What can badgers teach us about implementing implementation science? Science, politics and policies Sharon Witherspoon Deputy Director

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The Nuffield Foundation Endowed charitable trust, annual spend £12m (about $18m) General objective: “The advancement of social well-being particularly by means of scientific research” 3

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Randomised Badger Culling Trial Background: 25,000 cattle die of bovine TB each year in GB Compensation of £100m p.a. Half of all cattle infections come from badgers Trial launched,

Randomised Badger Culling Trial Trial: Triplets of areas, 100km 2 each – Proactive cull, each year – Reactive cull, only after TB outbreaks – Control zone, no cull 6

Randomised Badger Culling Trial Results: Reactive cull stopped as TB rates rose by 20% Explanation: perturbation Proactive cull: within zone, TB infections fell by 25%, but rose in the 2km ring around culling zone, because of ‘perturbation’ Had to think through system effect: link between size of zone and size of ring effect 7

Randomised Badger Culling Trial Implications: Larger rings (scaling up) would save money if proactive cull To enhance cost-effectiveness, killing method changed (without new pilot) Now have “real world” trial (aka scaling up) 8

Technical issues: fidelity, size of effects, scaling up, and value for money But also controversy and values

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Why relevant to human services implementation in UK? Experience of Multidimensional Treatment Foster Care Sure Start Youth justice reforms School reforms 15

Other badger issues CONTEXT of TB in cattle in Southwest: greater density of cattle, larger barns etc. institutional organisation underestimated in early discussions. But given pressures (economics, population growth etc), unlikely to change structures. Implementation science needs to appreciate structural issues too 16

Implementation programs on continuum with evidence-based wider policy change? When is universal intervention a structural policy change? And how context specific is this? Why we need to understand moderators and mediators UK family policy: shift from child outcomes to family form 17

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A. Cherlin Dominian lecture 19

Cherlin Dominian lecture 20

Effects of interventions to promote marriage (or stability) 21

Kiernan, Dominian lecture UK data 22

Family situation at age 5 by birth status 23

IFS study of selection and causality of ‘marriage effect’ Actively commissioned by Foundation Longitudinal data show that most differences in 2 outcomes for children (cognitive and social/behavioural) between married and cohabiting parents in UK are selection effects Longer term analysis suggests virtually all difference due to pre-existing differences 24

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Some general issues in policy brokerage Size of effects usually modest ( tho’ meaningful ) Greater effects more costly (up front at least): dose response Timescale for implementation vs. political cycle (ministerial career or parties) 26

Some general issues in policy brokerage II Values, and disagreement about aims (much less means) Self-interest but also ideology Politics: intermediaries and stakeholders: advocates of change 27

And some larger questions Is ultimate aim more and better interventions? Targeted or universal? If universal, is the game system change.... And at what point does intervention implementation require building capacity and internal drivers for improvement

Two tough questions Is there a ‘science’ of implementation or are there some general abstract features we can understand but not predict a priori? Why would politicians ever relinquish control of means, or agree about aims when they are value-laden (as well as politically-important)? 29

Political science not implementation science? Norway – longer-term commitment, development and funding Anglo Saxon countries more ideologically riven on aims ? Longer-term planning more difficult: US veto model, UK and other parliamentary systems have ‘pendulum swings’ 30

But not counsel of despair Features already know to be important Centres of substantive expertise, with longer- term engagement (foundation funders can help bridge) Intermediary bodies and strategic practitioners Political stakeholders (NGOs, parents, etc) Active PUSH for scaling: and communication 31

But not counsel of despair Features already know to be important – II Government advisers on inside (civil service, special advisers, research funding) Culture of evaluation spending (mandate is good: by law or political oversight) Longer term capacity building of ‘humans’ Economic evaluations 32

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But.... Isn’t this just the politics of creating critical mass and drivers to make implementation science and use of evidence more self-sustaining? Or at least ensuring that there is enough power to embarrass? 34

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