Measuring the Efficacy of Leaders to Assess Information and Make Decisions in a Crisis: The C-LEAD Scale

Based on literature and expert interviews, we developed the Crisis Leader Efficacy in Assessing and Deciding scale (C-LEAD) to capture the efficacy of leaders to assess information and make decisions in a public health and safety crisis. In Studies 1 and 2, we find that C-LEAD predicts decision-making difficulty and confidence in a crisis better than a measure of general leadership efficacy. In Study 3, C-LEAD predicts greater motivation to lead in a crisis, more crisis leader role-taking, and more accurate performance while in a crisis leader role. These findings support the scale's construct validity and broaden our theoretical understanding of the nature of crisis leader efficacy.

Measuring the Efficacy of Leaders to Assess Information and Make Decisions in a Crisis: The C-LEAD Scale

Based on literature and expert interviews, we developed the Crisis Leader Efficacy in Assessing and Deciding scale (C-LEAD) to capture the efficacy of leaders to assess information and make decisions in a public health and safety crisis. In Studies 1 and 2, we find that C-LEAD predicts decision-making difficulty and confidence in a crisis better than a measure of general leadership efficacy. In Study 3, C-LEAD predicts greater motivation to lead in a crisis, more crisis leader role-taking, and more accurate performance while in a crisis leader role. These findings support the scale’s construct validity and broaden our theoretical understanding of the nature of crisis leader efficacy

Measuring the Efficacy of Leaders to Assess Information and Make Decisions in a Crisis: The C-LEAD Scale.

Based on literature and expert interviews, we developed the Crisis Leader Efficacy in Assessing and Deciding scale (C-LEAD) to capture the efficacy of leaders to assess information and make decisions in a public health and safety crisis. In Studies 1 and 2, we find that C-LEAD predicts decision-making difficulty and confidence in a crisis better than a measure of general leadership efficacy. In Study 3, C-LEAD predicts greater motivation to lead in a crisis, more crisis leader role-taking, and more accurate performance while in a crisis leader role. These findings support the scale’s construct validity and broaden our theoretical understanding of the nature of crisis leader efficacy

The impact of mental health recovery narratives on recipients experiencing mental health problems: Qualitative analysis and change model.

BACKGROUND: Mental health recovery narratives are stories of recovery from mental health problems. Narratives may impact in helpful and harmful ways on those who receive them. The objective of this paper is to develop a change model identifying the range of possible impacts and how they occur. METHOD: Semi-structured interviews were conducted with adults with experience of mental health problems and recovery (n = 77). Participants were asked to share a mental health recovery narrative and to describe the impact of other people's recovery narratives on their own recovery. A change model was generated through iterative thematic analysis of transcripts. RESULTS: Change is initiated when a recipient develops a connection to a narrator or to the events descripted in their narrative. Change is mediated by the recipient recognising experiences shared with the narrator, noticing the achievements or difficulties of the narrator, learning how recovery happens, or experiencing emotional release. Helpful outcomes of receiving recovery narratives are connectedness, validation, hope, empowerment, appreciation, reference shift and stigma reduction. Harmful outcomes are a sense of inadequacy, disconnection, pessimism and burden. Impact is positively moderated by the perceived authenticity of the narrative, and can be reduced if the recipient is experiencing a crisis. CONCLUSIONS: Interventions that incorporate the use of recovery narratives, such as peer support, anti-stigma campaigns and bibliotherapy, can use the change model to maximise benefit and minimise harms from narratives. Interventions should incorporate a diverse range of narratives available through different mediums to enable a range of recipients to connect with and benefit from this material. Service providers using recovery narratives should preserve authenticity so as to maximise impact, for example by avoiding excessive editing

Changes in neuronal activation patterns in response to androgen deprivation therapy: a pilot study

