Top Articles (Article-Level Metrics)

 
 
Rank Article Tweets Tweets per MonthA
Tweets Influence FactorB
Twimpact Factor (tw7)C Twindex7D
 
191
Preventing Smoking Relapse via Web-Based Computer-Tailored Feedback: A Randomized Controlled Trial
Iman Elfeddali, Catherine Bolman, Math J.J.M. Candel, Reinout W. Wiers, Hein de Vries
J Med Internet Res 2012;14(4):e109
(Aug 20, 2012)
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1 0.17 0.00 8 40
 
 
192
Open Source, Open Standards, and Health Care Information Systems
Carl J Reynolds, Jeremy C Wyatt
J Med Internet Res 2011;13(1):e24
(Feb 17, 2011)
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1 0.17 0.00 8 30
 
 
193
Use of Behavioral Change Techniques in Web-Based Self-Management Programs for Type 2 Diabetes Patients: Systematic Review
Michael van Vugt, Maartje de Wit, Wilmy HJJ Cleijne, Frank J Snoek
J Med Internet Res 2013;15(12):e279
(Dec 13, 2013)
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1 0.17 0.00 8 65
 
 
194
Growing a Professional Network to Over 3000 Members in Less Than 4 Years: Evaluation of InspireNet, British Columbia’s Virtual Nursing Health Services Research Network
Noreen Frisch, Pat Atherton, Elizabeth Borycki, Grace Mickelson, Jennifer Cordeiro, Helen Novak Lauscher, Agnes Black
J Med Internet Res 2014;16(2):e49
(Feb 21, 2014)
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10 1.91 0.00 7 45
 
 
195
Efficacy of a Web-Based Computer-Tailored Smoking Prevention Intervention for Dutch Adolescents: Randomized Controlled Trial
Sanne de Josselin de Jong, Math Candel, Dewi Segaar, Henricus-Paul Cremers, Hein de Vries
J Med Internet Res 2014;16(3):e82
(Mar 21, 2014)
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9 2.08 0.00 7 80
 
 
196
Performance of eHealth Data Sources in Local Influenza Surveillance: A 5-Year Open Cohort Study
Toomas Timpka, Armin Spreco, Örjan Dahlström, Olle Eriksson, Elin Gursky, Joakim Ekberg, Eva Blomqvist, Magnus Strömgren, David Karlsson, Henrik Eriksson, James Nyce, Jorma Hinkula, Einar Holm
J Med Internet Res 2014;16(4):e116
(Apr 28, 2014)
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9 2.91 0.00 7 70
 
 
197
Who Uses Physician-Rating Websites? Differences in Sociodemographic Variables, Psychographic Variables, and Health Status of Users and Nonusers of Physician-Rating Websites
Ralf Terlutter, Sonja Bidmon, Johanna Röttl
J Med Internet Res 2014;16(3):e97
(Mar 31, 2014)
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9 2.25 0.00 7 60
 
 
198
Supporting Patients Treated for Prostate Cancer: A Video Vignette Study With an Email-Based Educational Program in General Practice
Moyez Jiwa, Georgia Halkett, Xingqiong Meng, Vinita Pillai, Melissa Berg, Tim Shaw
J Med Internet Res 2014;16(2):e63
(Feb 26, 2014)
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8 1.58 0.00 7 60
 
 
199
Adherence to Self-Monitoring via Interactive Voice Response Technology in an eHealth Intervention Targeting Weight Gain Prevention Among Black Women: Randomized Controlled Trial
Dori M Steinberg, Erica L Levine, Ilana Lane, Sandy Askew, Perry B Foley, Elaine Puleo, Gary G Bennett
J Med Internet Res 2014;16(4):e114
(Apr 29, 2014)
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8 2.61 0.00 7 65
 
 
200
Multiple Information Sources and Consequences of Conflicting Information About Medicine Use During Pregnancy: A Multinational Internet-Based Survey
Katri Hämeen-Anttila, Hedvig Nordeng, Esa Kokki, Johanna Jyrkkä, Angela Lupattelli, Kirsti Vainio, Hannes Enlund
J Med Internet Res 2014;16(2):e60
(Feb 20, 2014)
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7 1.33 0.00 7 50
 
 
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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.