Top Articles (Article-Level Metrics)

 
 
Rank Article Tweets Tweets per MonthA
Tweets
Influence
Factor
B
Twimpact Factor (tw7)C Twindex7D
 
381
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 0.33 0.00 1 95
 
 
382
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 0.88 0.00 4 45
 
 
383
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 0.33 0.00 52 95
 
 
384
What Are Young Adults Saying About Mental Health? An Analysis of Internet Blogs
Madalyn A Marcus, Henny A Westra, John D Eastwood, Kirsten L Barnes, Mobilizing Minds Research Group
J Med Internet Res 2012;14(1):e17
(Jan 30, 2012)
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4 0.33 0.00 38 95
 
 
385
Cancer Survivorship in the Age of YouTube and Social Media: A Narrative Analysis
Wen-Ying Sylvia Chou, Yvonne Hunt, Anna Folkers, Erik Augustson
J Med Internet Res 2011;13(1):e7
(Jan 17, 2011)
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4 0.33 0.00 30 100
 
 
386
Common Cold Symptoms in Children: Results of an Internet-Based Surveillance Program
Emanuel Troullos, Lisa Baird, Shyamalie Jayawardena
J Med Internet Res 2014;16(6):e144
(Jun 19, 2014)
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4 1.80 0.00 4 35
 
 
387
The Internet as a Vehicle to Communicate Health Information During a Public Health Emergency: A Survey Analysis Involving the Anthrax Scare of 2001
Anne F Kittler, John Hobbs, Lynn A Volk, Gary L Kreps, David W Bates
J Med Internet Res 2004;6(1):e8
(Mar 3, 2004)
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4 0.33 0.00 3 95
 
 
388
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 0.77 0.00 4 50
 
 
389
Mobile Phone Text Messaging Intervention for Cervical Cancer Screening: Changes in Knowledge and Behavior Pre-Post Intervention
Hee Yun Lee, Joseph S Koopmeiners, Taeho Greg Rhee, Victoria H Raveis, Jasjit S Ahluwalia
J Med Internet Res 2014;16(8):e196
(Aug 27, 2014)
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4 0.00 0.00 4 60
 
 
390
Motives for Participating in a Web-Based Nutrition Cohort According to Sociodemographic, Lifestyle, and Health Characteristics: The NutriNet-Santé Cohort Study
Caroline Méjean, Fabien Szabo de Edelenyi, Mathilde Touvier, Emmanuelle Kesse-Guyot, Chantal Julia, Valentina A Andreeva, Serge Hercberg
J Med Internet Res 2014;16(8):e189
(Aug 7, 2014)
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4 6.20 0.00 4 55
 
 
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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.