**Wellbeing:** Alternative Policy Perspectives **Edited by** Timothy Besley (LSE) and Irene Bucelli (LSE)

LSE Public Policy Review Series

citizens themselves?

Governments in liberal democracies pursue social welfare, but in many different ways. The wellbeing approach instead asks: Why not focus directly on increasing measured human happiness? Why not try to improve people's overall quality of life, as it is subjectively seen by

The radical implications of this stance include shifting attention to previously neglected areas (such as mental health and 'social infrastructure' services) and developing defensible measures of overall wellbeing or quality of life indicators. Can one 'master' concept of wellbeing work to create more holism in policy-making? Or should we stick with multiple metrics? These debates have been live in relation to an alternative 'capacities' approaches, and they are well-developed in health policymaking. Most recently, the connections between wellbeing

and political participation have come into sharper focus.

Wellbeing remains a contested concept, one that can be interpreted and used differently, with consequences for how it is incorporated into policy decisions. By bringing together scholars from economics, psychology and behavioural science, philosophy and political science, the authors explore how different disciplinary approaches can contribute to the study of wellbeing and how this can shape policy priorities.

## **Wellbeing Alternative Policy Perspectives**

edited by

*Timothy Besley and Irene Bucelli*

Published by LSE Press 10 Portugal Street London WC2A 2HD press.lse.ac.uk

Text © The Authors, 2022 Book first published 2022. Previous versions of the chapters were first published in LSE Public Policy Review (2021), Volume 2, Issue 2: *Wellbeing*. https://ppr.lse.ac.uk/7/volume/2 /issue/2/

Cover design by Diana Jarvis Cover image by Tim Mossholder via Unsplash

ISBN (Paperback): 978-1-909890-82-4 ISBN (PDF): 978-1-909890-81-7

DOI: https://doi.org/10.31389/lsepress.well

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This book has been peer-reviewed to ensure high academic standards. For our full publishing ethics policies, see https://press.lse.ac.uk

Suggested citation: Besley, Timothy and Bucelli, Irene. (eds.) 2022. *Wellbeing: Alternative Policy Perspectives*. London: LSE Press. DOI: https://doi.org/10.31389/lsepress.well. License: CC-BY 4.0

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# **LSE Public Policy Review Series**

This series republishes in book form selected issues on inter-disciplinary themes from the LSE Public Policy Review journal.

### *Series Editors*

Professor Timothy Besley, Department of Economics, LSE Dr Tania Burchardt, Department of Social Policy, LSE Professor Nicola Lacey, LSE Law School, LSE Professor Susana Mourato, Pro-Director of Research, LSE Professor Andrés Velasco, School of Public Policy, LSE

#### *Titles*

Wellbeing: Alternative Policy Perspectives (2022) Populism: Origins and Alternative Policy Responses (2022) Afghanistan: Long War, Forgotten Peace (2022)

## **Contents**


## **8. Health, Wellbeing, and Democratic Citizenship: A Review and Research Agenda 139**

*Christopher J. Anderson, Sara Hagemann, and Robert Klemmensen*

## **9. Health and Disability Gaps in Political Engagement: A Short Review 167**

*Mikko Mattila*

## **Editors**

**Timothy Besley** is School Professor of Economics of Political Science and W. Arthur Lewis Professor of Development Economics in the Department of Economics at LSE. He is also a member of the National Infrastructure Commission and, for 2018, is President of the Econometric Society. He is a Fellow of the Econometric Society and British Academy. He is also a Foreign Honorary Member of the American Economic Association and the American Academy of Arts and Sciences.

**Irene Bucelli** is a Research Officer at the LSE School of Public Policy and programme coordinator for the Beveridge 2.0: Redefining the Social Contract. She is also a Research Officer at the Centre for Analysis of Social Exclusion (LSE) where her research focuses on multidimensional inequality, poverty and deprivation.

## **Contributors**

**Paul Anand** is Professor of Economics at the Open University and Research Associate at HERC in Oxford University. He has acted as a consultant researcher on economic statistics to the OECD and NAO.

**Christopher J. Anderson** is Professor in Politics and Policy in the European Institute at LSE. He has won several scientific awards for his work and has held appointments at a number of universities, including Rice, Northwestern, Oxford, and Syracuse. Most recently, Chris was a Professor of Government and Labor Relations at Cornell University where he taught political economy and political sociology.

**Annette Bauer** is Assistant Professorial Research Fellow in the Care Policy and Evaluation Centre at LSE. Annette currently works on a large government-funded project in Tyrol (Austria) that seeks to develop, implement, and evaluate a social-network intervention for children of parents with a mental illness.

**Michael Daly** is Associate Professor in the Department of Psychology at Maynooth University. He has conducted doctoral research in Florida State University and post-doctoral training in the University of Aberdeen as part of Fulbright and Marie Sklodowska-Curie fellowships. He was previously an Assistant Professor in the University of Manchester and Associate Professor in the University of Stirling.

**Liam Delaney** is the Head of Department for Psychological and Behavioural Science at LSE. From 2017 to 2020 he was Professor of Economics at University College Dublin, where he led the development of MSc in Behavioural Economics and Geary Institute Experimental Lab. Prior to this, he was Deputy Dean of Stirling Management School, and led the development of the Stirling Behavioural Science centre.

**Paul Dolan** is Professor of Behavioural Science in the Department in Psychological and Behavioural Science at the LSE. He is author of the Sunday Times best-selling book *Happiness by Design*, and *Happy Ever After*, and the creator and presenter of the Duck – Rabbit podcast, a journey through our polarised culture.

**Sara Hagemann** is Professor of Political Science and Vice Dean at the Faculty of Social Sciences at Copenhagen University. She previously was Associate Professor in European Politics in the European Institute at LSE and Academic Director at the LSE School of Public Policy.

**Robert Klemmensen** is a professor of Political Science at the University of Southern Denmark. His research focuses on comparative politics, political psychology and political behaviour. His work has appeared in journals such as European *Journal of Political Research, Comparative Political Studies, Political Behavior* and *Political Psychology*.

**Richard Layard** is a labour economist who has worked for most of his life on how to reduce unemployment and inequality. He is founder-director of LSE's Centre for Economic Performance, and is co-director of the Centre's programme on Community Wellbeing.

**Mikko Mattila** is Professor of Political Science at the University of Helsinki. He has studied extensively political participation as well as political institutions in national and comparative settings. Recently, he has led a major project on the relationship between health and political engagement, which has produced valuable knowledge on inequalities in participation and in political influence between groups affected differently by health concerns.

**Johanna Thoma** is Assistant Professor in the Department of Philosophy, Logic and Scientific Method at LSE. She completed her PhD in philosophy at the University of Toronto under the supervision of Sergio Tenenbaum, after studying philosophy, economics and politics at Oxford University and Erasmus University Rotterdam.

## **1. Introduction: Making Wellbeing Policies Effective**

### Timothy Besley and Irene Bucelli

Few people would doubt that governments can make huge contributions to societal wellbeing by improving their choice of policies. One of the crowning achievements of much recent social science research has been to give greater prominence to the importance of mental wellbeing as a policy goal, in addition to the past focus on physical welfare, or on incomes and their economic situation. But to make government intervention practicable and effective in this area, metrics are needed that can be used to evaluate alternative policies. Recent years have seen a growing interest in wellbeing as a goal of public policy. This has led to significant advances in our understanding of the measurement of subjective wellbeing and its determinants. This book seeks to communicate to a wide audience of policy-makers, academics and students the policy implications of recent research on wellbeing, as well as emerging questions and challenges. New frameworks provide ways of moving ahead progress in measuring and acting on wellbeing at the household, regional or national levels. Some of the pioneers in the field are based at the LSE and the contributions in this book cover a mixture of well-known arguments and novel insights.

Richard Layard opens the book by considering the increasing **recognition of wellbeing** as an explicit and specific goal of policy-making in the past decades. An approach putting 'people and their wellbeing at the centre of policy design' recognises happiness and subjective wellbeing as the overarching good, and makes it the key criterion against which to judge the merit of different policy outcomes. This can lead to a radical shift in policy priorities because happiness research offers grounds to focus on social infrastructure policies and services – such as mental health, physical health, child development, family life and elderly care – rather than on the past priorities around economic infrastructure and long-term growth.

Paul Dolan's chapter next seeks to explore the far-reaching **policy consequences** of adopting wellbeing as a single, dominant metric to assess policy interventions. He advocates using the 'wellbeing-adjusted life-year (WELLBY)' concept for cost-benefit analysis. Focusing on the responses to the COVID-19 pandemic, Dolan points out a range of adverse distributional consequences that have been largely overlooked by focusing just on mortality risks, and by the use of very restrictive interventions such as lockdowns. This analysis argues that adopting a metric to capture subjective wellbeing and life experiences would enable policy-makers to better identify the costly ripple effects of policy responses, and who stands to gain or lose from them.

Yet looking at subjective wellbeing alone may also create different difficulties. In her response to Dolan, Johanna Thoma articulates how the use of a single metric necessarily relies on settling some contentious moral questions. For instance, wellbeing approaches that adopt an equity-weighted cost-benefit analysis, and prioritise the experiences of those who are worstoff on this indicator, neglect other factors. Yet in addition to subjective wellbeing resources, capabilities, or opportunities may all reasonably be thought of as of major concern for distributional equality. Other people may also object to the priority afforded to distributional concerns in the first place, for instance those who prioritise relational rather than distributional equality. Adopting a single metric may thus overlook and hide these contrasting moral concerns. Faced by reasonable disagreements about value Thoma argues that we need **multiple metrics** as an input into public deliberation.

The **capability approach** is one of the main alternative approaches to wellbeing in seeking to understand and measure quality of life. Its exponents often emphasise the challenges involved in trying to use subjective wellbeing as a reliable proxy for people's objective quality of life. These difficulties are especially acute because of the phenomenon of 'adaptation' – where people adversely affected by marked objective inequalities may nonetheless show high levels of subjective wellbeing. Their adaptation may hide (and possibly serve to justify) policy inaction on the objective inequalities involved. In his chapter, Paul Anand underscores not just the differences between the wellbeing and capabilities approaches, but also how in practice they often come to similar conclusions when identifying policy priorities. He sets out what the capability approach specifically contributes as a framework for policy, and how it enhances our understanding of the different dimensions and drivers of wellbeing.

In recent decades wellbeing research has had remarkable impact on health policy. Evidence showing a dynamic relationship between subjective wellbeing and health has grown, with influence running in both directions. There has been a widespread adoption of subjective measures of health and their incorporation into policy-setting. The next two chapters explore this relationship particularly in relation to mental health. Michael Daly and Liam Delaney analyse how the UK's **pandemic responses** affected mental health. They argue that the institutionalisation of wider measures of mental health and wellbeing would have led to a more holistic policy approach. It could also fulfil an important function in approaching emergency responses beyond the pandemic. Greater integration of multidimensional wellbeing measures into emergency responses would widen the disciplinary expertise informing government advisory bodies. And it would enable the development of better structures and frameworks for devising other timely policy interventions and evaluating societal impacts.

Annette Bauer next looks more in-depth at the specific types of mental health and wellbeing evidence that should be used to inform targeted, integrated, and long-term **responses to health emergencies**. Research exploring the root causes of poor mental health, and the mechanisms and factors that matter the most for addressing mental health problems, can contribute a lot here, as well as economic research to inform resourceallocation decisions.

Poor health and wellbeing may limit many aspects of people's social life, potentially including political participation in liberal democracies. Most political science attention has focused on the political determinants of health and health inequalities, but the last two chapters examine the less-explored side of the coin – how health status and wellbeing affect political participation and attitudes towards politics. A 'health gap hypothesis' was often assumed in the past, positing a positive relationship between a person's health and their political engagement. However, Christopher Anderson, Sara Hagemann and Robert Klemmensen present a more nuanced picture. They show that while ill-health is negatively correlated with political participation overall, there are **significant differences** across demographic groups. Indeed, for some groups there is a positive relationship between ill health and political motivation. Moreover, people's subjective sense of wellbeing and subjective health have stronger effects on their engagement with politics than does their reported health. This evidence opens up a set of questions which are crucial for policy, in relation to the role played by different health care systems and the political mechanisms underpinning them.

Mikko Mattila's chapter corroborates the **multifaceted impact of health** on different forms of political engagement. He particularly illuminates the distinctions and similarities between the definitions of health and disability in relation to political attitudes and activities. Disability can prevent some kinds of activism, but ill health need not. Conflating the two limits our understanding of their relationships with different forms of political engagement.

Looking across the book as a whole it is clear that wellbeing remains a powerful but contested concept, one that can be interpreted and used differently, with consequences for how it is incorporated into policy decisions. By bringing together scholars from economics, psychology and behavioural science, philosophy and political science, this book explores how different disciplinary approaches can contribute to the study of wellbeing and how this can shape both policy priorities and emerging research questions and challenges.

*Original versions of these chapters were commissioned for an issue of LSE Public Policy Review (https://ppr.lse.ac.uk), a journal that encourages inter-disciplinary commentary on contemporary issues, based on frontier-level research.*

## **2. Wellbeing as the Goal of Policy**

### Richard Layard

When policy-makers have multiple objectives, they still need an over-arching criterion which determines the importance of the different objectives. The most reasonable criterion is the wellbeing of the population. Fortunately, it turns out that this is also the outcome which most determines whether a government gets re-elected. We therefore argue that, wherever there is a fixed budget constraint, money should be allocated to those policies which give the greatest increase in wellbeing per pound of expenditure. If desired, now policies can focus especially on areas of life which cause the most misery. The new science of wellbeing provides evidence on which these are: especially mental and physical illness and poor relationships at work, at home or in the community. But, to approve a policy, there must be evidence of its effectiveness in dealing with the problem – preferably through controlled experiments. Where a policy increases the length of life, this counts as an addition to wellbeing, measured by Wellbeing-Years (or WELLBYs) per person born. Even policy-makers unmoved by wellbeing as an objective should promote it because of its large positive effects on productivity, academic learning and life-expectancy. If wellbeing is to play its proper role in decision-making, this will require a major re-organisation of Finance Ministries and other decision-making bodies.

## **The Overarching Criterion**

Most policy-makers have multiple objectives. But in the end, they have to decide whether one policy is better than another. Policy A may have a bigger impact on one objective and Policy B may on another objective. How to choose between the policies? The decision-maker must implicitly weight the importance of one objective compared with another. She must have some view about which objectives are most important. It would be much better to make this explicit by having and applying a single overarching criterion, against which to judge the merit of different outcomes.

That criterion should be the wellbeing of the people. There are of course many good things – health, wealth, freedom and so on. But for each of these goods we can ask 'Why are they good?' and expect an answer. For example, health matters because without it people feel lousy. Similarly with wealth, freedom etc. But if we ask 'Why does it matter how people feel?', we can give no answer. It self-evidently matters, which is why the happiness of the people is the most obvious candidate for the overarching good.

The great philosophers of the 18th-century Anglophone Enlightenment came up with the most obvious answer: the ultimate criterion is the happiness of the people – how they feel about the quality of their life as they themselves experience it **[1]**. As Thomas Jefferson put it 'The care of human life and happiness… is the first and only object of good government.'1 So a government committed to 'building back better' would wish to build back happier, and one committed to 'levelling up' would want to level up wellbeing and not just economic opportunity.

Many policy-makers have problems with the word happiness and instead prefer the term wellbeing. That is fine, provided we are clear that it is the people's wellbeing as they themselves judge it – not as some researcher or civil servant evaluates it. In other words, we are talking about 'subjective wellbeing'. The typical way of measuring this is to ask 'Overall, how satisfied are you with your life these days?' (0 = very dissatisfied, 10 = very satisfied). This question elicits very similar answers to the question 'Overall how happy are you with your life these days?' So when we talk about wellbeing, that is what most policy analysts have in mind.

Fortunately, more and more policy-makers in OECD countries and elsewhere now consider that policy should be targeted at wellbeing. In 2020 the EU Council of Ministers urged EU countries 'to put people and their wellbeing at the centre of policy design' **[2, 3 p76–79]**. In other words, the aim of policy must be to create conditions for the greatest possible wellbeing.

But this approach can only be implemented if we know what causes wellbeing. Until recently there was virtually no quantitative information on this subject, which is why the 18th-century ideal could only have been implemented crudely. But over the last forty years a whole new science of wellbeing has developed **[4, 5]**, which now tells us enough about the causes of wellbeing for this to become the stated objective of policy.

