Background Nurses’ burnout might affect their quality of life, productivity and nursing care services. Aim The aim of this systematic review was to systemically review the relationship between nurses’ burnout and quality of life and to introduce practical recommendations to reduce nurses’ BO and improve their QOL. Methods In April 2021, MeSH terms (("Nurses"[Mesh]) AND "Burnout, Professional"[Mesh]) AND "Quality of Life"[Majr] were used to search five electronic databases: CINAHL, PubMed, Medline, Psychology and Behavioral Sciences Collection and Google Scholar. Results The search produced 21 studies exploring nurses’ burnout and their quality of life within the last ten years (2009–2021). Most of these studies found significant relationships between the burnout dimension(s) and quality of life dimension(s) among the nurses. Conclusion Nurses have moderate to high levels of burnout and were negatively associated with poor quality of life. Interventional programs are needed to decrease nurses’ burnout and improve their quality of life.

Background To ensure accurate measurement of the health benefits of habitual physical activity in large sample epidemiological studies, physical activity questionnaires (PAQs) are the most feasible methods. Therefore, the purpose of this study was the validation and cultural adaptation to the Hungarian population of the International Physical Activity Questionnaire (IPAQ-HL). Methods A cross-sectional study among Hungarian healthy adults (age 21.375 ± 1.940 years, n = 120) was performed comparing measures of last 7 days IPAQ-HL self- administered questionnaire and obtained accelerometer (Actigraph GT3X) data for concurrent validity, reassessed by a random subsample ( n = 33) to measure reliability. Results Our results indicate acceptable criterion validity for total physical activity, moderate to vigorous physical activity ( R = 0.387, p < 0.001; R = 0.331 p < 0.001 respectively) and moderate physical activity ( R = 0.193, p = 0.034). The ICC scores revealed moderate to good correlations (ICC = 0.744–0.942, p < 0.001). Moderate Kaiser–Meyer–Olkin measure (0.531, p < 0.001) and good reproducibility for vigorous, moderate to vigorous and moderate activities was found for IPAQ-HL in the studied population. Nevertheless, like analogous self-reports in other languages, it overestimates the time spent on physical activity. Conclusions IPAQ-HL proved to be a reasonably valid measure for population prevalence epidemiological studies and is suggested for use to develop public health policy recommendations or to optimize public health interventions. However, the results on vigorous activity should be interpreted with caution, the questionnaire showed moderate validity for this particular intensity.

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Nuclear estrogen receptor (ER), progesterone receptor (PR) and Ki-67 protein positive tumor cell fractions are semiquantitatively assessed in breast cancer for prognostic and predictive purposes. These biomarkers are usually revealed using immunoperoxidase methods resulting in diverse signal intensity and frequent inhomogeneity in tumor cell nuclei, which are routinely scored and interpreted by a pathologist during conventional light-microscopic examination. In the last decade digital pathology-based whole slide scanning and image analysis algorithms have shown tremendous development to support pathologists in this diagnostic process, which can directly influence patient selection for targeted- and chemotherapy. We have developed an image analysis algorithm optimized for whole slide quantification of nuclear immunostaining signals of ER, PR, and Ki-67 proteins in breast cancers. In this study, we tested the consistency and reliability of this system both in a series of brightfield and DAPI stained fluorescent samples. Our method allows the separation of overlapping cells and signals, reliable detection of vesicular nuclei and background compensation, especially in FISH stained slides. Detection accuracy and the processing speeds were validated in routinely immunostained breast cancer samples of varying reaction intensities and image qualities. Our technique supported automated nuclear signal detection with excellent efficacy: Precision Rate/Positive Predictive Value was 90.23 ± 4.29%, while Recall Rate/Sensitivity was 88.23 ± 4.84%. These factors and average counting speed of our algorithm were compared with two other open source applications (QuPath and CellProfiler) and resulted in 6-7% higher Recall Rate, while 4- to 30-fold higher processing speed. In conclusion, our image analysis algorithm can reliably detect and count nuclear signals in digital whole slides or any selected large areas i.e. hot spots, thus can support pathologists in assessing clinically important nuclear biomarkers with less intra- and interlaboratory bias inherent of empirical scoring. © 2017 International Society for Advancement of Cytometry.