4 results match your criteria: "An Affiliate of the City of Hope National Medical Center[Affiliation]"

The lack of preparedness for detecting and responding to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pathogen (i.e., COVID-19) has caused enormous harm to public health and the economy.

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Single subject, or 'N-of-1,' studies are receiving a great deal of attention from both theoretical and applied researchers. This is consistent with the growing acceptance of 'personalized' approaches to health care and the need to prove that personalized interventions tailored to an individual's likely unique physiological profile and other characteristics work as they should. In fact, the preferred way of referring to N-of-1 studies in contemporary settings is as 'personalized studies.

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Article Synopsis
  • The study addresses the growing need for mental health care, highlighting how digital apps can provide personalized support for issues like stress and depression.
  • The research specifically focuses on how users of the Stop, Breathe & Think (SBT) app transition through various emotional states while using guided meditations tailored to their needs.
  • Analysis of data from over 650,000 users revealed that users' starting emotional states significantly affect their emotional transitions after engaging with recommended mindfulness activities.
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Power and Design Issues in Crossover-Based N-Of-1 Clinical Trials with Fixed Data Collection Periods.

Healthcare (Basel)

July 2019

Quantitative Medicine and Systems Biology, The Translational Genomics Research Institute (TGen), an affiliate of the City of Hope National Medical Center, 445 North Fifth Street, Phoenix, AZ 85004, USA.

"N-of-1," or single subject, clinical trials seek to determine if an intervention strategy is more efficacious for an individual than an alternative based on an objective, empirical, and controlled study. The design of such trials is typically rooted in a simple crossover strategy with multiple intervention response evaluation periods. The effect of serial correlation between measurements, the number of evaluation periods, the use of washout periods, heteroscedasticity (i.

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