## **Political Reality**

But why would policy-makers want to maximise the wellbeing of society? Isn't their aim to be re-elected? Indeed, it is bound to be. But recent research shows that the best way for a government to be re-elected is to maximise the wellbeing of the people. A study of national elections in European countries from 1974 onwards **[6]** found that the best predictor of the government's vote-share in national elections was the life-satisfaction of the people. The decisive factor is not, as a Clinton aide once said, 'the economy, stupid'. If we look, country by country, at the variation of life satisfaction from one election to another, one extra standard deviation of life-satisfaction gives the government an extra 6 percentage points of the popular vote. By contrast, one standard deviation of economic growth gives only 3 extra percentage points of the vote(see **Figure 2.1**). So politicians who target the people's wellbeing increase their chances of remaining in – or gaining – power.

### **Figure 2.1: Effect of life-satisfaction and economic growth on the government's % share of the vote**

*Note*: Effect of 1 standard deviation increase in each variable on the government vote share (% points). Source: **[6]**.

Thus, it is not pie-in-the-sky to advocate (on ethical grounds) that policy should target wellbeing. Not only is it ethical, but it makes political sense, and is operationally practicable thanks to the advances in science.

### **Policy Appraisal**

So how exactly would a policy-maker choose the priorities for spending? We have to assume that the total volume of public expenditure is set by political forces. The task is therefore how to spend this total in the way that produces the most wellbeing. That means choosing those policies which produce the most wellbeing per pound spent. There would be some cut-off value for the cost-effectiveness of policies, with policies only qualifying if their ratio of wellbeing-benefit to cost exceeds the cutoff. Similarly, the redistribution of income would only proceed until further redistribution began to reduce total wellbeing. And regulations would only be introduced when this would increase total wellbeing.

This approach is less revolutionary than it might appear. It has in fact been standard practice in the health field in many countries. Health states are evaluated for their quality-of-life (on a scale of 0–1) and medical treatments are evaluated in terms of their impact on quality-of-life-adjusted life-years (or QALYs). They are only approved if they produce enough QALYs per pound spent.2 The wellbeing approach is essentially an extension of this method.

There are of course important differences. Wellbeing is how people feel about their whole lives, not just their health. And we are looking at the effects of every aspect of policy, not just healthcare.

Some of these effects are economic. So how does the wellbeing approach differ from traditional cost-benefit analysis, where benefits are measured in units of money? Unlike the traditional approach, the wellbeing approach can cover the whole range of public expenditure. By contrast, traditional cost-benefit analysis can only be applied over a narrow range of issues where the benefits either have an actual price, or a value which is implicit in the choices people make. This condition is not satisfied in most of health, social care, child protection, law and order, the environment and redistribution. Indeed, the reason the state is active there is precisely because in these areas market valuations and outcomes would be sub-optimal. So in these areas there is really no alternative to wellbeing (directly measured) as the criterion of benefit.

However, traditional cost-benefit is a totally valid way of measuring benefits in those areas where it can be applied. So the two approaches are complementary and they can be combined by transforming the money measures of benefit (derived from traditional CBA) into wellbeing measures by multiplying them by the marginal impact of money on wellbeing.3 Fortunately the British Treasury's Green Book manual of policy analysis now endorses 'social wellbeing' as the goal and approves the use of direct measures of wellbeing as well as their monetary equivalents **[7, 8]**.

## **Social Justice**

We shall turn to the evidence on wellbeing shortly, but at this point we have to confront a difficult issue. Is total wellbeing really the goal? Or should we not pay more attention to the prevention or the relief of misery? In other words, is it more important to raise the happiness of someone who is miserable than that of someone who is already happy?

Jeremy Bentham, the founder of the wellbeing approach, opted for the total sum of wellbeing as the goal. But many modern thinkers would take a more egalitarian stance **[9]**. They argue that it is more important to increase the happiness of those who are more miserable than to increase the happiness of those who are already happy.

There are two practical ways of implementing this more egalitarian approach. One is to measure social welfare not by total happiness, but in a way that gives less value to additional happiness the happier a person is.4 So when policies are being analysed, their value would be subject to sensitivity analysis to see how their comparative claims change as the analysis becomes more egalitarian.

Another, more practical approach, is to focus the search for new policies more heavily on those areas of life which account for the greatest amount of misery in society. This, in essence, is what the New Zealand government has done in its wellbeing budget from 2019 onwards.

### **The Science of Wellbeing**

That brings us directly to the evidence base for selecting the areas for new policy development and for evaluating them **[5, 10]**. What are the main determinants of wellbeing? And what are the main causes of misery? Our team at LSE recently analysed the findings from major longitudinal surveys in Britain, Germany, Australia and the US. The findings were similar in all these countries, and **Figure 2.2** gives the results for Britain. It shows how each factor – mental health, physical health, employment, quality of work, relationships, income and education – contributes to the inequality of wellbeing, holding the other factors constant. A parallel analysis shows how much each factor contributes to the prevalence of misery, and the ranking of factors is the same for each analysis **[5 Table 16.1]**.

Thus, as **Figure 2.2** shows, more of the misery in our country is due to diagnosed mental illness than to any other factor – and physical illness is also important. Next come human relationships – at work and in the family – and only then comes income. This finding is repeated in country after country. So we need a new, broader concept of deprivation – the inability to enjoy life for whatever reason, rather than just because of poverty.

This view of priorities is found by relating differences in people's wellbeing to differences in their situation (see **Figure 2.2**). An alternative approach to priorities is to simply ask people 'How much do you worry about the following issues (0 – never, 10 – a lot)?'. The results for a representative UK sample are shown in **Figure 2.3**. They broadly confirm the ranking of priorities shown in **Figure 2.2**.

#### **Figure 2.2: What matters for wellbeing?5**

Source: Clark et al. **[5 p74]**.

#### **Figure 2.3: 'How much do you worry about the following issues (0 never, 10 a lot)?' [11]**

Many of our adult characteristics are laid down in childhood, which makes it pertinent to ask which aspects of child development best predict a satisfying adult life? The answer is that emotional health at 16 is a better predictor of a happy adult life than all the qualifications a person ever gets **[5 Fig.1.2]**. But how can we influence a child's emotional health? The evidence is striking: primary and secondary schools (and their teachers) affect the emotional health of children as much as their parents do **[5 Fig.1.5(b)]**.

The policy implication of all this is clear. Policy-makers should give much lower priority to long-term economic growth and much higher priority to the services which sustain mental health, physical health, child development, family life and elderly care. It is the social infrastructure which matters most, not the physical infrastructure (as so many politicians wrongly seem to assume). To level up those areas which are left behind it requires better services more than better economic infrastructure. And our education system should teach more than the skills of earning a living – it should teach the skills of life.

### **Experiments**

But precisely how should we spend the money for these important aspects of life? We can only know what works by the process of experiment. It is not enough to address the right problem and to have good intentions. The next step in advancing wellbeing is through conducting thousands of experiments to discover which policies make the most difference to wellbeing per pound spent. Let me give a few examples.

In British schools there have been a series of attempts to teach life skills. The last Labour Government introduced a programme called Social and Emotional Aspects of Learning (SEAL). Its impact was evaluated in secondary schools and found to be zero – no effect on emotional, behavioural or academic outcomes **[12]**. The reason was identified as insufficiently structured materials and a lack of teacher training. By contrast, a more recent 4-year weekly curriculum in secondary schools called Healthy Minds was found to raise the student's life-satisfaction by 0.4 points (out of 10). If we convert this into a measure of quality-of-life, the cost per extra QALY was only £1,000 – well below the standard criterion of around £25,000 for additional health expenditure **[13, 14]**.

Turning to adults, hundreds of clinical trials of modern psychological therapy show 50% rates of recovery for depression or anxiety disorders after an average of some 10 sessions. They also show that the patients treated will work on average one additional month over the next two years as a result of the treatment. This generates enough additional income to cover the cost of the therapy. On this basis, Layard et al. **[15]** proposed a programme of Improved Access to Psychological Therapy. When implemented, the results of the trials were repeated in the field **[16, 17]**.

Clearly the same experimental approach should be used by voluntary organisations as by public policy-makers. For example when the Action for Happiness movement's Exploring What Matters Couse was evaluated, it was found to increase life-satisfaction by over 1 point (out of 10) **[18]**.

One general point needs to be made about social experiments. Even if the experimenter's main target is not wellbeing, wellbeing should always be measured throughout the experiment.

### **Cost-Effectiveness and Modelling**

It is of course important to evaluate not only new policies but also existing policies in terms of their cost-effectiveness. This is not easy, and I offer **Table 2.1** in the hope that others will improve on it. In it I examine the cost effectiveness of different ways of reducing by one the number of people in misery over a twelvemonth period. According to this analysis, the cheapest of the four methods is treating more people for depression and anxiety disorders (this analysis ignores the flow-back of savings). Active labour market policies come second – encouraging evidence of what we might expect from the current government's Kickstart initiative. Then comes physical health, and finally come income transfers to the poor. We could alternatively do the analysis in terms of the impact on total wellbeing (rather than on misery) but the results would be very similar. Many of the coefficients


### **Table 2.1: Average cost of reducing the numbers in misery, by one person**

*Source:* **[20]**.

are already known, but others will need to be determined **[10, 19]**. And a major exercise will be needed on the costs and costsavings of each possible policy.

Either way, this analysis is very crude. But, as time passes, it will become possible for Finance Ministers to do a much better job. For this they will need


The second of these is a major project – just as it was in previous times a major project to develop models of the macroeconomy and of the impacts of policy changes upon the finances of households. This new project is equally important and will need significant money to finance it.

### **The Length of Life and WELLBYs**

One further point on modelling. Many policies affect the length of life. So our measure of the impact of policies needs to take this into account. How? We want people to have lives which are long and full of wellbeing. So the simplest approach is to say that we want for each individual the maximum total wellbeing-years, where we simply add up the wellbeing in each year of their life. A natural acronym for wellbeing-years is WELLBYs, (just as medics talk of QALYs meaning quality-of-life-adjusted life years). So we wish that each life will have the largest possible number of WELLBYs. (If the effects are distant – a pure social timepreference rate of say 1.5% a year needs to be applied.)

This approach has huge implications for policy, especially for policies involving safety and the risk of death. At present the value of life in terms of money is derived from one of two methods:


These methods involve major assumptions. By contrast, the wellbeing approach is very simple: it simply examines the change in WELLBYs **[21]**. And it yields a very different trade-off between money and life-years from that implied by traditional methods. In the wellbeing approach an extra year of life is of equivalent value to up to £750,000 **[22]**. 6 By contrast, existing methods yield values well below £100,000.

Which approach is the more plausible? Traditional values would not justify a lockdown to save lives threatened by COVID-19, while the wellbeing approach would **[23]**. And public opinion supported the lockdowns. So the wellbeing approach would seem to be in tune with public opinion. Thus it does seem that future policies should give more weight to the preservation of life relative to other objectives – compared with what happened before COVID-19. This does not mean an increase in public expenditure, which we take as given. But it does mean a rebalancing.7

## **The Effect of Wellbeing on Other Goods**

We have so far focused single-mindedly on wellbeing as the overarching good. We need recruits to this view! But, even if you do not buy that, you should take wellbeing very seriously because of its good effects on other things you value. So here are some important facts.


## **The New Organisation of Policy-Making**

So, if a government wanted to implement the wellbeing approach, what new procedures would it need? Bids for public money would need to be justified by their effects on wellbeing, and this would apply to current as well as to capital expenditure. Officials would need help in making these estimates. So the Finance Ministry would need to include a Wellbeing Appraisal Group to help train departments in how to make their proposals – and then to vet them when they arrive. At local level there would be Local Wellbeing Agreements between local authorities and local social services about how to raise the wellbeing of residents. There would be an annual report to Parliament on how the nation's wellbeing had developed – and how government policy had impacted on it.

### **Conclusion**

The wellbeing approach is not new. Its adherents have included William Beveridge, architect of the British welfare state and Sidney and Beatrice Webb, the founders of the London School of Economics.

But now its time has really come. There is an explosion of articles (academic and popular) on both wellbeing and mental health (see **Figure 2.4**). More and more universities around the world are teaching the subject, producing a body of trained analysts able to apply these ideas to policy. The OECD have persuaded all member countries to measure the wellbeing of their people **[32]**. The governments of five countries have formed an alliance called the Wellbeing Economy Governments partnership (WEGo).10 So in future years we shall surely see a major change in policy-making.

The common currency will become not money, but wellbeing.

**Figure 2.4: Articles on wellbeing in academic journals**

*Source:* George Ward in **[3]**. Number of papers in the EconLit and Web of Science databases with reference in the title or abstract to: subjective wellbeing, subjective wellbeing, life satisfaction, happy, or happiness.

### **Notes**

1 Thomas Jefferson to the Republicans of Washington County, Maryland, 31 March 1809.

2 The UK's NHS provides treatments approved by the National Institute of Health and Clinical Excellence (NICE) using the QALY framework.

3 What economists call the 'marginal utility of money'.

4 So social welfare would be not ∑*Wi*, where W is wellbeing. It would be *∑f(Wi) with f ' > o and f " < o*. One version of *f(Wi)* is *Wia/a, with a < 1.* 

5 On the quality of work see p.74; 0.16 = (0.4/1.9) × Labour force participation rate.

6 This depends on the value of the income coefficient in the wellbeing equation. This can be quite low. For example if In a typical wellbeing equation, Wellbeing = 0.3 log Income. So dIncome/ dWellbeing = Income/0.3 = say £100,000. Since the typical life-year provides 7.5 WELLBYs it would therefore be of equivalent value to £750,000.

7 If benefits are measured in WELLBYs, the monetary equivalent of a life-year does not appear directly in the calculations, but it is implicit.


10 Scotland, Iceland, New Zealand, Wales and Finland. https://weall.org/

### **References**


## **3. Accounting for Consequences and Claims in Policy**

## Paul Dolan

Fully appraising any policy requires us to capture all of its ripple effects and not simply the size of the splash when the pebble of intervention hits the water. It also requires that we weight the value of those effects according to morally relevant characteristics of people, such as their age. In this chapter, I discuss the consequences that should feed into policy appraisal and the claims that different groups may have on resources.

### **1. Introduction**

One of the main aims of government is to reduce misery and suffering by as much as possible, subject to resource constraints. Fully appraising any policy requires us to capture and quantify all its possible short- and long-term ripple effects, and not simply the size of the splash when the pebble of intervention hits the water. Indeed, sometimes the ripple effects might turn out to be much more significant than the initial splash, especially in the longer term.

In their response to the pandemic, policy-makers have prioritised preventing deaths from COVID-19 above everything else. Concerns for lives have trumped concerns for life expectancies, let alone concerns for life experiences, which have been largely ignored. Policies have focused on the splash with much less regard for the ripple effects. This has resulted in the use of very restrictive mandated non-pharmaceutical interventions (NPIs), or 'lockdowns'. Regardless of what our individual views on such responses may be, important lessons can be learned in terms of how policy-makers can and should respond to future crises. Indeed, there are lessons that come out of COVID-19 for how to make better policy decisions in calmer times too.

**Figure 3.1** sets out, in a highly stylised and linear way, the ten main steps to effective decision-making. It illustrates how step 3 – the expected splash – has dominated decision-making, whilst steps 4–9 – properly accounting for the ripple effects – have largely been bypassed. But these are crucial steps if governments are to minimise the harms caused by a pandemic, as well as if they are to use their resources wisely at any time. Anyone who understands the reality of living in a society with limited resources will recognise the incongruence of trying to make good policy decisions whilst ignoring the broad aggregated effects that those decisions have across society.

### **Figure 3.1: Ten steps to effective decision-making**


In this chapter, I will focus on steps 6 and 9, and especially distributional concerns, which can sometimes be an afterthought for economists. I will consider the ways in which we might bring together the myriad ripple effects of any policy decision into a single metric. Much as the ripples on a pond can be quantified in a single metric of displaced water, so do we need to construct a single metric for policy purposes that shows the cumulative effects of a pebble of intervention. Given that we all care strongly about how long we and other people live, as well as about the quality of those lives **[1]**, we need measures that can better capture changes in both life expectancy and life experience.

