78 research outputs found

    Old Goucher neighborhood : strengthening a community identity through an exploration of the past

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    "University of Maryland School of Architecture, Planning & Preservation, Graduate Program in Historic Preservation, Fall 2013.

    Machine Learning Model Based on Transthoracic Bioimpedance and Heart Rate Variability for Lung Fluid Accumulation Detection: Prospective Clinical Study

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    BACKGROUND: Accumulation of excess body fluid and autonomic dysregulation are clinically important characteristics of acute decompensated heart failure. We hypothesized that transthoracic bioimpedance, a noninvasive, simple method for measuring fluid retention in lungs, and heart rate variability, an assessment of autonomic function, can be used for detection of fluid accumulation in patients with acute decompensated heart failure. OBJECTIVE: We aimed to evaluate the performance of transthoracic bioimpedance and heart rate variability parameters obtained using a fluid accumulation vest with carbon black-polydimethylsiloxane dry electrodes in a prospective clinical study (System for Heart Failure Identification Using an External Lung Fluid Device; SHIELD). METHODS: We computed 15 parameters: 8 were calculated from the model to fit Cole-Cole plots from transthoracic bioimpedance measurements (extracellular, intracellular, intracellular-extracellular difference, and intracellular-extracellular parallel circuit resistances as well as fitting error, resonance frequency, tissue heterogeneity, and cellular membrane capacitance), and 7 were based on linear (mean heart rate, low-frequency components of heart rate variability, high-frequency components of heart rate variability, normalized low-frequency components of heart rate variability, normalized high-frequency components of heart rate variability) and nonlinear (principal dynamic mode index of sympathetic function, and principal dynamic mode index of parasympathetic function) analysis of heart rate variability. We compared the values of these parameters between 3 participant data sets: control (n=32, patients who did not have heart failure), baseline (n=23, patients with acute decompensated heart failure taken at the time of admittance to the hospital), and discharge (n=17, patients with acute decompensated heart failure taken at the time of discharge from hospital). We used several machine learning approaches to classify participants with fluid accumulation (baseline) and without fluid accumulation (control and discharge), termed with fluid and without fluid groups, respectively. RESULTS: Among the 15 parameters, 3 transthoracic bioimpedance (extracellular resistance, R0; difference in extracellular-intracellular resistance, R0 - Rinfinity, and tissue heterogeneity, alpha) and 3 heart rate variability (high-frequency, normalized low-frequency, and normalized high-frequency components) parameters were found to be the most discriminatory between groups (patients with and patients without heart failure). R0 and R0 - Rinfinity had significantly lower values for patients with heart failure than for those without heart failure (R0: P=.006; R0 - Rinfinity: P=.001), indicating that a higher volume of fluids accumulated in the lungs of patients with heart failure. A cubic support vector machine model using the 5 parameters achieved an accuracy of 92% for with fluid and without fluid group classification. The transthoracic bioimpedance parameters were related to intra- and extracellular fluid, whereas the heart rate variability parameters were mostly related to sympathetic activation. CONCLUSIONS: This is useful, for instance, for an in-home diagnostic wearable to detect fluid accumulation. Results suggest that fluid accumulation, and subsequently acute decompensated heart failure detection, could be performed using transthoracic bioimpedance and heart rate variability measurements acquired with a wearable vest. Emily Ensom, Eric Ding, Anna Hayes, Jarno Riistama, Chad Darling, David McManus, Ki H. Chon. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 27.08.2020

    Barriers and facilitators to implementation of menu labelling interventions from a food service industry perspective: a mixed methods systematic review

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    BACKGROUND: Eating outside the home contributes to poor dietary habits worldwide and is associated with increased body fat and weight gain. Evidence shows menu labelling is effective in promoting healthier food choices; however, implementation issues have arisen. The purpose of this systematic review was to synthesise the evidence on the perceived barriers and facilitators to implementation of menu labelling interventions from the perspective of the food service industry. METHODS: Peer-reviewed and grey literature were searched using databases, specialised search engines and public health organisation websites. Screening reference lists, citation chaining and contacting authors of all included studies were undertaken. Primary research studies relevant to direct supply-side stakeholders were eligible for inclusion. There were no restrictions on menu labelling scheme or format, study methods, publication year or language. At least two independent reviewers performed study selection, data extraction and quality appraisal. The results were synthesised using the 'best fit' framework synthesis approach, with reference to the Consolidated Framework for Implementation Research (CFIR). RESULTS: Seventeen studies met the eligibility criteria, with the majority rated as average quality (n =¿10). The most frequently cited barriers were coded to the CFIR constructs 'Consumer Needs & Resources' (e.g. lack of customer demand for/interest in menu labelling, risk of overwhelmed/confused customers) and 'Compatibility' with organisation work processes (e.g. lack of standardised recipes, limited space on menus). Frequently cited facilitators were coded to the CFIR constructs 'Relative Advantage' of menu labelling (e.g. improved business image/reputation) and 'Consumer Needs & Resources' (e.g. customer demand for/interest in menu labelling, providing nutrition information to customers). An adapted framework consisting of a priori and new constructs was developed, which illustrates the relationships between domains. CONCLUSION: This review generates an adapted CFIR framework for understanding implementation of menu labelling interventions. It highlights that implementation is influenced by multiple interdependent factors, particularly related to the external and internal context of food businesses, and features of the menu labelling intervention. The findings can be used by researchers and practitioners to develop or select strategies to address barriers that impede implementation and to leverage facilitators that assist with implementation effort

