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Assessing the Credibility and Authenticity of Social Media Content for Applications in Health Communication: Scoping Review

citation]Population groupKey significant resultsNumber of likesBorah and Xiao (2018) [47]StudentsIn the 2 studies conducted, the number of likes did not affect source credibility overall when looking at Facebook posts (study 1: P=.93; study 2: P=.09)Phua and Ahn

Eva L Jenkins, Jasmina Ilicic, Amy M Barklamb, Tracy A McCaffrey

J Med Internet Res 2020;22(7):e17296

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A Good Practice–Compliant Clinical Trial Imaging Management System for Multicenter Clinical Trials: Development and Validation Study

Youngbin Shin, Kyung Won Kim, Amy Junghyun Lee, Yu Sub Sung, Suah Ahn, Ja Hwan Koo, Chang Gyu Choi, Yousun Ko, Ho Sung Kim, Seong Ho Park

JMIR Med Inform 2019;7(3):e14310

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Medical Correctness and User Friendliness of Available Apps for Cardiopulmonary Resuscitation: Systematic Search Combined With Guideline Adherence and Usability Evaluation

Ahn et al described that the total number of downloads for CPR training apps is about several hundred thousand [22]. However, this field is getting increasingly complex and unmanageable [23].

Bibiana Metelmann, Camilla Metelmann, Louisa Schuffert, Klaus Hahnenkamp, Peter Brinkrolf

JMIR Mhealth Uhealth 2018;6(11):e190

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Association of Socioeconomic Changes due to the COVID-19 Pandemic With Health Outcomes in Patients With Skin Diseases: Cross-Sectional Survey Study

patient-reported outcomes of skin diseases (N=506).Exposure groupPerceived stress(VASa ≥7)Depression(PHQ-9b ≥8)Anxiety(GAD-7c ≥8)Impaired quality of life(DLQId ≥10)aORe,f95% CIP valueaOR95% CIP valueaOR95% CIP valueaOR95% CIP valueIsolationUnaffectedRefgN/AhN

Yeye Guo, Minxue Shen, Xu Zhang, Yi Xiao, Shuang Zhao, Mingzhu Yin, Wenbo Bu, Yan Wang, Xiang Chen, Juan Su

J Med Internet Res 2020;22(9):e22288

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The Effect of Robot Attentional Behaviors on User Perceptions and Behaviors in a Simulated Health Care Interaction: Randomized Controlled Trial

Deborah L Johanson, Ho Seok Ahn, Bruce A MacDonald, Byeong Kyu Ahn, JongYoon Lim, Euijun Hwang, Craig J Sutherland, Elizabeth Broadbent

J Med Internet Res 2019;21(10):e13667

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Correction: The Effect of Robot Attentional Behaviors on User Perceptions and Behaviors in a Simulated Health Care Interaction: Randomized Controlled Trial

Deborah L Johanson, Ho Seok Ahn, Bruce A MacDonald, Byeong Kyu Ahn, JongYoon Lim, Euijun Hwang, Craig J Sutherland, Elizabeth Broadbent

J Med Internet Res 2020;22(3):e18362

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Wearability Testing of Ambulatory Vital Sign Monitoring Devices: Prospective Observational Cohort Study

measurementsSpO2a, PRb, RRc, perfusion indexSpO2, PR, stepsSpO2, PRSpO2, PR, perfusion indexSpO2, PRbHRd, RR, ECGeHR, RR, ECG, body positionParticipant-identified problems (n)fDevice size203100160Disrupted ADLsg8656000Skin irritation0210233Finger probe uncomfortable6058N/AhN

Carlos Areia, Louise Young, Sarah Vollam, Jody Ede, Mauro Santos, Lionel Tarassenko, Peter Watkinson

JMIR Mhealth Uhealth 2020;8(12):e20214

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Explanatory Model of Dry Eye Disease Using Health and Nutrition Examinations: Machine Learning and Network-Based Factor Analysis From a National Survey

In contrast, omega-3 intake (node 13) and other ocular surgeries (node 6) were independent nodes with low centrality.In the previous study with KNHANES 2010-2011 by Ahn et al [3], 50- to 59-year-old and 60- to 69-year-old groups are presented as risk factors

Sang Min Nam, Thomas A Peterson, Atul J Butte, Kyoung Yul Seo, Hyun Wook Han

JMIR Med Inform 2020;8(2):e16153

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Application of Mobile Health Technologies Aimed at Salt Reduction: Systematic Review

not.StudyShort message serviceApp-basedOthers (eg, game device)Web-basedIn-personEyles et al [36]✓✓———Golshahi et al [39]✓————Yu et al [40]✓————Chen et al [41]✓———✓Huang [45]✓——✓—Nundy et al [46]✓————Zhang et al [37]—✓———Ipjian and Johnston [38]—✓———Lee et al [42]—✓———Ahn

Shahmir H Ali, Rong Luo, Yuan Li, Xiangjun Liu, Chengyao Tang, Puhong Zhang

JMIR Mhealth Uhealth 2019;7(4):e13250

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Psychometric Validation and Cultural Adaptation of the Simplified Chinese eHealth Literacy Scale: Cross-Sectional Study

0.500.8538.969 (18).00372.9527.05eHEALS 54.52−1.87−1.17−0.330.8932.962 (19).0570.7329.27eHEALS 63.83−1.89−1.24−0.310.9627.916 (20).1169.6730.33eHEALS 73.24−1.80−1.26−0.170.9541.64 (24).0166.5833.42eHEALS 82.63−1.80−1.20−0.061.0473.951 (25)<.00164.0135.99OverallN/AhN

Richard Huan Xu, Lingming Zhou, Sabrina Yujun Lu, Eliza Laiyi Wong, Jinghui Chang, Dong Wang

J Med Internet Res 2020;22(12):e18613

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