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Over the last twenty years integrated care has been touted as a solution to many issues in health services, such as insufficient coordination between services, cumbersome organizational boundaries, interrupted patient journeys, as well as spiraling health care costs. However, despite volumes of research, the field has seen few innovative advances in recent years. In particular, prevailing integrated care implementation practice and research appear to be very health science centred, spurning approaches from other disciplines. Axel Kaehne argues that it is time to re-evaluate how we investigate care integration. He asks us to radically question our assumptions about integrated care as a managerial, organisational and behavioural endeavor. This is a profound departure from conventional thinking about integration in health and social care. Kaehne reveals the tacit assumptions we make when we manage and change health services and offers a fresh perspective on care integration whilst inviting readers to examine long established research orthodoxies. This eclectic conceptual and theoretical approach produces surprising insights for everyone who is ready to see things anew.

This book critically examines integrated care, looking at integration from an unconventional angle to reveal the tacit assumptions we make when we manage and change health services. Kaehne questions our premises on health services management, the motivations for change and the shortcomings of health policy in complex environments.

Providing the first book-length comprehensive study of Russian political and social thought in the post-Communist era, this book portrays and critically examines the conceptual and theoretical attempts by Russian scholars and political thinkers to make sense of the challenges of post-communism

Providing the first book-length comprehensive study of Russian political and social thought in the post-Communist era, this book portrays and critically examines the conceptual and theoretical attempts by Russian scholars and political thinkers to make sense of the challenges of post-communism.

Pawson's article raises the important question of what constitutes good and bad modelling during a pandemic. His article makes the case for more involvement of social scientists to capture the complex adaptive nature of governmental policy. While articulating a welcome critique of epidemiological models, his article fails to recognise that all model use simplifications which make some models better than others. I will suggest a useful way of differentiating between good and bad, useful and less useful, models based on the difference between idealisation and abstraction, concepts I borrow from Onora O'Neill and political theory. They allow us to apply a more nuanced criticality to the current models used by the government. Refining our critique of the government's COVID response is important since we need to account for the fact that current government responses to the pandemic, while open to criticism, have had some effect in reducing infection rates.

In the battle between experimental study designs and realist approaches, Ray Pawson has fired the next shot. This time evidence based medicine is in his aim. He argues that evidence based medicine is becoming more appreciative of specific circumstances of interventions and hence medical research may be approximating realist evaluation's approach. He illustrates his argument with the history of cancer where the disease increasingly looks like it is playing 'cat and mouse' with researchers. In the paper I try to disentangle the epistemological and methodological dimensions of Pawson's claim. I argue that, what may look similar on a narrative level, may not be consequential for the different types of epistemologies that sustain medical and policy impact research.

Abstract Background: Complexity received increasing attention from researchers in integration and evaluation studies. Complex adaptive systems (CAS) are the most prominent formulation of complexity used in programme evaluations. However, there remain significant theoretical and conceptual barriers to using complexity as an explanatory model in social sciences, and thus in applying it successfully in integration and evaluation studies. Method: Discussion paper outlining the potential uses and risks of complexity theory for studying integration programmes in health and social care and programme evaluations in general. The paper proceeds by synthesising the work of various critics and proponents of complexity theory in the social sciences and evaluation theory. Results: Complexity offers opportunities and risks to social scientists working in programme evaluations and integration studies. The opportunities are defined by additional modelling and verification/falsification of possible cause and effect links in programme settings. The risks, on the other hand, are twofold. Social scientists may use complexity as a shorthand for as yet insufficient understanding of the contexts under examination, or they mistake it for an explanatory device without testing its potential to explain. The second risk emerges as a result of the nature of complexity and its role in natural sciences. Assigning complexity an explanatory role may prevent further investigation of a given setting that may reveal that complexity is insufficient to understand what is going on. Implications for practice: Researchers should make clear how they have operationalised and measured the various features of the complexity model to allow robust verification of the evidence. Scholars should also assume that complexity as defined by the natural sciences is philosophically and epistemologically problematic when transferred into the realm of social sciences that largely operate with concepts informed by the paradigm of understanding social behaviour.

BackgroundThe study reports the findings of an evaluation of Project SEARCH UK. The programme develops internships for young people with intellectual disabilities who are about to leave school or college. The aim of the evaluation was to investigate at what rate Project SEARCH provided employment opportunities to participants.MethodsThe evaluation obtained data from all sites operational in the UK at the time of evaluation (n = 17) and analysed employment outcomes.ResultsData were available for 315 young people (n = 315) in the programme and pay and other employment related data were available for a subsample. The results of the analysis suggest that Project SEARCH achieves on average employment rates of around 50 per cent.ConclusionProject SEARCH UK represents a valuable addition to the supported employment provision in the UK. Its unique model should inform discussions around best practice in supported employment. Implications for other supported employment programmes are discussed.