Nonlinear Analysis to Detect if Excellent Nursing Work Environments Have Highest Well-Being.

PURPOSE: To detect potentially nonlinear associations between nurses' work environment and nurse staffing on the one hand and nurse burnout on the other hand. DESIGN: A cross-sectional multicountry study for which data collection using a survey of 33,731 registered nurses in 12 European countries took place during 2009 to 2010. METHODS: A semiparametric latent variable model that describes both linear and potentially nonlinear associations between burnout (Maslach Burnout Inventory: emotional exhaustion, depersonalization, personal accomplishment) and work environment (Practice Environment Scale of the Nursing Work Index: managerial support for nursing, doctor-nurse collegial relations, promotion of care quality) and staffing (patient-to-nurse ratio). FINDINGS: Similar conclusions are reached from linear and nonlinear models estimating the association between work environment and burnout. For staffing, an increase in the patient-to-nurse ratio is associated with an increase in emotional exhaustion. At about 15 patients per nurse, no further increase in emotional exhaustion is seen. CONCLUSIONS: Absence of evidence for diminishing returns of improving work environments suggests that continuous improvement and achieving excellence in nurse work environments pays off strongly in terms of lower nurse-reported burnout rates. Nurse staffing policy would benefit from a larger number of studies that identify specific minimum as well as maximum thresholds at which inputs affect nurse and patient outcomes. CLINICAL RELEVANCE: Nurse burnout is omnipresent and has previously been shown to be related to worse patient outcomes. Additional increments in characteristics of excellent work environments, up to the highest possible standard, correspond to lower nurse burnout.

The residual-based predictiveness curve: A visual tool to assess the performance of prediction models.

It is agreed among biostatisticians that prediction models for binary outcomes should satisfy two essential criteria: first, a prediction model should have a high discriminatory power, implying that it is able to clearly separate cases from controls. Second, the model should be well calibrated, meaning that the predicted risks should closely agree with the relative frequencies observed in the data. The focus of this work is on the predictiveness curve, which has been proposed by Huang et al. (Biometrics 63, 2007) as a graphical tool to assess the aforementioned criteria. By conducting a detailed analysis of its properties, we review the role of the predictiveness curve in the performance assessment of biomedical prediction models. In particular, we demonstrate that marker comparisons should not be based solely on the predictiveness curve, as it is not possible to consistently visualize the added predictive value of a new marker by comparing the predictiveness curves obtained from competing models. Based on our analysis, we propose the "residual-based predictiveness curve" (RBP curve), which addresses the aforementioned issue and which extends the original method to settings where the evaluation of a prediction model on independent test data is of particular interest. Similar to the predictiveness curve, the RBP curve reflects both the calibration and the discriminatory power of a prediction model. In addition, the curve can be conveniently used to conduct valid performance checks and marker comparisons.

[Effects of the housing climate on the foot pad health of fattening turkeys of British United Turkeys 6 origin during the early rearing phase]. / Auswirkungen des Stallklimas auf die Fussballengesundheit von Mastputen der Herkunft B.U.T. 6 in der Aufzuchtphase.

The climate in the stables during the turkeys' first weeks of life is a crucial factor for a successful rearing and the following fattening period. The present study has examined the influence of climate parameters on the foot pad health status of 2681 fattened turkeys from twelve farms during the early rearing phase. In addition to wide-ranging collections of data concerning livestock husbandry and management an examination of the foot pads of 60 animals has been carried out respectively on day 3-5, as well as on day 22-35, shortly before relocation into another stable. For assessing the foot pads a scheme of five categories has been used (ranging from category 0 = no alteration to category 4 = deep lesion). Solely beak trimmed turkeys of the British United Turkeys (BUT) 6 strain, male and female, were examined. In twelve farms air temperature and humidity have been recorded continuously, ammonia and dust concentration were registered on each day of the examination. When assessing the foot pads, the first alterations could already be noted at the age of 3-5 days. On the second period of exzmination 55.6% of the turkeys showed category 2 or category 3. Examinations of the climate parameters showed strong differences concerning temperature, humidity and ammonia concentration among all farms. Using the Fisher's Exact Test, significant dependency of foot pad health on starting temperature (p < 0.001), on temperature measured one week before the second examination (p = 0.004), on humidity (p < 0.001), and on air ammonia concentration (p < 0.001) could be indicated.