Allied Health Professions Public Health Research Priorities: A modified e-delphi study in the United Kingdom

Objectives This study identifies the United Kingdom (UK) Allied Health Professions (AHP) public health research priorities through a modified e-Delphi study conducted with an expert panel. Study design A modified e-Delphi study was utilised in this study. Methods This study used a modified e-Delphi approach to reach a consensus on research priorities. Expert panel members were invited to participate and complete three rounds of the e-Delphi. Ethical approval was obtained through the Public Health England Research and Evidence Governance Group. Results A total of 38 participants completed three rounds of the e-Delphi study between September and November 2020. Consensus was reached on nine AHP public health research priorities. Conclusion Several areas of AHP public health research were identified as priority, however, a number of priorities refer to the impact of AHP public health activities as opposed to empirical research. The identified priorities will be used to progress the AHP public health research agenda through a UK wide AHP public health strategy implementation group and through support and engagement from the AHP professional bodies and arm's length bodies

What are the sources of patient experience feedback in the UK prison setting, and what do patients and healthcare staff think about giving and receiving feedback in prison? A qualitative study

Background: The collection of patient experience feedback (PEF) has seen a marked global increase in the past decade. Research about PEF has concentrated mainly on hospital settings albeit a recent interest in primary care. There has been minimal research about PEF in the prison healthcare setting. The aim of this study was to explore the role of prison PEF, the different forms it might take and the perceptions of healthcare staff and people in prison. Methods: Qualitative face to face interview study involving 24 participants across two prisons (male and female) in the North of England, involving 12 healthcare staff and 12 patients. Framework analysis was undertaken. Results: PEF sources were variable, from informal and verbal through to formal and written. The willingness of people in prison to give PEF related to whether they felt sufficiently comfortable to raise concerns, with some feeling too frightened and having apprehension about anonymity. It was viewed as disheartening to give PEF but not be informed of any outcome. Healthcare staff opinions about PEF were divergent but they found PEF unhelpful when it was about prison regime issues rather than healthcare. Suggestions for improving the PEF process were put forward and included accessibility, anonymity and digitalisation. Conclusions: This is the first study to report findings about prison PEF. There are broad similarities between our findings and research examining hospital-based PEF. Prison healthcare services seem to be listening to patients but the ways in which PEF is collected, considered and used could be improved. Experience Framework This article is associated with the Policy & Measurement lens of The Beryl Institute Experience Framework. (https://www.theberylinstitute.org/ExperienceFramework). Access other PXJ articles related to this lens. Access other resources related to this lens

EnteroBase : Hierarchical clustering of 100,000s of bacterial genomes into species/sub-species and populations

The definition of bacterial species is traditionally a taxonomic issue while bacterial populations are identified by population genetics. These assignments are species specific, and depend on the practitioner. Legacy multilocus sequence typing is commonly used to identify sequence types (STs) and clusters (ST Complexes). However, these approaches are not adequate for the millions of genomic sequences from bacterial pathogens that have been generated since 2012. EnteroBase (http://enterobase.warwick.ac.uk) automatically clusters core genome MLST allelic profiles into hierarchical clusters (HierCC) after assembling annotated draft genomes from short read sequences. HierCC clusters span core sequence diversity from the species level down to individual transmission chains. Here we evaluate HierCC’s ability to correctly assign 100,000s of genomes to the species/subspecies and population levels for Salmonella, Escherichia, Clostridoides, Yersinia, Vibrio and Streptococcus. HierCC assignments were more consistent with maximum-likelihood super-trees of core SNPs or presence/absence of accessory genes than classical taxonomic assignments or 95% ANI. However, neither HierCC nor ANI were uniformly consistent with classical taxonomy of Streptococcus. HierCC was also consistent with legacy eBGs/ST Complexes in Salmonella or Escherichia and with O serogroups in Salmonella. Thus, EnteroBase HierCC supports the automated 36 identification of and assignment to species/subspecies and populations for multiple genera

Genetic Analysis Workshop 17 mini-exome simulation

The data set simulated for Genetic Analysis Workshop 17 was designed to mimic a subset of data that might be produced in a full exome screen for a complex disorder and related risk factors in order to permit workshop participants to investigate issues of study design and statistical genetic analysis. Real sequence data from the 1000 Genomes Project formed the basis for simulating a common disease trait with a prevalence of 30% and three related quantitative risk factors in a sample of 697 unrelated individuals and a second sample of 697 individuals in large, extended pedigrees. Called genotypes for 24,487 autosomal markers assigned to 3,205 genes and simulated affection status, quantitative traits, age, sex, pedigree relationships, and cigarette smoking were provided to workshop participants. The simulating model included both common and rare variants with minor allele frequencies ranging from 0.07% to 25.8% and a wide range of effect sizes for these variants. Genotype-smoking interaction effects were included for variants in one gene. Functional variants were concentrated in genes selected from specific biological pathways and were selected on the basis of the predicted deleteriousness of the coding change. For each sample, unrelated individuals and family, 200 replicates of the phenotypes were simulated

Healthcare students’ perceptions about their role, confidence and competence to deliver brief public health interventions and advice

