Top Articles (Article-Level Metrics)

 
 
Rank Article Tweets Tweets per MonthA
Tweets Influence FactorB
Twimpact Factor (tw7)C Twindex7D
 
21
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 21.61 0.00 38 95
 
 
22
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 19.84 0.00 14 80
 
 
23
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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36 17.17 0.00 24 90
 
 
24
A Spanish Pillbox App for Elderly Patients Taking Multiple Medications: Randomized Controlled Trial
José Joaquín Mira, Isabel Navarro, Federico Botella, Fernando Borrás, Roberto Nuño-Solinís, Domingo Orozco, Fuencisla Iglesias-Alonso, Pastora Pérez-Pérez, Susana Lorenzo, Nuria Toro
J Med Internet Res 2014;16(4):e99
(Apr 4, 2014)
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92 16.88 0.00 51 100
 
 
25
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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41 16.09 0.00 18 95
 
 
26
The Behavioral Intervention Technology Model: An Integrated Conceptual and Technological Framework for eHealth and mHealth Interventions
David C Mohr, Stephen M Schueller, Enid Montague, Michelle Nicole Burns, Parisa Rashidi
J Med Internet Res 2014;16(6):e146
(Jun 5, 2014)
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46 13.33 0.00 35 95
 
 
27
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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10 12.92 0.00 9 75
 
 
28
Mapping Physician Twitter Networks: Describing How They Work as a First Step in Understanding Connectivity, Information Flow, and Message Diffusion
Ranit Mishori, Lisa Oberoi Singh, Brendan Levy, Calvin Newport
J Med Internet Res 2014;16(4):e107
(Apr 14, 2014)
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63 12.28 0.00 41 95
 
 
29
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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32 11.67 0.00 28 100
 
 
30
Purple: A Modular System for Developing and Deploying Behavioral Intervention Technologies
Stephen M Schueller, Mark Begale, Frank J Penedo, David C Mohr
J Med Internet Res 2014;16(7):e181
(Jul 30, 2014)
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19 11.33 0.00 16 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.