Top Articles (Article-Level Metrics)

 
 
Rank Article Tweets Tweets per MonthA
Tweets Influence FactorB
Twimpact Factor (tw7)C Twindex7D
 
261
Harnessing Context Sensing to Develop a Mobile Intervention for Depression
Michelle Nicole Burns, Mark Begale, Jennifer Duffecy, Darren Gergle, Chris J Karr, Emily Giangrande, David C Mohr
J Med Internet Res 2011;13(3):e55
(Aug 12, 2011)
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1 0.17 0.00 10 50
 
 
262
Preventing Smoking Relapse via Web-Based Computer-Tailored Feedback: A Randomized Controlled Trial
Iman Elfeddali, Catherine Bolman, Math J.J.M. Candel, Reinout W. Wiers, Hein de Vries
J Med Internet Res 2012;14(4):e109
(Aug 20, 2012)
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1 0.17 0.00 8 40
 
 
263
Classification Accuracies of Physical Activities Using Smartphone Motion Sensors
Wanmin Wu, Sanjoy Dasgupta, Ernesto E. Ramirez, Carlyn Peterson, Gregory J Norman
J Med Internet Res 2012;14(5):e130
(Oct 5, 2012)
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1 0.17 0.00 18 75
 
 
264
Patients’ Ratings of Family Physician Practices on the Internet: Usage and Associations With Conventional Measures of Quality in the English National Health Service
Felix Greaves, Utz J Pape, Henry Lee, Dianna M Smith, Ara Darzi, Azeem Majeed, Christopher Millett
J Med Internet Res 2012;14(5):e146
(Oct 17, 2012)
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1 0.17 0.00 42 95
 
 
265
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 0.17 0.00 40 95
 
 
266
A Pre-Post Study on the Appropriateness and Effectiveness of a Web- and Text Messaging-Based Intervention to Reduce Problem Drinking in Emerging Adults
Severin Haug, Michael P Schaub, Vigeli Venzin, Christian Meyer, Ulrich John, Gerhard Gmel
J Med Internet Res 2013;15(9):e196
(Sep 2, 2013)
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1 0.17 0.00 4 25
 
 
267
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 0.17 0.00 27 85
 
 
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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.