Top Articles (Article-Level Metrics)

 
 
Rank Article Tweets Tweets per MonthA
Tweets Influence FactorB
Twimpact Factor (tw7)C Twindex7D
 
21
Mobile Phone Applications for the Care and Prevention of HIV and Other Sexually Transmitted Diseases: A Review
Kathryn E Muessig, Emily C Pike, Sara LeGrand, Lisa B Hightow-Weidman
J Med Internet Res 2013;15(1):e1
(Jan 4, 2013)
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7 7.00 0.00 20 80
 
 
22
Comparative Analysis of Online Health Queries Originating From Personal Computers and Smart Devices on a Consumer Health Information Portal
Ashutosh Jadhav, Donna Andrews, Alexander Fiksdal, Ashok Kumbamu, Jennifer B McCormick, Andrew Misitano, Laurie Nelsen, Euijung Ryu, Amit Sheth, Stephen Wu, Jyotishman Pathak
J Med Internet Res 2014;16(7):e160
(Jul 4, 2014)
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6 6.00 0.00 10 75
 
 
23
Mapping mHealth Research: A Decade of Evolution
Maddalena Fiordelli, Nicola Diviani, Peter J. Schulz
J Med Internet Res 2013;15(5):e95
(May 21, 2013)
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6 6.00 0.00 82 100
 
 
24
Smartphones for Smarter Delivery of Mental Health Programs: A Systematic Review
Tara Donker, Katherine Petrie, Judy Proudfoot, Janine Clarke, Mary-Rose Birch, Helen Christensen
J Med Internet Res 2013;15(11):e247
(Nov 15, 2013)
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6 6.00 0.00 34 95
 
 
25
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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5 31.00 0.00 5 60
 
 
26
How an Online Intervention to Prevent Excessive Gestational Weight Gain Is Used and by Whom: A Randomized Controlled Process Evaluation
Margaret Mochon Demment, Meredith Leigh Graham, Christine Marie Olson
J Med Internet Res 2014;16(8):e194
(Aug 20, 2014)
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5 12.92 0.00 5 70
 
 
27
Interactive Sections of an Internet-Based Intervention Increase Empowerment of Chronic Back Pain Patients: Randomized Controlled Trial
Silvia Riva, Anne-Linda Camerini, Ahmed Allam, Peter J Schulz
J Med Internet Res 2014;16(8):e180
(Aug 13, 2014)
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5 8.16 0.00 5 55
 
 
28
Assessing the Applicability of E-Therapies for Depression, Anxiety, and Other Mood Disorders Among Lesbians and Gay Men: Analysis of 24 Web- and Mobile Phone-Based Self-Help Interventions
Tomas Rozbroj, Anthony Lyons, Marian Pitts, Anne Mitchell, Helen Christensen
J Med Internet Res 2014;16(7):e166
(Jul 3, 2014)
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5 5.00 0.00 18 95
 
 
29
A New Dimension of Health Care: Systematic Review of the Uses, Benefits, and Limitations of Social Media for Health Communication
S Anne Moorhead, Diane E. Hazlett, Laura Harrison, Jennifer K Carroll, Anthea Irwin, Ciska Hoving
J Med Internet Res 2013;15(4):e85
(Apr 23, 2013)
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5 5.00 0.00 87 90
 
 
30
Can Tweets Predict Citations? Metrics of Social Impact Based on Twitter and Correlation with Traditional Metrics of Scientific Impact
Gunther Eysenbach
J Med Internet Res 2011;13(4):e123
(Dec 16, 2011)
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5 5.00 0.00 529 100
 
 
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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.