    Assessing the pre-implementation context for financial navigation in rural and non-rural oncology clinics

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    BackgroundFinancial navigation (FN) is an evidence-based intervention designed to address financial toxicity for cancer patients. FN's success depends on organizations' readiness to implement and other factors that may hinder or support implementation. Tailored implementation strategies can support practice change but must be matched to the implementation context. We assessed perceptions of readiness and perceived barriers and facilitators to successful implementation among staff at nine cancer care organizations (5 rural, 4 non-rural) recruited to participate in the scale-up of a FN intervention. To understand differences in the pre-implementation context and inform modifications to implementation strategies, we compared findings between rural and non-rural organizations.MethodsWe conducted surveys (n = 78) and in-depth interviews (n = 73) with staff at each organization. We assessed perceptions of readiness using the Organizational Readiness for Implementing Change (ORIC) scale. In-depth interviews elicited perceived barriers and facilitators to implementing FN in each context. We used descriptive statistics to analyze ORIC results and deductive thematic analysis, employing a codebook guided by the Consolidated Framework for Implementation Research (CFIR), to synthesize themes in barriers and facilitators across sites, and by rurality.ResultsResults from the ORIC scale indicated strong perceptions of organizational readiness across all sites. Staff from rural areas reported greater confidence in their ability to manage the politics of change (87% rural, 76% non-rural) and in their organization's ability to support staff adjusting to the change (96% rural, 75% non-rural). Staff at both rural and non-rural sites highlighted factors reflective of the Intervention Characteristics (relative advantage) and Implementation Climate (compatibility and tension for change) domains as facilitators. Although few barriers to implementation were reported, differences arose between rural and non-rural sites in these perceived barriers, with non-rural staff more often raising concerns about resistance to change and compatibility with existing work processes and rural staff more often raising concerns about competing time demands and limited resources.ConclusionsStaff across both rural and non-rural settings identified few, but different, barriers to implementing a novel FN intervention that they perceived as important and responsive to patients' needs. These findings can inform how strategies are tailored to support FN in diverse oncology practices

    Quantifying HIV transmission flow between high-prevalence hotspots and surrounding communities: a population-based study in Rakai, Uganda

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    Background International and global organisations advocate targeting interventions to areas of high HIV prevalence (ie, hotspots). To better understand the potential benefits of geo-targeted control, we assessed the extent to which HIV hotspots along Lake Victoria sustain transmission in neighbouring populations in south-central Uganda. Methods We did a population-based survey in Rakai, Uganda, using data from the Rakai Community Cohort Study. The study surveyed all individuals aged 15–49 years in four high-prevalence Lake Victoria fishing communities and 36 neighbouring inland communities. Viral RNA was deep sequenced from participants infected with HIV who were antiretroviral therapy-naive during the observation period. Phylogenetic analysis was used to infer partial HIV transmission networks, including direction of transmission. Reconstructed networks were interpreted through data for current residence and migration history. HIV transmission flows within and between high-prevalence and low-prevalence areas were quantified adjusting for incomplete sampling of the population. Findings Between Aug 10, 2011, and Jan 30, 2015, data were collected for the Rakai Community Cohort Study. 25 882 individuals participated, including an estimated 75·7% of the lakeside population and 16·2% of the inland population in the Rakai region of Uganda. 5142 participants were HIV-positive (2703 [13·7%] in inland and 2439 [40·1%] in fishing communities). 3878 (75·4%) people who were HIV-positive did not report antiretroviral therapy use, of whom 2652 (68·4%) had virus deep-sequenced at sufficient quality for phylogenetic analysis. 446 transmission networks were reconstructed, including 293 linked pairs with inferred direction of transmission. Adjusting for incomplete sampling, an estimated 5·7% (95% credibility interval 4·4–7·3) of transmissions occurred within lakeside areas, 89·2% (86·0–91·8) within inland areas, 1·3% (0·6–2·6) from lakeside to inland areas, and 3·7% (2·3–5·8) from inland to lakeside areas. Interpretation Cross-community HIV transmissions between Lake Victoria hotspots and surrounding inland populations are infrequent and when they occur, virus more commonly flows into rather than out of hotspots. This result suggests that targeted interventions to these hotspots will not alone control the epidemic in inland populations, where most transmissions occur. Thus, geographical targeting of high prevalence areas might not be effective for broader epidemic control depending on underlying epidemic dynamics. Funding The Bill & Melinda Gates Foundation, the National Institute of Allergy and Infectious Diseases, the National Institute of Mental Health, the National Institute of Child Health and Development, the Division of Intramural Research of the National Institute for Allergy and Infectious Diseases, the World Bank, the Doris Duke Charitable Foundation, the Johns Hopkins University Center for AIDS Research, and the President's Emergency Plan for AIDS Relief through the Centers for Disease Control and Prevention

