Top Articles (Article-Level Metrics)

 
 
Rank Article Tweets Tweets per MonthA
Tweets Influence FactorB
Twimpact Factor (tw7)C Twindex7D
 
1
mHealth and Mobile Medical Apps: A Framework to Assess Risk and Promote Safer Use
Thomas Lorchan Lewis, Jeremy C Wyatt
J Med Internet Res 2014;16(9):e210
(Sep 15, 2014)
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59 228.59 0.00 59 100
 
 
2
Baby Boomers’ Adoption of Consumer Health Technologies: Survey on Readiness and Barriers
Cynthia LeRouge, Craig Van Slyke, Deborah Seale, Kevin Wright
J Med Internet Res 2014;16(9):e200
(Sep 8, 2014)
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33 68.20 0.00 33 100
 
 
3
A Medical Consultation Service on Facebook: Descriptive Analysis of Questions Answered
Otto Helve
J Med Internet Res 2014;16(9):e202
(Sep 4, 2014)
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29 47.32 0.00 25 100
 
 
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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29 29.00 0.00 17 85
 
 
5
Estimation of Geographic Variation in Human Papillomavirus Vaccine Uptake in Men and Women: An Online Survey Using Facebook Recruitment
Erik J Nelson, John Hughes, J Michael Oakes, James S Pankow, Shalini L Kulasingam
J Med Internet Res 2014;16(9):e198
(Sep 1, 2014)
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20 28.18 0.00 19 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 21.38 0.00 20 95
 
 
7
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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19 19.00 0.00 19 90
 
 
8
Online and Social Networking Interventions for the Treatment of Depression in Young People: A Systematic Review
Simon M. Rice, Joanne Goodall, Sarah E. Hetrick, Alexandra G. Parker, Tamsyn Gilbertson, G. Paul Amminger, Christopher G. Davey, Patrick D. McGorry, John Gleeson, Mario Alvarez-Jimenez
J Med Internet Res 2014;16(9):e206
(Sep 16, 2014)
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18 79.72 0.00 18 75
 
 
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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16 17.71 0.00 14 80
 
 
10
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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16 16.00 0.00 25 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.