This single metric should also account for distributional concerns. Accounting for who gains and who loses, as well as by how much, will enable us to allocate resources fairly as well as efficiently. Such accounting requires us to consider the legitimacy of the various claims that different groups may have on resources. In the case of COVID-19, the mortality and morbidity risks have been concentrated amongst older people, so we need to address the ethical justification of asking younger people to make enormous sacrifices for people they cannot expect to live as long as.1

## **2. A Single Metric**

Any policy designed to counter the threat of a pandemic will affect at least one, if not both, of life expectancy and life experience. Let us start slowly in our journey towards a single metric by focusing on life expectancy. Even if we moved away from lives to life years, it is possible to account for the expected effects on the life expectancies of those affected by COVID-19, plus those who will die sooner due to health services being displaced from elsewhere to treat COVID-19 patients, or due to patients missing urgent cancer diagnoses and treatment due to sticking to a 'stay at home' message **[2]**. At the same time, any appraisal of policy should acknowledge that reductions in educational opportunities and in people's mental health also reduce life expectancy **[3]**. Loneliness is another good example because it is a significant risk factor for all-cause mortality **[4]**.

The next step would be to adjust life-years to take into account their quality, here using quality-adjusted life-years (QALY). QALY values are obtained by asking individuals to make hypothetical trade-offs between length of life and particular quality-of-life-limiting health states, including limitations in areas such as mobility, self-care, ordinary activities, pain and discomfort, and mental health. By trading off life-years for improvements in each of these health states, the value that people attach to a particular state can be located on a scale between zero for death and one for full health **[5]**. Given the widespread use of QALYs in the UK, it is surprising that they have not featured prominently in appraisals of pandemic response policies either; see Miles et al. (2020) **[6]** as an exception.

Using QALYs as an established and widely used welfare metric allows us to readily account for lives as well as life experiences in appraising polices. There are two main problems here, though. This first is the hypothetical nature of eliciting values: we know that people are not particularly good at predicting how certain health states will actually impact their quality of life. For example, they may overestimate the duration of the impact that a change in their health may have on their lives, they may underestimate their capacity to adapt, or they may overly focus on specific details of that change without seeing the broader picture **[7]**.

The second challenge is that QALYs focus only on healthrelated life experiences. It is true that most health state descriptive systems do include a wide range of dimensions, but they will only capture the effects of loneliness, for example, through its effects on those dimensions, such as a person's usual activities. But being asked to stay at home in a single-person household for several months will directly and indirectly affect wellbeing through its effect on multiple health-related dimensions of wellbeing. The use of QALYs is a huge advance beyond using life-years alone, but it will continue to skew resource allocation decisions towards health-related interventions.

The next and final step, then, is to use people's self-reports of how they are feeling to adjust life-years by their quality. Subjective wellbeing (SWB) measures include people's overall life evaluation or their hedonic experiences on a day-today basis. Unlike QALYs, people are not asked to make hypothetical trade-offs but are surveyed about their wellbeing as they go about their lives. This makes these measures less prone to the bias resulting from the hypothetical nature of QALY-type tradeoffs. It also allows us to express changes in wellbeing that occur due to changes in health, economic, and social conditions in a single unit of account **[8]**. Combining this unit of account with life-years yields a wellbeing adjusted life-year (WELLBY).

There are important yet unresolved issues about how best to capture SWB for the purposes of generating WELLBYs. Any measure must be able to properly account for the duration as well as the intensity of wellbeing. It has therefore been proposed that we measure wellbeing as the flow of feelings over time **[9]**. I define this flow as including hedonic (pleasure-related) feelings such as joy, pain, and worry and eudemonic (purpose-related) ones such as worthwhileness, pointlessness, and futility **[10]**. This distinction matters. For example, working is an activity that is experienced as low in pleasure but relatively high in purpose **[11]**. How people's SWB is measured will affect conclusions about how societies can be structured and about how individual lives can be organised to maximise it.

Notice the focus is on a person's experiences, rather than on their evaluations of, say, life satisfaction. Evaluations of this sort will be relevant only when we are paying attention to how well, or badly, we think life is going, and even then only in terms of how they feed into our feelings of pleasure or purpose. Evaluations are also heavily influenced by relative comparisons and therefore are shaped by the attentional stimuli to which people are exposed **[12]**. In this way, much like preferences, evaluative measures of SWB feed into our feelings. Indeed, reports of life satisfaction are arguably closer to a preference-based account of welfare than they are to the mental state account **[13]**. The extent to which this is a good or a bad thing is beyond the scope of this chapter.

Whatever measure(s) of SWB we use, for the purposes of economic appraisal, it is entirely possible and legitimate to express its benefits in a single, non-monetary metric that can then be compared to its costs, so generating a cost-per benefit unit. Costper-QALY estimates, for example, allow us to determine the allocation of resources that would generate the most QALYs for a given budget allocated to healthcare. If all benefits across different sectors could be captured in WELLBYs, then the resources devoted to the public sector could be distributed in a way that would generate the greatest number of WELLBYs. This would be to use resources as efficiently as possible.

For the purposes of cost-benefit analysis (CBA), benefits need to be expressed in the same monetary units as costs. This will enable us to determine whether a policy intervention was worth it per se – by generating more benefits than costs – in addition to whether it was worth it compared to other interventions. In principle, this will enable us to determine the size of the public sector and how best to allocate resources within it. There are several ways of monetising wellbeing, but each raises several challenges beyond the scope of this chapter. Suffice to say that cost-per-WELLBY for analysis might be where we finally end up.

Wherever we do end up, we must be able to show just how much water is displaced when the pebble of policy intervention is dropped into the water. The consequences of policies introduced now are likely to have tidal waves of effect across many sectors and domains of society for years to come. These must be taken into account in deciding what action to take.

### **3. Distributional Concerns**

At the societal level, citizens and policy-makers care not only about how many life years, QALYs, WELLBYs or whatever are being generated per pound spent but also about how those benefits are distributed across people. Just as we care about national income and about inequalities in income, we care about the size of the wellbeing cake and about how fairly the slices are distributed. The fairness of the distribution will be determined by the legitimacy of the claims that different individuals or groups can make on resources **[14]**.

### **3.1 Five claims on resources**

There are some general statements that most of us would agree with when considering where different groups of people should be placed in the queue for scarce public resources. Other things being equal, those with the greatest claim on resources (those with the most ethically justifiable reasons for being towards the front of the queue) are those who most fully satisfy the five conditions discussed later.2 In principle, all five could be considered when setting priorities. There is no simple way to resolve any 'dispute' between the conditions, and different trade-offs between competing claims will doubtless be deemed acceptable in different circumstances. In determining how to weight each competing claim, public preferences over various trade-offs can help reach conclusions, so I discuss some of this evidence here.3

### *Those who have the most to gain*

This is a claim to resources based on an individual's 'capacity to benefit' as a result of any intervention. The more a person can expect to benefit from intervention, the closer to the front of the queue they should be. If Person A can expect to gain ten years of extra life from an intervention, then their claim is greater than Person B, who can expect to gain only ten months of extra life. Allocating resources only on this basis would mean that resources were being used so as to maximise the bang for the buck. Capacity to benefit is all that matters when we conduct CBA or cost-effectiveness analysis (CEA), for example, and it would mean generating as many WELLBYs as possible. On a fundamental level, capacity to benefit is a prerequisite for a person to even be in the queue: it would be a waste of resources to 'treat' them if there was no expected benefit at all. But it is not all that matters in determining their position in the queue. There are other morally relevant claims too.

### *Those who are currently suffering the most*

This is a claim to resources based on 'severity of condition' in the absence of intervention. Let us take the two individuals discussed above. If Person B will die shortly without an intervention and Person A will live for another five years regardless, then our priorities might change. There are now good ethical grounds for putting Person B in front of Person A in the queue for resources because their prospects are more immediately severe in the absence of intervention. The ethical grounds for putting Person A in front of Person B on the grounds that they will benefit from treatment more remain, however. Herein lies a classic trade-off between claims based on benefit and those based on severity.

I have conducted various empirical investigations into what the public thinks about how these competing claims should be accounted for and traded off against one another. In a nutshell, they suggest that a person's capacity to benefit and the severity of their condition both matter in every decision context I have enquired into, from triage decisions to macro resource allocations **[15]**. Context matters, of course, and it is impossible to provide a consistent value for the exchange rate between them. Suffice to say that the public would want policy-makers to account for what happens to people both in the presence and in the absence of an intervention when deciding what to do.

### *Those who will suffer the most over the lifetime*

Capacity to benefit and severity of condition are both prospective assessments of what the profiles of future wellbeing look like in the presence and absence of intervention. But some people might have a legitimate ethical claim to be further up the queue based on a retrospective assessment of what happened in their past, as well as based on what is expected to happen over their lifetime. Imagine that capacity to benefit and severity of condition are the same for two individuals or groups, but that one has experienced more suffering – or less wellbeing – in the past than the other. We might prioritise them on this basis. Or we may wish to afford higher priority to those who are expected to experience more suffering over their entire lifetime. We might also decide to prioritise those who have had less opportunity for wellbeing, such as when we prefer to give a given benefit to younger over older people.

It is also clear from public preference data that members of the public wish to account for wellbeing over the lifetime **[16]**. In one of my empirical studies on priorities by age, we controlled for capacity to benefit by asking people to prioritise a fixed fiveyear gain in life expectancy for people at age 5, 20, 35, and 55. In the study, 70–96 per cent of people had one of the three youngest ages ranked first **[17]**, with 'having lived less' life being the main reason for prioritising younger people **[18]**. This is consistent with the fair innings argument (FIA) – the egalitarian principle that everyone is entitled to some 'normal' span of health (usually expressed by life-years) and that anyone failing to achieve it has been 'cheated' **[19]**.

### *Those who are suffering because of 'bad luck'*

How well or how badly our life turns out is determined by factors that lie on a spectrum from being entirely outside of our control (exogenously determined) and entirely within our control (endogenously determined). Although nothing is ever truly chosen, most people would locate illness caused by a genetic cancer to be closer to the exogenous end of the spectrum than illness caused by the 'choice' to go mountaineering, for example. As such, someone suffering because of 'bad luck' would have a claim to be closer to the front of the queue than someone suffering, at least in part, because of 'bad choices' **[20]**.

The cause of any need for an intervention is a hotly contested area of ethical discourse, and public preferences are mixed and malleable. In some of my own work, people became much less 'harsh' on bad choices when they had been given opportunity to discuss and reflect upon why some people make very poor decisions, at least insofar as their heath is concerned **[21]**. For what it's worth, as I understand more about how so much of what we do is outside of our control, I am less convinced about the moral relevance of the causes of the need for resources than I was a couple of decades ago **[22]**. But if we accept that we have a modicum of agency (which most people do), then truly exogenous 'bad luck' will reflect a legitimate claim to be closer to the front of the queue for resources **[23]**.

### *Those who have the greatest impact on others*

Imagine that you are responsible for allocating one donor kidney, and you have two people whom it matches equally well. One is a 40-year-old homeless man with no family, and the other is a 40-year-old happily married man with two young children and parents that he supports emotionally and financially. Whom would you choose? Either decision is morally justifiable (including tossing a coin to decide), and your instincts might be to discount the wider benefits that might come from treating one person over the other. (The homeless person might also have experienced 'bad luck', which shows how interconnected the various claims can be.) In any case, the important point here is that it is legitimate to choose the married man on the grounds that he has the greatest capacity to benefit other people.

Unsurprisingly, the expected impact on other people is also hotly contested **[24]**. The utilitarian solution, which is embedded in the principles of CBA, is to treat benefits to other people no differently than benefits that go directly to the recipients of the intervention. Why treat the ripple effects any differently from the splash? Admittedly, not all of us are utilitarian, but there will most likely come a point at which most of us would want to account for spillover effects: imagine our married man was an integral part of a team that was on the verge of a cure for cancer. This somewhat extreme example illustrates how complex ethical decisions can be and how no single principle can be seen to dominate any other in all contexts.

### **3.2 Claims in the context of COVID-19**

Based on the foregoing discussion, we would expect policymakers to account for a person's capacity to benefit, severity of condition, and lifetime suffering in their prioritisation decisions. And yet in the case of COVID-19, arguably only severity has been considered. It has been very interesting to me that any attempts to raise concerns about capacity to benefit and lifetime wellbeing have been greeted with moral outrage. Despite the public outrage, this is morally relevant.

This in no way suggests that we simply let people die, but rather that we manage their deaths properly so as to create as much benefit as possible both for the dying person and, crucially, for those left behind. We must do more to accept death, especially in old age, and to minimise the impact death has on family and friends. Some of you might have baulked at the idea of treating a cancer specialist over a homeless person, but the utilitarian arguments for maximising the benefits from an intervention become much more compelling when they are framed around minimising the suffering of all those affected by someone's death.

The impact of a death is unquestionably affected by the age of death. The average life expectancy for an 18-year-old in the UK today is around 81. According to the ONS, around 60% of the deaths from COVID-19 in the UK have been in people who are 81 or older. Substantively, most of those bearing the biggest burden from COVID-19 won't live for as long as those who are dying from it. If people's lifetime prospects are an important measure of human welfare, then we have engaged in one of the biggest redistributions of resources from those who have the least to those who have the most in human history.

It is baffling to me that there has not been more – or any – real discussion of the potential injustice of this. Ever since I worked with Alan Williams at the University of York in the 1990s, I have supported the FIA. I contend that it is a sentiment shared by most of the public. You could say that we are ageist, and we are. But not all -*ism*s are unfair. If we afford a 35-year-old priority over a 70-year-old now, then in 35 years' time, the current 35-year-old will be given less priority as a 70-year-old, so everyone is treated equally over the lifetime. This is assuming that we are all lucky enough to live that long, which about one in five current 35-yearolds won't. When we look at a cohort of older people, we are subject to 'survivorship bias' – we see only the lucky ones who have survived and do not properly consider all those who have been cheated out of a fair innings.

I should again stress here that the FIA I have in mind here does not suggest that older people should simply be allowed to die because they have already achieved a fair innings, but only that they should be afforded less priority for life-saving interventions than those who have not yet lived as long. During the pandemic, younger people have been denied access, for instance, to cancer diagnoses and treatment to prevent the deaths of older people from COVID-19. This represents a gross violation of the FIA. You might say that it is all well and good to have rational principles in calmer times, but that a pandemic represents an immediate threat to life, so all efforts should rightly be directed towards mortality risks (severity of condition). Perhaps, but times of crisis arguably make rational considerations even more important.

Besides, concerns for lifetime wellbeing don't just disappear during a pandemic, to which empirical work I conducted with Amanda Henwood and Aki Tsuchiya attests **[25]**. We conducted an online discrete choice experiment (DCE) to elicit the preferences of the UK public on two occasions: May 2020 (*n* = 6,153) and February 2021 (*n* = 1,024). The DCE asked people to make trade-offs across four attributes, including excess deaths above age 70 and excess deaths below age 35. We found that the relative value of mortality above 70 to below 35 is roughly 1:24. These preferences were stable across the two surveys and across respondents of different ages.

A more sophisticated version of the FIA would account for life experience as well as life expectancy. It is impossible to know what ripple effects COVID-19 would have caused if we had pursued a different set of policy options (step 10 in **Figure 3.1** above), such as the focussed protection of older people **[26]**, so we must all be measured in our judgements of what should have been done. But we do know that lockdowns have disproportionately affected families of low income **[27]**, that domestic violence has increased for those at risk **[28, 29]**, that school closures will further widen the attainment gap **[30]**, and that social distancing causes greater harm to those with pre-existing mental health conditions **[31]**, lower starting wellbeing **[32]**, younger people **[33]**, women **[34]**, and children from disadvantaged backgrounds **[35]**. Some of these effects on mental health may not be easily restored **[36]**.

### **4. Conclusion**

This chapter is not only, or even primarily, about COVID-19. The 10 steps to effective decision-making set out in **Figure 3.1** are always required for policy-makers. The process of going through each step, especially steps 4 and 5, ensures that the important downstream effects of policy are properly accounted for. These consequences might affect a population group that is largely ignored (such as young adults who do not go to university), a dimension of wellbeing that falls between the cracks of government departments (such as loneliness), or that will occur some time into the future (such as the effects of childhood development on later life). We should be doing all we can to ensure that equity-weighted wellbeing measures are developed as quickly as possible and used as widely as possible.

The significance of these steps has been magnified during the pandemic. Around the world, the dominant response to COVID-19 was to seek to significantly reduce social contacts through MNPIs, or 'lockdowns'. This pebble of intervention – perhaps the biggest stone that ever has been dropped into the water – has been assessed almost entirely in terms of its effects on the splash of mortality risks (step 3 in **Figure 3.1**). Most of the significant ripple effects have barely been listed (step 4) let alone quantified (step 5). We must do better in the future. In this chapter, I have focused partly on generating a single index (step 6) and mostly on distributional concerns (step 9), which will come after the single index has been monetised (step 7) and compared to costs (step 8).