Background Public health improvement has long been an important focus for the United Kingdom Department of Health. The Allied Health Professions (AHP) Federation has 84,000 members, such a large number of AHP professionals should play a role in public health initiatives, but it is not clear if they or the AHP students who will be the future healthcare workforce feel themselves equipped to do so. Our aim was to understand the perceptions of AHP students about their role in delivering public health advice. Methods AHP students were recruited in one teaching university from different departments. Participants were final year AHP students who had completed all clinical placements related to their course. All students were emailed an invitation to participate, and those interested were asked to contact the researchers to participate in one of several focus groups. Data were recorded, transcribed, and analysed using framework analysis by two independent researchers. Results Nineteen students were recruited and participated in four focus groups. The main themes produced by the data analysis were: understanding of public health issues, perceptions of their role in this, challenges and opportunities to develop a public health role, and preparation for a public health role. Conclusions AHP students felt that they had a role in public health advice-giving, but barriers to providing this advice included their own lack of confidence and knowledge, time, and the environment of the clinical placement. They considered that there should be more teaching on public health issues, and that these should feature in both the curriculum and on clinical placement

Genetic signal maximization using environmental regression

Joint analyses of correlated phenotypes in genetic epidemiology studies are common. However, these analyses primarily focus on genetic correlation between traits and do not take into account environmental correlation. We describe a method that optimizes the genetic signal by accounting for stochastic environmental noise through joint analysis of a discrete trait and a correlated quantitative marker. We conducted bivariate analyses where heritability and the environmental correlation between the discrete and quantitative traits were calculated using Genetic Analysis Workshop 17 (GAW17) family data. The resulting inverse value of the environmental correlation between these traits was then used to determine a new β coefficient for each quantitative trait and was constrained in a univariate model. We conducted genetic association tests on 7,087 nonsynonymous SNPs in three GAW17 family replicates for Affected status with the β coefficient fixed for three quantitative phenotypes and compared these to an association model where the β coefficient was allowed to vary. Bivariate environmental correlations were 0.64 (± 0.09) for Q1, 0.798 (± 0.076) for Q2, and −0.169 (± 0.18) for Q4. Heritability of Affected status improved in each univariate model where a constrained β coefficient was used to account for stochastic environmental effects. No genome-wide significant associations were identified for either method but we demonstrated that constraining β for covariates slightly improved the genetic signal for Affected status. This environmental regression approach allows for increased heritability when the β coefficient for a highly correlated quantitative covariate is constrained and increases the genetic signal for the discrete trait

Two's Company, Three's a Crowd: Experimental Evaluation of the Evolutionary Maintenance of Trioecy in Mercurialis annua (Euphorbiaceae)

Trioecy is an uncommon sexual system in which males, females, and hermaphrodites co-occur as three clearly different gender classes. The evolutionary stability of trioecy is unclear, but would depend on factors such as hermaphroditic sex allocation and rates of outcrossing vs. selfing. Here, trioecious populations of Mercurialis annua are described for the first time. We examined the frequencies of females, males and hermaphrodites across ten natural populations and evaluated the association between the frequency of females and plant densities. Previous studies have shown that selfing rates in this species are density-dependent and are reduced in the presence of males, which produce substantially more pollen than hermaphrodites. Accordingly, we examined the evolutionary stability of trioecy using an experiment in which we (a) indirectly manipulated selfing rates by altering plant densities and the frequency of males in a fully factorial manner across 20 experimental plots and (b) examined the effect of these manipulations on the frequency of the three sex phenotypes in the next generation of plants. In the parental generation, we measured the seed and pollen allocations of hermaphrodites and compared them with allocations by unisexual plants. In natural populations, females occurred at higher frequencies in denser patches, a finding consistent with our expectations. Under our experimental conditions, however, no combination of plant densities and male frequencies was associated with increased frequencies of females. Our results suggest that the factors that regulate female frequencies in trioecious populations of M. annua are independent of those regulating male frequencies (density), and that the stable co-existence of all three sex phenotypes within populations is unlikely

High dimensional endophenotype ranking in the search for major depression risk genes.

BACKGROUND: Despite overwhelming evidence that major depression is highly heritable, recent studies have localized only a single depression-related locus reaching genome-wide significance and have yet to identify a causal gene. Focusing on family-based studies of quantitative intermediate phenotypes or endophenotypes, in tandem with studies of unrelated individuals using categorical diagnoses, should improve the likelihood of identifying major depression genes. However, there is currently no empirically derived statistically rigorous method for selecting optimal endophentypes for mental illnesses. Here, we describe the endophenotype ranking value, a new objective index of the genetic utility of endophenotypes for any heritable illness. METHODS: Applying endophenotype ranking value analysis to a high-dimensional set of over 11,000 traits drawn from behavioral/neurocognitive, neuroanatomic, and transcriptomic phenotypic domains, we identified a set of objective endophenotypes for recurrent major depression in a sample of Mexican American individuals (n = 1122) from large randomly selected extended pedigrees. RESULTS: Top-ranked endophenotypes included the Beck Depression Inventory, bilateral ventral diencephalon volume, and expression levels of the RNF123 transcript. To illustrate the utility of endophentypes in this context, each of these traits were utlized along with disease status in bivariate linkage analysis. A genome-wide significant quantitative trait locus was localized on chromsome 4p15 (logarithm of odds = 3.5) exhibiting pleiotropic effects on both the endophenotype (lymphocyte-derived expression levels of the RNF123 gene) and disease risk. CONCLUSIONS: The wider use of quantitative endophenotypes, combined with unbiased methods for selecting among these measures, should spur new insights into the biological mechanisms that influence mental illnesses like major depression