Spiritual Care in Undergraduate Nursing Education: An Integrative Review.

BACKGROUND: The growth of international migration and globalization has increasingly diversified patient populations, emphasizing the need for nursing students to provide competent spiritual care. PURPOSE: To understand the teaching and learning strategies used to prepare undergraduate nursing students for spiritual care. METHODS: An integrative review with deductive data analysis was used to evaluate, analyze, and synthesize diverse research methodologies. RESULTS: Three educational approaches were identified, including passive, reflective, and combinatory approaches. The combinatory approach appears most appropriate for diverse learning styles within a student group. CONCLUSIONS: No one strategy is best, but any combination of educational strategies can positively impact spiritual care competency within clinical practice.

A genome-wide association study of total child psychiatric problems scores.

Substantial genetic correlations have been reported across psychiatric disorders and numerous cross-disorder genetic variants have been detected. To identify the genetic variants underlying general psychopathology in childhood, we performed a genome-wide association study using a total psychiatric problem score. We analyzed 6,844,199 common SNPs in 38,418 school-aged children from 20 population-based cohorts participating in the EAGLE consortium. The SNP heritability of total psychiatric problems was 5.4% (SE = 0.01) and two loci reached genome-wide significance: rs10767094 and rs202005905. We also observed an association of SBF2, a gene associated with neuroticism in previous GWAS, with total psychiatric problems. The genetic effects underlying the total score were shared with common psychiatric disorders only (attention-deficit/hyperactivity disorder, anxiety, depression, insomnia) (rG > 0.49), but not with autism or the less common adult disorders (schizophrenia, bipolar disorder, or eating disorders) (rG < 0.01). Importantly, the total psychiatric problem score also showed at least a moderate genetic correlation with intelligence, educational attainment, wellbeing, smoking, and body fat (rG > 0.29). The results suggest that many common genetic variants are associated with childhood psychiatric symptoms and related phenotypes in general instead of with specific symptoms. Further research is needed to establish causality and pleiotropic mechanisms between related traits.

Phenotypic and genetic relationship between BMI and cigarette smoking in a sample of UK adults.

In addition to the health hazards posed individually by cigarette smoking and obesity, the combination of these conditions poses a particular impairment to health. Genetic factors have been shown to influence both traits and, to understand the connection between these conditions, we examined both the observed and genetic relationship between adiposity (an electrical impedance measure of body mass index (BMI)) and cigarettes smoked per day (CPD) in a large sample of current, former, and never smokers in the United Kingdom. In former smokers, BMI was positively associated with cigarettes formerly smoked; further, the genetic factors related to a greater number of cigarettes smoked were also responsible for a higher BMI. In current smokers, there was a positive association between BMI and number of cigarettes smoked, though this relationship did not appear to be influenced by similar genetic factors. We found a positive genetic relationship between smoking in current/former smokers and BMI in never smokers (who would be unmarred by the effects of nicotine). In addition to CPD, in current smokers, we looked at two variables, time from waking to first cigarette and difficulty not smoking for a day, that may align better with cigarette and food 'craving.' However, these smoking measures provided mixed findings with respect to their relationship with BMI. Overall, the positive relationships between the genetic factors that influence CPD in smokers and the genetic factors that influence BMI in former and never smokers point to common biological influences behind smoking and obesity.

Phenotypic and Genetic Relationship Between BMI and Drinking in a Sample of UK Adults.

The health impairments derived from both alcoholism and obesity are well known. However, reports that relate increased alcohol use with increased measures of obesity have been mixed in their findings, especially with respect to genetic factors that could potentially link these two behaviors. Here, using a large sample of adults from the UK (n ≈ 113,000), we report both the observed and genetic correlations between BMI (kg/m2) and two measures of alcohol use: reported quantity (drinks per week) and frequency of use (from never to daily). Overall, both observationally and genetically, alcohol intake is negatively correlated with BMI. Phenotypic correlations ranged from -0.01 to -0.17, and genetic correlations ranged from -0.1 to -0.4. Genetic correlations tended to be stronger than the phenotypic correlations, and these correlations were stronger in females and between BMI and, specifically, frequency of use. Though the mechanisms driving these relationships are yet to be identified, we can conclude that the genetic factors related to drinking both more and more often are shared with those responsible for lower BMI.

