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Objectives To determine the need for recovery (NFR) among emergency physicians and to identify demographic and occupational characteristics associated with higher NFR scores.Design Cross-sectional electronic survey.Setting Emergency departments (EDs) (n=112) in the UK and Ireland.Participants Emergency physicians, defined as any registered physician working principally within the ED, responding between June and July 2019.Main outcome measure NFR Scale, an 11-item self-administered questionnaire that assesses how work demands affect intershift recovery.Results The median NFR Score for all 4247 eligible, consented participants with a valid NFR Score was 70.0 (95% CI: 65.5 to 74.5), with an IQR of 45.5–90.0. A linear regression model indicated statistically significant associations between gender, health conditions, type of ED, clinical grade, access to annual and study leave, and time spent working out-of-hours. Groups including male physicians, consultants, general practitioners (GPs) within the ED, those working in paediatric EDs and those with no long-term health condition or disability had a lower NFR Score. After adjusting for these characteristics, the NFR Score increased by 3.7 (95% CI: 0.3 to 7.1) and 6.43 (95% CI: 2.0 to 10.8) for those with difficulty accessing annual and study leave, respectively. Increased percentage of out-of-hours work increased NFR Score almost linearly: 26%–50% out-of-hours work=5.7 (95% CI: 3.1 to 8.4); 51%–75% out-of-hours work=10.3 (95% CI: 7.6 to 13.0); 76%–100% out-of-hours work=14.5 (95% CI: 11.0 to 17.9).Conclusion Higher NFR scores were observed among emergency physicians than reported in any other profession or population to date. While out-of-hours working is unavoidable, the linear relationship observed suggests that any reduction may result in NFR improvement. Evidence-based strategies to improve well-being such as proportional out-of-hours working and improved access to annual and study leave should be carefully considered and implemented where feasible.

Previous studies have shown a correspondence between the abundance of particular plant species and methane flux. Here, we apply multivariate analyses, and weighted averaging, to assess the suitability of vegetation composition as a predictor of methane flux. We developed a functional classification of the vegetation, in terms of a number of plant traits expected to influence methane production and transport, and compared this with a purely taxonomic classification at species level and higher. We applied weighted averaging and indirect and direct ordination approaches to six sites in the United Kingdom, and found good relationships between methane flux and vegetation composition (classified both taxonomically and functionally). Plant species and functional groups also showed meaningful responses to management and experimental treatments. In addition to the United Kingdom, we applied the functional group classification across different geographical regions (Canada and the Netherlands) to assess the generality of the method. Again, the relationship appeared good at the site level, suggesting some general applicability of the functional classification. The method seems to have the potential for incorporation into large-scale (national) greenhouse gas accounting programmes (in relation to peatland condition/management) using vegetation mapping schemes. The results presented here strongly suggest that robust predictive models can be derived using plant species data (for use in national-scale studies). For trans-national-scale studies, where the taxonomic assemblage of vegetation differs widely between study sites, a functional classification of plant species data provides an appropriate basis for predictive models of methane flux., (© 2012 Blackwell Publishing Ltd.)