Search Articles

View query in Help articles search

Search Results (1 to 10 of 326 Results)

Download search results: END BibTex RIS


Assessing Diabetes-Relevant Data Provided by Undergraduate and Crowdsourced Web-Based Survey Participants for Honesty and Accuracy

Assessing Diabetes-Relevant Data Provided by Undergraduate and Crowdsourced Web-Based Survey Participants for Honesty and Accuracy

Clifford and Jerit provided even more striking data that showed that student samples self-reported cheating at rates between 24-41%, while comparable MTurk self-reports hovered between 4-7% [29].

Mary Turner DePalma, Michael C Rizzotti, Matthew Branneman

JMIR Diabetes 2017;2(2):e11

Asynchronous Distance Learning of the National Institutes of Health Stroke Scale During the COVID-19 Pandemic (E-Learning vs Video): Randomized Controlled Trial

Asynchronous Distance Learning of the National Institutes of Health Stroke Scale During the COVID-19 Pandemic (E-Learning vs Video): Randomized Controlled Trial

Asynchronous distance learning using these methods has yielded mixed results, probably due to differences in the quality of the content and the mode of delivery [21].Since the release of Patrick Lyden’s didactic video in 1994 [22], the development of NIHSS

Mélanie Suppan, Loric Stuby, Emmanuel Carrera, Philippe Cottet, Avinash Koka, Frédéric Assal, Georges Louis Savoldelli, Laurent Suppan

J Med Internet Res 2021;23(1):e23594

Effectiveness of Text Message Interventions for Weight Management in Adolescents: Systematic Review

Effectiveness of Text Message Interventions for Weight Management in Adolescents: Systematic Review

values (US reference data)Mameli et al, 2018, Italy [39]BMI z-scores based on age- and sex-specific reference values (Italian reference data)Nguyen et al, 2012, Australia [40,46]BMI z-scores based on age- and sex-specific reference values (US reference data)Patrick

Stephanie Ruth Partridge, Rebecca Raeside, Anna Singleton, Karice Hyun, Julie Redfern

JMIR Mhealth Uhealth 2020;8(5):e15849

Development of a Consumer Health Vocabulary by Mining Health Forum Texts Based on Word Embedding: Semiautomatic Approach

Development of a Consumer Health Vocabulary by Mining Health Forum Texts Based on Word Embedding: Semiautomatic Approach

In 2001, Patrick expanded UMLS, the Eurodicautom of the European Commission’s Translation Service, and the European Commission Glossary of popular and technical medical terms, by adding words from the Dictionary of American Regional English, but only focused

Gen Gu, Xingting Zhang, Xingeng Zhu, Zhe Jian, Ken Chen, Dong Wen, Li Gao, Shaodian Zhang, Fei Wang, Handong Ma, Jianbo Lei

JMIR Med Inform 2019;7(2):e12704

Efficacy and Effectiveness of Mobile Health Technologies for Facilitating Physical Activity in Adolescents: Scoping Review

Efficacy and Effectiveness of Mobile Health Technologies for Facilitating Physical Activity in Adolescents: Scoping Review

15Quasi-experimental; 8 weeks; Intervention and controlSchool (recruitment, measures); Home (implementation)Mendoza et al (2017) [30], USA5916.6 (1.5)RCT; 10 weeks; Intervention and controlSurvivor database and clinic (recruitment); Home (implementation and some measures)Patrick

Alexandra M Lee, Sarah Chavez, Jiang Bian, Lindsay A Thompson, Matthew J Gurka, Victoria G Williamson, François Modave

JMIR Mhealth Uhealth 2019;7(2):e11847