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Researchers’ Needs for Resource Discovery and Collaboration Tools: A Qualitative Investigation of Translational Scientists

Suresh K Bhavnani, Michael Warden, Kai Zheng, Mary Hill, Brian D Athey

J Med Internet Res 2012;14(3):e75

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How High-Risk Comorbidities Co-Occur in Readmitted Patients With Hip Fracture: Big Data Visual Analytical Approach

Suresh K Bhavnani, Bryant Dang, Rebekah Penton, Shyam Visweswaran, Kevin E Bassler, Tianlong Chen, Mukaila Raji, Rohit Divekar, Raed Zuhour, Amol Karmarkar, Yong-Fang Kuo, Kenneth J Ottenbacher

JMIR Med Inform 2020;8(10):e13567

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Computer-Controlled Virtual Humans in Patient-Facing Systems: Systematic Review and Meta-Analysis

There were more cross-sectional (k=15) [54,68,81,83,87,88,91,92,95] than longitudinal studies (k=11) [58,63,67,69,72,76,78,88]. Longitudinal studies ranged from 1 month to 6 months (see Multimedia Appendix 2).

Debaleena Chattopadhyay, Tengteng Ma, Hasti Sharifi, Pamela Martyn-Nemeth

J Med Internet Res 2020;22(7):e18839

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Text Messaging-Based Interventions for Smoking Cessation: A Systematic Review and Meta-Analysis

length, k (%)6 months or longer3 (15)3-5 months3 (15)Less than 3 months14 (70)Retention, k (%)Withdrawal/drop-outs reported20 (100)Attrition, cases lost to follow-up considered20 (100)Data collection, k (%)Anonymous1 (5)Collateral verification1 (5)Used objective

Lori A. J. Scott-Sheldon, Ryan C. Lantini, Ernestine G. Jennings, Herpreet Thind, Rochelle K. Rosen, Elena Salmoirago-Blotcher, Beth C. Bock

JMIR Mhealth Uhealth 2016;4(2):e49

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Novel Indicator to Ascertain the Status and Trend of COVID-19 Spread: Modeling Study

K’=−0.0263 ± 0.0006/d.

Takashi Nakano, Yoichi Ikeda

J Med Internet Res 2020;22(11):e20144

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Calibrating Wrist-Worn Accelerometers for Physical Activity Assessment in Preschoolers: Machine Learning Approaches

LPA, only the k-means LPA cut point resulted with sensitivity and specificity values greater than 50%.

Shiyu Li, Jeffrey T Howard, Erica T Sosa, Alberto Cordova, Deborah Parra-Medina, Zenong Yin

JMIR Form Res 2020;4(8):e16727

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Person-Generated Health Data in Simulated Rehabilitation Using Kinect for Stroke: Literature Review

Hence, the objective of this review is to answer the questions: To what extent do K-SRS enable PGHD? And to what effect?

Gerardo Luis Dimaguila, Kathleen Gray, Mark Merolli

JMIR Rehabil Assist Technol 2018;5(1):e11

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The Korean eHealth Literacy Scale (K-eHEALS): Reliability and Validity Testing in Younger Adults Recruited Online

Through the expert panel discussion, the translated instrument was adjusted and the complete K-eHEALS was produced. Then, back-translation of the K-eHEALS was done by an independent translator and was compared against the original eHEALS.

SeonYoon Chung, Bu Kyung Park, Eun-Shim Nahm

J Med Internet Res 2018;20(4):e138

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Using Passive Smartphone Sensing for Improved Risk Stratification of Patients With Depression and Diabetes: Cross-Sectional Observational Study

The dataset so obtained was divided into a training set (90%) and test set (10%), and a stratified K-fold cross-validation (CV) with K equal to 10 folds was performed on the training set for each of the 5 classifier methods (see Figure 2 for the modeling approach

Archana Sarda, Suresh Munuswamy, Shubhankar Sarda, Vinod Subramanian

JMIR Mhealth Uhealth 2019;7(1):e11041

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Psychometric Properties of the Korean Version of the PsyMate Scale Using a Smartphone App: Ecological Momentary Assessment Study

The HADS was assessed to compare the momentary negative affect and positive affect that were measured by the K-PsyMate scale, as described in a previous study [25].K-PsyMate Scale for Measuring Momentary MoodThe mood scale of the K-PsyMate was used for the

Yong Sook Yang, Gi Wook Ryu, Philippe A E G Delespaul, Mona Choi

JMIR Mhealth Uhealth 2020;8(7):e17926

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