Top Articles (Article-Level Metrics)

 
 
Rank Article Tweets Tweets per MonthA
Tweets Influence FactorB
Twimpact Factor (tw7)C Twindex7D
 
51
Exploring the Value of Technology to Stimulate Interprofessional Discussion and Education: A Needs Assessment of Emergency Medicine Professionals
Jennifer Riley, Melissa McGowan, Linda Rozmovits
J Med Internet Res 2014;16(6):e162
(Jun 30, 2014)
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2 2.00 0.00 5 55
 
 
52
Experiential Virtual Scenarios With Real-Time Monitoring (Interreality) for the Management of Psychological Stress: A Block Randomized Controlled Trial
Andrea Gaggioli, Federica Pallavicini, Luca Morganti, Silvia Serino, Chiara Scaratti, Marilena Briguglio, Giulia Crifaci, Noemi Vetrano, Annunziata Giulintano, Giuseppe Bernava, Gennaro Tartarisco, Giovanni Pioggia, Simona Raspelli, Pietro Cipresso, Cinzia Vigna, Alessandra Grassi, Margherita Baruffi, Brenda Wiederhold, Giuseppe Riva
J Med Internet Res 2014;16(7):e167
(Jul 8, 2014)
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2 2.00 0.00 12 80
 
 
53
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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1 1.00 0.00 29 85
 
 
54
Evaluation of an eHealth Intervention in Chronic Care for Frail Older People: Why Adherence is the First Target
Peter Makai, Marieke Perry, Sarah HM Robben, Henk J Schers, Maud M Heinen, Marcel GM Olde Rikkert, René F Melis
J Med Internet Res 2014;16(6):e156
(Jun 23, 2014)
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1 1.00 0.00 13 80
 
 
55
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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1 1.00 0.00 21 95
 
 
56
Supportive Accountability: A Model for Providing Human Support to Enhance Adherence to eHealth Interventions
David Mohr, Pim Cuijpers, Kenneth Lehman
J Med Internet Res 2011;13(1):e30
(Mar 10, 2011)
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1 1.00 0.00 2 0
 
 
57
Why Business Modeling is Crucial in the Development of eHealth Technologies
Maarten van Limburg, Julia EWC van Gemert-Pijnen, Nicol Nijland, Hans C Ossebaard, Ron MG Hendrix, Erwin R Seydel
J Med Internet Res 2011;13(4):e124
(Dec 28, 2011)
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1 1.00 0.00 27 85
 
 
58
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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1 1.00 0.00 41 95
 
 
59
Design of a Website on Nutrition and Physical Activity for Adolescents: Results From Formative Research
Debbe Thompson, Karen Weber Cullen, Carol Boushey, Karen Konzelmann
J Med Internet Res 2012;14(2):e59
(Apr 26, 2012)
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1 1.00 0.00 22 80
 
 
60
Social Media: A Review and Tutorial of Applications in Medicine and Health Care
Francisco Jose Grajales III, Samuel Sheps, Kendall Ho, Helen Novak-Lauscher, Gunther Eysenbach
J Med Internet Res 2014;16(2):e13
(Feb 11, 2014)
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1 1.00 0.00 104 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.