Explore the vast range of titles available.

ObjectivesTo understand self-reported potential cancer symptom help-seeking behaviours and attitudes during the first 6 months (March–August 2020) of the UK COVID-19 pandemic.DesignUK population-based survey conducted during August and September 2020. Correlates of help-seeking behaviour were modelled using logistic regression in participants reporting potential cancer symptoms during the previous 6 months. Qualitative telephone interviews with a purposeful subsample of participants, analysed thematically.SettingOnline UK wide survey.Participants7543 adults recruited via Cancer Research UK online panel provider (Dynata) and HealthWise Wales (a national register of ‘research ready’ participants) supplemented with social media (Facebook and Twitter) recruitment. 30 participants were also interviewed.Main outcome measuresSurvey measures included experiences of 15 potential cancer symptoms, help-seeking behaviour, barriers and prompts to help-seeking.ResultsOf 3025 (40.1%) participants who experienced a potential cancer symptom, 44.8% (1355/3025) had not contacted their general practitioner (GP). Odds of help-seeking were higher among participants with disability (adjusted OR (aOR)=1.38, 95% CI 1.11 to 1.71) and who experienced more symptoms (aOR=1.68, 95% CI 1.56 to 1.82), and lower among those who perceived COVID-19 as the cause of symptom(s) (aOR=0.36, 95% CI 0.25 to 0.52). Barriers included worries about wasting the doctor’s time (1158/7543, 15.4%), putting strain on healthcare services (945, 12.6%) and not wanting to make a fuss (907, 12.0%). Interviewees reported reluctance to contact the GP due to concerns about COVID-19 and fear of attending hospitals, and described putting their health concerns on hold.ConclusionsMany people avoided healthcare services despite experiencing potential cancer symptoms during the COVID-19 pandemic. Alongside current help-seeking campaigns, well-timed and appropriate nationally coordinated campaigns should signal that services are open safely for those with unusual or persistent symptoms.Trial registration numberISRCTN17782018.

In virtual screening for drug discovery, hit enrichment curves are widely used to assess the performance of ranking algorithms with regard to their ability to identify early enrichment. Unfortunately, researchers almost never consider the uncertainty associated with estimating such curves before declaring differences between performance of competing algorithms. Uncertainty is often large because the testing fractions of interest to researchers are small. Appropriate inference is complicated by two sources of correlation that are often overlooked: correlation across different testing fractions within a single algorithm, and correlation between competing algorithms. Additionally, researchers are often interested in making comparisons along the entire curve, not only at a few testing fractions. We develop inferential procedures to address both the needs of those interested in a few testing fractions, as well as those interested in the entire curve. For the former, four hypothesis testing and (pointwise) confidence intervals are investigated, and a newly developed EmProc approach is found to be most effective. For inference along entire curves, EmProc-based confidence bands are recommended for simultaneous coverage and minimal width. While we focus on the hit enrichment curve, this work is also appropriate for lift curves that are used throughout the machine learning community. Our inferential procedures trivially extend to enrichment factors, as well.

Diversifying diets and agricultural enterprises with fruit and vegetables is a potent weapon in the current global battle against malnutrition and poverty. Agricultural science can contribute substantially to enhance the development prospects and health of not only disadvantaged and vulnerable individuals at one end of the spectrum but also the growth and equity of national economies at the other. Moreover, with relatively simple applied research, new crop species and technologies can rapidly enter the development pathway to benefit even the poorest people or nations. More upstream research can help to guard fruit and vegetable production against the vagaries of potential climatic uncertainty, which is projected to become more prominent over future decades. However, historical and continuing widespread underinvestment in fruit and vegetable research and development from the national to the global level may severely compromise the world's ability to use such high-value species for crop diversification and as a major engine of development growth to ensure global food and nutritional security.