<p>Abstract</p> <p>Background</p> <p>A common treatment option for men with prostate cancer is androgen deprivation therapy (ADT). However, men undergoing ADT may experience physical side effects, changes in quality of life and sometimes psychiatric and cognitive side effects.</p> <p>Methods</p> <p>In this study, hormone naïve patients without evidence of metastases with a rising PSA were treated with nine months of ADT. Functional magnetic resonance imaging (fMRI) of the brain during three visuospatial tasks was performed at baseline prior to treatment and after nine months of ADT in five subjects. Seven healthy control patients, underwent neuroimaging at the same time intervals.</p> <p>Results</p> <p>ADT patients showed reduced, task-related BOLD-fMRI activation during treatment that was not observed in control subjects. Reduction in activation in right parietal-occipital regions from baseline was observed during recall of the spatial location of objects and mental rotation.</p> <p>Conclusions</p> <p>Findings, while preliminary, suggest that ADT reduces task-related neural activation in brain regions that are involved in mental rotation and accurate recall of spatial information.</p

Limited diversity associated with duplicated class II MHC-DRB genes in the red squirrel population in the United Kingdom compared with continental Europe

The red squirrel (Sciurus vulgaris) population in the United Kingdom has declined over the last century and is now on the UK endangered species list. This is the result of competition from the eastern grey squirrel (S. carolinensis) which was introduced in the 19th century. However, recent evidence suggests that the rate of population decline is enhanced by squirrelpox disease, caused by a viral infection carried asymptomatically by grey squirrels but to which red squirrels are highly susceptible. Population genetic diversity provides some resilience to rapidly evolving or exotic pathogens. There is currently no data on genetic diversity of extant UK squirrel populations with respect to genes involved in disease resistance. Diversity is highest at loci involved in the immune response including genes clustered within the major histocompatibility complex (MHC). Using the class II DRB locus as a marker for diversity across the MHC region we genotyped 110 red squirrels from locations in the UK and continentalEurope. Twenty four Scvu-DRB alleles at two functional loci; Scvu-DRB1 and Scvu- DRB2, were identified. High levels of diversity were identified at both loci in the continental populations. In contrast, no diversity was observed at the Scvu-DRB2 locus in the mainland UK population while a high level of homozygosity was observed at the Scvu-DRB1 locus. The red squirrel population in the UK appears to lack the extensive MHC diversity associated with continental populations, a feature which may have contributed to their rapid decline

The pipeline project:Pre-publication independent replications of a single laboratory's research pipeline

This crowdsourced project introduces a collaborative approach to improving the reproducibility of scientific research, in which findings are replicated in qualified independent laboratories before (rather than after) they are published. Our goal is to establish a non-adversarial replication process with highly informative final results. To illustrate the Pre-Publication Independent Replication (PPIR) approach, 25 research groups conducted replications of all ten moral judgment effects which the last author and his collaborators had "in the pipeline" as of August 2014. Six findings replicated according to all replication criteria, one finding replicated but with a significantly smaller effect size than the original, one finding replicated consistently in the original culture but not outside of it, and two findings failed to find support. In total, 40% of the original findings failed at least one major replication criterion. Potential ways to implement and incentivize pre-publication independent replication on a large scale are discussed. (C) 2015 The Authors. Published by Elsevier Inc.</p

The pipeline project: Pre-publication independent replications of a single laboratory's research pipeline

This crowdsourced project introduces a collaborative approach to improving the reproducibility of scientific research, in which findings are replicated in qualified independent laboratories before (rather than after) they are published. Our goal is to establish a non-adversarial replication process with highly informative final results. To illustrate the Pre-Publication Independent Replication (PPIR) approach, 25 research groups conducted replications of all ten moral judgment effects which the last author and his collaborators had “in the pipeline” as of August 2014. Six findings replicated according to all replication criteria, one finding replicated but with a significantly smaller effect size than the original, one finding replicated consistently in the original culture but not outside of it, and two findings failed to find support. In total, 40% of the original findings failed at least one major replication criterion. Potential ways to implement and incentivize pre-publication independent replication on a large scale are discussed

Data from a pre-publication independent replication initiative examining ten moral judgement effects

We present the data from a crowdsourced project seeking to replicate findings in independent laboratories before (rather than after) they are published. In this Pre-Publication Independent Replication (PPIR) initiative, 25 research groups attempted to replicate 10 moral judgment effects from a single laboratory's research pipeline of unpublished findings. The 10 effects were investigated using online/lab surveys containing psychological manipulations (vignettes) followed by questionnaires. Results revealed a mix of reliable, unreliable, and culturally moderated findings. Unlike any previous replication project, this dataset includes the data from not only the replications but also from the original studies, creating a unique corpus that researchers can use to better understand reproducibility and irreproducibility in science

