Multidimensional Bosonization

Bosonization of degenerate fermions yields insight both into Landau Fermi liquids, and into non-Fermi liquids. We begin our review with a pedagogical introduction to bosonization, emphasizing its applicability in spatial dimensions greater than one. After a brief historical overview, we present the essentials of the method. Well known results of Landau theory are recovered, demonstrating that this new tool of many-body theory is robust. Limits of multidimensional bosonization are tested by considering several examples of non-Fermi liquids, in particular the composite fermion theory of the half-filled Landau level. Nested Fermi surfaces present a different challenge, and these may be relevant in the cuprate superconductors. We conclude by discussing the future of multidimensional bosonization.Comment: 91 pages, 15 eps figures, LaTeX. Minor changes to match the published versio

Predicting outcome in acute low back pain using different models of patient profiling

Study Design: Prospective observational study of prognostic indicators, utilising data from a randomised, controlled trial of physiotherapy care of acute low back pain (ALBP) with follow up at 6 weeks, 3 months and 6 months. Objective: To evaluate which patient profile offers the most useful guide to long-term outcome in ALBP. Summary of Background Data: The evidence used to inform prognostic decision-making is derived largely from studies where baseline data is used to predict future status. Clinicians often see patients on multiple occasions so may profile patients in a variety of ways. It is worth considering if better prognostic decisions can be made from alternative profiles. Methods: Clinical, psychological and demographic data were collected from a sample of 54 ALBP patients. Three clinical profiles were developed from information collected at baseline, information collected at 6 weeks, and the change in status between these two time points. A series of regression models were used to determine the independent and relative contributions of these profiles to the prediction of chronic pain and disability. Results: The baseline profile predicted long-term pain only. The 6-week profile predicted both long-term pain and disability. The change profile only predicted long-term disability (p \u3c 0.01). When predicting long-term pain, after the baseline profile had been added to the model, the 6-week profile did not add significantly when forced in at the second step (p \u3e 0.05). A similar result was obtained when the order of entry was reversed. When predicting long-term disability, after the 6-week profile was entered at the first step, the change profile was not significant when forced in at the second step. However, when the change profile was entered at the first step and the 6-week clinical profile was forced in at the second step, a significant contribution of the 6-week profile was found. Conclusions: The profile derived from information collected at 6 weeks provided the best guide to long-term pain and disability. The baseline profile and change in status offered less predictive value

Quantitative neurosymptomatics: Linking quantitative biology to neuropsychiatry

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Burnout in UK care home staff and its effect on staff turnover: MARQUE English national care home longitudinal survey

BACKGROUND: staff burnout and turnover lead to care home residents receiving poorer quality care. Burnout is thought to cause turnover, but this has never been investigated. We know little about which care home staffs are burnt out. AIMS: to explore burnout's relationship with staff turnover and prevalence and predictors of burnout. METHOD: we calculated the relationship between Maslach Burnout Inventory scores and future staff turnover (12-month number of staff leaving/number employed). We explored staff, resident and care home predictors of burnout, measured as emotional exhaustion (EE), depersonalisation (DP) and personal accomplishment (PA). RESULTS: two-thousand sixty-two care staff in 97 care home units participated. Median yearly staff turnover was 22.7%, interquartile range (IQR) 14.0-37.7%. Care staff recorded low median burnout (median EE: 14, IQR: 7-22; DP: 1, IQR: 0-5; PA 42, IQR: 36-45). We found no association between staff burnout and turnover rate. Younger staff age was associated with higher burnout (EE coefficient - 0.09; 95% confidence interval (CI): -0.13, -0.05; DP -0.02; 95% CI: -0.04, -0.01; PA 0.05; 95% CI: 0.02, 0.08). Speaking English as a second language predicted higher EE (1.59; 95% CI: 0.32, 2.85), males had higher DP (0.02; 95% CI: 0.01, 0.04) and staff working only night shifts lower PA (-2.08; 95% CI: -4.05, -1.30). CONCLUSIONS: we found no association between care homes staff burnout level and staff turnover rates. It is a myth that burnout levels are high. Interventions for burnout could focus on at-risk groups. Future studies could consider turnover at an individual level