Adolescent peer choice and cigarette smoking: evidence of active gene-environment correlation?

Both peer groups and genetics have been associated with adolescent smoking behavior. Recently, Loehlin (Loehlin, J. C. (2010). Is there an active gene-environment correlation in adolescent drinking behavior? Behavior Genetics, 40, 447-451) reported that twin differences in alcohol use were associated with differences in the number of common friends. Twins with more common friends were more similar in drinking, but only for dizygotic pairs. Using the same sample as Loehlin's (the National Merit twins), we replicated all of these findings for a composite cigarette smoking measure and for smoking initiation, but not persistence. The pattern of results is most consistent with homophily, or the tendency to associate with individuals that are like oneself. If peer influence occurs in the presence of homophily, then active genotype-environment correlation will be induced.

Recent methods for polygenic analysis of genome-wide data implicate an important effect of common variants on cardiovascular disease risk.

BACKGROUND: Traditional genome-wide association studies are generally limited in their ability explain a large portion of genetic risk for most common diseases. We sought to use both traditional GWAS methods, as well as more recently developed polygenic genome-wide analysis techniques to identify subsets of single-nucleotide polymorphisms (SNPs) that may be involved in risk of cardiovascular disease, as well as estimate the heritability explained by common SNPs. METHODS: Using data from the Framingham SNP Health Association Resource (SHARe), three complimentary methods were applied to examine the genetic factors associated with the Framingham Risk Score, a widely accepted indicator of underlying cardiovascular disease risk. The first method adopted a traditional GWAS approach - independently testing each SNP for association with the Framingham Risk Score. The second two approaches involved polygenic methods with the intention of providing estimates of aggregate genetic risk and heritability. RESULTS: While no SNPs were independently associated with the Framingham Risk Score based on the results of the traditional GWAS analysis, we were able to identify cardiovascular disease-related SNPs as reported by previous studies. A predictive polygenic analysis was only able to explain approximately 1% of the genetic variance when predicting the 10-year risk of general cardiovascular disease. However, 20% to 30% of the variation in the Framingham Risk Score was explained using a recently developed method that considers the joint effect of all SNPs simultaneously. CONCLUSION: The results of this study imply that common SNPs explain a large amount of the variation in the Framingham Risk Score and suggest that future, better-powered genome-wide association studies, possibly informed by knowledge of gene-pathways, will uncover more risk variants that will help to elucidate the genetic architecture of cardiovascular disease.

Mutational load analysis of unrelated individuals.

Evolutionary genetic models predict that the cumulative effect of rare deleterious mutations across the genome-known as mutational load burden-increases the susceptibility to complex disease. To test the mutational load burden hypothesis, we adopted a two-tiered approach: assessing the impact of whole-exome minor allele load burden and then conducting individual-gene screening. For our primary analysis, we examined various minor allele frequency (MAF) thresholds and weighting schemes to examine the overall effect of minor allele load on affection status. We found a consistent association between minor allele load and affection status, but this effect did not markedly increase within rare and/or functional single-nucleotide polymorphisms (SNPs). Our follow-up analysis considered minor allele load in individual genes to see whether only one or a few genes were driving the overall effect. Examining our most significant result-minor allele load of nonsynonymous SNPs with MAF < 2.4%-we detected no significantly associated genes after Bonferroni correction for multiple testing. After moderately significant genes (p < 0.05) were removed, the overall effect of rare nonsynonymous allele load remained significant. Overall, we did not find clear support for mutational load burden on affection status; however, these results are ultimately dependent on and limited by the nature of the Genetic Analysis Workshop 17 simulation.