Structure, function and diversity of the healthy human microbiome

Author Posting. © The Authors, 2012. This article is posted here by permission of Nature Publishing Group. The definitive version was published in Nature 486 (2012): 207-214, doi:10.1038/nature11234.Studies of the human microbiome have revealed that even healthy individuals differ remarkably in the microbes that occupy habitats such as the gut, skin and vagina. Much of this diversity remains unexplained, although diet, environment, host genetics and early microbial exposure have all been implicated. Accordingly, to characterize the ecology of human-associated microbial communities, the Human Microbiome Project has analysed the largest cohort and set of distinct, clinically relevant body habitats so far. We found the diversity and abundance of each habitat’s signature microbes to vary widely even among healthy subjects, with strong niche specialization both within and among individuals. The project encountered an estimated 81–99% of the genera, enzyme families and community configurations occupied by the healthy Western microbiome. Metagenomic carriage of metabolic pathways was stable among individuals despite variation in community structure, and ethnic/racial background proved to be one of the strongest associations of both pathways and microbes with clinical metadata. These results thus delineate the range of structural and functional configurations normal in the microbial communities of a healthy population, enabling future characterization of the epidemiology, ecology and translational applications of the human microbiome.This research was supported in part by National Institutes of Health grants U54HG004969 to B.W.B.; U54HG003273 to R.A.G.; U54HG004973 to R.A.G., S.K.H. and J.F.P.; U54HG003067 to E.S.Lander; U54AI084844 to K.E.N.; N01AI30071 to R.L.Strausberg; U54HG004968 to G.M.W.; U01HG004866 to O.R.W.; U54HG003079 to R.K.W.; R01HG005969 to C.H.; R01HG004872 to R.K.; R01HG004885 to M.P.; R01HG005975 to P.D.S.; R01HG004908 to Y.Y.; R01HG004900 to M.K.Cho and P. Sankar; R01HG005171 to D.E.H.; R01HG004853 to A.L.M.; R01HG004856 to R.R.; R01HG004877 to R.R.S. and R.F.; R01HG005172 to P. Spicer.; R01HG004857 to M.P.; R01HG004906 to T.M.S.; R21HG005811 to E.A.V.; M.J.B. was supported by UH2AR057506; G.A.B. was supported by UH2AI083263 and UH3AI083263 (G.A.B., C. N. Cornelissen, L. K. Eaves and J. F. Strauss); S.M.H. was supported by UH3DK083993 (V. B. Young, E. B. Chang, F. Meyer, T. M. S., M. L. Sogin, J. M. Tiedje); K.P.R. was supported by UH2DK083990 (J. V.); J.A.S. and H.H.K. were supported by UH2AR057504 and UH3AR057504 (J.A.S.); DP2OD001500 to K.M.A.; N01HG62088 to the Coriell Institute for Medical Research; U01DE016937 to F.E.D.; S.K.H. was supported by RC1DE0202098 and R01DE021574 (S.K.H. and H. Li); J.I. was supported by R21CA139193 (J.I. and D. S. Michaud); K.P.L. was supported by P30DE020751 (D. J. Smith); Army Research Office grant W911NF-11-1-0473 to C.H.; National Science Foundation grants NSF DBI-1053486 to C.H. and NSF IIS-0812111 to M.P.; The Office of Science of the US Department of Energy under Contract No. DE-AC02-05CH11231 for P.S. C.; LANL Laboratory-Directed Research and Development grant 20100034DR and the US Defense Threat Reduction Agency grants B104153I and B084531I to P.S.C.; Research Foundation - Flanders (FWO) grant to K.F. and J.Raes; R.K. is an HHMI Early Career Scientist; Gordon&BettyMoore Foundation funding and institutional funding fromthe J. David Gladstone Institutes to K.S.P.; A.M.S. was supported by fellowships provided by the Rackham Graduate School and the NIH Molecular Mechanisms in Microbial Pathogenesis Training Grant T32AI007528; a Crohn’s and Colitis Foundation of Canada Grant in Aid of Research to E.A.V.; 2010 IBM Faculty Award to K.C.W.; analysis of the HMPdata was performed using National Energy Research Scientific Computing resources, the BluBioU Computational Resource at Rice University