No abstract

Gliomas are notoriously aggressive, malignant brain tumors that have variable response to treatment. These patients often have poor prognosis, informed primarily by histopathology. Mathematical neuro-oncology (MNO) is a young and burgeoning field that leverages mathematical models to predict and quantify response to therapies. These mathematical models can form the basis of modern “precision medicine” approaches to tailor therapy in a patient-specific manner. Patient-specific models (PSMs) can be used to overcome imaging limitations, improve prognostic predictions, stratify patients, and assess treatment response in silico. The information gleaned from such models can aid in the construction and efficacy of clinical trials and treatment protocols, accelerating the pace of clinical research in the war on cancer. This review focuses on the growing translation of PSM to clinical neuro-oncology. It will also provide a forward-looking view on a new era of patient-specific MNO.

The shortage of healthcare workers is a growing problem across the globe. Nurses and physicians, in particular, are vulnerable as a result of the COVID-19 pandemic. Understanding why they might leave is imperative for improving retention. This systematic review explores both the prevalence of nurses and physicians who are intent on leaving their position at hospitals in European countries and the main determinants influencing job retention among nurses and physicians of their respective position in a hospital setting in both European and non-European countries. A comprehensive search was fulfilled within 3 electronic databases on June 3rd 2021. In total 345 articles met the inclusion criteria. The determinants were categorized into 6 themes: personal characteristics, job demands, employment services, working conditions, work relationships, and organizational culture. The main determinants for job retention were job satisfaction, career development and work-life balance. European and non-European countries showed similarities and differences in determinants influencing retention. Identifying these factors supports the development of multifactorial interventions, which can aid the formulation of medical strategies and help to maximize retention.

The aim of this study was to investigate the consensus of skin care advice given by nurses during radiotherapy. Sixty-seven nurses, identified through nine Belgian radiotherapy departments, responded to a questionnaire survey consisting of 58 items regarding prevention and management of erythema, dry desquamation and moist desquamation. Consensus for a given advice was categorized as small if less than 50% of the nurses gave the same answer, as moderate if between 50% and 75% and as large when more than 75%. Overall, 33% of the items showed small consensus, 29% showed moderate consensus and 38% showed large consensus. The highest consensus was seen for advice in cases of moist and dry desquamation. There was less agreement in the case of erythema and it decreased further for preventive advice. Some skin care techniques that were frequently used by the nurses cannot be supported by the literature. Also, some techniques recommended by the literature are not frequently used. Further, few differences (P < 0.05) between nurses working in a university hospital and the ones working in a non-university hospital were found in terms of advice given to patients. To increase consensus on skin care issues more conclusive research is needed. Of equal importance is the translation of existing research results into daily clinical practice.

IntroductionBurnout is a growing problem among young researchers, affecting individuals, organizations and society. Our study aims to identify burnout profiles and highlight the corresponding job demands and resources, resulting in recommendations to reduce burnout risk in the academic context.MethodsThis cross-sectional study collected data from young researchers (n = 1,123) at five Flemish universities through an online survey measuring burnout risk, work engagement, sleeping behavior, and the most prominent job demands (e.g., publication pressure) and resources (e.g., social support). We conducted Latent Profile Analysis (LPA) to identify burnout profiles in young researchers and subsequently compared these groups on job demands and resources patterns.ResultsFive burnout profiles were identified: (1) High Burnout Risk (9.3%), (2) Cynical (30.1%), (3) Overextended (2.3%), (4) Low Burnout Risk (34.8%), and (5) No Burnout Risk (23.6%). Each burnout profile was associated with a different pattern of job demands and resources. For instance, high levels of meaningfulness (OR = −1.96) decreased the odds to being classified in the Cynical profile.ConclusionOur findings show that the Cynical profile corresponds to a relatively high number of young researchers, which may imply that they are particularly vulnerable to the cynicism dimension of burnout. Additionally, work-life interference and perceived publication pressure seemed the most significant predictors of burnout risk, while meaningfulness, social support from supervisor and learning opportunities played an important protective role.