Top Articles (Article-Level Metrics)

 
 
Rank Article Tweets Tweets per MonthA
Tweets Influence FactorB
Twimpact Factor (tw7)C Twindex7D
 
1
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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61 105.06 0.00 58 100
 
 
2
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 88.57 0.00 20 95
 
 
3
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 74.18 0.00 29 95
 
 
4
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 71.04 0.00 25 95
 
 
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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25 70.46 0.00 19 90
 
 
6
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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11 56.85 0.00 11 80
 
 
7
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 41.94 0.00 17 85
 
 
8
Social Network Sites as a Mode to Collect Health Data: A Systematic Review
Fahdah Alshaikh, Farzan Ramzan, Salman Rawaf, Azeem Majeed
J Med Internet Res 2014;16(7):e171
(Jul 14, 2014)
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65 41.12 0.00 53 100
 
 
9
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
 
 
10
Predictors of eHealth Usage: Insights on The Digital Divide From the Health Information National Trends Survey 2012
Emily Kontos, Kelly D Blake, Wen-Ying Sylvia Chou, Abby Prestin
J Med Internet Res 2014;16(7):e172
(Jul 16, 2014)
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46 30.34 0.00 38 95
 
 
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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.