The assessment of efforts to return to work in the European Union

Background: Assessment of efforts to promote return-to-work (RTW) includes all efforts (vocational and non-vocational) designed to improve the work ability of the sick-listed employee and increase the chance to return to work. Aim of the study was to investigate whether in 13 European countries these RTW efforts are assessed and to compare the procedures by means of six criteria. METHODS: Data were gathered in the taxonomy project of the European Union of Medicine in Assurance and Social Security and by means of an additional questionnaire. RESULTS: In seven countries RTW efforts are subject of the assessment in relation to the application for disability benefits. Description of RTW efforts is a prerequisite in five countries. Guidelines on the assessment of RTW efforts are only available in the Netherlands and no countries report the use of the ICF model. Based on the results of the additional questionnaire, the assessor is a social scientist or a physician. The information used to assess RTW efforts differs, from a report on the RTW process to medical information. A negative outcome of the assessment leads to delay of the application for disability benefits or to application for rehabilitation subsidy. Conclusion: RTW efforts are assessed in half of the participating European countries. When compared, the characteristics of the assessment of RTW efforts in the participating European countries show both similarities and differences. This study may facilitate the gathering and exchange of knowledge and experience between countries on the assessment of RTW efforts

The impact of Arctic warming on the midlatitude jetstream: Can it? Has it? Will it?

Copyright © 2015 John Wiley & Sons, LtdThe Arctic lower atmosphere has warmed more rapidly than that of the globe as a whole, and this has been accompanied by unprecedented sea ice melt. Such large environmental changes are already having profound impacts on the flora, fauna, and inhabitants of the Arctic region. An open question, however, is whether these Arctic changes have an effect on the jet-stream and thereby influence weather patterns farther south. This broad question has recently received a lot of scientific and media attention, but conclusions appear contradictory rather than consensual. We argue that one point of confusion has arisen due to ambiguities in the exact question being posed. In this study, we frame our inquiries around three distinct questions: Can Arctic warming influence the midlatitude jet-stream? Has Arctic warming significantly influenced the midlatitude jet-stream? Will Arctic warming significantly influence the midlatitude jet-stream? We argue that framing the discussion around the three questions: Can it?, Has it?, and Will it? provides insight into the common themes emerging in the literature as well as highlights the challenges ahead

Arctic sea-ice change: a grand challenge of climate science

Over the period of modern satellite observations, Arctic sea-ice extent at the end of the melt season (September) has declined at a rate of >11% per decade, and there is evidence that the rate of decline has accelerated during the last decade.While climate models project further decreases in seaice mass and extent through the 21st century, the model ensemble mean trend over the period of instrumental records is smaller than observed. Possible reasons for the apparent discrepancy between observations and model simulations include observational uncertainties, vigorous unforced climate variability in the high latitudes, and limitations and shortcomings of the models stemming in particular from gaps in understanding physical process. The economic significance of a seasonally sea-ice-free future Arctic, the increased connectivity of a warmer Arctic with changes in global climate, and large uncertainties in magnitude and timing of these impacts make the problem of rapid sea-ice loss in the Arctic a grand challenge of climate science. Meaningful prediction/projection of the Arctic sea-ice conditions for the coming decades and beyond requires determining priorities for observations and model development, evaluation of the ability of climate models to reproduce the observed sea-ice behavior as a part of the broader climate system, improved attribution of the causes of Arctic sea-ice change, and improved understanding of the predictability of sea-ice conditions on seasonal through centennial timescales in the wider context of the polar climate predictability

A Global Portrait of Counselling Psychologists’ Characteristics, Perspectives, and Professional Behaviors

Counselling psychologists in eight countries (Australia, Canada, New Zealand, South Africa, South Korea, Taiwan, the United Kingdom, and the United States) responded to survey questions that focused on their demographics as well as their professional identities, roles, settings and activities. As well, they were asked about satisfaction with the specialty and the extent to which they endorsed 10 core counselling psychology values. This article reports those results, focusing both on areas in which there were between-country similarities as well as on those for which there were differences. These data provide is a snapshot of counselling psychology globally and establish a foundation for the other articles in this special issue of the journal

