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OBJECTIVETo determine whether improvements in glycemic control and diabetes-specific quality of life (QoL) scores reported in research studies for the type 1 diabetes structured education program Dose Adjustment For Normal Eating (DAFNE) are also found when the intervention is delivered within routine U.K. health care.RESEARCH DESIGN AND METHODSBefore and after evaluation of DAFNE to assess impact on glycemic control and QoL among 262 adults with type 1 diabetes.RESULTSThere were significant improvements in HbA1c from baseline to 6 and 12 months (from 9.1 to 8.6 and 8.8%, respectively) in a subgroup with suboptimal control. QoL was significantly improved by 3 months and maintained at both follow-up points.CONCLUSIONSLonger-term improved glycemic control and QoL is achievable among adults with type 1 diabetes through delivery of structured education in routine care, albeit with smaller effect sizes than reported in trials.

Over the past 25 years, there has been significant acknowledgement of the importance of assessing the impact of diabetes on quality of life. Yet, despite the development of several diabetes‐specific quality of life measures, the challenges we faced in 1995 remain. There is little consensus on the definition of quality of life because of the complexity and subjectivity of the concept. General quality of life comprises several domains of life, and these are highly individualized. Assessing the impact of diabetes on these life domains adds to the complexity. While comprehensive diabetes‐specific quality‐of‐life measures typically increase respondent burden, brief questionnaires may not capture all relevant/important domains. Today, the lack of resolution of these challenges may explain why the impact of diabetes on quality of life is not systematically assessed in research or clinical care. Few researchers report detailed rationales for assessment, there is often a mismatch between the concept of interest and the measure selected, and data are misinterpreted as assessing the impact of diabetes on quality of life when, in reality, related but distinct constructs have been assessed, such as diabetes distress, treatment satisfaction or health status. While significant efforts are being made to increase routine monitoring of psychological well‐being and understand the lived experience, no guidelines currently recommend routine clinical assessment of diabetes‐specific quality of life, and there is no consensus on which questionnaire(s) to use. The gaps identified in this review need urgent attention, starting with recognition that assessment of diabetes‐specific quality of life is as important as biomedical markers, if we are to improve the lives of people with diabetes.

BackgroundSelf-management interventions have become increasingly popular in the management of long-term health conditions; however, little is known about their impact on psychological well-being in people with Multiple Sclerosis (MS).PurposeTo examine the effectiveness of self-management interventions on improving depression, anxiety and health related quality of life in people with MS.MethodA structured literature search was conducted for the years 2000 to 2016. The review process followed the PRISMA guidelines, and is registered with PROSPERO (no. CRD42016033925).ResultsThe review identified 10 RCT trials that fulfilled selection criteria and quality appraisal. Self-management interventions improved health-related quality of life in 6 out of 7 studies, with some evidence of improvement in depression and anxiety symptoms.ConclusionAlthough the results are promising more robust evaluation is required in order to determine the effectiveness of self-management interventions on depression, anxiety and quality of life in people with MS. Evaluation of the data was impeded by a number of methodological issues including incomplete content and delivery information for the intervention and the exclusion of participants representing the disease spectrum. Recommendations are made for service development and research quality improvement.

Generalized linear inversion, sometimes known as model perturbation, nonlinear regression, or inverse modeling, is applied to synthetic and real seismic data sets with the objective of obtaining an impedance profile as a function of time. The impedances solved for are parameterized in a manner that describes the unknown earth using fewer variables than previous seismic generalized linear inversion techniques. In this application only single traces of common‐midpoint (CMP) processed data will be inverted. The method of generalized linear inversion (GLI) presented here is designed to improve on the shortcomings of recursive inversion with respect to relative and absolute scale of the impedance results, resolution of impedance boundaries, and distortion from residual wavelet effects. In obtaining these goals other advantageous aspects of GLI were discovered. For example, it is insensitive to noise in many cases, and it will allow an interpreter to fix the impedance of any number of known lithologies in an interval being inverted. This last property is extremely useful when evaluating a prospect on an otherwise well‐understood seismic line. The GLI method is illustrated on a number of synthetic examples and one field data set from the Powder River basin of Wyoming.