Enhancing patient experience by training local trainers in fundamental communication skills

Medical centers have a vested interest in improving patient experience through enhancing communication skills. The American Academy on Communication in Healthcare has helped institutions across the country establish internal expertise through delivering train-the-trainer programs. The phases of the program include preparing for implementation of the program, having program participants undergo a fundamental communication skills workshop and then understanding the theoretical and practical rationales underlying the workshop, setting up practice sessions for participants to achieve mastery, and ensuring long-term viability of a communication skills improvement initiative. Outcomes for participants include increased self-assessed personal communication skill, optimism about rolling out a communication skills program, and enhanced communication and hopefulness in working with colleagues. Train-the-trainer programs are a viable way to create enduring communities of local experts who can implement and support institutions’ commitments to excellence in the communication skills of their providers

More than a whistle: Automated detection of marine sound sources with a convolutional neural network

Publication history: Accepted - 14 September 2022; Published online - 04 October 2022The effective analysis of Passive Acoustic Monitoring (PAM) data has the potential to determine spatial and temporal variations in ecosystem health and species presence if automated detection and classification algorithms are capable of discrimination between marine species and the presence of anthropogenic and environmental noise. Extracting more than a single sound source or call type will enrich our understanding of the interaction between biological, anthropogenic and geophonic soundscape components in the marine environment. Advances in extracting ecologically valuable cues from the marine environment, embedded within the soundscape, are limited by the time required for manual analyses and the accuracy of existing algorithms when applied to large PAM datasets. In this work, a deep learning model is trained for multi-class marine sound source detection using cloud computing to explore its utility for extracting sound sources for use in marine mammal conservation and ecosystem monitoring. A training set is developed comprising existing datasets amalgamated across geographic, temporal and spatial scales, collected across a range of acoustic platforms. Transfer learning is used to fine-tune an open-source state-of-the-art ‘small-scale’ convolutional neural network (CNN) to detect odontocete tonal and broadband call types and vessel noise (from 0 to 48 kHz). The developed CNN architecture uses a custom image input to exploit the differences in temporal and frequency characteristics between each sound source. Each sound source is identified with high accuracy across various test conditions, including variable signal-to-noise-ratio. We evaluate the effect of ambient noise on detector performance, outlining the importance of understanding the variability of the regional soundscape for which it will be deployed. Our work provides a computationally low-cost, efficient framework for mining big marine acoustic data, for information on temporal scales relevant to the management of marine protected areas and the conservation of vulnerable species.This work was supported by the Natural Environmental Research Council [grant number NE/S007210/1]. The COMPASS project has been supported by the EU’s INTERREG VA Programme, managed by the Special EU Programmes Body. The views and opinions expressed in this document do not necessarily reflect those of the European Commission or the Special EU Programmes Body (SEUPB)

Approaches and considerations for the assessment of immunotoxicity for environmental chemicals: A workshop summary

AbstractAs experience is gained with toxicology testing and as new assays and technologies are developed, it is critical for stakeholders to discuss opportunities to advance our overall testing strategies. To facilitate these discussions, a workshop on practices for assessing immunotoxicity for environmental chemicals was held with the goal of sharing perspectives on immunotoxicity testing strategies and experiences, developmental immunotoxicity (DIT), and integrated and alternative approaches to immunotoxicity testing. Experiences across the chemical and pharmaceutical industries suggested that standard toxicity studies, combined with triggered-based testing approaches, represent an effective and efficient approach to evaluate immunotoxic potential. Additionally, discussions on study design, critical windows, and new guideline approaches and experiences identified important factors to consider before initiating DIT evaluations including assay choice and timing and the impact of existing adult data. Participants agreed that integrating endpoints into standard repeat-dose studies should be considered for fulfilling any immunotoxicity testing requirements, while also maximizing information and reducing animal use. Participants also acknowledged that in vitro evaluation of immunosuppression is complex and may require the use of multiple assays that are still being developed. These workshop discussions should contribute to developing an effective but more resource and animal efficient approach for evaluating chemical immunotoxicity

Risk of Ovarian Cancer and Inherited Variants in Relapse-Associated Genes

Background: We previously identified a panel of genes associated with outcome of ovarian cancer. The purpose of the current study was to assess whether variants in these genes correlated with ovarian cancer risk. Methods and Findings: Women with and without invasive ovarian cancer (749 cases, 1,041 controls) were genotyped at 136 single nucleotide polymorphisms (SNPs) within 13 candidate genes. Risk was estimated for each SNP and for overall variation within each gene. At the gene-level, variation within MSL1 (male-specific lethal-1 homolog) was associated with risk of serous cancer (p = 0.03); haplotypes within PRPF31 (PRP31 pre-mRNA processing factor 31 homolog) were associated with risk of invasive disease (p = 0.03). MSL1 rs7211770 was associated with decreased risk of serous disease (OR 0.81, 95 % CI 0.66–0.98; p = 0.03). SNPs in MFSD7, BTN3A3, ZNF200, PTPRS, and CCND1A were inversely associated with risk (p,0.05), and there was increased risk at HEXIM1 rs1053578 (p = 0.04, OR 1.40, 95 % CI 1.02–1.91). Conclusions: Tumor studies can reveal novel genes worthy of follow-up for cancer susceptibility. Here, we found that inherited markers in the gene encoding MSL1, part of a complex that modifies the histone H4, may decrease risk of invasiv

No association between a candidate TCF7L2 variant and risk of breast or ovarian cancer

