We obtain an exact Kerr like black hole solution by solving the corresponding gravitational field equations in Einstein-bumblebee gravity model where Lorentz symmetry is spontaneously broken once a vector field acquires a vacuum expectation value. Results are presented for the purely radial Lorentz symmetry breaking. In order to study the effects of this breaking, we consider the black hole shadow and find that the radial of the unstable spherical orbit on the equatorial plane rc decreases with the Lorentz breaking constant ℓ > 0, and increases with ℓ < 0.
Objectives
With this study, we aimed to develop a mobile technology (mHealth) intervention to improve medication adherence among patients with coronary heart disease (CHD).
Methods
The study was conducted in two phases with CHD patients from a Cardiology Department of a hospital located in China. Each phase was independent from the other. Phase 1 tested the integration of the two apps — “WeChat” and “BB Reminder” — as an mHealth intervention. All participants received the same educational materials via WeChat every two days. Participants in the experimental group received a reminder from BB Reminder for every dose of their medications. The duration of Phase 1 was 30 days for each participant. Phase 2 refined the intervention, in which educational materials were sent every five days rather than every two days, and medication-taking reminders were sent daily rather than every dose.
Results
In Phase 1, an mHealth intervention was developed by integrating two mobile apps. In Phase 2, medication adherence increased at 30-day follow-up in both groups compared to baseline. At the 30-day follow-up, the mean of the decrease in medication non-adherence score in the experimental group (
M
= −1.35,
SD
= 2.18,
n
= 36) was more than the decrease in control group (
M
= −0.69, S
D
= 1.58,
n
= 36), which means the medication adherence improved more in the experimental group.
Conclusion
The feasibility of using mHealth to remind CHD patients to take their medications is high.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.