Associations between Demographic Characteristics, Perceived Threat, Perceived Stress, Coping Responses and Adherence to COVID-19 Prevention Measures among Healthcare Students in China: A Cross-Sectional Survey with Implications for the Control of COVID-19

ObjectivesTo investigate the associations between demographic characteristics, perceived threat, perceived stress, coping responses and adherence to COVID-19 prevention measures in Chinese Healthcare students. DesignA cross-sectional survey collecting data in Hong Kong and Fujian Province of China. Self-administered questionnaires were collected via online platform in April 2020. ParticipantsA convenience and snowball sample of 2706 students aged 18 years or older and studying a healthcare programme in Hong Kong or Fujian. SettingStudents were recruited in tertiary education institutions/universities in Hong Kong and Putian (a prefecture-level city in eastern Fujian province). The institutions offered various healthcare programmes in degree or sub-degree levels. Main outcome measuresCompliances to social distancing and personal hygiene measures were assessed by 10-item Social Distancing Scale and 5-item Personal Hygiene Scale respectively. Path analysis was performed to identify factors associated with the compliance outcomes. ResultsThe participants reported high compliances to both social distancing and personal hygiene measures. Confidence to manage the current situation, wishful thinking and empathetic responding directly predicted compliance to social distancing ({beta}=-0.31, p<0.001; {beta}=0.35, p=0.015; {beta}=0.33, p<0.001 respectively) and personal hygiene measures ({beta}==-0.16, p<0.001; {beta}=0.21, p<0.001; {beta}=0.16, p<0.001 respectively). Gender, geographical location, and clinical experience were the only three demographic variables having direct and/or indirect effects on social distancing and personal hygiene measures. The final model constructed demonstrated a very good fit to the data (Chi-square X2=27.27, df=17, P=0.044; X2/df=1.61; GFI=0.998, CFI=0.997, TLI=0.992, RMSEA=0.015). ConclusionsThe predictive model constructed in this study is the first one to explore factors associating with the compliance to infection control measures in healthcare students amid the COVID-19 outbreak. The findings suggest that students who are male, habituate in Hong Kong, have more clinical experience and weak confidence to manage the threat tend to have lower compliance to social distancing and personal hygiene measures. Wishful thinking, contrasting to previous studies, was first found to positively associate with adherence to COVID-19 control measures.

MITK-ToF--range data within MITK.

PURPOSE: The time-of-flight (ToF) technique is an emerging technique for rapidly acquiring distance information and is becoming increasingly popular for intra-operative surface acquisition. Using the ToF technique as an intra-operative imaging modality requires seamless integration into the clinical workflow. We thus aim to integrate ToF support in an existing framework for medical image processing. METHODS: MITK-ToF was implemented as an extension of the open-source C++ Medical Imaging Interaction Toolkit (MITK) and provides the basic functionality needed for rapid prototyping and development of image-guided therapy (IGT) applications that utilize range data for intra-operative surface acquisition. This framework was designed with a module-based architecture separating the hardware-dependent image acquisition task from the processing of the range data. RESULTS: The first version of MITK-ToF has been released as an open-source toolkit and supports several ToF cameras and basic processing algorithms. The toolkit, a sample application, and a tutorial are available from http://mitk.org. CONCLUSIONS: With the increased popularity of time-of-flight cameras for intra-operative surface acquisition, integration of range data supports into medical image processing toolkits such as MITK is a necessary step. Handling acquisition of range data from different cameras and processing of the data requires the establishment and use of software design principles that emphasize flexibility, extendibility, robustness, performance, and portability. The open-source toolkit MITK-ToF satisfies these requirements for the image-guided therapy community and was already used in several research projects.

Computer-assisted trajectory planning for percutaneous needle insertions.

PURPOSE: Computed tomography (CT) guided minimally invasive interventions such as biopsies or ablation therapies often involve insertion of a needle-shaped instrument into the target organ (e.g., the liver). Today, these interventions still require manual planning of a suitable trajectory to the target (e.g., the tumor) based on the slice data provided by the imaging modality. However, taking into account the critical structures and other parameters crucial to the success of the intervention--such as instrument shape and penetration angle--is challenging and requires a lot of experience. METHODS: To overcome these problems, we present a system for the automatic or semiautomatic planning of optimal trajectories to a target, based on 3D reconstructions of all relevant structures. The system determines possible insertion zones based on so-called hard constraints and rates the quality of these zones by so-called soft constraints. The concept of pareto optimality is utilized to allow for a weight-independent proposal of insertion trajectories. In order to demonstrate the benefits of our method, automatic trajectory planning was applied retrospectively to n = 10 data sets from interventions in which complications occurred. RESULTS: The efficient (graphics processing unit-based) implementation of the constraints results in a mean overall planning time of about 9 s. The examined trajectories, originally chosen by the physician, have been rated as follows: in six cases, the insertion point was labeled invalid by the planning system. For two cases, the system would have proposed points with a better rating according to the soft constraints. For the remaining two cases the system would have indicated poor rating with respect to one of the soft constraints. The paths proposed by our system were rated feasible and qualitatively good by experienced interventional radiologists. CONCLUSIONS: The proposed computer-assisted trajectory planning system is able to detect unsafe and propose safe insertion trajectories and may especially be helpful for interventional radiologist at the beginning or during their interventional training.