"A hard day’s night?" The effects of Compressed Working Week interventions on the health and work-life balance of shift workers: a systematic review

Objective: To systematically review studies of the effects of the Compressed Working Week on the health and work-life balance of shift workers, and to identify any differential impacts by socio-economic group. Methods: Systematic review. Following QUORUM guidelines, published or unpublished experimental and quasi-experimental studies were identified. Data were sourced from 27 electronic databases, websites, bibliographies, and expert contacts. Results: Forty observational studies were found. The majority of studies only measured self-reported outcomes and the methodological quality of the included studies was not very high. Interventions did not always improve the health of shift workers, but in the five prospective studies with a control group, there were no detrimental effects on self-reported health. However, work-life balance was generally improved. No studies reported differential impacts by socio-economic group; however, most of the studies were conducted on homogeneous populations. Conclusion: This review suggests that the Compressed Working Week can improve work-life balance, and that it may do so with a low risk of adverse health or organisational effects. However, better designed studies that measure objective health outcomes are needed

What helps to support people affected by Adverse Childhood Experiences? A review of evidence

Adverse Childhood Experiences (ACEs) include physical, sexual or emotional abuse; neglect; domestic violence in the home; homelessness or living in care; parental mental health problems or substance abuse; and parents who are absent through imprisonment, separation or death. We sought to understand how people affected by ACEs can best be supported by conducting a review of evidence. The review involved three components: a qualitative synthesis of UK views studies; a systematic review of reviews which measured the effectiveness of interventions to support people affected by ACEs; and a stakeholder workshop with young people with lived experience of ACEs. The review was commissioned by the Department of Health and Social Care

Effects of Pacing When Using Material Handling Manipulators

Common manipulator-assisted materials handling tasks were performed in a laboratory simulation at self-selected and faster (paced) speeds. The effects of pacing on peak hand forces, torso kinematics, spine moments and forces, and muscle antagonism were determined, along with any influences of several task variables on these effects. The faster trials were performed 20% more rapidly than the self-paced trials. It was found that (a) achieving this level of performance required 10% higher hand forces and 5%-10% higher torso moments, (b) consistent torso postures and motions were used for both speed conditions, and (c) the faster trials resulted in 10% higher spine forces and 15% higher levels of lumbar muscle antagonism. On whole, these results suggest a higher risk of musculoskeletal injury associated with performance of object transfers at faster than self-selected speeds with and without a manipulator. Further analysis provided evidence that the use of manipulators involves higher levels of motor coordination than do manual tasks. Several implications regarding the use of material handling manipulators in paced operations are discussed. Results from this investigation can be used in the design, evaluation, and selection of material handling manipulators.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/67067/2/10.1518_001872099779591240.pd

The Bivariate Normal Copula

We collect well known and less known facts about the bivariate normal distribution and translate them into copula language. In addition, we prove a very general formula for the bivariate normal copula, we compute Gini's gamma, and we provide improved bounds and approximations on the diagonal.Comment: 24 page

Cost-effectiveness of Microsoft Academic Graph with machine learning for automated study identification in a living map of coronavirus disease 2019 (COVID-19) research

BACKGROUND: Conventionally, searching for eligible articles to include in systematic reviews and maps of research has relied primarily on information specialists conducting Boolean searches of multiple databases and manually processing the results, including deduplication between these multiple sources. Searching one, comprehensive source, rather than multiple databases, could save time and resources. Microsoft Academic Graph (MAG) is potentially such a source, containing a network graph structure which provides metadata that can be exploited in machine learning processes. Research is needed to establish the relative advantage of using MAG as a single source, compared with conventional searches of multiple databases. This study sought to establish whether: (a) MAG is sufficiently comprehensive to maintain our living map of coronavirus disease 2019 (COVID-19) research; and (b) eligible records can be identified with an acceptably high level of specificity. METHODS: We conducted a pragmatic, eight-arm cost-effectiveness analysis (simulation study) to assess the costs, recall and precision of our semi-automated MAG-enabled workflow versus conventional searches of MEDLINE and Embase (with and without machine learning classifiers, active learning and/or fixed screening targets) for maintaining a living map of COVID-19 research. Resource use data (time use) were collected from information specialists and other researchers involved in map production. RESULTS: MAG-enabled workflows dominated MEDLINE-Embase workflows in both the base case and sensitivity analyses. At one month (base case analysis) our MAG-enabled workflow with machine learning, active learning and fixed screening targets identified n=469 more new, eligible articles for inclusion in our living map – and cost £3,179 GBP ($5,691 AUD) less – than conventional MEDLINE-Embase searches without any automation or fixed screening targets. CONCLUSIONS: MAG-enabled continuous surveillance workflows have potential to revolutionise study identification methods for living maps, specialised registers, databases of research studies and/or collections of systematic reviews, by increasing their recall and coverage, whilst reducing production costs