Top Articles (Article-Level Metrics)

 
 
Rank Article Tweets Tweets per MonthA
 Tweets Influence FactorB
 Twimpact Factor (tw7)C Twindex7D
 
41
Internet Skills Performance Tests: Are People Ready for eHealth?
Alexander J.A.M. van Deursen, Jan A.G.M. van Dijk
J Med Internet Res 2011;13(2):e35
(Apr 29, 2011)
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70 2.86 163.00 39 90
 
 
42
Short Message Service (SMS) Applications for Disease Prevention in Developing Countries
Carole Déglise, L. Suzanne Suggs, Peter Odermatt
J Med Internet Res 2012;14(1):e3
(Jan 12, 2012)
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70 4.34 77.00 27 80
 
 
43
Public Access and Use of Health Research: An Exploratory Study of the National Institutes of Health (NIH) Public Access Policy Using Interviews and Surveys of Health Personnel
Jamie O'Keeffe, John Willinsky, Lauren Maggio
J Med Internet Res 2011;13(4):e97
(Nov 21, 2011)
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68 3.82 129.00 52 100
 
 
44
Features Predicting Weight Loss in Overweight or Obese Participants in a Web-Based Intervention: Randomized Trial
Emily Brindal, Jill Freyne, Ian Saunders, Shlomo Berkovsky, Greg Smith, Manny Noakes
J Med Internet Res 2012;14(6):e173
(Dec 12, 2012)
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63 11.84 180.00 57 90
 
 
45
Managing the Personal Side of Health: How Patient Expertise Differs from the Expertise of Clinicians
Andrea Hartzler, Wanda Pratt
J Med Internet Res 2011;13(3):e62
(Aug 16, 2011)
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62 2.96 125.00 39 100
 
 
46
Individually Tailored Internet-Based Treatment for Young Adults and Adults With Panic Attacks: Randomized Controlled Trial
Kristin Silfvernagel, Per Carlbring, Julia Kabo, Sara Edström, Jenny Eriksson, Lisa Månson, Gerhard Andersson
J Med Internet Res 2012;14(3):e65
(Jun 26, 2012)
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62 5.75 57.00 13 50
 
 
47
Review of Extracting Information From the Social Web for Health Personalization
Luis Fernandez-Luque, Randi Karlsen, Jason Bonander
J Med Internet Res 2011;13(1):e15
(Jan 28, 2011)
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60 2.19 144.00 50 100
 
 
48
An Evaluation of the Use of Smartphones to Communicate Between Clinicians: A Mixed-Methods Study
Robert Wu, Peter Rossos, Sherman Quan, Scott Reeves, Vivian Lo, Brian Wong, Mark Cheung, Dante Morra
J Med Internet Res 2011;13(3):e59
(Aug 29, 2011)
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60 2.92 83.00 29 95
 
 
49
Should Health Organizations Use Web 2.0 Media in Times of an Infectious Disease Crisis? An In-depth Qualitative Study of Citizens’ Information Behavior During an EHEC Outbreak
Lex van Velsen, Julia E.W.C. van Gemert-Pijnen, Desirée J.M.A. Beaujean, Jobke Wentzel, Jim E. van Steenbergen
J Med Internet Res 2012;14(6):e181
(Dec 20, 2012)
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60 11.85 61.00 20 80
 
 
50
Mapping mHealth Research: A Decade of Evolution
Maddalena Fiordelli, Nicola Diviani, Peter J. Schulz
J Med Internet Res 2013;15(5):e95
(May 21, 2013)
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59 365.78 121.00 59 100
 
 
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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.

 * Tweets Data Collection began January 2008