Spirituality and the care of patients at the end-of-life: an essential component of care

Spirituality is an essential component of the care of patients with serious illness and those that are dying. Dame Cicely Saunders developed the hospice movement based on the biopsychosocialspiritual model of care, in which all four dimensions are important in the care of patients. Of all the models of care, hospice and palliative care recognize the importance of spiritual issues in the care of patients and their families. The National Consensus Project Guidelines for Quality Palliative Care, in the United States, provides specific recommendations about all domains of care including the spiritual domain, which is recognized as a critical component of care (The National Consensus Project for Quality Palliative Care www.nationalconsensusproject.org). Studies indicate that the majority of patients would like their spiritual issues addressed, yet find that their spiritual needs are not being met by the current system of care. Interestingly, spirituality is the one dimension that seems to get slightly less emphasis than the biopsychosocial dimensions of care. Some reasons may include the difficulty with definitions of spirituality for clinical and research purposes, the time constraints and financial burdens in the current healthcare system in the United States, and the lack of uniform training for all healthcare professionals. Yet, there are theoretical and ethical frameworks that support spiritual care as well as some educational models in spirituality and health that have been successful in medical education in the United States. Spirituality can be seen as the essential part of the humanity of all people. It is at its root, relational and thus forms the basis of the altruistic care healthcare professionals are committed to. Spirituality has to do with respecting the inherent value and dignity of all persons, regardless of their health status. It is the part of humans that seeks healing, particularly in the midst of suffering. Spiritual care models are based on an intrinsic aspect that calls for compassionate presence to patients as well as an extrinsic component where healthcare professionals address spiritual issues with patients and their loved ones. Currently in the healthcare system, evidence-base models are the criteria for practice recommendations. Yet, spirituality may not be amenable entirely to strict evidence-base criteria. As hospice and palliative care continues to develop as a field, healthcare professionals are challenged to think of ways to advocate for and include the spiritual dimension of care.     

Reproducibility of clinical data I: continuous outcomes

Across a variety of clinical settings, repeated measurements on an individual, obtained under identical circumstances, often differ from one another. This implies the measurements lack perfect reproducibility. Topics related to reproducibility of clinical measurements are introduced in this paper. In this first of two parts, continuous outcomes are addressed. The intraclass correlation coefficient, ρ, has been the traditional coefficient of reproducibility for continuous outcomes. The importance of ρ regarding observations on an individual, and observations among populations, is outlined. Estimation and inferential procedures for ρ are reviewed and worked examples are provided. Copyright © 2004 John Wiley & Sons, Ltd.     

Information for Authors

Instructions for Authors

Information for Authors     

Nonlinear structural equation modeling: is partial least squares an alternative?

Nonlinear structural equation modeling provides many advantages over analyses based on manifest variables only. Several approaches for the analysis of latent interaction effects have been developed within the last 15 years, including the partial least squares product indicator approach (PLS-PI), the constrained product indicator approach using the LISREL software (LISREL-PI), and the distribution-analytic latent moderated structural equations approach (LMS) using the Mplus program. An assumed advantage of PLS-PI is that it is able to deal with very large numbers of indicators, while LISREL-PI and LMS have not been investigated under such conditions. In a Monte Carlo study, the performance of LISREL-PI and LMS was compared to PLS-PI results previously reported in Chin et al. (2003) and Goodhue et al. (2007) for identical conditions. The latent interaction model included six indicator variables for the measurement of each latent predictor variable and the latent criterion, and sample size was N=100. The results showed that PLS-PI’s linear and interaction parameter estimates were downward biased, while parameter estimates were unbiased for LISREL-PI and LMS. True standard errors were smallest for PLS-PI, while the power to detect the latent interaction effect was higher for LISREL-PI and LMS. Compared to the symmetric distributions of interaction parameter estimates for LISREL-PI and LMS, PLS-PI showed a distribution that was symmetric for positive values, but included outlying negative estimates. Possible explanations for these findings are discussed.     

A four factor model predicting likelihood of foster carer retention

This study used a self‐report method to test a conceptual model for predicting the likelihood of retention of foster carers for children requiring out‐of‐home care. It was hypothesized that satisfaction levels of foster carers would be determined by locus of control and social support, and that the decision to stay or leave fostering within the next 18 months would be influenced by foster carer satisfaction, and commitment to a child/ren in care. Participants were 185 Queensland foster carers. Results supported the proposed model. Logistic regression analysis revealed that an increase in either satisfaction or commitment would result in foster carers being more likely to decide to stay in fostering. Multiple regression analysis found that both locus of control and social support made a significant contribution to the prediction of carer satisfaction. The findings were further supported by qualitative data. Implications of the findings are discussed.     

Quantitative Risk Assessment of Listeria monocytogenes in French Cold-Smoked Salmon: II. Risk Characterization

A model for the assessment of exposure to Listeria monocytogenes from cold-smoked salmon consumption in France was presented in the first of this pair of articles (Pouillot et al ., 2007, Risk Analysis, 27:683–700). In the present study, the exposure model output was combined with an internationally accepted hazard characterization model, adapted to the French situation, to assess the risk of invasive listeriosis from cold-smoked salmon consumption in France in a second-order Monte Carlo simulation framework. The annual number of cases of invasive listeriosis due to cold-smoked salmon consumption in France is estimated to be 307, with a very large credible interval ([10; 12,453]), reflecting data uncertainty. This uncertainty is mainly associated with the dose-response model. Despite the significant uncertainty associated with the predictions, this model provides a scientific base for risk managers and food business operators to manage the risk linked to cold-smoked salmon contaminated with L. monocytogenes. Under the modeling assumptions, risk would be efficiently reduced through a decrease in the prevalence of L. monocytogenes or better control of the last steps of the cold chain (shorter and/or colder storage during the consumer step), whereas reduction of the initial contamination levels of the contaminated products and improvement in the first steps of the cold chain do not seem to be promising strategies. An attempt to apply the recent risk-based concept of FSO (food safety objective) on this example underlines the ambiguity in practical implementation of the risk management metrics and the need for further elaboration on these concepts.