All policy responses, especially lockdowns, have had enormous distributional consequences **[37]**. Based on evidence from previous and less impactful pandemics, we can be confident that inequalities in health and wealth will widen **[38]**. We also need to be alert to the fact that what feeds into the wellbeing of the worst off may be different to that which matters on average, or to those who are doing the best in society. The policy responses to the pandemic have reminded us just how much policy can shape the distribution of wellbeing across society.

Whatever our own views on the measures taken – and the absence of a good counterfactual (step 10) makes it impossible for any of us to be sure about what should have done **[39]** – we need more public preference data on how people weigh up competing claims to resources and precisely which principles of justice matter most in which contexts. Despite the widespread support for MNPIs from polling data, when people are asked to consider their effects beyond mortality risks amongst older people, there exists a potential disconnect between public preferences and the policy responses.

Empirical investigation of these issues can only get us so far. We also need to ensure that the policy-making processes better reflect the myriad concerns and impacts of policies, and we need to consider that there is a constant backdrop of a powerful social narrative to preserve life at almost any cost **[40]**. But that's another story. For now, the two main messages from this chapter are that in times of calm as well as at times of crisis, we should (1) seek to express all the consequences of a given policy in a single metric and (2) properly account for the legitimate claims that different people may have on resources that extend beyond any snapshot in time and encompass wellbeing over their entire lifetimes.

### **Author Contributions**

This paper is the result of various discussions, collaborations, blogs, and reports. Those who have inspired me (and whose ideas I may even have stolen) know who they are. I am indebted to Celia Blanco-Jimenez for helping me pull together the references and for providing helpful comments on a draft of this paper. The usual disclaimers apply.

## **Notes**

1 Effective decision-making not only requires distributive justice (an efficient and fair allocation of resources) but also requires procedural justice (that the processes by which decisions are made are seen to be fair). Processes will be especially important when there is uncertainty about the outcomes. In court cases, for example, we don't know whether they 'did it' or not, so we seek to ensure that the trial process by which we reach that conclusion is a fair one. This paper focuses only on distributive justice. For more on details on what I would propose in relation to better processes, see Dolan et al. (2021) and Dolan and Henwood (2021).

2 In what follows, I will assume that (1) there is an agreed measure of welfare – life-years, health, happiness, or whatever – and (2) the measure allows for some degree of interpersonal comparability.

3 It should go without saying (but I'll say it anyway) that public preference data can never resolve the normative debate about the legitimacy of claims – and neither can they resolve the normative debate about the degree to which those preferences should be used to inform moral judgements in the first place.

## **References**


*Health Economics*. 2005; 14(2): 197–208. DOI: https://doi.org /10.1002/hec.924


*Economics Letters*. 2015; 136: 99–102. DOI: https://doi.org/10.1016/j .econlet.2015.09.010


## **4. Weighing the Costs and Benefits of Public Policy: On the Dangers of Single Metric Accounting**

## Johanna Thoma

This chapter presents two related challenges to the idea that, to ensure policy evaluation is comprehensive, all costs and benefits should be aggregated into a single, equity-weighted wellbeing metric. The first is to point out how, even allowing for equity-weighting, the use of a single metric limits the extent to which we can take distributional concerns into account. The second challenge starts from the observation that in this and many other ways, aggregating diverse effects into a single metric of evaluation necessarily involves settling many moral questions that reasonable people disagree about. This raises serious questions as to what role such a method of policy evaluation can and should play in informing policy-making in liberal democracies. Ultimately, to ensure comprehensiveness of policy evaluation in a wider sense, namely, that all the diverse effects that reasonable people might think matter are kept score of, we need multiple metrics as inputs to public deliberation.

## **On Comprehensive Policy Evaluation and Single Metric Accounting**

When policy interventions have far-reaching consequences for years to come it is important to make sure to take proper account of all relevant effects in evaluating one's options. This is the case for decisions made at times of crisis, like those in response to the COVID-19 pandemic, as well as for decisions made in ordinary times. As Paul Dolan puts it, there is the initial splash of the policy, but there are also the ripple effects. We must pay attention to both [**1**, Chapter 3 of this book]. He laments that, in the UK at least, there has been too much of a focus on one type of initial effect of pandemic responses, measured using a single metric, namely, number of lives lost in the short-term. Too narrow a focus on this single measure has made us lose sight of costly ripple effects on long-term health (including mental health) and the economic prospects of young generations in particular.

It is hard to disagree with a call for public policy evaluation to be comprehensive, in particular when the stakes are high. Yet clearly, this is also a point that often needs (re-)emphasising. The pandemic appears to be such a moment in time. Beyond a call for comprehensiveness, however, Dolan also defends a particular form that policy evaluation should take, drawing on his long record of ground-breaking research on happiness and public policy. Interestingly, a single metric also features as part of his proposed strategy for making sure everything is taken into account: all costs and benefits, short- and long-term, should be aggregated using a single metric. And then policies should be evaluated in terms of the value and distribution of that metric. More specifically, the metric Dolan proposes to be used is subjective wellbeing adjusted life years, or WELLBYs **[1 p4]**. 1 That is, what we should be aggregating is how many life years are gained and lost as a consequence of the policy intervention, where life years are weighted by a measure of the self-reported quality of people's experiences. This WELLBY metric is then used in an equity-weighted cost-benefit or cost-effectiveness analysis, allowing for gains and losses in WELLBYs to count for more when they occur to the worst off.2

WELLBYs will remind the reader of the more well-known QALY (quality-adjusted life year) metric, widely used in policy evaluation in public health (although, interestingly, as Dolan points out, little-used so far during the pandemic). But QALYs are restricted to the evaluation of health-related outcomes, whereas WELLBYs are intended to be, in line with the guiding thought of the proposal at hand, more comprehensive. And while the measurement of QALYs typically relies on hypothetical comparative judgements people make about different health states, the measurement of WELLBYs is supposed to be based, as much as possible, on direct reports of how different outcomes are actually experienced when lived through. Here Dolan puts his cards on the table **[1 p5]:** What WELLBYs aim to capture is a hedonistic notion of wellbeing; a good life is one of good (pleasurable, purposeful) experiences.

Relative to a hedonistic standard of what a good life is, people's own hypothetical comparative judgements often come out biased. Using a hedonistic metric as a measure of costs and benefits in a standard cost-benefit analysis is a way of implementing a hedonistic form of utilitarianism, according to which the sum-total of subjective wellbeing should be maximised. Equityweighting one's cost-benefit analysis, on the other hand, implements a hedonistic form of prioritarianism, according to which the experiences of the worst-off count for more.

The philosophical debate on hedonism as a theory of wellbeing, and on utilitarianism and prioritarianism is vast,3 and, it is safe to say, will never reach a consensus on the central issues. Instead of offering a critical discussion of these particular moral views and their application in public policy evaluation, I would like to take a step back and consider the more general idea that a single metric should be used in order to aggregate the many effects of public policies and to articulate the trade-offs involved in making a decision. I will offer two related challenges to this idea.

The first is to point out how the use of a single metric limits the extent to which we can take 'distributional concerns' into account, making the moral commitments embodied in such approaches narrower than it might initially seem. The possibility of equity-weighting is often presented as a way to flexibly accommodate those with more egalitarian leanings, giving the appearance of a 'broad church'. But equity-weighting can only accommodate concerns about the distribution of the single metric that is being equity-weighted. And those with egalitarian leanings often also care about the distribution of other things (or indeed equality of a non-distributional kind).

The second challenge starts from the observation that in this, and in many other ways, the choice of a single metric and its implementation in the aggregation of diverse effects necessarily involves settling many moral questions that reasonable people (including even, sometimes, philosophers) disagree on. This raises serious questions as to what role such a method of policy evaluation can and should play in informing policy-making in liberal democracies. Ultimately, to ensure comprehensiveness of policy evaluation in a wider sense, namely, that all the diverse effects that reasonable people might think matter are kept score of, we need multiple metrics as an input into public deliberation.

### **What Else Might Matter**

The hedonistic theory of individual wellbeing is only one of several major kinds of theories of what is good for individuals. Some have argued that what is good for you is to get the things you desire, or would desire under some ideal conditions, whether you desire pleasurable experiences or not. The pandemic and the policy responses to it around the world have massively frustrated people's life plans. According to desire-fulfilment theories, this would matter a great deal whether or not going through with those plans would have made people happy. Others have argued that there are some things that are good for people whether they enjoy or desire them or not. If education, engagement with the arts, regular gatherings with family, or direct contact with different ways of life are such things, again the pandemic and policy responses have undermined these in ways that a hedonistic wellbeing measure might not capture.

Using a metric for policy evaluation based on any one of the available theories of wellbeing means using a metric that risks leaving out or not doing full justice to some of the things at least some reasonable people take to be morally relevant. Moreover, many people believe that there are things other than wellbeing that matter, such as freedom (as is again very relevant during the pandemic), or the preservation of the environment for its own sake. In this respect, too, equity-weighted cost-benefit analysis using a broadly hedonistic wellbeing measure cannot capture everything deemed to be morally relevant by at least some parts of the population. Perhaps less obviously, I want to focus here on how even those who agree that the hedonistic theory is the correct theory of individual wellbeing, and that all else that matters are 'distributional concerns' may not be satisfied that equity-weighted subjective wellbeing-based costbenefit analysis captures everything that is morally relevant. This is because the framework can accommodate some, but not all distributional concerns.

Just as there is lively debate on what the correct theory of individual wellbeing is, there is debate on the metric(s) of equality or priority: Equality *of what* or priority in access *to what* matters? Having a single metric for the purposes of policy evaluation, and accommodating distributional concerns through equityweighting commits us to using that same single metric as our metric of equality or priority. In the proposal under discussion, what matters is an equitable distribution of subjective wellbeing, or giving greater weight to the subjective wellbeing of those who are worse-off in terms of subjective wellbeing. As Dolan puts the idea of equity-weighting, the claims individuals have to resources depend both on the gain in WELLBYs they can expect as a result of those resources, and on their current and expected lifetime suffering or wellbeing compared to others (as well as the WELLBY effects they have on others) **[1]**.

But those who defend some form of distributional equality or priority often care about the distributions of things other than wellbeing (be it hedonic or not). For instance, resources, capabilities, or opportunities for wellbeing are alternative potential metrics of equality or priority.4 Again, it is easy to think of ways in which distributions of these alternative metrics may have been affected in ways not perfectly correlated with wellbeing itself during the ongoing pandemic, which would not be captured by the proposed method of policy evaluation under discussion. For instance, the pandemic and policy response have affected – and have most likely diminished – the ways in which resources can be translated into wellbeing, but despite that, you might think it still matters that some simply have more than others. And the pandemic response has taken away many opportunities for welfare people may not actually have made use of, but which you might think were nevertheless important for them to have as much of as those who did use them.

So, equity-weighted WELLBY-based cost-benefit analysis is narrower in the ways in which it can accommodate distributional concerns than it might initially seem. And in large part, this is down to the ambition of using a single metric to both capture expected harms and benefits, and to capture distributional concerns. Whatever your single measure of costs and benefits, an equity-weighted cost-benefit analysis can only take into account the distribution of that single metric, and will miss other distributional concerns that have been defended by prioritarians and egalitarians. A prominent branch of egalitarianism, social egalitarianism, is not even concerned directly with distribution at all, but rather with making sure that people can engage with each other as equals.5

Finally, even granting a single metric for the purposes of capturing harms and benefits and for distributional concerns, there remains an important ambiguity about what kind of distributional concern equity-weighting involves in the context of risk; that is, when policies impose probabilities of harms and benefits on people, rather than certainties. In such contexts, is what matters the *ex ante* distribution of risks of harm and chances of benefit, or is it the *ex post* distribution of harms and benefits? Given how central risk is to the evaluation of policy responses to the COVID-19 pandemic, the next section will explain this ambiguity in some more detail, and argue that talk of a single metric of policy evaluation risks obfuscating the issue.

## **Distributing Harms, Distributing Risks**

Consider the following choice problem loosely based on an example by Peter Diamond **[16]**. You are in charge of making sure one of your equally well-off flatmates – Amal or Bella – moves out, and this outcome would be equally bad for each. Do you:


There seems to be an intuitive equity case for C, even though ex post, the outcomes of all three choices have the same wellbeing distribution. If you agree, this is likely because you think the distribution of chances of harms and benefits matters. To show how such an intuition might extend to a stylised policy case, suppose that as a policy-maker, you have to choose between the following two prospects for a population of ten million:

*D. Everybody faces an additional 0.002% risk each of a loss of 30 WELLBYs.*

*E. One thousand people who are currently at welfare levels that are representative of the population at large face an additional 10% chance each of a loss of 30 WELLBYs.*

Here, there seems to be an intuitive equity case for D, even though it is virtually certain that the loss of WELLBYs is larger in D and no more equally distributed ex post. If you agree, then again this seems to express concern for the distribution of risks of harm, which are much more concentrated on a few individuals in E.

Cost-benefit analysis in the social welfare function tradition can implement equity-weighting in two main different ways in the context of risk: It can either introduce equity weights on the ex ante expectations of harms and benefits a proposed policy imposes on individuals; or it can equity-weight the ex post distributions of harms and benefits in the population for each potential policy outcome, and recommend the policy option with the best expectation of equity-weighted outcomes.6 The recommendations of the two approaches can come apart, as they (likely) would in the two examples just described. The first strategy is sensitive to the distribution of risks, would recommend option C in the first case, and, with the right parameter choices, could recommend option D in the second case. The second strategy is insensitive to ex ante distributions of risks, and would be indifferent between the options in the first case, and recommend E in the second case.

There is a lively debate about which of these two strategies is better. There are also ways to combine them.7 The point I want to raise here is not only that defence of an equity-weighted cost-benefit analysis is ambiguous on this morally important question. It is also that talk of a single metric may obfuscate the issue. Both the ex ante and the ex post approaches (and any combination between them) use a single wellbeing metric, and then merely proceed to combine this with probabilities and equity-weights in different ways. But in so doing, the ex ante approach implements a distributive concern for a currency different from wellbeing, namely chances of wellbeing, or conversely, risks of harm. If we think that the distribution of such chances and risks matters, so if we favour the ex ante or a mixed approach, then there are really two things we need to keep track of: The expected wellbeing distribution in the population as a consequence of policies, and how the risks of harms and chances of benefits are distributed in the population. If we don't, there is something else that our approach to policy evaluation does not keep track of that at least some people find morally relevant.

This issue is especially relevant in the pandemic given how central risk is in the management of the pandemic response. The virus itself poses a risk of death or serious adverse health outcomes that is much higher for some parts of the population rather than others. And different potential policy responses differ in the extent to which they concentrate or spread risks of harmful outcomes, such as unemployment, within the population. If avoiding an unequal spread of risks of harm is acknowledged as a distinct policy goal, this may in some cases lead us to accept lower and no more equitably distributed expected aggregate wellbeing in the population ex post, as in the stylised policy example above.

### **The Problem of Reasonable Disagreement**

The last two sections canvassed a number of things that matter morally, according to at least some of the people who have thought about them, but that the framework of policy evaluation proposed by Dolan will not account for – and that indeed any framework insisting on a single metric to capture both costs and benefits, as well as distributional concerns will fail to account for. There are many more ways in which implementing an equityweighted WELLBY-based cost-benefit analysis involves settling on specific answers to a number of contentious moral questions: What is the right theory of wellbeing? If it is hedonistic in general, which experiences count as bad, which as good? Is wellbeing all that matters? Whose wellbeing matters? What should the equity weights be? Should they be applied ex ante or ex post (or both)? And so on. These are all questions that reasonable, thoughtful and well-informed people disagree about. So, policy evaluation using this framework can only hope to be comprehensive in the sense that all effects of a policy are accounted for against the background of specific answers to these questions. It can't be comprehensive in the sense that it accounts for everything that at least some reasonable people take to be morally relevant.

This problem is not specific to Dolan's proposal, of course. It arises especially starkly for proposals that aspire to aggregate all potential effects of policies into a single metric, and output specific policy recommendations (rather than, say, simply present an array of potentially relevant considerations to policy-makers). Doing so must involve making judgements about what matters, how it matters, and how trade-offs between the things that matter are to be made. Of course, public decision-makers cannot get around making such judgements eventually. They have to choose, after all, and they must do so against a backdrop of reasonable disagreement in the population they aim to serve. The question is what role comprehensive frameworks of policy evaluation, presented and advocated for by social scientists – such as the one under discussion – can and should play in this eventual decision-making process.

