Top Articles (Article-Level Metrics)

 
 
Rank Article Tweets Tweets per MonthA
Tweets Influence FactorB
Twimpact Factor (tw7)C Twindex7D
 
171
Adolescents Just Do Not Know What They Want: A Qualitative Study to Describe Obese Adolescents’ Experiences of Text Messaging to Support Behavior Change Maintenance Post Intervention
Kyla L Smith, Deborah A Kerr, Ashley A Fenner, Leon M Straker
J Med Internet Res 2014;16(4):e103
(Apr 8, 2014)
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4 0.77 0.00 4 45
 
 
172
Animated Randomness, Avatars, Movement, and Personalization in Risk Graphics
Holly O Witteman, Andrea Fuhrel-Forbis, Harindra C Wijeysundera, Nicole Exe, Mark Dickson, Lisa Holtzman, Valerie C Kahn, Brian J Zikmund-Fisher
J Med Internet Res 2014;16(3):e80
(Mar 18, 2014)
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4 0.68 0.00 4 50
 
 
173
Do Email and Mobile Phone Prompts Stimulate Primary School Children to Reuse an Internet-Delivered Smoking Prevention Intervention?
Henricus-Paul Cremers, Liesbeth Mercken, Rik Crutzen, Paul Willems, Hein de Vries, Anke Oenema
J Med Internet Res 2014;16(3):e86
(Mar 18, 2014)
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4 0.68 0.00 4 55
 
 
174
Caught in the Web: A Review of Web-Based Suicide Prevention
Mee Huong Lai, Thambu Maniam, Lai Fong Chan, Arun V Ravindran
J Med Internet Res 2014;16(1):e30
(Jan 28, 2014)
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4 0.67 0.00 4 25
 
 
175
Online Access to Doctors' Notes: Patient Concerns About Privacy
Elisabeth Vodicka, Roanne Mejilla, Suzanne G Leveille, James D Ralston, Jonathan D Darer, Tom Delbanco, Jan Walker, Joann G Elmore
J Med Internet Res 2013;15(9):e208
(Sep 26, 2013)
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4 0.67 0.00 32 100
 
 
176
Patients’ Engagement With “Sweet Talk” – A Text Messaging Support System for Young People With Diabetes
Victoria Franklin, Alexandra Greene, Annalu Waller, Stephen Greene, Claudia Pagliari
J Med Internet Res 2008;10(2):e20
(Jun 30, 2008)
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4 0.67 0.00 1 95
 
 
177
Young Men, Mental Health, and Technology: Implications for Service Design and Delivery in the Digital Age
Louise A Ellis, Philippa Collin, Tracey A Davenport, Patrick J Hurley, Jane M Burns, Ian B Hickie
J Med Internet Res 2012;14(6):e160
(Nov 22, 2012)
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4 0.67 0.00 52 95
 
 
178
Broad Reach and Targeted Recruitment Using Facebook for an Online Survey of Young Adult Substance Use
Danielle E. Ramo, Judith J. Prochaska
J Med Internet Res 2012;14(1):e28
(Feb 23, 2012)
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4 0.67 0.00 10 35
 
 
179
Increased Use of Twitter at a Medical Conference: A Report and a Review of the Educational Opportunities
Douglas RA McKendrick, Grant P Cumming, Amanda J Lee
J Med Internet Res 2012;14(6):e176
(Dec 11, 2012)
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4 0.67 0.00 105 95
 
 
180
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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4 0.67 0.00 118 100
 
 
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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.