<p>Abstract</p> <p>Background</p> <p>TCF7L2 is a transcription factor involved in Wnt/β-catenin signaling which has a variant known to be associated with risk of Type 2 diabetes and, in some studies, with risk of certain cancers, including familial breast cancer. No studies of ovarian cancer have been reported to date.</p> <p>Methods</p> <p>Two clinic-based case-control studies at the Mayo Clinic were assessed including 798 breast cancer cases, 843 breast cancer controls, 391 ovarian cancer cases, and 458 ovarian cancer controls. Genotyping at <it>TCF7L2 </it>rs12255372 used a 5' endonuclease assay, and statistical analysis used logistic regression among participants as a whole and among <it>a priori</it>-defined subsets.</p> <p>Results</p> <p>No associations with risk of breast or ovarian cancer were observed (ordinal model, p = 0.62 and p = 0.75, respectively). In addition, no associations were observed among sub-groups defined by age, BMI, family history, stage, grade, histology, or tumor behavior.</p> <p>Conclusion</p> <p>Although the biology of the Wnt/β-catenin signaling pathway and prior association between rs12255372 and numerous phenotypes warranted examination of this <it>TCF7L2 </it>SNP, no compelling evidence for association with breast or ovarian cancer was observed.</p

The decline and rise of neighbourhoods: the importance of neighbourhood governance

There is a substantial literature on the explanation of neighbourhood change. Most of this literature concentrates on identifying factors and developments behind processes of decline. This paper reviews the literature, focusing on the identification of patterns of neighbourhood change, and argues that the concept of neighbourhood governance is a missing link in attempts to explain these patterns. Including neighbourhood governance in the explanations of neighbourhood change and decline will produce better explanatory models and, finally, a better view about what is actually steering neighbourhood change

Reliability of a 1-week recall period for the Medical Outcomes Study Sleep Scale (MOS-SS) in patients with fibromyalgia

<p>Abstract</p> <p>Objective</p> <p>To evaluate the reliability of a one-week versus a four-week recall period of the Medical Outcomes Study Sleep Scale (MOS-SS) in patients with fibromyalgia (FM).</p> <p>Methods</p> <p>The MOS-SS was administered by mail to patients with a confirmed diagnosis of FM and a current pain rating of > 2 (0–10 point numerical rating scale) recruited through newspapers, support groups, and the Internet. Reliability of MOS-SS subscale domains was evaluated using test-retest methodology separated by a 1–3 day interval for the 4-week recall period and a 7-day interval for the 1-week recall period. Patient Impression of Change was evaluated for sleep, and for patients with no change, the intraclass correlation coefficient (ICC) and the Pearson correlation coefficient was calculated for MOS-SS subscales.</p> <p>Results</p> <p>Of 129 patients enrolled, 91.3% were female, mean age was 49.4 ± 11.0 years; self-rated FM severity was moderate-to-severe in 88.1% of patients. MOS-SS subscale scores were similar for both recall periods with little variation between test-retest. The 9-item Sleep Problems Index scores ranged from 57.2 ± 14.5 to 61.9 ± 15.8 across all assessments and demonstrated high reliability which was similar for the 1-week (ICC 0.81) and 4-week (ICC 0.89) recall periods. For the other MOS-SS subscales, the 1-week recall period also showed good reliability, which was consistent for the ICC and Pearson correlation coefficients.</p> <p>Conclusion</p> <p>A 1-week recall period is adequately reliable for use of the MOS-SS in studies evaluating sleep disturbance in patients with FM.</p

Discovering gene annotations in biomedical text databases

<p>Abstract</p> <p>Background</p> <p>Genes and gene products are frequently annotated with Gene Ontology concepts based on the evidence provided in genomics articles. Manually locating and curating information about a genomic entity from the biomedical literature requires vast amounts of human effort. Hence, there is clearly a need forautomated computational tools to annotate the genes and gene products with Gene Ontology concepts by computationally capturing the related knowledge embedded in textual data.</p> <p>Results</p> <p>In this article, we present an automated genomic entity annotation system, GEANN, which extracts information about the characteristics of genes and gene products in article abstracts from PubMed, and translates the discoveredknowledge into Gene Ontology (GO) concepts, a widely-used standardized vocabulary of genomic traits. GEANN utilizes textual "extraction patterns", and a semantic matching framework to locate phrases matching to a pattern and produce Gene Ontology annotations for genes and gene products.</p> <p>In our experiments, GEANN has reached to the precision level of 78% at therecall level of 61%. On a select set of Gene Ontology concepts, GEANN either outperforms or is comparable to two other automated annotation studies. Use of WordNet for semantic pattern matching improves the precision and recall by 24% and 15%, respectively, and the improvement due to semantic pattern matching becomes more apparent as the Gene Ontology terms become more general.</p> <p>Conclusion</p> <p>GEANN is useful for two distinct purposes: (i) automating the annotation of genomic entities with Gene Ontology concepts, and (ii) providing existing annotations with additional "evidence articles" from the literature. The use of textual extraction patterns that are constructed based on the existing annotations achieve high precision. The semantic pattern matching framework provides a more flexible pattern matching scheme with respect to "exactmatching" with the advantage of locating approximate pattern occurrences with similar semantics. Relatively low recall performance of our pattern-based approach may be enhanced either by employing a probabilistic annotation framework based on the annotation neighbourhoods in textual data, or, alternatively, the statistical enrichment threshold may be adjusted to lower values for applications that put more value on achieving higher recall values.</p