Chapter 10 - Detection and attribution of climate change: From global to regional

This chapter assesses the causes of observed changes assessed in Chapters 2 to 5 and uses understanding of physical processes, climate models and statistical approaches. The chapter adopts the terminology for detection and attribution proposed by the IPCC good practice guidance paper on detection and attribution (Hegerl et al., 2010) and for uncertainty Mastrandrea et al. (2011). Detection and attribution of impacts of climate changes are assessed by Working Group II, where Chapter 18 assesses the extent to which atmospheric and oceanic changes influence ecosystems, infrastructure, human health and activities in economic sectors

Identification of the factors associated with outcomes in a condition management programme

<p>Background: A requirement of the Government’s Pathways to Work (PtW) agenda was to introduce a Condition Management Programme (CMP). The aim of the present study was to identify the differences between those who engaged and made progress in this telephone-based biopsychosocial intervention, in terms of their health, and those who did not and to determine the client and practitioner characteristics and programme elements associated with success in a programme aimed at improving health.</p> <p>Methods: Data were obtained from the CMP electronic spreadsheets and clients paper-based case records. CMP standard practice was that questionnaires were administered during the pre- and post-assessment phases over the telephone. Each client’s record contains their socio-demographic data, their primary health condition, as well as the pre- and post-intervention scores of the health assessment tool administered. Univariate and multivariate statistical analysis was used to investigate the relationships between the database variables. Clients were included in the study if their records were available for analysis from July 2006 to December 2007.</p> <p> Results: On average there were 112 referrals per month, totalling 2016 referrals during the evaluation period. The majority (62.8%) of clients had a mental-health condition. Successful completion of the programme was 28.5% (575 “completers”; 144 “discharges”). Several factors, such as age, health condition, mode of contact, and practitioner characteristics, were significant determinants of participation and completion of the programme. The results showed that completion of the CMP was associated with a better mental-health status, by reducing the number of clients that were either anxious, depressed or both, before undertaking the programme, from 74% to 32.5%.</p> <p>Conclusions: Our findings showed that an individual's characteristics are associated with success in the programme, defined as completing the intervention and demonstrating an improved health status. This study provides some evidence that the systematic evaluation of such programmes and interventions could identify ways in which they could be improved.</p&gt

Results of the first Arctic Heat Open Science Experiment

Author Posting. © American Meteorological Society, 2018. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Bulletin of the American Meteorological Society 99 (2018): 513-520, doi:10.1175/BAMS-D-16-0323.1.Seasonally ice-covered marginal seas are among the most difficult regions in the Arctic to study. Physical constraints imposed by the variable presence of sea ice in all stages of growth and melt make the upper water column and air–sea ice interface especially challenging to observe. At the same time, the flow of solar energy through Alaska’s marginal seas is one of the most important regulators of their weather and climate, sea ice cover, and ecosystems. The deficiency of observing systems in these areas hampers forecast services in the region and is a major contributor to large uncertainties in modeling and related climate projections. The Arctic Heat Open Science Experiment strives to fill this observation gap with an array of innovative autonomous floats and other near-real-time weather and ocean sensing systems. These capabilities allow continuous monitoring of the seasonally evolving state of the Chukchi Sea, including its heat content. Data collected by this project are distributed in near–real time on project websites and on the Global Telecommunications System (GTS), with the objectives of (i) providing timely delivery of observations for use in weather and sea ice forecasts, for model, and for reanalysis applications and (ii) supporting ongoing research activities across disciplines. This research supports improved forecast services that protect and enhance the safety and economic viability of maritime and coastal community activities in Alaska. Data are free and open to all (see www.pmel.noaa.gov/arctic-heat/).This work was supported by NOAA Ocean and Atmospheric Research and the Joint Institute for the Study of the Atmosphere and Ocean (JISAO) under NOAA Cooperative Agreement NA15OAR4320063 and by the Innovative Technology for Arctic Exploration (ITAE) program at JISAO/PMEL. Jayne, Robbins, and Ekholm were supported by ONR (N00014-12-10110)