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A Scalable Risk-Scoring System Based on Consumer-Grade Wearables for Inpatients With COVID-19: Statistical Analysis and Model Development

A Scalable Risk-Scoring System Based on Consumer-Grade Wearables for Inpatients With COVID-19: Statistical Analysis and Model Development

In this paper, we develop a risk score for inpatients with COVID-19 in general wards based on scalable consumer-grade wearables (see Figure 1 for our overview). The consumer-grade wearables are used to monitor physiological measurements of patients: HR, heart rate variability (HRV), and RF. Based on these measurements, our risk score assesses the risk of different patient outcomes, defined as the probability of hospital discharge and ICU admission. Monitoring and risk scoring.

Simon Föll, Adrian Lison, Martin Maritsch, Karsten Klingberg, Vera Lehmann, Thomas Züger, David Srivastava, Sabrina Jegerlehner, Stefan Feuerriegel, Elgar Fleisch, Aristomenis Exadaktylos, Felix Wortmann

JMIR Form Res 2022;6(6):e35717

Web-Based Single Session Intervention for Perceived Control Over Anxiety During COVID-19: Randomized Controlled Trial

Web-Based Single Session Intervention for Perceived Control Over Anxiety During COVID-19: Randomized Controlled Trial

Identifying an intervention to facilitate independent coping with anxiety—ideally, one that is brief and easily scalable—could help mitigate negative effects of increasing anxiety nationwide. Perceived control, or one’s subjectively felt ability to control one’s environment and inner experiences, prospectively predicts lower distress during and following numerous uncontrollable stressors, from experiencing sexual assault [12] to recovering from breast cancer surgery [13] and a heart attack [14].

Michael Mullarkey, Mallory Dobias, Jenna Sung, Isaac Ahuvia, Jason Shumake, Christopher Beevers, Jessica Schleider

JMIR Ment Health 2022;9(4):e33473

24-Month Outcomes of Primary Care Web-Based Depression Prevention Intervention in Adolescents: Randomized Clinical Trial

24-Month Outcomes of Primary Care Web-Based Depression Prevention Intervention in Adolescents: Randomized Clinical Trial

To evaluate the efficacy of CATCH-IT in a scalable setting, we used a hybrid type 1 efficacy-implementation design in which we tested the efficacy of the clinical intervention while simultaneously collecting information for large-scale implementation [19]. Focus groups tested the prototype of the system for usability and accessibility in urban minority adolescents.

Benjamin W Van Voorhees, Tracy R G Gladstone, Kunmi Sobowale, C Hendricks Brown, David A Aaby, Daniela A Terrizzi, Jason Canel, Eumene Ching, Anita D Berry, James Cantorna, Milton Eder, William Beardslee, Marian Fitzgibbon, Monika Marko-Holguin, Linda Schiffer, Miae Lee, Sarah A de Forest, Emily E Sykes, Jennifer H Suor, Theodore J Crawford, Katie L Burkhouse, Brady C Goodwin, Carl Bell

J Med Internet Res 2020;22(10):e16802