Top Articles (Article-Level Metrics)

 
 
Rank Article Tweets Tweets per MonthA
Tweets Influence FactorB
Twimpact Factor (tw7)C Twindex7D
 
281
Healthy Weight Regulation and Eating Disorder Prevention in High School Students: A Universal and Targeted Web-Based Intervention
Megan Jones, Katherine Taylor Lynch, Andrea E Kass, Amanda Burrows, Joanne Williams, Denise E Wilfley, C Barr Taylor
J Med Internet Res 2014;16(2):e57
(Feb 27, 2014)
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6 1.21 0.00 4 40
 
 
282
Perceptions of Successful Cues to Action and Opportunities to Augment Behavioral Triggers in Diabetes Self-Management: Qualitative Analysis of a Mobile Intervention for Low-Income Latinos With Diabetes
Elizabeth R Burner, Michael D Menchine, Katrina Kubicek, Marisela Robles, Sanjay Arora
J Med Internet Res 2014;16(1):e25
(Jan 29, 2014)
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6 1.02 0.00 4 30
 
 
283
Effects of a Web-Based Tailored Multiple-Lifestyle Intervention for Adults: A Two-Year Randomized Controlled Trial Comparing Sequential and Simultaneous Delivery Modes
Daniela N Schulz, Stef PJ Kremers, Corneel Vandelanotte, Mathieu JG van Adrichem, Francine Schneider, Math JJM Candel, Hein de Vries
J Med Internet Res 2014;16(1):e26
(Jan 27, 2014)
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6 1.01 0.00 6 40
 
 
284
Exploring the Use and Effects of Deliberate Self-Harm Websites: An Internet-Based Study
Isobel Marion Harris, Lesley Martine Roberts
J Med Internet Res 2013;15(12):e285
(Dec 20, 2013)
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6 0.83 10.00 5 30
 
 
285
Perceived Barriers and Facilitators of Using a Web-Based Interactive Decision Aid for Colorectal Cancer Screening in Community Practice Settings: Findings From Focus Groups With Primary Care Clinicians and Medical Office Staff
Masahito Jimbo, Cameron Garth Shultz, Donald Eugene Nease, Michael Derwin Fetters, Debra Power, Mack Thomas Ruffin IV
J Med Internet Res 2013;15(12):e286
(Dec 18, 2013)
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6 0.83 8.00 6 55
 
 
286
Leveraging Text Messaging and Mobile Technology to Support Pediatric Obesity-Related Behavior Change: A Qualitative Study Using Parent Focus Groups and Interviews
Mona Sharifi, Eileen M Dryden, Christine M Horan, Sarah Price, Richard Marshall, Karen Hacker, Jonathan A Finkelstein, Elsie M Taveras
J Med Internet Res 2013;15(12):e272
(Dec 6, 2013)
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6 0.78 15.00 5 60
 
 
287
Young Men’s Views Toward the Barriers and Facilitators of Internet-Based Chlamydia Trachomatis Screening: Qualitative Study
Karen Lorimer, Lisa McDaid
J Med Internet Res 2013;15(12):e265
(Dec 3, 2013)
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6 0.78 23.00 5 45
 
 
288
Metadata Correction: Design and Evaluation of a Simulation for Pediatric Dentistry in Virtual Worlds
Lazaros Papadopoulos, Afroditi-Evaggelia Pentzou, Konstantinos Louloudiadis, Thrasyvoulos-Konstantinos Tsiatsos
J Med Internet Res 2013;15(11):e268
(Nov 26, 2013)
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6 0.75 15.00 6 30
 
 
289
Design and Evaluation of a Simulation for Pediatric Dentistry in Virtual Worlds
Lazaros Papadopoulos, Afroditi-Evaggelia Pentzou, Konstantinos Louloudiadis, Thrasyvoulos-Konstantinos Tsiatsos
J Med Internet Res 2013;15(10):e240
(Oct 29, 2013)
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6 0.68 7.00 5 35
 
 
290
Infodemiology of Alcohol Use in Hong Kong Mentioned on Blogs: Infoveillance Study
KL Chan, SY Ho, TH Lam
J Med Internet Res 2013;15(9):e192
(Sep 2, 2013)
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6 0.56 17.00 6 30
 
 
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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.