Prevention-Strategies Aimed at Improving Health and Well-Being

21 Oct

How do you design, implement, evaluate and adapt a strategy aimed at improving the health, well-being and resilience of a community? The requirement within the UK of having to “do more with less”, places the focus of strategy on preventing poor health and well-being. Prevention requires greater public knowledge leading to improved self-management and decision making. It also means increased community resilience so coping and recovery occurs and occurs quickly, and the need for services to adapt (and ideally innovate) to feedback gained from increased public knowledge. Adaption for services also means leveraging current assets, designing “new ways of working” and creating partnerships to improve and widen delivery. Health and well-being strategies play out in an incredibly complex and changing environment, this places pressure on evaluation and adaption of a strategy in motion. So, with scarce resources where is effort best concentrated to improve prevention? In this article I’m going to examine an approach of collecting and applying data to improve the strategy of prevention by focusing on community knowledge acquisition, decision making and resilience.

At the heart of every strategy there is a philosophy. This philosophy is the guiding theory which has produced the strategy (Pawson, 2006) or the deep structure (Rugg, 2013) upon which the strategy is built. Both programme theory, philosophy and deep structure, in my view, share the same function- they are the intention, the vision, and the ideology. Around the philosophy is built a range of plans and tactics which are designed to deliver the strategy. Particularly in complex areas, with multiple departments, stakeholders and professions, each with competing world views and pressures, the plans and tactics can become a series of compromises and concessions. This can leave the central philosophy buried under a pile of political and professional debris. There is no immunity to these circumstances, and it can sometimes be helpful, but it’s a good idea to “gut” the philosophy, exposing its component parts, at the start of a strategy. The component parts can act as a “lens” to analyse the various plans and tactics which emerge to assess whether they contradict, complicate, improve or adapt the underlying philosophy. In short, the process aims to make sure the wood is not lost amongst the trees. Below is an example of how to potentially focus intention when creating and delivering a strategy aimed at prevention.

To focus on the prevention of poor health and well-being within a community requires certain conditions to be met. If a strategy intends to improve prevention then it creates (for example) the following logic chain-

What does increasing prevention within a community require?>

>Prevention requires increased knowledge of health and well-being across partner services and communities>

>What type of knowledge will improve prevention?>

>Local and contextual>what works, for who and why, and in what circumstances (Pawson, 2006)>

>How do you collect this contextual knowledge?>

>Placing a focus on tacit learning> Recovery from mistakes> Expertise

>What form should this knowledge take?> How should it be shared?>

>Simple, easy to understand, remember and apply>

The above is a crude example but it makes the case that prevention could be improved by developing, collecting and sharing expertise in the form of simple lessons and rules of thumb. If prevention requires increased knowledge then this knowledge needs to be easy to understand and apply by both services and communities. By contrast, if the knowledge which underpins increasing prevention is hard to understand, complex and difficult to apply then it is less likely to be used. This produces a “lens” through which to assess emerging plans and tactics- knowledge needs to be effective, practical and simple. This follows the research of Gigerenzer (2008) who found that simple solutions to problems in complex environments are both more effective and more likely to be used. In addition, Crandall et al (2006) found that if knowledge or knowledge support does not simply “plug” into existing ways of decision making it is highly unlikely to be used. In summary, prevention requires increased knowledge, but the knowledge needs to be effective and easy to use.

Drilling down further into the philosophy of prevention, I’ve so far tried to establish the role of simple usable knowledge. Simple usable knowledge should have the purpose of improving the quality of decision making. Preventing poor health and well-being can be improved, to a degree, by increasing the capacity to make better decisions through knowledge acquisition. This increases the “requisite variety” (Weick and Sutcliffe, 2007) of a community (and services) when faced with challenges. Requisite variety is essentially the range of coping strategies available to an individual and organisation when faced with unexpected events and challenges. Gigerenzer identifies a similar concept when he discusses the role of “adaptive toolkits” to tackle unexpected events and challenges. Adaptive toolkits perform a similar function, they increase the range of coping mechanisms available to meet challenges which deviate from the norm. Both requisite variety and adaptive toolkits are fundamental to improving prevention, largely through increasing resilience; the ability to bounce back from unexpected events whilst maintaining high function, whether that be mental health or service delivery.

To condense the points so far; prevention requires increased knowledge, knowledge needs to be simple and effective for it to be used, if it is used, it should improve decision making and resilience by increasing the range of options available to communities and services. To close the circle, all this is achieved through knowledge acquisition which is “packaged” effectively.

Following the above logic places the emphasis of data collection and evaluation on knowledge acquisition, with the intent of improving requisite variety and adaptive toolkits. This should not be at the expense of epidemiology, but should serve to support it. Collecting knowledge for the purposes of creating simple solutions to complex problems needs to be driven by a similar philosophy to prevention. Given time, access and budget constraints the collection methods need to be simple and highly effective, with analysis placed on simple usable knowledge.

I’ve covered the subject of methods under time, budget and access constraints in the article below, but I’ll return to it in the next article by focusing on knowledge acquisition.


Pawson, R. (2006) Evidence Based Policy: A Realist Perspective, Sage

Weick, K. E., & Sutcliffe, K. M. (2007). Managing the Unexpected: Resilient Performance in and Age of Uncertainty, Second Edition. San Francisco, CA: Jossey-Bass

Gigerenzer, G (2008) Gut Feelings: Shorts Cuts to Better Decision Making. Penguin

Crandall, B. Klein, G. Hoffman, R. (2006) Working Minds: A Practitioners Guide to Cognitive Task Analysis. The MIT Press

Rugg, G. (2013) Blind Spot: Why We Fail to See the Solution Right in Front of Us: How Finding a Solution to One of the World’s Greatest Mysteries. Harperone. With D’Adnese. J.

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