Background: Excessive sedentary behaviour (sitting) is a risk factor for poor health in children and adults. Incorporating sit-stand desks in the classroom environment has been highlighted as a potential strategy to reduce children's sitting time. The primary aim of this study was to examine the feasibility of conducting a cluster randomised controlled trial (RCT) of a sit-stand desk intervention within primary school classrooms. Methods: We conducted a two-armed pilot cluster RCT involving 8 primary schools in Bradford, United Kingdom. Schools were randomised on a 1:1 basis to the intervention or usual practice control arm. All children (aged 9-10 years) in participating classes were eligible to take part. Six sit-stand desks replaced three standard desks (sitting 6 children) in the intervention classrooms for 4.5-months. Teachers were encouraged to use a rotation system to ensure all pupils were exposed to the sit-stand desks for > 1 h/day on average. Trial feasibility outcomes (assessed using quantitative and qualitative measures) included school and participant recruitment and attrition, intervention and outcome measure completion rates, acceptability, and preliminary effectiveness of the intervention for reducing sitting time. A weighted linear regression model compared changes in weekday sitting time (assessed using the activPAL accelerometer) between trial arms. Results: School and child recruitment rates were 33% (n = 8) and 75% (n = 176). At follow-up, retention rates were 100% for schools and 97% for children. Outcome measure completion rates ranged from 63 to 97%. A preliminary estimate of intervention effectiveness revealed a mean difference in change in sitting of − 30.6 min/day (95% CI: − 56.42 to − 4.84) in favour of the intervention group, after adjusting for baseline sitting and wear time. Qualitative measures revealed the intervention and evaluation procedures were acceptable to teachers and children, except for some problems with activPAL attachment.

Background Sedentary behaviour (sitting) is a highly prevalent negative health behaviour, with individuals of all ages exposed to environments that promote prolonged sitting. The school classroom represents an ideal setting for environmental change through the provision of sit–stand desks. Objectives The aim of this study was to undertake a pilot cluster randomised controlled trial of the introduction of sit–stand desks in primary school classrooms, to inform a definitive trial. Objectives included providing information on school and participant recruitment and retention, acceptability of the intervention, and outcome measures. A preliminary estimate of the intervention’s effectiveness on the proposed primary outcome (change in weekday sitting time) for inclusion in a definitive trial was calculated, along with a preliminary assessment of potential cost-effectiveness. A full process evaluation was also undertaken. Design A two-armed pilot cluster randomised controlled trial with economic and qualitative evaluations. Schools were randomised on a 1 : 1 basis to the intervention (n = 4) or control (n = 4) trial arms. Setting Primary schools in Bradford, West Yorkshire, UK. Participants Children in Year 5 (i.e. aged 9–10 years). Intervention Six sit–stand desks replaced three standard desks (sitting six children) in the intervention classrooms for 4.5 months. Teachers were encouraged to ensure that all pupils were exposed to the sit–stand desks for at least 1 hour per day, on average, using a rotation system. Schools assigned to the control arm continued with their usual practice. Main outcome measures Trial feasibility outcomes included school and participant recruitment and attrition, acceptability of the intervention, and acceptability of and compliance with the proposed outcome measures [including weekday sitting measured using activPAL™ (PAL Technologies Ltd, Glasgow, UK) accelerometers, physical activity, adiposity, blood pressure, cognitive function, musculoskeletal comfort, academic progress, engagement and behaviour]. Results Thirty-three per cent of schools approached and 75% (n = 176) of eligible children took part. At the 7-month follow-up, retention rates were 100% for schools and 97% for children. Outcome measure completion rates ranged from 63% to 97%. A preliminary estimate of intervention effectiveness, from a weighted linear regression model (adjusting for baseline sitting time and wear time) revealed a mean difference in change in sitting of –30.6 minutes per day (95% confidence interval –56.42 to –4.84 minutes per day) between the intervention and control trial arms. The process evaluation revealed that the intervention, recruitment and evaluation procedures were acceptable to teachers and children, with the exception of minor issues around activPAL attachment. A preliminary within-trial economic analysis revealed no difference between intervention and control trial arms in health and education resource use or outcomes. Long-term modelling estimated an unadjusted incremental cost-effectiveness ratio of Stand Out in Class of £78,986 per quality-adjusted life-year gained. Conclusion This study has provided evidence of the acceptability and feasibility of the Stand Out in Class intervention and evaluation methods. Preliminary evidence suggests that the intervention may have a positive direction of effect on weekday sitting time, which warrants testing in a full cluster randomised controlled trial. Lessons learnt from this trial will inform the planning of a definitive trial. Trial registration Current Controlled Trials ISRCTN12915848. Funding This project was funded by the National Institute for Health Research (NIHR) Public Health Research programme and will be published in full in Public Health Research; Vol. 8, No. 8. See the NIHR Journals Library website for further project information.