The danger, as I see it, is illustrated by this caricature: If social scientists were to simply present policy recommendations based on evaluations in terms of a single metric capturing many different effects to policy-makers and to the public without further context and qualification, this would not only mask all of the contentious moral decisions that went into the construction of that metric, but it it would also endow the recommendation with the authority of scientific expertise, making it hard for public decision-makers to diverge from the recommendation.8 And that would be a threat to the liberal democratic ideal of how public decision-making in the face of reasonable disagreement should be done: Value conflicts should be resolved by democratically elected officials in a way that is open to public scrutiny.9 Of course, policy-making needs social scientific input, and recent philosophy of science is also rich in demonstrations that social science, just like any science, can't help but be value-laden.10 But there are clearly ways in which social scientists can make sure to help, rather than undermine, democratic decision-making. When it comes to comprehensive frameworks for policy evaluation like the one advocated by Dolan, there seem to be two main strategies for doing so.

One strategy is to work closely with the public and democratically elected officials to devolve as much as possible all important value judgements, so that the resulting recommendations would have democratic legitimacy.11 There are some suggestions in Dolan's text pointing towards this kind of strategy. For instance, he writes '[e]ven if we never end using a single metric as the final arbiter on what to do, the processes by which we discuss the data required to generate one, and debates about how to make the diverse array of human experiences commensurable with one another, will lead to policy decisions that better account for the myriad of ripple effects they generate' **[1 p3]**. Moreover, he suggests drawing on, and generating more evidence on, what the public thinks about various kinds of trade-off to inform, for instance, how equity-weights are set, while at the same time conceding that '[e]mpirical investigation of these issues can only get us so far. We need to ensure that the policymaking processes better reflect the myriad of concerns and impacts' **[1 p11]**.

To assuage worries about a lack of democratic legitimacy of methods of evaluation that take sides on morally contentious questions, however, there would need to be democratic input on all the contentious value assumptions. And as the foregoing aimed to illustrate, these go far beyond the ways in which equity-weights are set, but also concern what the appropriate currency of distributive justice is to begin with, and much more. Ensuring the democratic legitimacy of every element of the analysis would be a large undertaking.12 And it is, moreover, not clear to me that such an undertaking would result in anything like an equity-weighted WELLBY-based cost-benefit analysis. For instance, there is some evidence that many people are reluctant to trade-off especially large burdens against any number of smaller burdens, which is antithetical to this framework.13

The alternative strategy involves presenting one's preferred framework of policy evaluation (or its specific applications) to policy-makers as only one of several reasonable ways of evaluating policy options. Rather than a way of settling what policymakers should do, the analysis would be an input into public decision-making. To serve as a good basis for public discussion and eventual policy choice, there has to be transparency about all the value judgements that went into the assessment and that are inherent in the general framework.14 But if we care about comprehensiveness in the wider sense – that there is proper accounting of all the things that reasonable people might find morally relevant – we also have to make sure that alternative frameworks and metrics are presented to the public, to enable there to be an informed public debate amongst people with different values, to reveal whether there are options that can be endorsed from any or most moral perspectives, and ultimately to give policy-makers informed options as to which values to pursue.

Of course, ensuring such wider comprehensiveness is not the responsibility of any one scientist or research team or even subfield, but rather of the scientific community at large and the science policy that sets its parameters. It is from this wider perspective that I think the call for a single metric of policy evaluation is problematic. From within some particular value frameworks (for instance, a hedonistic ex post prioritarian one), the call for a single metric of policy evaluation makes sense (assuming there is transparency about what goes into the metric) and can be a means of comprehensively aggregating everything morally relevant within that moral framework.15 But from the wider political perspective, where the goal should be to ensure that the outputs of policy-relevant social science enable and inform public discourse in the context of reasonable disagreement, what we need are multiple metrics and frameworks.

## **Conclusion**

I have presented two related challenges to the idea that, to ensure policy evaluation is comprehensive, all costs and benefits should be aggregated into a single, equity-weighted metric. Firstly, the only distributional concerns such equity weighting can accommodate concern the distribution of that single metric. But those with prioritarian or egalitarian leanings often care about the distributions of things other than our chosen metric of costs and benefits (subjective wellbeing in Dolan's case). Moreover, this is just one of many ways in which aggregating diverse effects into a single metric of policy evaluation involves settling on specific answers to controversial moral questions that reasonable people disagree on. The second challenge is that this raises serious questions as to what role such a method of policy evaluation, and advocacy for it by social scientists, can and should play in informing policy-making in liberal democracies. There is a wider sense of comprehensiveness of policy analysis, where the ideal is that everything that reasonable people might think is morally relevant is kept proper score of as an input into public deliberation and choice. Given reasonable people disagree on many important questions of value, achieving such wider comprehensiveness requires the use of multiple metrics.

## **Acknowledgements**

I thank the participants of the Beveridge 2.0 Symposium on Wellbeing at the LSE for helpful discussion, my colleagues Alex Voorhoeve and Liam Kofi Bright for valuable feedback on an earlier draft, and Paul Dolan for the opportunity to comment on his work.

## **Notes**

1 See **[2]** for a fuller defence of the use of WELLBYs as a currency for the evaluation of public health interventions, and **[3]** for an overview of the subjective wellbeing approach to cost-benefit analysis and its potential advantages and disadvantages more generally.

2 See **[4]** on equity-weighting using the more standard QALY metric.

3 **[5]** and **[6]** are useful overviews of the philosophical debate on theories of wellbeing, including hedonism. **[7]** provides a good overview of defences and critiques of utilitarianism. See **[8]** for a recent, and **[9]** for the classic defence of the prioritarian view, and **[10]** for an application of prioritarianism to the public health response to the pandemic. For a defence of a utilitarian pandemic response, see **[11]**, and for an exploration of the difference that the use of utilitarian or prioritarian social welfare functions in cost-benefit analysis is likely to make in evaluating pandemic responses, see **[12]**.

4 See Section 3 in **[13]**.

5 See **[14]** for a classic statement of this view. **[15]** defends a pluralist view according to which both social equality and fair distribution matter.

6 On these approaches, see **[17]** and **[18]** who defends an ex post prioritarian approach.

7 **[17]** reviews some of the formal ways to combine them. **[19]** defends a hybrid egalitarian view that cares about both ex ante and ex post equality.

8 Or, if the recommendations diverge from those of other groups of scientists, e.g. medical ones, call into question the authority of scientific expertise.

9 Also see **[20]** on this worry in the context of the pandemic.

10 See, for instance, **[21]** and **[22]**. **[23]** raises the problem of valueladenness specifically in the context of studying the effects of the pandemic.

11A similar proposal is made by Anna Alexandrova in the context of establishing 'mixed claims' (claims that are partly descriptive and partly evaluative) in wellbeing science, to establish a kind of objectivity for these claims **[24]**. Scientists should check value presuppositions for controversy, and then consult the relevant parties on their views on these controversies.

12Alexandrova is already concerned about the cost of such exercises in establishing mixed claims about wellbeing only, which would only be one input in a comprehensive policy evaluation **[24]**. Also note that by departing from classic cost-benefit analysis in abandoning preference in favour of subjective wellbeing as a measure of individual welfare, Dolan loses what some have taken to be the democratic appeal of cost-benefit analysis – that it is a neutral way of aggregating people's preferences over policy options. See, e.g., **[25]**.

13As discussed in **[26]**, which also defends the reasonableness of such reluctance.

14This is a common minimal demand made by most philosophers of science writing on the value-ladenness of science, including, for instance, Alexandrova and, in the context of the pandemic, Stephen John **[24, 23]**.

15 Other value frameworks, for instance ones that are pluralist about the objects of egalitarian concern, will themselves require more than a single metric of account, even before we consider the need to accommodate reasonable disagreement. See **[15]** for such a pluralist egalitarian critique of an exclusive focus on equity-weighted costeffectiveness analysis in health care priority-setting.

## **References**


## **5. Wellbeing in Public Policy: Contributions Based on Sen's Capability Approach**

## Paul Anand

This chapter provides a brief introduction to the capability approach and its use in public policy-making around the world. Specifically, it shows the approach provides a definition of wellbeing and a framework for understanding how it is produced and distributed. It notes that the framework is useful across the entire life course and so helpful for understanding wellbeing in children and retirees as well as working age adults. The chapter then discusses the practical impacts of the approach on the development of monitoring systems in the OECD and UN where the Human Development Index paved the way for the globally adopted Sustainable Development Goals. It highlights the fact that behavioural and psychological factors are an important contributor to understanding how resources are converted into wellbeing.

Over the past two decades, economists in research and policy have helped transform the way governments think about and act on wellbeing **[1]**. The traditional economic approach, which holds that income is broadly correlated with most dimensions of human wellbeing, has been supplemented with two approaches that have significantly affected public policy. The first focuses on life satisfaction as experienced by individuals, and has encouraged the use of wellbeing in government priority setting, of behavioural insights in policy design, and has led to the introduction of programmes to help individuals improve their lives through polices ranging from increased funding of mental health services and to the reduction of youth unemployment **[2–4]**.

A second approach, developed by Amartya Sen and others, focuses ultimately on how humans can fulfil their capabilities and live a flourishing life, rooting itself in both economics and moral philosophy **[5]**. This 'capability' approach often, but not always, arrives at similar policy conclusions as the first, though sometimes by different routes. Specifically, it argues that an individual's quality of life depends on their activities and experiences, but also on the opportunities and constraints they face **[6–7]**. This approach recognises the multiple dimensions of quality of life, and has contributed to the development of the UN's Sustainable Development Goals (SDGs). Philosophically sophisticated, this approach is grounded in standard economic analysis tools, but by applying them to human wellbeing is transforming international policy-making, as well as practice across a range of professions. Crucially, it offers a singular, coherent and widely applicable language and framework for policy-makers to understand human wellbeing with some advantages discussed in this chapter.

## **Defining Wellbeing and its Production**

The capability approach emphasises three aspects of wellbeing. The first element consists of an individual's activities and states (functionings), which depends on the resources they can access and their ability to convert these resources into valued activities. The second element comprises the individual's subjective experience, which depends on their activities and the states in which they find themselves. The third and final element comprises all the opportunities to do things in different dimensions of life – the individual's capabilities given their resources and conversion abilities. This approach can be summarised as defining wellbeing in terms of three relations:

*Activities and States = f(Resources x Conversion Abilities) Happiness = u(Activities and States) Capabilities = (All Possible Activities and States given Resources and Conversion Abilities)*

Sen's approach is similar to that of the subjective wellbeing model, in that it argues that the individual's experiential aspect of wellbeing depends on activities and states. But it also allows for the fact that a person's wellbeing might be judged on the basis of their potentiality, which cannot be directly observed. Policies concerned with equality of opportunity are an obvious example of how sometimes it matters to the individual and society not just what they are doing, and how feel about it, but also that the opportunities they have in life are appropriate and fair. The philosopher Isaiah Berlin called this aspect 'positive freedom'. Examples range from the ability to bring up a family to being able to find good and suitable employment, and are distinct from negative freedoms, such as the ability to make a decision without interference from a third party. What a person can decide for themselves is part of their agency and has intrinsic value as well as the instrumental value that economists have for a long time emphasised. This approach can therefore be used to emphasise mental health because it is essential for agency, rather than because it has an impact on empirical measures such as life satisfaction, which is how the subjective wellbeing approach addresses it. So, both approaches emphasise mental health, albeit for different reasons. In addition, Sen's capability approach emphasises that public deliberation, and inclusive involvement in it by different groups, can be valuable for collective choice where the legitimacy of any choice is a consideration, in addition to any instrumental and intrinsic benefits it may result in.

There are various ways to depict the capability approach.

**Figure 5.1** offers a generic diagram drawn from a discussion of how to apply the approach to housing policy **[8]**.

Kimhur argues that policy often focusses on physical housing stock, rather than considering how housing policy bears on a range of human wellbeing outcomes and opportunities, including: safety, permanence, health, access to decent work, community membership, tenants' rights, affordability, access to information on housing options and the ability to be consulted about maintenance or developments. These contributors to wellbeing may seem obvious but it is far from clear that they get the attention they deserve. While they may not appear in models of satisfaction with total life, such factors are likely to be significant in models of satisfaction with housing, especially when there are problems or constraints. The multi-dimensional emphasis of the capability approach helps to direct attention towards the assessment of different dimensions.

### **Figure 5.1: Example of a capability approach to housing policy**

The framework can also be used to understand that these dimensions of wellbeing do not depend just on income, but also on personal abilities that help individuals convert resources into the activities they value. Someone with a mobility impairment, for example, may find it harder to obtain accommodation that provides suitable access to decent employment opportunities because the travel environment the accommodation is located within is less likely to be suited to their situation. Thus, personal abilities are important 'conversion' factors. Furthermore, it is conceivable that the impact of some conversion factor, such as disability status, might show up more strongly in more specific models, for instance, in housing satisfaction models more than in models of overall life satisfaction. Life satisfaction might adapt to, or be compensated by, other factors, whereas problems with housing might be salient and specific, making them harder to ignore.

Through this framework, it is also possible for other challenges to be more effectively redressed. In particular, it can be particularly helpful for identifying priority issues and/or target populations. Coates et al., **[9]** for example, looked at housing policy in relation to Irish travellers. Within focus groups conducted for the research, which was ostensibly directed towards housing provision, other problems affecting wellbeing emerged. One woman noted that a house built by sub-contractors to a local authority was damp in winter and caused her children to be hospitalised. Another observed that the neighbourhood where she was housed was blighted by unemployment due to local employer attitudes towards the traveller community, with almost three quarters of adults in that community unemployed. And a third, younger woman reported that teachers did not 'push' traveller children, and that this had, ultimately, discouraged her from aiming for university.

The story that emerged, as a result, was that by focussing on housing, rather than considering the broader wellbeing of the community, policy-makers were failing to address the substantive problems. Hopefully, this housing example, of what Robeyns calls 'place based' capabilities,**[10]** gives a brief flavour of how some of the general concepts can be applied in practical policy settings and how the emphasis shifts and broadens as issues of wellbeing are brought into the conversation more directly. In the next section, we extend these discussions by considering how the approach can be used to consider the production of wellbeing at different points in the life course.

### **The Production and Distribution of Wellbeing Over the Life Course**

Considering wellbeing through this perspective can help us answer some perennial questions for science and public policy. For instance, what are the dimensions of wellbeing and how are individuals in certain groups able to produce it? Many policies seek to improve the capabilities of individuals either by acting on the individuals' own resources or conversion factors, or on the environment in which they live and work. Empirical evidence on individual capabilities, activities, and states, and how these are produced and enhanced is therefore required. What follows below is an account of three case studies from the long-standing capability measurement project that help to illustrate how such evidence can be produced.

#### *Adult wellbeing*

In a survey of working age adults conducted internationally, Anand et al. asked them to provide Likert ratings **[11–12]**, which rate their abilities to do or achieve certain things related to home, work, community, physical environment and service access. From this work, it is possible to identify some stylised facts about the drivers of capabilities at national level. For instance, what individuals are able to do in their lives reflects the state of economic development of their country, as well as their position within its socio-economic strata, although there are also notable cross-country variations, even in countries that have comparable levels of economic development. In the USA, for example, individuals report that they are more able to get help from the police than in European countries, while in the UK, individuals report that they are more freely able to get medical assistance, and in Italy, respondents appear relatively more critical of their local governments' clearing of waste. These responses reflect the approaches taken to particular public services by different countries, such as the UK's free-at-point-of-use NHS, but also reflect differences in political institutions, such as the accountability of Italian local authorities to the people. These data also help to identify the possible need for other kinds of responses. For example, in all countries, work-life balance was low, which may suggest the existence of a prisoner dilemma situation that is contributing to low wellbeing, which warrants a non-market intervention from the state.

### *Child development and happiness*

Wellbeing depends on what individuals are able to do, and this changes most rapidly in childhood. To explore this dynamic aspect, therefore, it is natural to ask how and when do individual capabilities develop, and how might this development be supported where necessary? Accordingly, in a second project, we sought to assess the happiness and development of toddlers in Germany using data from the annual German socio-economic panel survey **[13]**. Within this dataset, the 'mother and child' module contains a particularly rich array of questions on the child's activity involvement, skills and happiness, as reported by the parent. Three equations were estimated to understand child happiness, with the results showing that of all activities, reading with a parent and going on shopping trips were significantly and positively correlated with a child's happiness.

