Background: Systematic reviews are vital to the pursuit of evidence-based medicine within healthcare. Screening titles and abstracts (T&Ab) for inclusion in a systematic review is an intensive, and often collaborative, step. The use of appropriate tools is therefore important. In this study, we identified and evaluated the usability of software tools that support T&Ab screening for systematic reviews within healthcare research. Methods:We identified software tools using three search methods: a web-based search; a search of the online "systematic review toolbox"; and screening of references in existing literature. We included tools that were accessible and available for testing at the time of the study (December 2018), do not require specific computing infrastructure and provide basic screening functionality for systematic reviews. Key properties of each software tool were identified using a feature analysis adapted for this purpose. This analysis included a weighting developed by a group of medical researchers, therefore prioritising the most relevant features. The highest scoring tools from the feature analysis were then included in a user survey, in which we further investigated the suitability of the tools for supporting T&Ab screening amongst systematic reviewers working in medical research.Results: Fifteen tools met our inclusion criteria. They vary significantly in relation to cost, scope and intended user community. Six of the identified tools (Abstrackr, Colandr, Covidence, DRAGON, EPPI-Reviewer and Rayyan) scored higher than 75% in the feature analysis and were included in the user survey. Of these, Covidence and Rayyan were the most popular with the survey respondents. Their usability scored highly across a range of metrics, with all surveyed researchers (n = 6) stating that they would be likely (or very likely) to use these tools in the future. Conclusions: Based on this study, we would recommend Covidence and Rayyan to systematic reviewers looking for suitable and easy to use tools to support T&Ab screening within healthcare research. These two tools consistently demonstrated good alignment with user requirements. We acknowledge, however, the role of some of the other tools we considered in providing more specialist features that may be of great importance to many researchers.

Background The coronavirus disease 2019 (COVID-19) pandemic has had a profound impact on both the physical and mental well-being of the global population. Relatively few studies have measured the impact of lockdown on utilisation of secondary mental health services in England. Aims To describe secondary mental health service utilisation pre-lockdown and during lockdown within Leicestershire, UK, and the numbers of serious incidents during this time frame. Method Data pertaining to mental health referral and hospital admissions to adult mental health, child and adolescent mental health, intellectual disability and mental health services for older people were collated retrospectively from electronic records for both 8 weeks pre-lockdown and the first 8 weeks of lockdown in England. Serious incidents during this time frame were also analysed. Results Significantly (P < 0.05) reduced referrals to a diverse range of mental health services were observed during lockdown, including child and adolescent, adult, older people and intellectual disability services. Although admissions remained relatively stable before and during lockdown for several services, admissions to both acute adult and mental health services for older people were significantly (P < 0.05) reduced during lockdown. Numbers of serious incidents in the pre-lockdown and lockdown periods were similar, with 23 incidents pre-lockdown, compared with 20 incidents in lockdown. Conclusions To the best of our knowledge, this is the first UK-based study reporting patterns of use of mental health services immediately prior to and during COVID-19 lockdown. Overall numbers of referrals and admissions reduced following commencement of COVID-19 lockdown. Potential reasons for these observations are discussed.

Background Using risk stratification approaches to determine eligibility has the potential to improve efficiency of screening. Objectives To compare the public acceptability and potential impact on uptake of using different approaches to determine eligibility for screening. Design An online population‐based survey of 668 adults in the UK aged 45‐79 including a series of scenarios in the context of a potential kidney cancer screening programme in which eligibility was determined by age, sex, age and sex combined, a simple risk score (age, sex, body mass index, smoking status), a complex risk score additionally incorporating family history and lifestyle, or a genetic risk score. Outcome measures We used multi‐level ordinal logistic regression to compare acceptability and potential uptake within individuals and multivariable ordinal logistic regression differences between individuals. Results Using sex, age and sex, or the simple risk score were less acceptable than age (P < .0001). All approaches were less acceptable to women than men. Over 70% were comfortable waiting until they were older if the complex risk score or genetics indicated a low risk. If told they were high risk, 85% would be more likely to take up screening. Being told they were low risk had no overall influence on uptake. Conclusions Varying the starting age of screening based on estimated risk from models incorporating phenotypic or genetic risk factors would be acceptable to most individuals and may increase uptake. Patient or Public Contribution Two members of the public contributed to the development of the survey and have commented on this paper.

Context: Early detection of kidney cancer improves survival; however, low prevalence means that population-wide screening may be inefficient. Stratification of the population into risk categories could allow for the introduction of a screening programme tailored to individuals. Objective: This review will identify and compare published models that predict the risk of developing kidney cancer in the general population. Evidence acquisition: A search identified primary research reporting or validating models predicting the risk of kidney cancer in Medline and EMBASE. After screening identified studies for inclusion, we extracted data onto a standardised form. The risk models were classified using the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) guidelines and evaluated using the PROBAST assessment tool. Evidence synthesis: The search identified 15 281 articles. Sixty-two satisfied the inclusion criteria; performance measures were provided for 11 models. Some models predicted the risk of prevalent undiagnosed disease and others future incident disease. Six of the models had been validated, two using external populations. The most commonly included risk factors were age, smoking status, and body mass index. Most of the models had acceptable-to-good discrimination (area under the receiver-operating curve >0.7) in development and validation. Many models also had high specificity; however, several had low sensitivity. The highest performance was seen for the models using only biomarkers to detect kidney cancer; however, these were developed and validated in small case-control studies. Conclusions: We identified a small number of risk models that could be used to stratify the population according to the risk of kidney cancer. Most exhibit reasonable discrimination, but a few have been validated externally in population-based studies. Patient summary: In this review, we looked at mathematical models predicting the likelihood of an individual developing kidney cancer. We found several suitable models, using a range of risk factors (such as age and smoking) to predict the risk for individuals. Most of the models identified require further testing in the general population to confirm their usefulness.

Introduction: Using risk stratification to determine eligibility for cancer screening is likely to improve the efficiency of screening programmes by targeting resources towards those most likely to benefit. We aimed to explore the implications of this approach from a societal perspective by understanding public views on the most acceptable stratification strategies.Methods: We conducted three online community juries with 9 or 10 participants in each. Participants were purposefully sampled by age (40-79 years), sex, ethnicity, social grade and English region. On the first day, participants were informed of the potential benefits and harms of cancer screening and the implications of different ways of introducing stratification using scenarios based on phenotypic and genetic risk scores. On the second day, participants deliberated to reach a verdict on the research question, 'Which approach(es) to inviting people to screening are acceptable, and under what circumstances?' Deliberations and feedback were recorded and analysed using thematic analysis.