Top Articles (Article-Level Metrics)

 
 
Rank Article Tweets Tweets per MonthA
Tweets Influence FactorB
Twimpact Factor (tw7)C Twindex7D
 
21
Use of Twitter Among Local Health Departments: An Analysis of Information Sharing, Engagement, and Action
Brad L Neiger, Rosemary Thackeray, Scott H Burton, Callie R Thackeray, Jennifer H Reese
J Med Internet Res 2013;15(8):e177
(Aug 19, 2013)
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1 1.00 0.00 40 95
 
 
22
A Lot of Action, But Not in the Right Direction: Systematic Review and Content Analysis of Smartphone Applications for the Prevention, Detection, and Management of Cancer
Jacqueline Lorene Bender, Rossini Ying Kwan Yue, Matthew Jason To, Laetitia Deacken, Alejandro R Jadad
J Med Internet Res 2013;15(12):e287
(Dec 23, 2013)
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4 4.00 0.00 38 100
 
 
23
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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3 3.00 0.00 38 95
 
 
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
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 69.24 0.00 29 95
 
 
26
Are Health Behavior Change Interventions That Use Online Social Networks Effective? A Systematic Review
Carol A Maher, Lucy K Lewis, Katia Ferrar, Simon Marshall, Ilse De Bourdeaudhuij, Corneel Vandelanotte
J Med Internet Res 2014;16(2):e40
(Feb 14, 2014)
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3 3.00 0.00 29 85
 
 
27
Characterizing the Followers and Tweets of a Marijuana-Focused Twitter Handle
Patricia Cavazos-Rehg, Melissa Krauss, Richard Grucza, Laura Bierut
J Med Internet Res 2014;16(6):e157
(Jun 27, 2014)
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2 2.00 0.00 28 100
 
 
28
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 65.58 0.00 25 95
 
 
29
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
 
 
30
Consensus on Use of the Term “App” Versus “Application” for Reporting of mHealth Research
Thomas Lorchan Lewis, Matthew Alexander Boissaud-Cooke, Timothy Dy Aungst, Gunther Eysenbach
J Med Internet Res 2014;16(7):e174
(Jul 17, 2014)
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2 2.00 0.00 24 90
 
 
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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.