One interpretation of this data is that these activities contribute to a child's sense of wellbeing above all others. A more subtle interpretation is that other activities also contribute to wellbeing but that the ones with the strongest positive correlation were constrained in some way. For example, if reading with a parent promotes the child's happiness and is constrained for some children, such as those whose parents have low amounts of time for or interest in reading, then the significant coefficient for reading could indicate that for some children, the amount of reading with a parent is too little compared with what might be optimal. Further, then considering the factors behind these numbers, it would seem that income has a small positive effect on reading specifically, while it has a negative effect on shopping, with lower income families more likely to shop with toddlers.

Other factors that proved relevant included the location of the children, (possibly reflecting different policies and cultures in the former East and West Germanies), certain characteristics of the mother, including her education level and migrant status, and the number of siblings the child has. More education seems to make it easier for mothers to read to their child, while having migrant mothers were related to more outdoor activities – perhaps because there are fewer social ties and therefore invitations to indoor activities. Siblings have multiple impacts as they compete for parental time but also provide alternative sources of stimulation. Finally, we investigate how these activities contribute to skill development and find that involvement in related activities appears to be particularly important. For example, singing and reading help with speech development, while visiting other families is a significant predictor for the development of social skills. These results confirm the assumption that income plays only a modest role in child development and happiness, and that more direct support for parental activities and investments may generate skills more efficiently.

### *Female empowerment and micro-finance*

In our third case study, we consider the situation of women in an empowerment and enterprise programme based in Uttar Pradesh, Northern India **[14]**. One puzzle in the economics literature is the fact that these micro-finance programmes often are found to have only a modest impact in raising income, but that they are subscribed to by vast numbers of people – with 90 million women participating in India alone. One possible explanation is that participation in such programmes has a more substantial positive impact on other aspects of wellbeing. In order to test this hypothesis, we conducted a programme evaluation, comparing capability indicators for women who had participated in the programme for some time against those for women who were not members.

Using propensity score matching to select controls with similar characteristics, and including data on length of time in programme to control for unobserved selection effects, we find that many aspects of women's wellbeing are enhanced through participation in a self-help group, whether being able to meet socially to being able to find interesting employment (see **Table 5.1**). However, there are exceptions. For instance, health limitations become more of a constraint on activity as women in the programme are now more active outside the house. In a similar, but distinct, vein, the risk of assault and discrimination are unaffected, but this is unsurprising, as the programme targeted the women themselves and their capacities, not the social environments in which they lived. It seems probable that the significant nonfinancial wellbeing impacts of this programme may help explain its popularity and those like it with many women



in rural communities in lower income countries. These case studies are just examples of ideas of how the production and distribution of wellbeing can be assisted by the approach. In the section that follows, we consider other applications relating to childhood, health, psychology and social justice.

## **Capabilities in Children, Health, Psychology and Social Justice**

The literature that uses the capability approach to study wellbeing over the life course is now large, and includes work by Biggieri et al. who asked children of primary school age and above from a range of countries about the dimensions of wellbeing that mattered most to them **[15]**. Within their responses, the most prominent were the need for respect, the ability to live according to their own identity and religion, some autonomy in time use, the ability to move freely, and the value of familial connections, such as being loved. These dimensions of wellbeing are related to those in adulthood but not identical, with it being noticeable how the desired level of autonomy changes as children grow.

Work by Heckman et al. has also encouraged the development of a significant literature on the technology of skill development in children **[16]**. This literature suggests that there are multiple critical periods in childhood for the development of particular skills, and that success in life is best enabled through the development of both socio-emotional and cognitive skills, skills that are developed through parental and educational investment.

Health has also seen a burgeoning literature considered through the prism of capability, using it to produce measures of health and wellbeing for use in clinical trials. The ICECAP-O, developed by Keeley et al. has helped to highlight the value of access to socialising in older age, while the OXCAP-MH comprises 16 dimensions of life quality that might be impacted by mental illness **[17–18]**. Others have used the approach to examine issues of disability, arguing for a need to capture non-physical aspects of wellbeing loss not covered by medical models. Mitra with Kuklys argue that for those suffering from disability, satisfaction with their finances indicates that mobility impairment is equivalent to the loss of over 25% of income **[19–20]**.

There are also interesting connections between the capability approach and psychological literatures. The ability to persist, captured by psychometric measures of GRIT, by Duckworth et al., has been shown to predict a range of successful education-related outcomes, while the closely related ability to plan ahead has been found to predict both life satisfaction and income **[21–22]**. One of the founders of positive psychology, Marty Seligman has also drawn on ideas about human flourishing to argue that positive emotion, engagement, relationships, meaning and accomplishment are the building blocks for wellbeing, which he nonetheless concludes is subjective **[23]**. Certainly, capabilities researchers would accept that items such as relationships and accomplishments are valuable functionings, and by extension, so are the capabilities required for achievements on these dimensions, though they stop short of viewing subjective wellbeing as their final metric of wellbeing. Looking into particular dimensions is often informative for policy purposes, while life satisfaction measures fail to identify all aspects of wellbeing, particularly non-salient sources of wellbeing, outcomes to which adaptation has taken place, or activities and states of being that have intrinsic value not reflected in mental experience.

The capability approach has also helped to encourage work related to inequality and social justice, another important source of misery in Layard's language. For example, within economics, there is a closely related work that formalises inequality of opportunity, and finds that cross-sectional income-based measures may over-estimate inequalities when compared with measures based on permanent incomes, given the presence of some social mobility **[24]**. Taking inequality of opportunity (opportunities related to environmental aspects of an individual's capability) into account therefore gives rise to different measures compared with those based on income. In other disciplines, much of the work is more conceptual and oriented towards the drivers of wellbeing. Ruger for example, develops a capability approach towards social justice in health, and argues that global health institutions can contribute to human welfare variously by generating information to alleviate health inequalities, by empowering individuals and groups in national and global forums, by providing technical and financial assistance, and by adopting multi-sectoral policies that recognise many determinants of a healthy life are social and economic rather than based on healthcare per se **[25]**.

In work applying the approach to equity in education, Unterhalter also considers how failures to ensure that boys and girls have the same opportunities for learning might be investigated **[26]**. She argues that ensuring effective equity, rather than just formal equality, is important. Girls and boys, for example, may be equally entitled to do homework in formal terms but there may also be social norms that make some groups less able to make use of these entitlements than others. This distinction between formal freedom and freedom on the ground is often particularly useful when trying to understand effectiveness in public policies.

### **International Impacts of Capabilities on Wellbeing Policy**

The single most important global governance consequence of the capability approach is the development and pursuit of the Sustainable Development Goals adopted by the United Nations in 2015. However, the capability approach's effect has been wider than this, with many organisations moving towards multidimensional approaches that co-exist with income-based approaches to wellbeing. The first of these was the development of the Human Development Index, which added to income, health and education as areas to be monitored at a global level and has been published almost every year since 1990 **[27]**. A decade later saw the launch of the Millennium Development Goals, which covered health (particularly maternal and child health) and education, and can be seen as one of the first international attempts to establish a partial international social welfare function for economic development. Nearly a decade later, the OECD started to produce its own response which took the form of a Better Life Compendium **[28]**, an interactive index which allows users to compare countries based on capabilities and functionings in 11 domains using their own weightings. It also instructed departments to take account of wellbeing in all their areas of policy analysis. Then in 2021, the EU launched a multi-dimensional set of inequality indicators that drew explicitly and in several ways on the capability approach **[12]**.

There have also been several country initiatives that drew on or were motivated by the capability approach or aspects of it. In Australia, it was used as a framework for articulating priorities within government as well as to the public, while Bhutan has used it to argue for the preservation of the natural environment, including wellbeing measures in the country's planning procedures. In the UK, a coalition government, inspired by the OECD work, commissioned its National Office of Statistics to hold a public consultation and develop a wellbeing dashboard comprising 40 indicators, as well as a set of 'what works' research hubs that have helped support research impact development and interactions between practitioners and researchers.

There are also many examples of not-for-profit organisations using the capability approach, though these are typically only documented, if at all, in grey literature. The old adage about 'giving someone a fish and you feed them for a day, teach them how to fish and you might feed them for life' represents an ongoing and deep distinction between the ways of supporting individuals that not-for-profit organisations adopt. Many NGOs do aim to help individuals to have better opportunities than would otherwise be the case, and the fit between their empowerment narratives and the conceptual resources of the capability approach has proven natural and productive. NGOs are often concerned to help individuals improve their own wellbeing by helping individuals take actions for themselves that are empowering, though of course lobbying to remove external constraints on individuals who are disadvantaged can also be important.

So, what is the future for wellbeing and capabilities? Does wellbeing stand a chance or do these impacts reflect the influence of some prominent economic thinkers in the late 20th and early 21st centuries? I want to be optimistic, and cannot ignore the evidence that both Sen's capability approach, based on the concepts of real opportunity and wellbeing production functions, and the Layardian reworking of utilitarianism, have had huge impacts at the international, governmental and local levels. However, ideas have to become embedded and able to address new challenges and there are a variety of headwinds and tailwinds, deriving from psychological, governance and economics sources, that the wellbeing agenda faces. In terms of policy impact, the two variants of the wellbeing model often come to similar conclusions, even if some important differences remain at the level of theory. Those who advocate using the insights of subjective wellbeing models to inform policy generally accept the importance of choice, but implicitly. Those who advocate using Sen's account of wellbeing, which emphasises capabilities, accept also that personal experience is informative about and important for wellbeing and only demur from the proposal that it is the sole source of information about wellbeing.

### **What the Capability Approach Contributes**

Sen's capability approach to welfare economics and the economics of happiness literatures have both been successful in terms of empirical research and social impact. Together they can be seen as subfields of approaches that view income as an input to human wellbeing rather than a proxy for it. While their conceptual differences dominate academic discourse, for the most part, they lead to similar policy conclusions in practical policy settings. For instance, Layard has successfully used happiness benefits to argue for improvements to mental health services but mental health is also vital for human agency and the ability to make decisions and hence valued by capability researchers. Happiness economics has highlighted the importance of good social relations, and such relations also feature in many lists of capabilities that are important.

Nonetheless, there are differences. Both value democracy but in different ways. The capability approach explicitly maintains the importance of public deliberation and scrutiny while happiness economics stresses the importance of weights (inferred from models of life subjective wellbeing) given to different factors by individuals. In line with this, the capability approach tends to focus on philosophical and social science literatures relating to rights, with the happiness literature engaging particularly with psychological research on experienced wellbeing measures. As a result, the capability literature has the potential to identify sources of wellbeing (or its absence) that are not often used in economic analyses and derive largely from household surveys (for example discrimination).

In sum, the capability approach contributes to our understanding of wellbeing in various ways but its particular contribution appears to be a foundational framework for thinking about the dimensions, drivers and distribution of wellbeing. The most practical impact of this framework has been its use by UN bodies, motivating first an annual index of human development, and then creating a social welfare function for global action (the SDGs). Similar kinds of dashboards have been adopted by the OECD, EU and several countries and they generally seek to cover key domains of life with a mix of indicators that cover the objective-subjective spectrum. These initiatives have not replaced the national income paradigm nor do they seek to do so, but they do complement it by providing direct indicators of wellbeing across key domains and over the life course.

## **References**


*of Life Outcomes*. 2016; 14(1): 1–5. DOI: https://doi.org/10.1186 /s12955-016-0430-x


## **6. Incorporating Wellbeing and Mental Health Research to Improve Pandemic Response**

Michael Daly and Liam Delaney

This chapter discusses the potential for wellbeing research to be institutionalised into emergency response in the UK. We review the short and long-run wellbeing impacts of COVID-19 policies and argue for a wider scope of groups such as the Scientific Advisory Group for Emergencies (SAGE). The potential form of such response could be based both on emerging multi-dimensional societal wellbeing frameworks and on rapid and scalable policy appraisal capacities that incorporate wellbeing considerations.

During the pandemic, infection risk, hospitalisations, and deaths formed the basis for modelling and government advice. For instance, school closures and the introduction of broader social lockdown measures were two policies used to reduce infection and mortality levels **[1–2]**. However, anti-contagion measures were accompanied by large societal costs including job losses, financial uncertainty, mental distress, schooldisengagement, and domestic abuse **[3–4]**. While predictions of hospitalisations and excess deaths strongly informed government decision-making **[5]**, less attention has been paid to how the virus and associated government responses may have impacted and may continue to impact population wellbeing. How such impacts should be measured and inform part of the institutional response to major emergencies such as COVID-19 is an important question that has so far been neglected, but that we aim to address here.

Specifically, we outline a strong body of research that has emerged over the course of the pandemic on immediate harms to wellbeing and potential long-term wellbeing effects. We then discuss how this evidence has not been reflected in the structure of the pandemic response, as the main advisory bodies have been predominantly focused on the physical health outcomes of disease control strategies. Further, we outline how this omission can lead to distortions in policy advice and implementation, including, but not limited to, incomplete or inadequate communication of risks, and invalidation of the experiences of wide groups of people during the course of the restrictions. This is particularly heightened by the fact that groups at high degrees of risk, such as marginalised children, may have particularly low voice in the media and in policy-making processes.

The chapter then examines the potential for integrating wider measures of mental health and wellbeing into a more holistic pandemic response. It draws from a range of literatures, in particular the development of multi-dimensional wellbeing indicators, the growing movement to integrate wellbeing metrics into policy appraisal **[6]**, and the development of ethical frameworks in behavioural public policy. This reflects the fact that many societies are moving away from using Gross Domestic Product (GDP) as a measure of national wellbeing **[7–8]** and are moving towards citizen-driven, multi-dimensional wellbeing indices. A process like this offers strong potential for more holistic responses to major emergencies, including pandemics. The integration of wellbeing is therefore important both from the point of view of the ongoing pandemic response as well as more generally, in terms of responses to future pandemics and to other types of systemic risks.

We conclude by outlining the case for institutionalising wellbeing impacts into policy response, including the potential for multidimensional scales to inform strategy, the role of wellbeing measures in policy appraisal, and the use of wellbeing considerations in appraising the ethics of behaviourally informed risk communication strategies.

### **Wellbeing During the COVID-19 Pandemic in the UK**

The widespread disruption and worry caused by the emergence of the pandemic gave rise to concerns that the wellbeing of the population may be adversely affected. The early stages of the pandemic saw the rapid publication of research focused on the potential mental health and wellbeing effects of COVID-19 **[9]**. While the value of much of this research was limited due to a reliance on cross-sectional and convenience samples, high-quality evidence from largescale, often pre-existing, longitudinal and probability-based samples was acquired and published as the pandemic progressed **[10]**. This survey data allowed changes in mental health from before to during the pandemic to be estimated. By integrating this evidence, a systematic review and meta-analysis of longitudinal studies could show that there was an increase in mental health symptoms during the initial stages of the pandemic (March/April 2020), with depressive symptoms most affected **[11]**. After this point (May–July 2020), the severity of mental health symptoms declined, potentially as a result of the easing of restrictions and adaptation to the stressors associated with the pandemic (e.g., continuous media coverage, fear of infection, financial uncertainty).

In the UK, this pattern was also evident, with notable declines in mental health and life satisfaction being observed after the outbreak of the pandemic. Data collected as part of the UK Household Longitudinal Study showed that an increase in mental health symptoms occurred between April and June 2020 **[12]**. Similarly, estimates from the UK Annual Population Survey suggested that life satisfaction declined and anxiety worsened throughout this period **[13]**. The declines in mental health and wellbeing were generally most marked for young people and women, perhaps reflecting the major social disruption experienced by both groups and the disproportionate way in which family and caregiving responsibilities fell upon women **[14, 15]**.

Improvements in wellbeing occurred during the summer and autumn of 2020, as restrictions were loosened in the UK **[4, 13, 16, 17]**. However, emerging evidence suggests that declines in mental health and wellbeing began once again after the reintroduction of lockdown measures during the pandemic's second wave, in the winter of 2020/2021 **[13, 16]**. At this point, parents of school-aged children were most likely to experience elevated psychological distress, most probably due to the disruptive character of home-schooling coupled with existing childcare and work responsibilities.

As such, there is at least initial evidence that population wellbeing was related to the scale of the pandemic and to the associated anti-contagion measures in the UK – suffering as cases and deaths rose and restrictions tightened and reverting slowly to baseline as transmission levels declined and restrictions loosened. There is also initial evidence that population subgroups considered to be most affected by COVID-19 restrictions experienced the most significant harms to their wellbeing. However, understanding the mechanisms linking the pandemic and social lockdown measures to population wellbeing has proven difficult because changes in infection and mortality rates and restrictions tend to occur in tandem.

