, Annemieke van Straten, Ad J.F.M. Kerkhof
J Med Internet Res 2012;14(5):e141
(Oct 26, 2012)
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1 1.00 0.00 9 35
 
 
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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.