Understanding and Measuring the Wellbeing of Carers of People With Dementia

Background and Objectives  To determine how the wellbeing of carers of people with dementia is understood and measured in contemporary health research.  Research Design and Methods  A systematic review of reviews was designed, registered with PROSPERO, and then conducted. This focused on systematic reviews of research literature published from 2010 onwards; with the wellbeing of carers of people with dementia being a primary focus. N = 19 studies met the inclusion criteria. Quality appraisal was conducted using the AMSTAR tool (2015). A narrative synthesis was conducted to explore how wellbeing is currently being understood and measured.  Results  Contemporary health research most frequently conceptualizes wellbeing in the context of a loss–deficit model. Current healthcare research has not kept pace with wider discussions surrounding wellbeing which have become both more complex and more sophisticated. Relying on the loss–deficit model limits current research in understanding and measuring the lived experience of carers of people with dementia. There remains need for a clear and consistent measurement of wellbeing.  Discussion and Implications  Without clear consensus, health professionals must be careful when using the term “wellbeing”. To help inform healthcare policy and practice, we offer a starting point for a richer concept of wellbeing in the context of dementia that is multi-faceted to include positive dimensions of caregiving in addition to recognized aspects of burden. Standardized and robust measurements are needed to enhance research and there may be benefit from developing a more mixed, blended approach to measurement

Tocilizumab in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial

Background: In this study, we aimed to evaluate the effects of tocilizumab in adult patients admitted to hospital with COVID-19 with both hypoxia and systemic inflammation. Methods: This randomised, controlled, open-label, platform trial (Randomised Evaluation of COVID-19 Therapy [RECOVERY]), is assessing several possible treatments in patients hospitalised with COVID-19 in the UK. Those trial participants with hypoxia (oxygen saturation <92% on air or requiring oxygen therapy) and evidence of systemic inflammation (C-reactive protein ≥75 mg/L) were eligible for random assignment in a 1:1 ratio to usual standard of care alone versus usual standard of care plus tocilizumab at a dose of 400 mg–800 mg (depending on weight) given intravenously. A second dose could be given 12–24 h later if the patient's condition had not improved. The primary outcome was 28-day mortality, assessed in the intention-to-treat population. The trial is registered with ISRCTN (50189673) and ClinicalTrials.gov (NCT04381936). Findings: Between April 23, 2020, and Jan 24, 2021, 4116 adults of 21 550 patients enrolled into the RECOVERY trial were included in the assessment of tocilizumab, including 3385 (82%) patients receiving systemic corticosteroids. Overall, 621 (31%) of the 2022 patients allocated tocilizumab and 729 (35%) of the 2094 patients allocated to usual care died within 28 days (rate ratio 0·85; 95% CI 0·76–0·94; p=0·0028). Consistent results were seen in all prespecified subgroups of patients, including those receiving systemic corticosteroids. Patients allocated to tocilizumab were more likely to be discharged from hospital within 28 days (57% vs 50%; rate ratio 1·22; 1·12–1·33; p<0·0001). Among those not receiving invasive mechanical ventilation at baseline, patients allocated tocilizumab were less likely to reach the composite endpoint of invasive mechanical ventilation or death (35% vs 42%; risk ratio 0·84; 95% CI 0·77–0·92; p<0·0001). Interpretation: In hospitalised COVID-19 patients with hypoxia and systemic inflammation, tocilizumab improved survival and other clinical outcomes. These benefits were seen regardless of the amount of respiratory support and were additional to the benefits of systemic corticosteroids. Funding: UK Research and Innovation (Medical Research Council) and National Institute of Health Research

Assessment of flow changes from hydropower development and operations in Sekong, Sesan and Srepok Rivers of the Mekong Basin

The Mekong River supports unique biodiversity and provides food security for over sixty million people in the Indo-Burma region, but potential changes to natural flow patterns from hydropower development are a major risk to the wellbeing of this system. Of particular concern is the ongoing and future development of 42 dams in the transboundary Srepok, Sesan and Sekong (3S) Basin which contributes up to 20% of the Mekong's annual flows and provides critical ecosystem services to the downstream Tonle Sap Lake and the Mekong Delta. To assess the magnitude of potential changes, daily flows were simulated over 20 years using the HEC ResSim and SWAT models for a range of dam operations and development scenarios. A 63% increase in dry season flows and a 22% decrease in wet season flows at the outlet of the 3S Basin can result from the potential development of new dams in the main 3S Rivers under an operation scheme to maximize electricity production. Water level changes in the Mekong River from this scenario are comparable to changes induced by the current development of Chinese dams in the Upper Mekong Basin and are significantly higher than potential flow changes from the proposed 11 mainstream dams in the Lower Mekong Basin. Dams on the upper sub tributaries of the 3S Basin have very low impacts on seasonal flow regimes because most of those projects are run-of-river dams and have small reservoir storages. Impacts on hourly flow changes due to intra daily reservoir operations, sediment movement, water quality and ecology need further study. Strategic site selection and coordinated reservoir operations between countries are necessary to achieve an acceptable level of development in the basin and mitigate negative impacts to seasonal flow patterns which sustain downstream ecosystem productivity and livelihoods