One approach that has proven somewhat informative for understanding the role of changing living conditions during the pandemic is the assessment of daily experience through time-use diaries and experience sampling methods. For example, Lades et al. **[18]** conducted a day reconstruction study to examine time-use and positive and negative affect during the first phase of COVID-19 restrictions in Ireland in April 2020. This study showed that home-schooling children, social media use, and staying informed about COVID-19 during the pandemic were associated with adverse wellbeing effects, whereas spending time outdoors and in nature predicted wellbeing benefits. Similarly, a study of the everyday experiences of Australian adults during the pandemic showed that greater screen time was associated with reduced wellbeing, whereas time spent outdoors was associated with raised emotional wellbeing **[19]**.

By probing the daily activities, interactions, movements, and experiences of people, experience sampling and daily diary surveys have the potential to highlight the channels through which the pandemic affected and may continue to affect psychological wellbeing. The pandemic has also seen the implementation of a pioneering 'continuous tracking' approach to gathering data on mental health and wellbeing that capitalises on the strengths of real-time daily and experience surveys and the representativeness of national surveys. This approach is illustrated by the Understanding America Study **[20]** where participants drawn from a subset of a nationally representative internet-panel complete a tracking survey on a specific day at regular intervals, thus providing a representative picture of national trends in key wellbeing, behavioural, and attitudinal metrics for each day of the pandemic **[12]**. The German COMPASS survey took a similar approach, collecting information on wellbeing, behaviour, and COVID-19 related variables from approximately 300 participants every day throughout the pandemic **[21]**.

These large-scale, high frequency assessments have been vital in tracking and demonstrating wellbeing trajectories during the pandemic. For instance, there was a marked rise in distress during the initial phase of the pandemic in the United States **[22, 23]** that was followed by a decline in subsequent months, which could be attributed to a return to everyday activities and reduction in the perceived health and economic risks posed by the pandemic **[22]**. Tracking surveys can also play a crucial part in understanding the potential wellbeing impact of COVID-19 policies and restrictions across time and regions, and the evolution of the long-term wellbeing consequences of COVID-19 including unemployment, poverty, and financial insecurity **[24]**.

### **Lasting Wellbeing Effects of COVID-19**

At the population-level, the general effects of living through the pandemic may have dissipated. However, harms to wellbeing may persist for specific groups, such as immunocompromised people, those with extended symptoms of COVID-19 **[25]**, healthcare staff who have witnessed mortality among patients and colleagues **[26]**, those at risk of domestic abuse **[13]**, and children whose specialised educational needs have been neglected. These groups may represent part of the coronavirus' negative longer-term legacy **[27]** and planning to address the ongoing needs of the groups most impacted by the pandemic has begun, as evidenced by the COVID-19 Mental Health and Wellbeing Recovery Action Plan **[28]**. This report highlights policy actions that are planned to support such at-risk groups through investment within the health and education systems and beyond.

In addition, as acknowledged within the action plan, the longer-term economic repercussions of the pandemic require consideration. For instance, those who go on to experience unemployment and underemployment following the pandemic may suffer financial and wellbeing 'scarring' as a result of financial insecurity and weak attachment to the labour force following the pandemic **[29–33]**. Such wellbeing considerations may be particularly useful for understanding the longer-term dynamic impacts of COVID-19 and the effects of different types of COVID-19 policy response. For example, because longerterm employment displacement has deeper scarring effects than short-term displacement, policies that prioritise macroeconomic recovery and a return to work may attenuate the scale of these effects. Furthermore, it is likely that younger people can recover wellbeing from short-run impacts on friendships and social engagement **[34]**. But far more information is needed on what will happen to longer-run wellbeing in the case that restrictions become an embedded part of response to emerging variants and new waves of the pandemic.

### **Institutionalising Wellbeing Approaches to Emergencies**

One feature of COVID-19 is that the economic and wellbeing impact has been disproportionately borne by younger people who have experienced significant labour market displacement and significant disruption to social activities **[10, 30]**. However, they have been poorly represented in the governmental decisionmaking focused on COVID-19 responses, with their views and experiences likely undercounted and underweighted **[35]**. While it is probable that those who have the expertise necessary to make recommendations to government do not fall into this category – or the many other categories that are under-represented here – it clearly creates the potential for the experiences and preferences of younger people and other less represented groups to be neglected in the decision-making process.

The potential for elements of young people's wellbeing to be trivialised as a result of this is important to reflect on. For example, the need to develop social relationships in early adulthood and to find social and sexual partners and to form lifelong relationships is widely recognised in many developmental frameworks as a key aspect of early adulthood **[36]**. Framing social activity as non-essential compared to the wider goal of reducing infection risk and preserving life diminishes, and even potentially invalidates, this important aspect of human development and experience. There are many other aspects of human social engagement and support that were neglected in this way throughout the period **[37]**. In some sense this is ironic, given that a huge amount of literature in recent decades has sought to counter the over-focus on economic outcomes by pointing to the importance of robust social support as underpinning wellbeing.

Many of the major risks faced by society in the 21st century, such as global warming and population growth, are currently being managed by people with very defined, and in some ways limited, expertise, despite the responses and consequences being spread across the whole of society **[38]**.

In a recent paper, the authors proposed a wellbeing commission to evaluate the potential population wellbeing impacts of major policy projects, including pandemic responses **[39]**. Such a commission could help resolve such limitations within government by ensuring that its decision-making is informed by a wide range of disciplinary expertise and by the life experiences and evaluations of citizens from a range of backgrounds. Already, Britain has a range of infrastructure that would facilitate the development of this type of institutional capacity, such as regular wellbeing measurement **[40]** and UK Research and Innovation (UKRI)-funded centres that include substantial capacity for evaluating wellbeing impacts, as well as a history of working across government departments and developing ideas in this area **[6]**.

The integration of behavioural and social scientists into the COVID-19 policy response has been repeatedly and broadly discussed, and to some degree, implemented by government **[41– 43]**. In the UK, the role of the Scientific Pandemic Insights Group on Behaviours (SPI-B) was to provide 'behavioural science advice aimed at anticipating and helping people adhere to interventions that are recommended by medical or epidemiological experts' **[44]**. While SPI-B contained members that had written on wellbeing related topics, such as psychosocial resilience, the primary function of this group was limited to supporting the monitoring of and adherence to behaviours, such as social distancing, that sought to control the pandemic. Their remit did not allow for a holistic assessment of wellbeing impacts of policies. For example, it is difficult to imagine how a group like SPI-B could, for example, provide wellbeing impact assessment of investments in mitigating the long-run psychosocial costs of school disruption or of being exposed to bullying or domestic violence.

A report by the Institute for Government illustrates the decision-making structure of the UK government's pandemic response during the first six months of the pandemic **[45]**. While evolving over time, the basic structure of a core scientific advisory team complemented by a behavioural advisory group was maintained. Developing this structure to allow for rapid assessments of medium to long-run psychosocial impacts is something that should be considered as a matter of urgency, both in the context of the ongoing pandemic response and in relation to preparedness for future emergency situations. This is further emphasised in evidence submitted by the Nuffield Council on Bioethics and the Institute of Development Studies, which discussed the importance of social science perspectives in informing decision-making. There, the latter stated that SAGE had 'minimal social science representation and is largely confined to narrow **behavioural science perspectives**' **[46]** which compared '**unfavourably**' **[46]** with other European countries. The Institute also suggested that more expert input was required from '**anthropology, geography, sociology, economics, history and** related fields' **[46]**.

The major point of our current paper is not that the research community was not providing research on wellbeing effects – and indeed, it is clear that there is now a large literature in this area both within the context of the UK and internationally. Instead, the more pressing point is that there is not an obvious channel through which this research could have a meaningful impact on ongoing emergency responses.

The institutionalisation of wellbeing measurement into emergency responses could potentially fulfil a number of functions:


### **Multidimensional Wellbeing Indices**

One potential way to improve the process of responding to emergencies would be to draw from pre-existing multidimensional measures of wellbeing. The OECD Better Life Index, for example, contains 11 different dimensions of wellbeing, encompassing income/wealth, housing, job quality, skills, environmental quality, subjective wellbeing, safety, work-life balance, social connections, and civil engagement **[48]**. While such measures are already intended as top-level indicators of overall societal wellbeing, they provide a basis for developing more in-depth measures and evaluation structures. Anand **[49]** argues for the incorporation of such indices to assess the impact of COVID-19 on capabilities to enable priority setting in policy-making. The development and integration of multidimensional wellbeing scales into emergency response would enable a more holistic approach to the assessment of COVID-19 outcomes.

However, the use of multi-dimensional indices such as the OECD framework potentially also comes at the cost of conceptual clarity and speed of aggregation. In the context of an emergency situation, moving from eleven broadly defined dimensions down to an actionable set of policy actions is not particularly straightforward. Similarly, the frameworks themselves do not provide off-the-shelf procedures for ranking policy actions in a clearly quantifiable way. They should be seen as ways of ensuring that key considerations of societal welfare gain a share of attention in the development of responses and in the formulation of decision-making structures rather than in and of themselves providing clear-cut solutions.

### **Wellbeing and Policy Appraisal**

Another aspect of COVID-19 decision-making that could potentially benefit from a wellbeing approach is the assessment of particular policies at different stages of the pandemic. Many policies aimed at reducing infection risk have impacts on a wider set of factors that influence people's wellbeing, and the benefits they provide in one arena could be usefully set against the harms they do elsewhere. For instance, decisions to restrict visits to people in nursing homes, mandates for face coverings in educational settings, and restrictions on social visits, all potentially have impacts on wellbeing in a variety of ways.

Furthermore, such impacts may be subtle and hard to measure in traditional wellbeing formats. For example, the psychic cost of not being able to visit a dying loved one may not be measurable using any standard measure of life satisfaction or episodic wellbeing but may occupy a particularly meaningful loss for people. It is important that there is a place to consider determinants such as this.

Another potential input into emergency response would be to identify overall impacts on life satisfaction using an integrated index of wellbeing. For instance, the concept of WELLBYs, or wellbeing years, was developed to provide a scaled unit to examine different policies from a cost-benefit perspective **[50]**. Clark et al. **[27]** employ the WELLBY concept to examine the impacts of a range of lock-down scenarios in response to the first wave of COVID-19 in the UK. A limitation of this approach is the extent of uncertainty surrounding the infection responses to different types of non-pharmaceutical interventions (NPIs). However, it does serve, within assumptions around NPI impacts, to take into account important aspects of COVID-19 response such as the psychological impacts of COVID-19 on unemployment, as well as a range of other psychologically significant factors.

#### **Wellbeing and Ethics of Behavioural Change Strategies**

A focus on wellbeing is also informative for the ethics of behavioural change strategies. In some sense, people's wellbeing and adherence to COVID-19 restrictions are mutually supportive, for example research shows that happier people are more likely to comply with COVID-19 restrictions **[51]**. However, there are clearly trade-offs in this domain. As case numbers come down, people relax and exhibit less fear of the virus both psychologically and behaviourally. As discussed above, wellbeing improved dramatically during the low period of infection and loosening of restrictions in summer and autumn of 2020. However, communications that emphasise and make salient the degree of personal risk during such periods could potentially reduce the risk of further outbreaks, while also harming wellbeing. More generally, regular targeting of COVID-19 information in highly salient and emotive ways could potentially encourage people to adhere to regulations at the expense of their daily wellbeing and experience.

Many bodies, including the WHO **[52]** and ECDC, advise people to limit the amount of time they spend consuming information in the media about COVID-19. In our own study, spending time reading about COVID-19 is one of the most psychologically unpleasant daily activities people regularly undertake **[18]**. In that case, there is an interesting ethical tradeoff surrounding the potential behavioural adherence effects of regular press briefings and the discussion of the threat it poses and the experiential effect that this has upon the population.

In many frameworks, one explicit goal of risk communication is to help people manage anxiety and set risk in proportion, whereas a policy focused solely on mortality reduction may involve explicitly attempting to get people to focus on COVID-19 risk at the expense of other aspects of their wellbeing. As said above, it is also possible that in actuality there is not a trade-off. If people become desensitised to regular, alarming broadcasts about mortality then their efficacy as a behavioural change tool will be diminished **[53]**. Furthermore, it is highly possible that those engaging most with these messages are both already compliant and highly anxious about COVID-19 anyway.

### **Conclusion**

In 2021, the UK government released a report on integrating mental health into pandemic responses **[28]**. It was very welcome but came one year after Covid was a fully live policy issue. It is urgent to rebuild the discussion of COVID-19 around multi-dimensional measures of wellbeing that situate health and mortality risk among the factors that allow for quality of life across the life cycle. A wellbeing focus can inform the development of structures that advise the government on its pandemic response and its wider emergency response, ensuring that the government's focus is less myopic. It can also potentially be informative with regard to ongoing communication efforts to influence people's behaviour over the course of the next stages of the current pandemic response in the UK. More broadly, moving to a wellbeing discourse might serve to better recognise the discrete experiences of different groups of people during pandemic circumstances, and to provide the government with the means to tailor or adjust its response to reflect the different needs and struggles of these groups.

The integration of wellbeing considerations into emergency preparedness and response also comes with a number of questions, while the extent to which the public trust and value inputs from social and behavioural science relative to STEM is still not apparent. In a recent paper Sanders et al. **[54]**, find that the media discourse around the role of behavioural science in the UK's COVID-19 response was largely positive, but highly controversial with regard to the specific inputs that drove the central response. Understanding trust in social science in highstakes environments is thus a high priority for capacity building in this area, in particular understanding both public and policy-makers perception of the role of social and behavioural scientists in expert advisory groups.

### **Acknowledgements**

We thank Annette Bauer and Paul Dolan for detailed and insightful comments on an earlier draft of this article.

## **References**


from two large UK samples. *Soc Sci Med*. 2020; 244(112641): 112641. DOI: https://doi.org/10.1016/j.socscimed.2019.112641


## **7. COVID-19 and Mental Health and Wellbeing Research: Informing Targeted, Integrated, and Long-Term Responses to Health Emergencies**

Annette Bauer

The COVID-19 pandemic has posed many questions as to how governments should best respond to health emergencies, including questions as to how to develop responses that consider mental health and wellbeing impacts. This chapter argues that mental health and wellbeing research should have an important role in informing responses that are targeted, integrated and long-term. It provides relevant examples of mental health research, policy, and practice in the UK, including research on the dynamic and complex relationships between mental health and social determinants of mental health such as poverty and social support. A particular focus here is on the impacts of the pandemic on children's and young peoples' mental health and wellbeing. The chapter continues by referring to examples of the role of economic research in informing trade-off decisions. The chapter ends by describing the role of networks and partnerships between policy, practice and research to ensure that relevant evidence is produced and appropriately disseminated during health emergencies and beyond. The author presents a perspective in this paper, which draws on her own research and research conducted by the Centre for Care Policy and Evaluation Centre (CPEC) at LSE.

The COVID-19 pandemic has posed many questions for governments around the world, not least in terms of how to best respond to health crises while still maintaining the general health and wellbeing of the nation. The standard response of most governments has been to impose lockdown measures, which have had a disproportionate impact on children's and young peoples' mental health and wellbeing.

More generally, the strong focus on the physical impacts of the virus might have inhibited governments' ability to recognise the impact on mental health and wellbeing that policies such as school closures and social contact restrictions entailed. As argued in the chapter by Daly and Delaney in this book (Chapter 6), a stronger focus on the mental health and wellbeing impacts of the pandemic might have led to the development of more balanced and nuanced government measures, including some that prioritised the needs of children and young people. Daly and Delaney propose the use of policy frameworks and tools to ensure that mental health and wellbeing data are available on time and are considered by decision-makers during health emergencies. This, however, also raises questions about the types of mental health and wellbeing evidence that should be used and the contributions that they can make in responses to health emergencies. In addition, there are questions of how decision-makers can have timely access to mental health and wellbeing data that they can use in response to health emergencies, and what the role of those involved in producing and disseminating such evidence should be.

Building on some of the arguments made by Daly and Delaney, I reflect on these questions in the context of the UK by drawing on examples of research conducted my myself or colleagues at CPEC, and consider what their potential role may be in informing targeted, integrated and long-term responses to health emergencies. This includes the role of economic evidence in helping decision-makers faced with difficult trade-offs between different courses of action. Assuming the use of evidence in policy and practice as a shared responsibility between those using, generating and disseminating evidence, I provide a few examples of how stakeholders can be involved in research. I refer to children and young people as a population whose mental health and wellbeing needs deserve particular attention during health emergencies.