    The UK stand together trial: protocol for a multicentre cluster randomised controlled trial to evaluate the effectiveness and cost-effectiveness of KiVa to reduce bullying in primary schools

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    Background Reducing bullying is a public health priority. KiVa, a school-based anti-bullying programme, is effective in reducing bullying in Finland and requires rigorous testing in other countries, including the UK. This trial aims to test the effectiveness and cost-effectiveness of KiVa in reducing child reported bullying in UK schools compared to usual practice. The trial is currently on-going. Recruitment commenced in October 2019, however due to COVID-19 pandemic and resulting school closures was re-started in October 2020. Methods Design: Two-arm pragmatic multicentre cluster randomised controlled trial with an embedded process and cost-effectiveness evaluation. Participants: 116 primary schools from four areas; North Wales, West Midlands, South East and South West England. Outcomes will be assessed at student level (ages 7–11 years; n = approximately 13,000 students). Intervention: KiVa is a whole school programme with universal actions that places a strong emphasis on changing bystander behaviour alongside indicated actions that provide consistent strategies for dealing with incidents of bullying. KiVa will be implemented over one academic year. Comparator: Usual practice. Primary outcome: Student-level bullying-victimisation assessed through self-report using the extensively used and validated Olweus Bully/Victim questionnaire at baseline and 12-month follow-up. Secondary outcomes: student-level bullying-perpetration; student mental health and emotional well-being; student level of, and roles in, bullying; school related well-being; school attendance and academic attainment; and teachers’ self-efficacy in dealing with bullying, mental well-being, and burnout. Sample size: 116 schools (58 per arm) with an assumed ICC of 0.02 will provide 90% power to identify a relative reduction of 22% with a 5% significance level. Randomisation: recruited schools will be randomised on 1:1 basis stratified by Key-Stage 2 size and free school meal status. Process evaluation: assess implementation fidelity, identify influences on KiVa implementation, and examine intervention mechanisms. Economic evaluation: Self-reported victimisation, Child Health Utility 9D, Client Service Receipt Inventory, frequency of services used, and intervention costs. The health economic analysis will be conducted from a schools and societal perspective. Discussion This two-arm pragmatic multicentre cluster randomised controlled trial will evaluate the KiVa anti-bullying intervention to generate evidence of the effectiveness, cost-effectiveness and scalability of the programme in the UK. Our integrated process evaluation will assess implementation fidelity, identify influences on KiVa implementation across England and Wales and examine intervention mechanisms. The integrated health economic analysis will be conducted from a schools and societal perspective. Our trial will also provide evidence regarding the programme impact on inequalities by testing whether KiVa is effective across the socio-economic gradient

    Prevention and treatment of long-term social disability amongst young people with emerging severe mental illness with social recovery therapy (The PRODIGY Trial): Study protocol for a randomised controlled trial

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    © 2017 The Author(s). Background: Young people who have social disability associated with severe and complex mental health problems are an important group in need of early intervention. Their problems often date back to childhood and become chronic at an early age. Without intervention, the long-term prognosis is often poor and the economic costs very large. There is a major gap in the provision of evidence-based interventions for this group, and therefore new approaches to detection and intervention are needed. This trial provides a definitive evaluation of a new approach to early intervention with young people with social disability and severe and complex mental health problems using social recovery therapy (SRT) over a period of 9 months to improve mental health and social recovery outcomes. Methods: This is a pragmatic, multi-centre, single blind, superiority randomised controlled trial. It is conducted in three sites in the UK: Sussex, Manchester and East Anglia. Participants are aged 16 to 25 and have both persistent and severe social disability (defined as engaged in less than 30 hours per week of structured activity) and severe and complex mental health problems. The target sample size is 270 participants, providing 135 participants in each trial arm. Participants are randomised 1:1 using a web-based randomisation system and allocated to either SRT plus optimised treatment as usual (enhanced standard care) or enhanced standard care alone. The primary outcome is time use, namely hours spent in structured activity per week at 15 months post-randomisation. Secondary outcomes assess typical mental health problems of the group, including subthreshold psychotic symptoms, negative symptoms, depression and anxiety. Time use, secondary outcomes and health economic measures are assessed at 9, 15 and 24 months post-randomisation. Discussion: This definitive trial will be the first to evaluate a novel psychological treatment for social disability and mental health problems in young people presenting with social disability and severe and complex non-psychotic mental health problems. The results will have important implications for policy and practice in the detection and early intervention for this group in mental health services. Trial registration: Trial Registry: International Standard Randomised Controlled Trial Number (ISRCTN) Registry. Trial Registration Number: ISRCTN47998710(registered 29/11/2012)
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