Parental concern about childhood fever and consequent use of antipyretics is increasing. Little is known about childhood fever management among Arab parents. No scales to measure parents’ fever management practices in Palestine are available. The aim of this study was to validate the Arabic version of the Parent Fever Management Scale (PFMS) using a sample of parents in Palestine. A standard “forward–backward” procedure was used to translate PFMS into Arabic language. It was then validated on a convenience sample of 402 parents between July and October 2012. Descriptive statistics were used, and instrument reliability was assessed for internal consistency using Cronbach’s alpha coefficient. Validity was confirmed using convergent and known group validation. Applying the recommended scoring method, the median (interquartile range) score of the PFMS was 26 (23–30). Acceptable internal consistency was found (Cronbach’s alpha = 0.733) and the test–retest reliability value was 0.92 (P < 0.001). The Chi squared (χ 2) test showed a significant relationship between PFMS groups and frequent daily administration of antipyretic groups (χ 2 = 52.86; P < 0.001). The PFMS sensitivity and specificity were 77.67 and 57.75 %, respectively. The positive and negative predictive values were 67.89 and 32.11 %, respectively. The Arabic version of the PFMS is a reliable and valid measure and can be used as a useful tool for health professionals to identify parents’ fever management practices. The Arabic version of the PFMS can be used to reduce unnecessary parental practices in fever management for a febrile child.
In this paper a variety of shrinkage methods for estimating unknown population parameters has been considered. Aprior distribution for the parameters around their natural origins has been postulated and the ordinary Bayes estimators are used in place of natural origins in the ordinary shrinkage estimators to obtain Bayesian shrinkage estimators. The results are applied to the problem of estimating the location and scale parameters and the reliability function of the two-parameter exponential distribution. Simulation experiments are used to study the performances of these estimators.
In this paper, we consider two types of failure data namely grouped and non-grouped, which can be motivated from a linear mixed degradation model. We propose a Bayesian approach to estimate the parameters of the time-to-failure distribution and its percentiles. A simulation study conducted to study the performance of the proposed method showed that in terms of the mean squares error and the length of the bootstrap confidence intervals, the behavior of the proposed method is satisfactory. Also, it showed that the Bayesian approach with non-grouped data is better than the Bayesian approach with a grouped data. Application to a real data set is given.