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A Novel Score for mHealth Apps to Predict and Prevent Mortality: Further Validation and Adaptation to the US Population Using the US National Health and Nutrition Examination Survey Data Set

A Novel Score for mHealth Apps to Predict and Prevent Mortality: Further Validation and Adaptation to the US Population Using the US National Health and Nutrition Examination Survey Data Set

Sensitivity analysis on all-cause mortality for the marginal effect of the reaction time variable using NHANESa III (N=1440).b a NHANES: National Health and Nutrition Examination Survey. b All models included a dummy variable for the survey rounds. Survey weights were included in all analyses. The C-Score was calculated using five out of seven covariates: waist to height ratio, self-rated health, resting heart rate, smoking, and reaction time.

Shatha Elnakib, Andres I Vecino-Ortiz, Dustin G Gibson, Smisha Agarwal, Antonio J Trujillo, Yifan Zhu, Alain B Labrique

J Med Internet Res 2022;24(6):e36787

Feasibility of a Mobile Health Tool for Mothers to Identify Neonatal Illness in Rural Uganda: Acceptability Study

Feasibility of a Mobile Health Tool for Mothers to Identify Neonatal Illness in Rural Uganda: Acceptability Study

The following 4 screens ask her to indicate the presence of the 4 qualitative danger signs in her infant: lethargy (Figure 2, B), chest indrawing (Figure 2, C), convulsions (Figure 2, D), and difficulty breastfeeding (Figure 2, E) by displaying 2 Graphic Interchange Format (GIF) images, one showing a newborn exhibiting the danger sign and one showing a healthy infant. The mother is asked to select the picture that best represents her newborn.

Shababa B Matin, Allison Wallingford, Shicheng Xu, Natalie Ng, Anthony Ho, Madison Vanosdoll, Peter Waiswa, Alain B Labrique, Soumyadipta Acharya

JMIR Mhealth Uhealth 2020;8(2):e16426