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JMIR is the leading peer-reviewed eHealth/mHealth journal (Impact Factor: 4.7),
ranked #1 in Medical Informatics, and #2 in Health Sciences/Health Services Research - Now publishing daily!


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Recent Articles

How Feedback Biases Give Ineffective Medical Treatments a Good Reputation
by Mícheál de Barra, Kimmo Eriksson, Pontus Strimling
(Published on 21 Aug 2014)
Background: Medical treatments with no direct effect (like homeopathy) or that cause harm (like bloodletting) are common across cultures and throughout history. How do such treatments spread and persist? Most medical treatments result in a range of outcomes: some people improve while others deteriorate. If the people who improve are more inclined to tell others about their experiences than the people who deteriorate, ineffective or even harmful treatments can maintain a good reputation. Objective: The intent of this study was to test the hypothesis that positive outcomes are overrepresented in online medical product reviews, to examine if this reputational distortion is large enough to bias people’s decisions, and to explore the implications of this bias for the cultural evolution...
 
 
How an Online Intervention to Prevent Excessive Gestational Weight Gain Is Used and by Whom: A Randomized Controlled Process Evaluation
by Margaret Mochon Demment, Meredith Leigh Graham, Christine Marie Olson
(Published on 20 Aug 2014)
Background: Online interventions have emerged as a popular strategy to promote healthy behaviors. Currently, there is little agreement about how to capture online intervention engagement. It is also uncertain who engages with weight-related online interventions and how engagement differs by demographic and weight characteristics. Objective: The objectives of this study were to (1) characterize how pregnant women engaged with features of an online intervention to prevent excessive gestational weight gain, (2) identify demographic and weight status subgroups of women within the sample, and (3) examine differences in use of intervention features across the demographic and weight status subgroups. Methods: A sample of racially and socioeconomically diverse pregnant women from a northeastern...
 
 

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