CONTEXT: Since its launch in 2001, Wikipedia has become the most popular general reference site on the Internet and a popular source of health care information. To evaluate the accuracy of this resource, the authors compared Wikipedia articles on the most costly medical conditions with standard, evidence-based, peer-reviewed sources. METHODS: The top 10 most costly conditions in terms of public and private expenditure in the United States were identified, and a Wikipedia article corresponding to each topic was chosen. In a blinded process, 2 randomly assigned investigators independently reviewed each article and identified all assertions (ie, implication or statement of fact) made in it. The reviewer then conducted a literature search to determine whether each assertion was supported by evidence. The assertions found by each reviewer were compared and analyzed to determine whether assertions made by Wikipedia for these conditions were supported by peer-reviewed sources. RESULTS: For commonly identified assertions, there was statistically significant discordance between 9 of the 10 selected Wikipedia articles (coronary artery disease, lung cancer, major depressive disorder, osteoarthritis, chronic obstructive pulmonary disease, hypertension, diabetes mellitus, back pain, and hyperlipidemia) and their corresponding peer-reviewed sources (P<.05) and for all assertions made by Wikipedia for these medical conditions (P<.05 for all 9). CONCLUSION: Most Wikipedia articles representing the 10 most costly medical conditions in the United States contain many errors when checked against standard peer-reviewed sources. Caution should be used when using Wikipedia to answer questions regarding patient care.
CONTEXT: Since its launch in 2001, Wikipedia has become the most popular general reference site on the Internet and a popular source of health care information. To evaluate the accuracy of this resource, the authors compared Wikipedia articles on the most costly medical conditions with standard, evidence-based, peer-reviewed sources. METHODS: The top 10 most costly conditions in terms of public and private expenditure in the United States were identified, and a Wikipedia article corresponding to each topic was chosen. In a blinded process, 2 randomly assigned investigators independently reviewed each article and identified all assertions (ie, implication or statement of fact) made in it. The reviewer then conducted a literature search to determine whether each assertion was supported by evidence. The assertions found by each reviewer were compared and analyzed to determine whether assertions made by Wikipedia for these conditions were supported by peer-reviewed sources. RESULTS: For commonly identified assertions, there was statistically significant discordance between 9 of the 10 selected Wikipedia articles (coronary artery disease, lung cancer, major depressive disorder, osteoarthritis, chronic obstructive pulmonary disease, hypertension, diabetes mellitus, back pain, and hyperlipidemia) and their corresponding peer-reviewed sources (P<.05) and for all assertions made by Wikipedia for these medical conditions (P<.05 for all 9). CONCLUSION: Most Wikipedia articles representing the 10 most costly medical conditions in the United States contain many errors when checked against standard peer-reviewed sources. Caution should be used when using Wikipedia to answer questions regarding patient care.
Authors: Daniel A London; Steven M Andelman; Anthony V Christiano; Joung Heon Kim; Michael R Hausman; Jaehon M Kim Journal: Surg Radiol Anat Date: 2019-07-01 Impact factor: 1.246
Authors: Jonathan P Tennant; Jonathan M Dugan; Daniel Graziotin; Damien C Jacques; François Waldner; Daniel Mietchen; Yehia Elkhatib; Lauren B Collister; Christina K Pikas; Tom Crick; Paola Masuzzo; Anthony Caravaggi; Devin R Berg; Kyle E Niemeyer; Tony Ross-Hellauer; Sara Mannheimer; Lillian Rigling; Daniel S Katz; Bastian Greshake Tzovaras; Josmel Pacheco-Mendoza; Nazeefa Fatima; Marta Poblet; Marios Isaakidis; Dasapta Erwin Irawan; Sébastien Renaut; Christopher R Madan; Lisa Matthias; Jesper Nørgaard Kjær; Daniel Paul O'Donnell; Cameron Neylon; Sarah Kearns; Manojkumar Selvaraju; Julien Colomb Journal: F1000Res Date: 2017-07-20
Authors: Jörn Conell; Rita Bauer; Tasha Glenn; Martin Alda; Raffaella Ardau; Bernhard T Baune; Michael Berk; Yuly Bersudsky; Amy Bilderbeck; Alberto Bocchetta; Letizia Bossini; Angela Marianne Paredes Castro; Eric Yat Wo Cheung; Caterina Chillotti; Sabine Choppin; Maria Del Zompo; Rodrigo Dias; Seetal Dodd; Anne Duffy; Bruno Etain; Andrea Fagiolini; Julie Garnham; John Geddes; Jonas Gildebro; Ana Gonzalez-Pinto; Guy M Goodwin; Paul Grof; Hirohiko Harima; Stefanie Hassel; Chantal Henry; Diego Hidalgo-Mazzei; Vaisnvy Kapur; Girish Kunigiri; Beny Lafer; Chun Lam; Erik Roj Larsen; Ute Lewitzka; Rasmus Licht; Anne Hvenegaard Lund; Blazej Misiak; Patryk Piotrowski; Scott Monteith; Rodrigo Munoz; Takako Nakanotani; René E Nielsen; Claire O'Donovan; Yasushi Okamura; Yamima Osher; Andreas Reif; Philipp Ritter; Janusz K Rybakowski; Kemal Sagduyu; Brett Sawchuk; Elon Schwartz; Ângela Miranda Scippa; Claire Slaney; Ahmad Hatim Sulaiman; Kirsi Suominen; Aleksandra Suwalska; Peter Tam; Yoshitaka Tatebayashi; Leonardo Tondo; Eduard Vieta; Maj Vinberg; Biju Viswanath; Julia Volkert; Mark Zetin; Iñaki Zorrilla; Peter C Whybrow; Michael Bauer Journal: Int J Bipolar Disord Date: 2016-08-24
Authors: Clive E Adams; Alan A Montgomery; Tony Aburrow; Sophie Bloomfield; Paul M Briley; Ebun Carew; Suravi Chatterjee-Woolman; Ghalia Feddah; Johannes Friedel; Josh Gibbard; Euan Haynes; Mohsin Hussein; Mahesh Jayaram; Samuel Naylor; Luke Perry; Lena Schmidt; Umer Siddique; Ayla Serena Tabaksert; Douglas Taylor; Aarti Velani; Douglas White; Jun Xia Journal: BMJ Open Date: 2020-02-20 Impact factor: 2.692