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 71.62 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 99.53 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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55 68.20 0.00 25 95
 
 
4
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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25 64.58 0.00 19 90
 
 
5
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 39.61 0.00 17 85
 
 
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 77.49 0.00 20 95
 
 
7
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
 
 
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
Changes Over Time in the Utilization of Disease-Related Internet Information in Newly Diagnosed Breast Cancer Patients 2007 to 2013
Christoph Kowalski, Eva Kahana, Kathrin Kuhr, Lena Ansmann, Holger Pfaff
J Med Internet Res 2014;16(8):e195
(Aug 26, 2014)
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12 53.14 0.00 12 80
 
 
10
CONSORT-EHEALTH: Improving and Standardizing Evaluation Reports of Web-based and Mobile Health Interventions
Gunther Eysenbach, CONSORT-EHEALTH Group
J Med Internet Res 2011;13(4):e126
(Dec 31, 2011)
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12 12.00 0.00 24 80
 
 
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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.