Mother-Child Spiritual Discourse: A Mixed Methods Study

Parents and children, starting at very young ages, discuss religious and spiritual issues¿where we come from, what happens to us after we die, is there a God, and so on. Unfortunately, few studies have analyzed the content and structure of parent-child conversation about religion and spirituality (Boyatzis & Janicki, 2003; Dollahite & Thatcher, 2009), and most studies have relied on self-report with no direct observation. The current study examined mother-child (M-C) spiritual discourse to learn about its content, structure, and frequency through a survey inventory in combination with direct video observation using a novel structured task. We also analyzed how mothers¿ religiosity along several major dimensions related to their communication behaviors within both methods. Mothers (N = 39, M age = 40) of children aged 3-12 completed a survey packet on M-C spiritual discourse and standard measures of mothers¿ religious fundamentalism, intrinsic religiosity, sanctification of parenting (how much the mother saw herself as doing God¿s work as a parent), and a new measure of parental openness to children¿s spirituality. Then, in a structured task in our lab, mothers (N = 33) and children (M age = 7.33) watched a short film or read a short book that explored death in an age-appropriate manner and then engaged in a videotaped conversation about the movie or book and their religious or spiritual beliefs. Frequency of M-C spiritual discourse was positively related to mothers¿ religious fundamentalism (r = .71, p = .00), intrinsic religiosity (r = .77, p = .00), and sanctification of parenting (r = .79, p = .00), but, surprisingly, was inversely related to mothers¿ v openness to child¿s spirituality (r = -.52, p = .00). Survey data showed that the two most common topics discussed were God (once a week) and religion as it relates to moral issues (once a week). According to mothers their children¿s most common method of initiating spiritual discourse was to repeat what he or she has heard parents or family say about religious issues (M = 2.97; once a week); mothers¿ most common method was to describe their own religious/spiritual beliefs (M = 2.92). Spiritual discourse most commonly occurred either at bedtime or mealtime as reported by 26% of mothers, with the most common triggers reported as daily routine/random thoughts (once a week) and observations of nature (once a week). Mothers¿ most important goals for spiritual discourse were to let their children know that they love them (M = 3.72; very important) and to help them become a good and moral person (M = 3.67; very important). A regression model showed that significant variance in frequency of mother-child spiritual discourse (R2 = .84, p = .00) was predicted by the mothers¿ importance of goals during discourse (ß = 0.46, p = .00), frequency that the mother¿s spirituality was deepened through spiritual discourse (ß = 0.39, p = .00), and the mother¿s fundamentalism (ß = 0.20, p = .05). In a separate regression, the mother¿s comfort in the structured task (ß = 0.70, p = .00), and the number of open-ended questions she asked (ß = -0.26, p = .03) predicted the reciprocity between mother and child (R2 = .62, p = .00). In addition, the mother¿s age (ß = 0.22, p = .059) and comfort during the task (ß = 0.73, p = .00) predicted the child¿s engagement within the structured task. Other findings and theoretical and methodological implications will be discussed.

Good efficacy of drug-eluting balloons in a mixed population of patients with coronary artery disease

Drug-coated balloons (DCB) are being increasingly used in interventional cardiology and are established for the treatment of in-stent restenosis (ISR). It is unclear how effective they are in patients with de novo lesions.

Inhibition of indoleamine 2,3-dioxygenase in mixed lymphocyte reaction affects glucose influx and enzymes involved in aerobic glycolysis and glutaminolysis in alloreactive T-cells

Indoleamine 2,3-dioxygenase (IDO) suppresses adaptive immunity. T-cell proliferation and differentiation to effector cells require increased glucose consumption, aerobic glycolysis and glutaminolysis. The effect of IDO on the above metabolic pathways was evaluated in alloreactive T-cells. Mixed lymphocyte reaction (MLR) in the presence or not of the IDO inhibitor, 1-DL-methyl-tryptophane (1-MT), was used. In MLRs, 1-MT decreased tryptophan consumption, increased cell proliferation, glucose influx and lactate production, whereas it decreased tricarboxylic acid cycle activity. In T-cells, from the two pathways that could sense tryptophan depletion, i.e. general control nonrepressed 2 (GCN2) kinase and mammalian target of rapamycin complex 1, 1-MT reduced only the activity of the GCN2 kinase. Additionally 1-MT treatment of MLRs altered the expression and/or the phosphorylation state of glucose transporter-1 and of key enzymes involved in glucose metabolism and glutaminolysis in alloreactive T-cells in a way that favors glucose influx, aerobic glycolysis and glutaminolysis. Thus in alloreactive T-cells, IDO through activation of the GCN2 kinase, decreases glucose influx and alters key enzymes involved in metabolism, decreasing aerobic glycolysis and glutaminolysis. Acting in such a way, IDO could be considered as a constraining factor for alloreactive T-cell proliferation and differentiation to effector T-cell subtypes.

Gauss-Seidel Estimation of Generalized Linear Mixed Models with Application to Poisson Modeling of Spatially Varying Disease Rates

Generalized linear mixed models (GLMMs) provide an elegant framework for the analysis of correlated data. Due to the non-closed form of the likelihood, GLMMs are often fit by computational procedures like penalized quasi-likelihood (PQL). Special cases of these models are generalized linear models (GLMs), which are often fit using algorithms like iterative weighted least squares (IWLS). High computational costs and memory space constraints often make it difficult to apply these iterative procedures to data sets with very large number of cases. This paper proposes a computationally efficient strategy based on the Gauss-Seidel algorithm that iteratively fits sub-models of the GLMM to subsetted versions of the data. Additional gains in efficiency are achieved for Poisson models, commonly used in disease mapping problems, because of their special collapsibility property which allows data reduction through summaries. Convergence of the proposed iterative procedure is guaranteed for canonical link functions. The strategy is applied to investigate the relationship between ischemic heart disease, socioeconomic status and age/gender category in New South Wales, Australia, based on outcome data consisting of approximately 33 million records. A simulation study demonstrates the algorithm's reliability in analyzing a data set with 12 million records for a (non-collapsible) logistic regression model.

A Diagnostic Test for the Mixing Distribution in a Generalised Linear Mixed Model

We introduce a diagnostic test for the mixing distribution in a generalised linear mixed model. The test is based on the difference between the marginal maximum likelihood and conditional maximum likelihood estimates of a subset of the fixed effects in the model. We derive the asymptotic variance of this difference, and propose a test statistic that has a limiting chi-square distribution under the null hypothesis that the mixing distribution is correctly specified. For the important special case of the logistic regression model with random intercepts, we evaluate via simulation the power of the test in finite samples under several alternative distributional forms for the mixing distribution. We illustrate the method by applying it to data from a clinical trial investigating the effects of hormonal contraceptives in women.