Top Articles (Article-Level Metrics)

 
 
Rank Article Tweets Tweets per MonthA
Tweets Influence FactorB
Twimpact Factor (tw7)C Twindex7D
 
1
Representation of Health Conditions on Facebook: Content Analysis and Evaluation of User Engagement
Timothy M Hale, Akhilesh S Pathipati, Shiyi Zan, Kamal Jethwani
J Med Internet Res 2014;16(8):e182
(Aug 4, 2014)
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67 79.89 0.00 29 95
 
 
2
Massive Open Online Courses on Health and Medicine: Review
Tharindu Rekha Liyanagunawardena, Shirley Ann Williams
J Med Internet Res 2014;16(8):e191
(Aug 14, 2014)
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61 118.19 0.00 58 100
 
 
3
Numeracy and Literacy Independently Predict Patients’ Ability to Identify Out-of-Range Test Results
Brian J Zikmund-Fisher, Nicole L Exe, Holly O Witteman
J Med Internet Res 2014;16(8):e187
(Aug 8, 2014)
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52 73.27 0.00 25 95
 
 
4
Behavior Change Techniques Implemented in Electronic Lifestyle Activity Monitors: A Systematic Content Analysis
Elizabeth J Lyons, Zakkoyya H Lewis, Brian G Mayrsohn, Jennifer L Rowland
J Med Internet Res 2014;16(8):e192
(Aug 15, 2014)
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23 47.53 0.00 17 85
 
 
5
How Feedback Biases Give Ineffective Medical Treatments a Good Reputation
Mícheál de Barra, Kimmo Eriksson, Pontus Strimling
J Med Internet Res 2014;16(8):e193
(Aug 21, 2014)
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21 72.34 0.00 19 90
 
 
6
Massive Open Online Courses on Health and Medicine: Will They Be Sustainable?
Kieran Walsh
J Med Internet Res 2014;16(8):e197
(Aug 25, 2014)
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20 123.99 0.00 20 95
 
 
7
Purple: A Modular System for Developing and Deploying Behavioral Intervention Technologies
Stephen M Schueller, Mark Begale, Frank J Penedo, David C Mohr
J Med Internet Res 2014;16(7):e181
(Jul 30, 2014)
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19 19.00 0.00 16 90
 
 
8
Infodemiology and Infoveillance: Framework for an Emerging Set of Public Health Informatics Methods to Analyze Search, Communication and Publication Behavior on the Internet
Gunther Eysenbach
J Med Internet Res 2009;11(1):e11
(Mar 27, 2009)
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15 15.00 0.00 17 100
 
 
9
Opportunities and Challenges for Smartphone Applications in Supporting Health Behavior Change: Qualitative Study
Laura Dennison, Leanne Morrison, Gemma Conway, Lucy Yardley
J Med Internet Res 2013;15(4):e86
(Apr 18, 2013)
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15 15.00 0.00 97 95
 
 
10
Crowdsourcing Malaria Parasite Quantification: An Online Game for Analyzing Images of Infected Thick Blood Smears
Miguel Angel Luengo-Oroz, Asier Arranz, John Frean
J Med Internet Res 2012;14(6):e167
(Nov 29, 2012)
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14 14.00 0.00 189 100
 
 
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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.