Top Articles (Article-Level Metrics)

 
 
Rank Article Tweets Tweets per MonthA
Tweets
Influence
Factor
B
Twimpact Factor (tw7)C Twindex7D
 
261
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
 
 
262
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
 
 
263
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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1 0.17 0.00 2 75
 
 
264
Use of a Text Message Program to Raise Type 2 Diabetes Risk Awareness and Promote Health Behavior Change (Part II): Assessment of Participants' Perceptions on Efficacy
Lorraine R Buis, Lindsey Hirzel, Scott A Turske, Terrisca R Des Jardins, Hossein Yarandi, Patricia Bondurant
J Med Internet Res 2013;15(12):e282
(Dec 19, 2013)
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1 0.17 0.00 8 60
 
 
265
A Text Messaging Intervention to Improve Heart Failure Self-Management After Hospital Discharge in a Largely African-American Population: Before-After Study
Shantanu Nundy, Rabia R Razi, Jonathan J Dick, Bryan Smith, Ainoa Mayo, Anne O'Connor, David O Meltzer
J Med Internet Res 2013;15(3):e53
(Mar 11, 2013)
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1 0.17 0.00 12 50
 
 
266
The Effect of Patient Narratives on Information Search in a Web-Based Breast Cancer Decision Aid: An Eye-Tracking Study
Victoria A Shaffer, Justin Owens, Brian J Zikmund-Fisher
J Med Internet Res 2013;15(12):e273
(Dec 17, 2013)
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1 0.17 0.00 5 40
 
 
267
Using Chat and Text Technologies to Answer Sexual and Reproductive Health Questions: Planned Parenthood Pilot Study
Margaret M Giorgio, Leslie M Kantor, Deborah S Levine, Whitney Arons
J Med Internet Res 2013;15(9):e203
(Sep 20, 2013)
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1 0.17 0.00 15 85
 
 
268
Design of an mHealth App for the Self-management of Adolescent Type 1 Diabetes: A Pilot Study
Joseph A Cafazzo, Mark Casselman, Nathaniel Hamming, Debra K Katzman, Mark R Palmert
J Med Internet Res 2012;14(3):e70
(May 8, 2012)
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1 0.17 0.00 47 90
 
 
269
How Patients With Schizophrenia Use the Internet: Qualitative Study
Beate Schrank, Ingrid Sibitz, Annemarie Unger, Michaela Amering
J Med Internet Res 2010;12(5):e70
(Dec 19, 2010)
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1 0.17 0.00 19 100
 
 
270
Silence is Golden: Effect of Encouragement in Motivating the Weak Link in an Online Exercise Video Game
Brandon C Irwin, Deborah L Feltz, Norbert L Kerr
J Med Internet Res 2013;15(6):e104
(Jun 4, 2013)
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1 0.17 0.00 5 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.