A Pilot Intervention to Increase Parent-Child Communication About Alcohol Avoidance

Enhancing parent-child communication regarding alcohol use through educational print correspondence is a potentially cost-effective tool in health promotion. The purpose of this pilot study was to examine whether a series of postcards addressing specific alcohol risk and protective factors, sent to the parents/guardians of preadolescents in two different school settings, influenced parent-child communication regarding alcohol use. Subjects for this study included parents of participating 6th grade students attending one neighborhood (N=262) and one magnet (bused) (N=388) inner-city school. Participating students were randomly assigned to the intervention or control group. Baseline data were collected from students, enabling the intervention to be tailored to students\u27 individual needs. Parents of students assigned to the intervention were mailed up to 10 prevention postcards over five weeks. Parents completed a 10-item telephone survey eight weeks after implementation of the prevention postcards. The overall parent response rate was 74% (N=478). Results of this pilot intervention found that postcards increased parent-child communication regarding alcohol use, but that these efects difered by school setting and race. Although significant efects were found for the intervention group, further analysis revealed that efects were found only for White parents at the magnet school. Discussion of these differences and implications for research and educational programming are provided

No-Boundary Thinking in Bioinformatics Research

Currently there are definitions from many agencies and research societies defining bioinformatics as deriving knowledge from computational analysis of large volumes of biological and biomedical data. Should this be the bioinformatics research focus? We will discuss this issue in this review article. We would like to promote the idea of supporting human-infrastructure (HI) with no-boundary thinking (NT) in bioinformatics (HINT)

Analysis of negative historical control group data from the in vitro micronucleus assay using TK6 cells.

The recent revisions of the Organisation for Economic Co-operation and Development (OECD) genetic toxicology test guidelines emphasize the importance of historical negative controls both for data quality and interpretation. The goal of a HESI Genetic Toxicology Technical Committee (GTTC) workgroup was to collect data from participating laboratories and to conduct a statistical analysis to understand and publish the range of values that are normally seen in experienced laboratories using TK6 cells to conduct the in vitro micronucleus assay. Data from negative control samples from in vitro micronucleus assays using TK6 cells from 13 laboratories were collected using a standard collection form. Although in some cases statistically significant differences can be seen within laboratories for different test conditions, they were very small. The mean incidence of micronucleated cells/1000 cells ranged from 3.2/1000 to 13.8/1000. These almost four-fold differences in micronucleus levels cannot be explained by differences in scoring method, presence or absence of exogenous metabolic activation (S9), length of treatment, presence or absence of cytochalasin B or different solvents used as vehicles. The range of means from the four laboratories using flow cytometry methods (3.7-fold: 3.5-12.9 micronucleated cells/1000 cells) was similar to that from the nine laboratories using other scoring methods (4.3-fold: 3.2-13.8 micronucleated cells/1000 cells). No laboratory could be identified as an outlier or as showing unacceptably high variability. Quality Control (QC) methods applied to analyse the intra-laboratory variability showed that there was evidence of inter-experimental variability greater than would be expected by chance (i.e. over-dispersion). However, in general, this was low. This study demonstrates the value of QC methods in helping to analyse the reproducibility of results, building up a 'normal' range of values, and as an aid to identify variability within a laboratory in order to implement processes to maintain and improve uniformity

Biomarkers as Common Data Elements for Symptom and Selfâ Management Science

PurposeBiomarkers as common data elements (CDEs) are important for the characterization of biobehavioral symptoms given that once a biologic moderator or mediator is identified, biologically based strategies can be investigated for treatment efforts. Just as a symptom inventory reflects a symptom experience, a biomarker is an indicator of the symptom, though not the symptom per se. The purposes of this position paper are to (a) identify a â minimum setâ of biomarkers for consideration as CDEs in symptom and selfâ management science, specifically biochemical biomarkers; (b) evaluate the benefits and limitations of such a limited array of biomarkers with implications for symptom science; (c) propose a strategy for the collection of the endorsed minimum set of biologic samples to be employed as CDEs for symptom science; and (d) conceptualize this minimum set of biomarkers consistent with National Institute of Nursing Research (NINR) symptoms of fatigue, depression, cognition, pain, and sleep disturbance.Design and MethodsFrom May 2016 through January 2017, a working group consisting of a subset of the Directors of the NINR Centers of Excellence funded by P20 or P30 mechanisms and NINR staff met bimonthly via telephone to develop this position paper suggesting the addition of biomarkers as CDEs. The full group of Directors reviewed drafts, provided critiques and suggestions, recommended the minimum set of biomarkers, and approved the completed document. Best practices for selecting, identifying, and using biological CDEs as well as challenges to the use of biological CDEs for symptom and selfâ management science are described. Current platforms for sample outcome sharing are presented. Finally, biological CDEs for symptom and selfâ management science are proposed along with implications for future research and use of CDEs in these areas.FindingsThe recommended minimum set of biomarker CDEs include proâ and antiâ inflammatory cytokines, a hypothalamicâ pituitaryâ adrenal axis marker, cortisol, the neuropeptide brainâ derived neurotrophic factor, and DNA polymorphisms.ConclusionsIt is anticipated that this minimum set of biomarker CDEs will be refined as knowledge regarding biologic mechanisms underlying symptom and selfâ management science further develop. The incorporation of biological CDEs may provide insights into mechanisms of symptoms, effectiveness of proposed interventions, and applicability of chosen theoretical frameworks. Similarly, as for the previously suggested NINR CDEs for behavioral symptoms and selfâ management of chronic conditions, biological CDEs offer the potential for collaborative efforts that will strengthen symptom and selfâ management science.Clinical RelevanceThe use of biomarker CDEs in biobehavioral symptoms research will facilitate the reproducibility and generalizability of research findings and benefit symptom and selfâ management science.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/143764/1/jnu12378.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/143764/2/jnu12378_am.pd

Nonsteroidal Anti-inflammatory Drugs and Endometrial Carcinoma Mortality and Recurrence

Background: Recent data suggest that the use of nonsteroidal anti-inflammatory drugs (NSAIDs) may be associated with reductions in endometrial cancer risk, yet very few have examined whether their use is related to prognosis among endometrial cancer patients