Exploring parents' memories of their child's death related sensory experiences as a dimension of grieving

Little is known about how dying children and their parents experience death. Dying children have reported death related sensory experiences (DRSEs), defined as seeing or hearing someone or something not visible or audible to others, associated with dying. Although parents report that they and the dying child benefit from these experiences, healthcare providers often unknowingly dismiss them. The aims of this phenomenological inquiry were to describe children's DRSEs and their meaning from the parents' perspectives. Four fathers and six mothers of African American, Caucasian, or Hispanic ethnicity, all Christian, ranging in age from 35 to 59 years, whose child died 23 to 52 months prior and was treated at a children's cancer center, were interviewed in the home or hospital setting of their choice. Children's ages at the time of their death ranged from 4 to 13 years. A modification of van Kaarn's phenomenological method of analysis was used to analyze data. Themes emerging from the data for the first aim were: perceiving someone or something from a spiritual realm others could not, expressing awareness tempered by parental reactions, and embracing transcendence. Themes emerging from the data for the second aim were: spiritual beings prepared child; child revealed reality, preparing parents; and child transcended wholly, easing parents' grief. Post-interview surveys revealed that parents found participating in this study a "very positive" or "positive" experience, particularly being able to tell the story of their child. Children's DRSEs have clinical implications for all who provide care near the end of life. Informing parents of DRSEs, cautioning that not all dying children express them, may help parents to anticipate this phenomenon, which may decrease anxiety when their child expresses them, increasing the opportunity for open dialogue between parent and child about dying and death, and decrease regrets associated with being unreceptive to their child's expressions of death awareness. Validating a child's DRSE can have profound effects on bereaved parents. Examining DRSEs from the child's perspective and the influence of informing parents of DRSEs on the dying experience of the child and the parental grieving process are recommended. ^

Regression with autocorrelated data: A study of time trend of global infant mortality rate

The infant mortality rate (IMR) is considered to be one of the most important indices of a country's well-being. Countries around the world and other health organizations like the World Health Organization are dedicating their resources, knowledge and energy to reduce the infant mortality rates. The well-known Millennium Development Goal 4 (MDG 4), whose aim is to archive a two thirds reduction of the under-five mortality rate between 1990 and 2015, is an example of the commitment. ^ In this study our goal is to model the trends of IMR between the 1950s to 2010s for selected countries. We would like to know how the IMR is changing overtime and how it differs across countries. ^ IMR data collected over time forms a time series. The repeated observations of IMR time series are not statistically independent. So in modeling the trend of IMR, it is necessary to account for these correlations. We proposed to use the generalized least squares method in general linear models setting to deal with the variance-covariance structure in our model. In order to estimate the variance-covariance matrix, we referred to the time-series models, especially the autoregressive and moving average models. Furthermore, we will compared results from general linear model with correlation structure to that from ordinary least squares method without taking into account the correlation structure to check how significantly the estimates change.^

The number and timing of time -dependent covariate measurements for the Cox regression model

The problem of analyzing data with updated measurements in the time-dependent proportional hazards model arises frequently in practice. One available option is to reduce the number of intervals (or updated measurements) to be included in the Cox regression model. We empirically investigated the bias of the estimator of the time-dependent covariate while varying the effect of failure rate, sample size, true values of the parameters and the number of intervals. We also evaluated how often a time-dependent covariate needs to be collected and assessed the effect of sample size and failure rate on the power of testing a time-dependent effect.^ A time-dependent proportional hazards model with two binary covariates was considered. The time axis was partitioned into k intervals. The baseline hazard was assumed to be 1 so that the failure times were exponentially distributed in the ith interval. A type II censoring model was adopted to characterize the failure rate. The factors of interest were sample size (500, 1000), type II censoring with failure rates of 0.05, 0.10, and 0.20, and three values for each of the non-time-dependent and time-dependent covariates (1/4,1/2,3/4).^ The mean of the bias of the estimator of the coefficient of the time-dependent covariate decreased as sample size and number of intervals increased whereas the mean of the bias increased as failure rate and true values of the covariates increased. The mean of the bias of the estimator of the coefficient was smallest when all of the updated measurements were used in the model compared with two models that used selected measurements of the time-dependent covariate. For the model that included all the measurements, the coverage rates of the estimator of the coefficient of the time-dependent covariate was in most cases 90% or more except when the failure rate was high (0.20). The power associated with testing a time-dependent effect was highest when all of the measurements of the time-dependent covariate were used. An example from the Systolic Hypertension in the Elderly Program Cooperative Research Group is presented. ^