Background COVID-19 related lockdowns may have affected engagement in health behaviours among the UK adult population. This prospective observational study assessed socio-demographic patterning in attempts to change and maintain a range of health behaviours and changes between two time points during the pandemic. Methods Adults aged 18 years and over ( n  = 4,978) were recruited using Dynata (an online market research platform) and the HealthWise Wales platform, supplemented through social media advertising. Online surveys were conducted in August/September 2020 when lockdown restrictions eased in the UK following the first major UK lockdown (survey phase 1) and in February/March 2021 during a further national lockdown (survey phase 2). Measures derived from the Cancer Awareness Measure included self-reported attempts to reduce alcohol consumption, increase fruit/vegetable consumption, increase physical activity, lose weight and reduce/stop smoking. Multivariable logistic regressions were used to assess individual health behaviour change attempts over time, adjusted for age, sex, ethnicity, employment and education. Results Around half of participants in survey phase 1 reported trying to increase physical activity ( n  = 2607, 52.4%), increase fruit/vegetables ( n  = 2445, 49.1%) and lose weight ( n  = 2413, 48.5%), with 19.0% ( n  = 948) trying to reduce alcohol consumption among people who drink. Among the 738 participants who smoked, 51.5% ( n  = 380) were trying to reduce and 27.4% ( n  = 202) to stop smoking completely. Most behaviour change attempts were more common among women, younger adults and minority ethnic group participants. Efforts to reduce smoking (aOR: 0.98, 95% CI: 0.82–1.17) and stop smoking (aOR: 0.98, 95% CI: 0.80–1.20) did not differ significantly in phase 2 compared to phase 1. Similarly, changes over time in attempts to improve other health behaviours were not statistically significant: physical activity (aOR: 1.07; 95% CI: 0.99–1.16); weight loss (aOR: 0.95; 95% CI: 0.90–1.00); fruit/vegetable intake (aOR: 0.98, 95% CI: 0.91–1.06) and alcohol use (aOR: 1.32, 95% CI: 0.92–1.91). Conclusion A substantial proportion of participants reported attempts to change health behaviours in the initial survey phase. However, the lack of change observed over time indicated that overall motivation to engage in healthy behaviours was sustained among the UK adult population, from a period shortly after the first lockdown toward the end of the second prolonged lockdown.

Permeation of chemical solutes through skin can create major health issues. Using the membrane-coated fiber (MCF) as a solid phase membrane extraction (SPME) approach to simulate skin permeation, we obtained partition coefficients for 37 solutes under 90 treatment combinations that could broadly represent formulations that could be associated with occupational skin exposure. These formulations were designed to mimic fluids in the metalworking process, and they are defined in this manuscript using: one of mineral oil, polyethylene glycol-200, soluble oil, synthetic oil, or semi-synthetic oil; at a concentration of 0.05 or 0.5 or 5 percent; with solute concentration of 0.01, 0.05, 0.1, 0.5, 1, or 5 ppm. A single linear free-energy relationship (LFER) model was shown to be inadequate, but extensions that account for experimental conditions provide important improvements in estimating solute partitioning from selected formulations into the MCF. The benefit of the Expanded Nested-Solute-Concentration LFER model over the Expanded Crossed-Factors LFER model is only revealed through a careful leave-one-solute-out cross-validation that properly addresses the existence of replicates to avoid an overly optimistic view of predictive power. Finally, the partition theory that accompanies the MCF approach is thoroughly tested and found to not be supported under complex experimental settings that mimic occupational exposure in the metalworking industry.

Background Paediatric mortality rates in the United Kingdom are amongst the highest in Europe. Clinically missed deterioration is a contributory factor. Evidence to support any single intervention to address this problem is limited, but a cumulative body of research highlights the need for a systems approach. Methods An evidence-based, theoretically informed, paediatric early warning system improvement programme (PUMA Programme) was developed and implemented in two general hospitals (no onsite Paediatric Intensive Care Unit) and two tertiary hospitals (with onsite Paediatric Intensive Care Unit) in the United Kingdom. Designed to harness local expertise to implement contextually appropriate improvement initiatives, the PUMA Programme includes a propositional model of a paediatric early warning system, system assessment tools, guidance to support improvement initiatives and structured facilitation and support. Each hospital was evaluated using interrupted time series and qualitative case studies. The primary quantitative outcome was a composite metric (adverse events), representing the number of children monthly that experienced one of the following: mortality, cardiac arrest, respiratory arrest, unplanned admission to Paediatric Intensive Care Unit, or unplanned admission to Higher Dependency Unit. System changes were assessed qualitatively through observations of clinical practice and interviews with staff and parents. A qualitative evaluation of implementation processes was undertaken. Results All sites assessed their paediatric early warning systems and identified areas for improvement. All made contextually appropriate system changes, despite implementation challenges. There was a decline in the adverse event rate trend in three sites; in one site where system wide changes were organisationally supported, the decline was significant (ß = -0.09 (95% CI: − 0.15, − 0.05); p  = < 0.001). Changes in trends coincided with implementation of site-specific changes. Conclusions System level change to improve paediatric early warning systems can bring about positive impacts on clinical outcomes, but in paediatric practice, where the patient population is smaller and clinical outcomes event rates are low, alternative outcome measures are required to support research and quality improvement beyond large specialist centres, and methodological work on rare events is indicated. With investment in the development of alternative outcome measures and methodologies, programmes like PUMA could improve mortality and morbidity in paediatrics and other patient populations.