Device-based measures of sit-to-stand and stand-to-sit transitions of healthy working adults, 2020,Dataset belonging to "The temporal dynamics of sitting and standing at work, 2020"

Item does not contain fulltextThis data folder contains all processed data and analyses scripts used for analyses in the research described in the PNAS paper "The Temporal Dynamics of Sitting Behaviour at Work" by ten Broeke and colleagues (2020). In the paper, sitting behaviour was conceptualised as a continuous chain of sit-to-stand and stand-to-sit transitions, and multilevel time-to-event analysis was used to analyse the timing of these transitions. The data comprise ~30,000 posture transitions during work time from 156 UK-based employees from various work sites, objectively-measured by an activPAL monitor that was continuously worn for approximately one week. For the paper, a split-samples cross-validation procedure was used. Prior to looking at the data, we randomly split the data into two samples of equal size: A training sample (n = 79; 7,316 sit-to-stand and 7,263 stand-to-sit transitions) and a testing sample (n = 77; 7,216 sit-to-stand and 7,158 stand-to-sit transitions). We used the training sample for data exploration and fine-tuning of analyses and analytical decisions. After this, we preregistered our analysis plan for the testing sample and performed these analyses on the testing sample. Unless otherwise specified, in the paper we report results from the preregistered analyses on the testing sample. A more detailed description of the procedure and all measures is given in the Methodology file. The readme file describes the content and function of all files in the data folder, and all terminology and abbreviations used in the data sets and analyses scripts. The R markdown files and HTML output files contain all R code that was used for data processing, analysis, and visualization, and the power simulation.nul

Device-based measures of sit-to-stand and stand-to-sit transitions of healthy working adults, 2020: Dataset belonging to “The temporal dynamics of sitting and standing at work, 2020”

This data folder contains all processed data and analyses scripts used for analyses in the research described in the PNAS paper "The Temporal Dynamics of Sitting Behaviour at Work" by ten Broeke and colleagues (2020). In the paper, sitting behaviour was conceptualised as a continuous chain of sit-to-stand and stand-to-sit transitions, and multilevel time-to-event analysis was used to analyse the timing of these transitions. The data comprise ~30,000 posture transitions during work time from 156 UK-based employees from various work sites, objectively-measured by an activPAL monitor that was continuously worn for approximately one week. For the paper, a split-samples cross-validation procedure was used. Prior to looking at the data, we randomly split the data into two samples of equal size: A training sample (n = 79; 7,316 sit-to-stand and 7,263 stand-to-sit transitions) and a testing sample (n = 77; 7,216 sit-to-stand and 7,158 stand-to-sit transitions). We used the training sample for data exploration and fine-tuning of analyses and analytical decisions. After this, we preregistered our analysis plan for the testing sample and performed these analyses on the testing sample. Unless otherwise specified, in the paper we report results from the preregistered analyses on the testing sample. A more detailed description of the procedure and all measures is given in the Methodology file. The readme file describes the content and function of all files in the data folder, and all terminology and abbreviations used in the data sets and analyses scripts. The R markdown files and HTML output files contain all R code that was used for data processing, analysis, and visualization, and the power simulation

Dataset belonging to “The temporal dynamics of sitting and standing at work, 2020”

This data folder contains all processed data and analyses scripts used for analyses in the research described in the PNAS paper "The Temporal Dynamics of Sitting Behaviour at Work" by ten Broeke and colleagues (2020). In the paper, sitting behaviour was conceptualised as a continuous chain of sit-to-stand and stand-to-sit transitions, and multilevel time-to-event analysis was used to analyse the timing of these transitions. The data comprise ~30,000 posture transitions during work time from 156 UK-based employees from various work sites, objectively-measured by an activPAL monitor that was continuously worn for approximately one week. For the paper, a split-samples cross-validation procedure was used. Prior to looking at the data, we randomly split the data into two samples of equal size: A training sample (n = 79; 7,316 sit-to-stand and 7,263 stand-to-sit transitions) and a testing sample (n = 77; 7,216 sit-to-stand and 7,158 stand-to-sit transitions). We used the training sample for data exploration and fine-tuning of analyses and analytical decisions. After this, we preregistered our analysis plan for the testing sample and performed these analyses on the testing sample. Unless otherwise specified, in the paper we report results from the preregistered analyses on the testing sample. A more detailed description of the procedure and all measures is given in the Methodology file. The readme file describes the content and function of all files in the data folder, and all terminology and abbreviations used in the data sets and analyses scripts. The R markdown files and HTML output files contain all R code that was used for data processing, analysis, and visualization, and the power simulation