Top Articles (Article-Level Metrics)

 
 
Rank Article Tweets Tweets per MonthA
Tweets Influence FactorB
Twimpact Factor (tw7)C Twindex7D
 
1
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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58 128.43 0.00 53 100
 
 
2
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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42 108.50 0.00 38 95
 
 
3
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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28 78.92 0.00 24 90
 
 
4
Response to: Self-Directed Interventions to Promote Weight Loss: A Systematic Review of Reviews
Melinda Hutchesson, Philip Morgan, Penelope Jones, Clare Collins
J Med Internet Res 2014;16(7):e178
(Jul 24, 2014)
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8 62.02 0.00 8 70
 
 
5
A Web-Based Peer-Modeling Intervention Aimed at Lifestyle Changes in Patients With Coronary Heart Disease and Chronic Back Pain: Sequential Controlled Trial
Rebecca Schweier, Matthias Romppel, Cynthia Richter, Eike Hoberg, Harry Hahmann, Inge Scherwinski, Gregor Kosmützky, Gesine Grande
J Med Internet Res 2014;16(7):e177
(Jul 23, 2014)
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9 55.80 0.00 9 70
 
 
6
On Supplementing “Foot in the Door” Incentives for eHealth Program Engagement
Marc Steven Mitchell, Guy E Faulkner
J Med Internet Res 2014;16(7):e179
(Jul 25, 2014)
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5 51.65 0.00 5 55
 
 
7
Assessing the Applicability of E-Therapies for Depression, Anxiety, and Other Mood Disorders Among Lesbians and Gay Men: Analysis of 24 Web- and Mobile Phone-Based Self-Help Interventions
Tomas Rozbroj, Anthony Lyons, Marian Pitts, Anne Mitchell, Helen Christensen
J Med Internet Res 2014;16(7):e166
(Jul 3, 2014)
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36 44.64 0.00 18 95
 
 
8
The Role of Facebook in Crush the Crave, a Mobile- and Social Media-Based Smoking Cessation Intervention: Qualitative Framework Analysis of Posts
Laura Louise Struik, Neill Bruce Baskerville
J Med Internet Res 2014;16(7):e170
(Jul 11, 2014)
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21 38.29 0.00 21 95
 
 
9
Online Health Information Seeking Behaviors of Hispanics in New York City: A Community-Based Cross-Sectional Study
Young Ji Lee, Bernadette Boden-Albala, Elaine Larson, Adam Wilcox, Suzanne Bakken
J Med Internet Res 2014;16(7):e176
(Jul 22, 2014)
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6 31.01 0.00 6 60
 
 
10
A Web-Based Non-Intrusive Ambient System to Measure and Classify Activities of Daily Living
Reto A Stucki, Prabitha Urwyler, Luca Rampa, René Müri, Urs P Mosimann, Tobias Nef
J Med Internet Res 2014;16(7):e175
(Jul 21, 2014)
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7 31.00 0.00 7 65
 
 
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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.