Background/aims The value of using qualitative methods within clinical trials is widely recognised. How qualitative research is integrated within trials units to achieve this is less clear. This paper describes the process through which qualitative research has been integrated within Cardiff University’s Centre for Trials Research (CTR) in Wales, UK. We highlight facilitators of, and challenges to, integration. Methods We held group discussions on the work of the Qualitative Research Group (QRG) within CTR. The content of these discussions, materials for a presentation in CTR, and documents relating to the development of the QRG were interpreted at a workshop attended by group members. Normalisation Process Theory (NPT) was used to structure analysis. A writing group prepared a document for input from members of CTR, forming the basis of this paper. Results Actions to integrate qualitative research comprised: its inclusion in Centre strategies; formation of a QRG with dedicated funding/roles; embedding of qualitative research within operating systems; capacity building/training; monitoring opportunities to include qualitative methods in studies; maximising the quality of qualitative research and developing methodological innovation. Facilitators of these actions included: the influence of the broader methodological landscape within trial/study design and its promotion of the value of qualitative research; and close physical proximity of CTR qualitative staff/students allowing sharing of methodological approaches. Introduction of innovative qualitative methods generated interest among other staff groups. Challenges included: pressure to under-resource qualitative components of research, preference for a statistical stance historically in some research areas and funding structures, and difficulties faced by qualitative researchers carving out individual academic profiles when working across trials/studies. Conclusions Given that CTUs are pivotal to the design and conduct of RCTs and related study types across multiple disciplines, integrating qualitative research into trials units is crucial if its contribution is to be fully realised. We have made explicit one trials unit’s experience of embedding qualitative research and present this to open dialogue on ways to operationalise and optimise qualitative research in trials. NPT provides a valuable framework with which to theorise these processes, including the importance of sense-making and legitimisation when introducing new practices within organisations.

Background The UK government ‘Everyone In’ initiative in response to COVID-19 in England saw an unprecedented number of individuals experiencing homelessness moved into temporary accommodation (TA). A limited supply of settled housing meant swift access to settled accommodation (SA) would not be possible for all. This pilot RCT pursued a unique opportunity to examine the feasibility and acceptability of randomising people experiencing homelessness (PEH) to SA or TA and the impact on COVID-19 infection and housing instability. Methods A pilot RCT, with embedded process and health economic evaluations. 1:1 participant randomisation to SA (intervention group) or TA (control group). Recruitment in two local authorities (LA) in England. Participants were aged 18 and over, in single-person homeless households, temporarily accommodated by the LA with recourse to public funds. Primary outcomes: (i) LA recruitment; (ii) Participant recruitment; (iii) participant retention; (iv) LA adherence. Secondary outcomes: (i) completeness of data collection at 3 and 6 months; (ii) data linkage: percentage of participants consenting to data linkage and successful match rate. Results Of 144 LAs approached, 26 showed interest in participating, two entered the trial. LA hesitancy to participate reflects an unease with trials in services where RCTs are rare. These recruitment challenges resulted in an amendment from full-scale effectiveness RCT to pilot RCT design. Fifty PEH were recruited (29% from 175 approached). Fifty-six percent of participants were retained at 6 months. Fifty percent of randomisation allocations were adhered to by LAs, identifying difficulties in LA systems not amenable to randomisation and a lack of support for randomisation amongst front-line staff. Frontline workers felt strongly that allocations should be based on their judgement. There was a high level of outcome measure completion. All participants consented to sharing identifiers for linkage to health and other data. A match rate with NHS Digital was sought but could not be reported due to procedural challenges. Conclusions Whilst not recommended to proceed to a full-scale RCT in its current design, considerable uncertainties remain about the effectiveness and cost effectiveness of different housing interventions on health outcomes, COVID-19 infection and housing stability for PEH. Trial registration ISRCTN69564614 . Registered on December 16, 2020.

The goal of chemmodlab is to streamline the fitting and assessment pipeline for many machine learning models in R, making it easy for researchers to compare the utility of these models. While focused on implementing methods for model fitting and assessment that have been accepted by experts in the cheminformatics field, all of the methods in chemmodlab have broad utility for the machine learning community. chemmodlab contains several assessment utilities, including a plotting function that constructs accumulation curves and a function that computes many performance measures. The most novel feature of chemmodlab is the ease with which statistically significant performance differences for many machine learning models is presented by means of the multiple comparisons similarity plot. Differences are assessed using repeated k -fold cross validation, where blocking increases precision and multiplicity adjustments are applied. chemmodlab is freely available on CRAN at https://cran.r-project.org/web/packages/chemmodlab/index.html .