Top Articles (Article-Level Metrics)

 
 
Rank Article Tweets Tweets per MonthA
Tweets Influence FactorB
Twimpact Factor (tw7)C Twindex7D
 
191
Online Mental Health Resources in Rural Australia: Clinician Perceptions of Acceptability
Craig Sinclair, Kristi Holloway, Geoffrey Riley, Kirsten Auret
J Med Internet Res 2013;15(9):e193
(Sep 5, 2013)
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5 0.83 0.00 8 55
 
 
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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4 0.67 0.00 8 30
 
 
193
Using Metrics to Describe the Participative Stances of Members Within Discussion Forums
Ray Jones, Siobhan Sharkey, Janet Smithson, Tamsin Ford, Tobit Emmens, Elaine Hewis, Bryony Sheaves, Christabel Owens
J Med Internet Res 2011;13(1):e3
(Jan 10, 2011)
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1 0.17 0.00 8 75
 
 
194
Internet and Mobile Technology Use Among Urban African American Parents: Survey Study of a Clinical Population
Stephanie J Mitchell, Leandra Godoy, Kanya Shabazz, Ivor B Horn
J Med Internet Res 2014;16(1):e9
(Jan 13, 2014)
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11 3.59 0.00 7 70
 
 
195
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 5.54 0.00 7 45
 
 
196
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 9.96 0.00 7 80
 
 
197
Using Google AdWords for International Multilingual Recruitment to Health Research Websites
Margaret S Gross, Nancy H Liu, Omar Contreras, Ricardo F Muñoz, Yan Leykin
J Med Internet Res 2014;16(1):e18
(Jan 20, 2014)
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9 3.17 0.00 7 60
 
 
198
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 15.50 0.00 7 60
 
 
199
Comparison of US Panel Vendors for Online Surveys
Benjamin M Craig, Ron D Hays, A Simon Pickard, David Cella, Dennis A Revicki, Bryce B Reeve
J Med Internet Res 2013;15(11):e260
(Nov 29, 2013)
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8 1.77 2.00 7 45
 
 
200
Text Messaging Data Collection for Monitoring an Infant Feeding Intervention Program in Rural China: Feasibility Study
Ye Li, Wei Wang, Michelle Helena van Velthoven, Li Chen, Josip Car, Igor Rudan, Yanfeng Zhang, Qiong Wu, Xiaozhen Du, Robert W Scherpbier
J Med Internet Res 2013;15(12):e269
(Dec 4, 2013)
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8 1.84 24.00 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.