Top Articles (Article-Level Metrics)

 
 
Rank Article Tweets Tweets per MonthA
Tweets Influence FactorB
Twimpact Factor (tw7)C Twindex7D
 
51
Consensus on Use of the Term “App” Versus “Application” for Reporting of mHealth Research
Thomas Lorchan Lewis, Matthew Alexander Boissaud-Cooke, Timothy Dy Aungst, Gunther Eysenbach
J Med Internet Res 2014;16(7):e174
(Jul 17, 2014)
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2 2.00 0.00 24 90
 
 
52
Definition of Health 2.0 and Medicine 2.0: A Systematic Review
Tom H Van De Belt, Lucien JLPG Engelen, Sivera AA Berben, Lisette Schoonhoven
J Med Internet Res 2010;12(2):e18
(Jun 11, 2010)
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2 2.00 0.00 89 100
 
 
53
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
 
 
54
Assessing the Internal and External Validity of Mobile Health Physical Activity Promotion Interventions: A Systematic Literature Review Using the RE-AIM Framework
Kacie CA Blackman, Jamie Zoellner, Leanna M Berrey, Ramine Alexander, Jason Fanning, Jennie L Hill, Paul A Estabrooks
J Med Internet Res 2013;15(10):e224
(Oct 4, 2013)
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1 1.00 0.00 12 65
 
 
55
Searching for Cancer Information on the Internet: Analyzing Natural Language Search Queries
Judith L Bader, Mary Frances Theofanos
J Med Internet Res 2003;5(4):e31
(Dec 11, 2003)
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1 1.00 0.00 3 100
 
 
56
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
 
 
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
 
 
58
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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1 1.00 0.00 41 95
 
 
59
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
 
 
60
Medicine 2.0: Social Networking, Collaboration, Participation, Apomediation, and Openness
Gunther Eysenbach
J Med Internet Res 2008;10(3):e22
(Aug 25, 2008)
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1 1.00 0.00 8 100
 
 
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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.