Why patients switch help from online to offline: An empirical investigation of emotions and effects of cognitions

People have different reactions when they encounter different levels of health threats. Individual cognitions towards the seriousness of health threat and emotions arise from health threats often motivate people to seek help online and offline. To examine the effects of cognitions and emotions on help seeking behaviors on different levels of health threats, we propose a research model based on protection motivation theory and cognition-emotion-behavior framework. Empirical data were collected through questionnaires and analyzed by Smart PLS. The results show that perceived susceptibility and perceived severity have positive significant influence on fear which leads on anxiety. Perceived health knowledge has negative influence on anxiety. Fear and anxiety can motivate individuals to seek help online and offline, especially in the high health threats condition. In addition, fear has significant influence on help seeking offline while anxiety has significant influence on help seeking online. Expectation confirmation has different effects on help seeking offline in different levels of health threats. This study extends PMT through the lens of cognition-emotion-behavior framework, and it expands research scope to help seeking behaviors

Extracting respiratory signals from thoracic cone beam CT projections

Patient respiratory signal associated with the cone beam CT (CBCT) projections is important for lung cancer radiotherapy. In contrast to monitoring an external surrogate of respiration, such signal can be extracted directly from the CBCT projections. In this paper, we propose a novel local principle component analysis (LPCA) method to extract the respiratory signal by distinguishing the respiration motion-induced content change from the gantry rotation-induced content change in the CBCT projections. The LPCA method is evaluated by comparing with three state-of-the-art projection-based methods, namely, the Amsterdam Shroud (AS) method, the intensity analysis (IA) method, and the Fourier-transform based phase analysis (FT-p) method. The clinical CBCT projection data of eight patients, acquired under various clinical scenarios, were used to investigate the performance of each method. We found that the proposed LPCA method has demonstrated the best overall performance for cases tested and thus is a promising technique for extracting respiratory signal. We also identified the applicability of each existing method.Comment: 21 pages, 11 figures, submitted to Phys. Med. Bio

A patient-specific lumped-parameter model of coronary circulation

A new lumped-parameter model for coronary hemodynamics is developed. This model is developed for the whole coronary network based on CT scans of a patient-specific geometry including the right coronary tree, which is absent in many previous mathematical models. The model adopts the structured tree model boundary conditions similar to the work of Olufsen et al., thus avoiding the necessity of invasive perfusion measurements. In addition, we also incorporated the effects of the head loss at the two inlets of the large coronary arteries for the first time. The head loss could explain the phenomenon of a sudden increase of the resistance at the inlet of coronary vessel. The estimated blood pressure and flow rate results from the model agree well with the clinical measurements. The computed impedances also match the experimental perfusion measurement. The effects of coronary arterial stenosis are considered and the fractional flow reserve and relative flow in the coronary vessels for a stenotic vessel computed in this model show good agreement with published experimental data. It is believed that the approach could be readily translated to clinical practice to facilitate real time clinical diagnosis