Background Patients with low estimated glomerular filtration rates may be at higher risk of post-contrast acute kidney injury following contrast-enhanced computed tomography imaging. Point-of-care devices allow rapid measurement of estimated glomerular filtration rates for patients referred without a recent estimated glomerular filtration rate result. Objectives To assess the clinical effectiveness and cost-effectiveness of point-of-care creatinine tests for outpatients without a recent estimated glomerular filtration rate measurement who need contrast-enhanced computed tomography imaging. Methods Three systematic reviews of test accuracy, implementation and clinical outcomes, and economic analyses were carried out. Bibliographic databases were searched from inception to November 2018. Studies comparing the accuracy of point-of-care creatinine tests with laboratory reference tests to assess kidney function in adults in a non-emergency setting and studies reporting implementation and clinical outcomes were included. Risk of bias of diagnostic accuracy studies was assessed using a modified version of the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool. Probabilities of individuals having their estimated glomerular filtration rates correctly classified were estimated within a Bayesian framework and pooled using a fixed-effects model. A de novo probabilistic decision tree cohort model was developed to characterise the decision problem from an NHS and a Personal Social Services perspective. A range of alternative point-of-care testing approaches were considered. Scenario analyses were conducted. Results Fifty-four studies were included in the clinical reviews. Twelve studies reported diagnostic accuracy for estimated glomerular filtration rates; half were rated as being at low risk of bias, but there were applicability concerns for most. i-STAT (Abbott Point of Care, Inc., Princeton, NJ, USA) and ABL (Radiometer Ltd, Crawley, UK) devices had higher probabilities of correctly classifying individuals in the same estimated glomerular filtration rate categories as the reference laboratory test than StatSensor® devices (Nova Biomedical, Runcorn, UK). There was limited evidence for epoc® (Siemens Healthineers AG, Erlangen, Germany) and Piccolo Xpress® (Abaxis, Inc., Union City, CA, USA) devices and no studies of DRI-CHEM NX 500 (Fujifilm Corporation, Tokyo, Japan). The review of implementation and clinical outcomes included six studies showing practice variation in the management decisions when a point-of-care device indicated an abnormal estimated glomerular filtration rate. The review of cost-effectiveness evidence identified no relevant studies. The de novo decision model that was developed included a total of 14 strategies. Owing to limited data, the model included only i-STAT, ABL800 FLEX and StatSensor. In the base-case analysis, the cost-effective strategy appeared to be a three-step testing sequence involving initially screening all individuals for risk factors, point-of-care testing for those individuals with at least one risk factor, and including a final confirmatory laboratory test for individuals with a point-of-care-positive test result. Within this testing approach, the specific point-of-care device with the highest net benefit was i-STAT, although differences in net benefit with StatSensor were very small. Limitations There was insufficient evidence for patients with estimated glomerular filtration rates < 30 ml/minute/1.73 m2, and on the full potential health impact of delayed or rescheduled computed tomography scans or the use of alternative imaging modalities. Conclusions A three-step testing sequence combining a risk factor questionnaire with a point-of-care test and confirmatory laboratory testing appears to be a cost-effective use of NHS resources compared with current practice. The risk of contrast causing acute kidney injury to patients with an estimated glomerular filtration rate of < 30 ml/minute/1.73 m2 is uncertain. Cost-effectiveness of point-of-care testing appears largely driven by the potential of point-of-care tests to minimise delays within the current computed tomography pathway. Future work Studies evaluating the impact of risk-stratifying questionnaires on workflow outcomes in computed tomography patients without recent estimated glomerular filtration rate results are needed. Study registration This study is registered as PROSPERO CRD42018115818. Funding This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 24, No. 39. See the NIHR Journals Library website for further project information.

Background Policy evaluations often focus on ex post estimation of causal effects on short-term surrogate outcomes. The value of such information is limited for decision making, as the failure to reflect policy-relevant outcomes and disregard for opportunity costs prohibits the assessment of value for money. Further, these evaluations do not always consider all relevant evidence, other courses of action, or decision uncertainty. Methods In this article, we explore how policy evaluation could better meet the needs of decision making. We begin by defining the evidence required to inform decision making. We then conduct a literature review of challenges in evaluating policies. Finally, we highlight potential methods available to help address these challenges. Results The evidence required to inform decision making includes the impacts on the policy-relevant outcomes, the costs and associated opportunity costs, and the consequences of uncertainty. Challenges in evaluating health policies are described using 8 categories: 1) valuation space; 2) comparators; 3) time of evaluation; 4) mechanisms of action; 5) effects; 6) resources, constraints, and opportunity costs; 7) fidelity, adaptation, and level of implementation; and 8) generalizability and external validity. Methods from a broad set of disciplines are available to improve policy evaluation, relating to causal inference, decision-analytic modeling, theory of change, realist evaluation, and structured expert elicitation. Limitations The targeted review may not identify all possible challenges, and the methods covered are not exhaustive. Conclusions Evaluations should provide appropriate evidence to inform decision making. There are challenges in evaluating policies, but methods from multiple disciplines are available to address these challenges. Implications Evaluators need to carefully consider the decision being informed, the necessary evidence to inform it, and the appropriate methods. [Box: see text]

Background Healthcare decision makers require accurate long-term economic models to evaluate the cost-effectiveness of new mental health interventions. Aims To assess the suitability of current patient-level economic models to estimate long-term economic outcomes in severe mental illness. Method We undertook pre-specified systematic searches in MEDLINE, Embase and PsycINFO to identify reviews and stand-alone publications of economic models of interventions for schizophrenia, bipolar disorder and major depressive disorder (PROSPERO: CRD42020158243). We screened paper titles and abstracts to identify unique patient-level economic models. We conducted a structured extraction of identified models, recording the presence of key predefined model features. Model quality and validation were appraised using the 2014 ISPOR and 2016 AdViSHE model checklists. Results We identified 15 unique patient-level models for psychosis and major depressive disorder from 1481 non-duplicate records. Models addressed schizophrenia (n = 6), bipolar disorder (n = 2) and major depressive disorder (n = 7). The predominant model type was discrete event simulation (n = 9). Model complexity and incorporation of patient heterogeneity varied considerably, and only five models extrapolated costs and outcomes over a lifetime horizon. Key model parameters were often based on low-quality evidence, and checklist quality assessment revealed weak model verification procedures. Conclusions Existing patient-level economic models of interventions for severe mental illness have considerable limitations. New modelling efforts must be supplemented by the generation of good-quality, contemporary evidence suitable for model building. Combined effort across the research community is required to build and validate economic extrapolation models suitable for accurately assessing the long-term value of new interventions from short-term clinical trial data.