### **Relevance of Mental Health Research to Informing Policy Responses to Health Emergencies**

In the UK, a wide range of mental health and wellbeing data has been collected throughout the pandemic, either as a part of ongoing research or as part of research conducted specifically in response to it. This data has provided important knowledge about the population groups most affected by the pandemic, and revealed significant patterns in terms of the pandemic's effects on mental health over time, and helps us understand the underlying mechanisms that explain differing rates of mental health problems for different populations **[1, 2]**. In addition, experiences from past, comparable events also provide further evidence that can be drawn upon, including research that investigates mental health impacts from previous economic and health emergencies or shocks. This kind of research is particularly helpful in showing the very long-term impacts and in offering explanations for these consequences and identifying their root causes. Drawing **Figure 7.1: Relationship between depression and income during the COVID-19 pandemic: Percentage of working age adults with depressive symptoms by gross personal income, Great Britain, 27 January to 7 March 2021**

*Source:* Office for National Statistics – Opinions and Lifestyle Survey.

from two areas of research concerned with two important social determinants of mental health, i.e., poverty and social support, the following examples seek to illustrate opportunities for using mental health evidence to inform targeted, integrated and longterm responses to health emergencies.

#### *Example 1: Mental health and poverty*

National data revealed that the pandemic did not affect people's mental health equally, and that certain groups, including those living in or at risk of poverty, were much more affected. For example, among the general population, depression prevalence was 11 percentage points higher in deprived than in the least deprived areas (28% vs. 17%) **[3]**. Whilst one in ten of those earning £50,000 or more experienced depressive symptoms, the prevalence for those earning less than £10,000 a year was four in ten **[3]**. **Figure 7.1** shows this strong relationship between depressive symptoms and gross personal income, with the analysis of longitudinal household survey data **[1]** showing that financial difficulties were a main predictor for deterioration in mental health during the course of the pandemic.

As well as this, other data shows that children's and young people's mental health has been particularly affected by the pandemic **[4]**. Whilst most impacts are likely to be short-term, it is likely that some of them will be long-term, especially when they are linked with a reduced ability for those affected to find jobs and with harm to their long-term earnings prospects. For example, a report has estimated the long-term 'scarring' cost of the pandemic to young people entering the labour market in 2021 in terms of lost earnings and damage to employment prospects at £14 billion **[5]**.

The link between poverty and mental health and the vicious cycle which it inculcates is well established, as is the potential for it to lead to substantial long-term harms over a person's life **[6]**. For example, poverty can adversely affect children and young people's brain development and functioning and lead to stressdriven or otherwise impaired decision-making, in which future benefits are discounted over more immediate rewards, thus increasing the likelihood of failure in the education system or in future unemployment **[7, 8]**.

There is a growing understanding that interventions which seek to reduce poverty have the potential to positively influence mental health **[9]**, although important evidence gaps remain in terms of what constitutes the best design for programmes or interventions that seek to reduce poverty whilst also improving mental health, and how to vary this design for maximum efficacy with different populations **[10]**. Two examples of poverty alleviation programmes, cash transfer and debt advice programmes illustrate their relevance in addressing the vicious cycle of poverty and mental health problems.

Cash transfer programmes, which provide regular cash payments to individuals or households identified as at risk of poverty, are one of the most frequently used povertyalleviation measures globally. Their use has been heavily expanded in many countries over the course of the COVID-19 pandemic **[11]**. Evaluations of these programmes provide important evidence as to the effects that poverty alleviation measures can have, demonstrating that they can achieve a range of health and wellbeing impacts for individuals and communities **[9]**. Whilst not one of their intended programme goals, benefits can include a reduction in certain mental health problems, such as depression, including for children and young people living in households receiving cash transfer payments, or who receive cash payments themselves **[10]**.

However, depending on the design and implementation of programmes in practice, they can also have adverse effects on children and young people's mental health; for example, when children or young people struggle to adhere to a programmes' conditionalities, such as regular school attendance **[12]**. Whilst most evidence on cash transfer programmes stems from lowand middle-income countries, there have been evaluations of similar programmes, like universal credit schemes, in highincome countries, including in the UK. Findings here suggest that the introduction of the universal credit scheme in the UK, which replaced existing benefit schemes and included an increased use of conditionalities and sanctions, led to a significant increase in psychological distress and depression among unemployed individuals affected by the policy **[12]**.

Debt advice programmes, which seek to alleviate poverty by supporting people to pay off their debt, are another commonly used welfare measure in the UK. An estimated 2.4 million children and young people in England and Wales live in households with 'problem' debt, of which a fifth are thought to have low wellbeing **[13]**. National surveys further suggest that up to a quarter of young people have already experienced debt themselves, with many reporting this as substantially affecting their mental health **[14, 15]**. Given this, it is unsurprising that debt advice programmes can play an important role in improving young people's mental health. Studies have shown that they can help in preventing families and individuals from becoming homeless and from falling under the poverty line, as well as in alleviating the mental health effects associated with debt **[16]**. In addition to improving general health and reducing anxiety, they can increase feelings of hope and optimism towards the future, although more research is needed to establish those effects and possible pathways to mental health impact **[17]**.

Both these examples illustrate that programmes in one area influence outcomes in the other thus highlighting the importance of integrated responses. In a Lancet Psychiatry commentary **[11]**, myself and colleagues argue for the need for integrated responses to improve the life chances of young people during and after the pandemic. We recommend that the integration of mental health into poverty alleviation measures should ensure that: 1) welfare measures specifically target young people at risk of mental health problems; 2) the potential impacts of poverty alleviation programmes on young people's mental health are considered when (re-)designing and improving programmes; 3) this includes the use of evaluation frameworks that include mental health; 4) mental health education and promotion resources are available through programmes; and 5) mental health treatment is promoted and offered through programmes.

Calls for integrated action to address poverty and mental health together have been made long before the pandemic **[13, 18]**. A few examples already exist in the UK, which demonstrate the feasibility of such integration efforts. For instance, specialised online mental health programmes have been developed for integration with financial services, which seek to address negative thinking patterns, avoidance habits and impulse spending behaviours **[15]**. Other examples of interventions, introduced before or during the pandemic, include measures to protect people using mental health crises services from creditors **[20]**, and employment advice services offered alongside mental health treatment **[19]**. More research is needed to understand whether those or other interventions are (cost-)effective.

### *Example 2: Mental health and social support*

Measures taken by governments in the UK and in many other countries to reduce the spread of the COVID-19 virus have had substantial impacts on people's social lives. In particular, children's and young people's access to their regular social networks were affected through measures such as school closures. Loneliness among children and young people increased sharply during the pandemic, with one in three reporting feeling lonely often or most of the time **[18]**. Even before the pandemic, one in ten children or young people in England said they often felt lonely, which is a higher proportion than for the adult population **[19]**. However, not all children or young people have been equally affected. Those with pre-existing mental health problems, living in or at risk of poverty, or from Black, Asian or mixed ethnicity backgrounds have been more likely to experience loneliness **[20]**. Whilst more research is needed to establish the potential longerterm impacts of the current COVID-19 pandemic on social support networks or loneliness, and the reasons for them, given that childhood and adolescence are important years for building and developing social skills and relationships for the future, it is plausible to think that the disruption to social life, including at school or workplaces, might have long-term impacts for some children and young people. Evidence from previous lockdown measures in response to other pandemics also suggests that social isolation and loneliness can persist after enforced isolation ends **[21]**.

The close link between mental health and social networks, and the support perceived as coming from such networks, is well established **[22]**. Most research shows the protective effects of social support, and the negative long-term impacts of low social support or loneliness on quality of life, and for older people, on morbidity and mortality, or the negative effects of a lack thereof, on mental and physical health **[23, 24]**. Policy responses before the pandemic included a loneliness strategy with allocated resources to implement proposed actions, and the appointment of a loneliness minister **[25]**. In addition to funding allocated under pre-pandemic policies, the government invested, in response to the pandemic, £31.5 million to organisations supporting people who experience loneliness **[26]**.

Whilst mental health and wellbeing research has played an important role in highlighting the importance of addressing loneliness to increase population wellbeing, there is currently limited and inconclusive evidence about what works and what is good value for the money in this area **[27]**. The absence of evidence on what works has potentially encouraged well-intended but potentially oversimplified recommendations or interventions, such as those that postulate or assume that simply increasing numbers of social contacts will automatically reduce loneliness **[28]**. While those suggested actions might have benefits for some, they might not be feasible or appropriate for the populations most at risk of loneliness, including marginalised children and young people. In our recent systematic review **[29]**, which investigated the 'logic model' behind interventions that successfully mobilise social support for children and young people at risk of social isolation, we found that most interventions involved complex and long-term processes that endeavour to build hope, self-esteem and trust. While often assumed to be low-cost, interventions in this area, if targeting disadvantaged groups, required substantial resources in the form of professionals' and volunteers' time, whether from public health, social care or education services, and some required joined-up efforts from communities **[29]**. The complex mechanisms between social support and mental health have been subject to more recent studies, including studies concerned with the impact of the pandemic on social support **[21, 30–32]**.

Positively, the national COVID-19 Mental Health and Wellbeing Recovery Action Plan **[26]** sets out an integrated, cross-sector response to address the mental health and wellbeing impacts of the pandemic, recognising both the importance of addressing social determinants of mental as well as of addressing the needs of children and young people in particular. For example, the plan includes actions to put in place training for teachers to recognise and support children and young people with mental health problems at school. It also includes actions for the provision of additional mental health support to young people not in education, training or employment. However, the plan does not set out long-term measures. Especially as government measures to protect financially against the implications of lockdown measures on jobs and employment have ended, so will their buffering and protective effects on mental health and wellbeing, thus exacerbating the need for long-term responses **[18]**.

### **Role of Economic Evidence in Informing Trade-offs**

As argued in the previous section, mental health and wellbeing research should have an important role in generating knowledge about the complex, multi-dimensional and interconnected nature of mental health and its social determinants. By generating knowledge about root causes and connections, it can inform targeted, integrated and long-term policy responses to important societal problems. However, given limited government budgets, decision-makers are often left with difficult trade-offs in terms of choosing between different policies. The large and far-reaching impacts of the COVID-19 pandemic require careful consideration of particularly complex trade-offs between and within areas of wellbeing and populations.

Economic evidence has – together with other considerations, such as those of equity and fairness – an important role in informing decisions about which population groups to target and which kinds of interventions are best designed to maximise long-term wellbeing given different government budgets. Economic research can inform difficult trade-off decisions by making the likely costs and economic consequences linked to different courses of action more transparent. Although often challenging to conduct **[33]**, economic research has an important role in assessing costs and benefits from wider family, community, societal and long-term perspectives, thus highlighting the less 'visible' costs or cost savings for and across different government sectors. Economic modelling approaches, which project long-term costs and benefits, can be a helpful tool to inform decisions amid uncertainty, including in situations when there is not sufficient time or resources to conduct new studies, or where it is impossible to get all required data from one data source **[34]**. A couple of examples of how economic research, conducted by CPEC at LSE, has informed resource allocation decisions in the UK are presented below.

By highlighting the size of the problem, and the potential opportunity costs for not investing into an area, cost-of-illness or cost impact studies can inform priorities for action. For example, research which showed that over a third of the total costs that can be attributed to dementia are those linked to informal care inputs by family members and other unpaid carers **[35]** informed policies and actions concerned with supporting unpaid carers, such as those outlined in the 2009 National Dementia Strategy **[36]** and the 2019 NHS Long-Term Plan **[37]**. Research **[38]** showing the high costs of maternal mental health problems during the perinatal period, occurring due to long-term impacts on mothers as well as on children, led to substantial investment into specialist perinatal mental health services in the UK as manifested in the Five Year Forward View for Mental Health **[39]** and NHS Long-Term Plan **[37]**. Utilising evidence from longitudinal studies on the long-term impacts of maternal mental health on children's emotional, behavioural and cognitive problems, the research highlighted the losses of quality of life and productivity in addition to the costs for publicly funded services including not just those of mothers giving birth but also those of children who have been exposed to maternal mental illness.

Whilst cost-of-illness studies generate important evidence about the size of a problem, and thus help in prioritising populations and problem areas, they do not provide information that can inform decision-making about investing in alternative courses of actions to address a problem. Cost-effectiveness studies, which measure and compare costs and outcomes linked to different interventions, are required for this. An example of an economic evaluation that informed policy action is the analysis of parenting programmes that seek to improve children's or young peoples' conduct problems, and which showed that these programmes can achieve large cost savings – many of which are achieved due to a reduction in costs linked to criminal justice services and costs to victims of crime, such as through reductions in ambulance or victim support services **[41]**. The study is another example of how including a perspective which includes more than just immediate outcomes occurring to the person receiving the intervention influences the economic case for choosing one intervention over another.

### **The Use of Research in Policy and Practice**

Mental health and wellbeing research needs to ultimately be of benefit to those in need of mental health treatment or support (including prevention and early intervention). For this to be realised, it must also be of use to those policy-makers, influencers and practitioners interpreting and using the research findings. Processes by which research informs policy and practice are typically long-winded and complex **[42]**, while the COVID-19 pandemic has highlighted the need for quick and effective processes of translating evidence into practice.

Individuals or organisations that advocate on behalf of certain populations or for certain causes can have an important brokerage function in utilising evidence, including of research commissioned by them. For example, the above-mentioned research on the costs of perinatal mental health problems was part of the *Everyone's Business* campaign led by the Maternal Mental Health Alliance and used to make the economic case for increasing access to specialist treatment for women. Economic evidence reviewed on interventions to reduce loneliness **[27]** informed the case for investing into actions by the *Campaign to End Loneliness* and evidence on the costs of inadequate support for early years was used by the Big Change Start Small campaign of the Royal Foundation **[40]**.

Although, as illustrated by those examples, campaigning and advocacy can have an important role in achieving impact, they are probably only suitable for some types of research addressing certain questions. Campaigns have, by definition, a very specific purpose under which the research and its findings are subsumed, meaning that they are limited in their capacity to use research independently or to answer a broader range of questions. Therefore, depending on the purpose of the research, other processes, including those led by researchers or conducted in partnership with different stakeholder groups, might be more suitable. This includes knowledge exchange initiatives between policy, practice and research, which move away from the more traditional 'knowledge push strategies', in which the focus is on disseminating the findings of researcher's work. This means that there is more engagement between the researchers and the stakeholders, enhancing the practical viability of the research.

Two projects led by CPEC, which seek to facilitate the use of research, are described below. The focus of the two projects is on social care users and their carers, which are populations at high risk of poor wellbeing and mental health, and who have been affected disproportionally by the pandemic, in terms of excess mortality and morbidity. The *Economics of Social Care Compendium* project (https://essenceproject.uk/) provides synthesised economic evidence about interventions in ways that ensure it is accessible to and useful for decision-makers, adding knowledge that helps them to interpret the evidence, such as information about the quality and relevance of the evidence in the current context. The project has been co-produced with practitioners, policy-makers and service users, and offers a number of knowledge exchange opportunities, including seminars and webinars. Feedback from people using the website and attending seminars has been positive, and the project received further funding from the NIHR School for Social Care Research to continue with its activities.

During the pandemic, international platforms for sharing evidence and resources among health and social care providers, commissioners and users have emerged. An example is the *Long-term Care Covid* platform (https://ltccovid.org/), which was started in March 2020 by colleagues at CPEC at LSE with members of the International Long-term Care Policy Network (https:// www.ilpnetwork.org/). It has expanded rapidly, now including a significant social media presence, and is working alongside many partner organisations. Ultimately, the project seeks to share evidence that can inform the response of the long-term care sector to the pandemic. Its main aims and objectives are to globally share learning on the impact of COVID-19 on people using and providing social care, including unpaid or informal carers, as well as about the factors that mediate and mitigate impacts, and to identify effective policy and practices. Thus far, the project has produced country reports and received inputs from members in more than thirty countries, in addition to a wide range of international reports, articles and blogs, some of which directly informed policy by international organisations such as the World Health Organization. It holds seminars or events on a regular basis. The work of the project has received significant coverage, especially for producing the first UK and international evidence on the number of deaths of care home residents due to COVID-19 **[43]**.

Both projects, Essence and LTC-Covid, build on networks and partnerships between policy-makers or influencers, practitioners, service user and carer representatives, and researchers. These often involve developing collaborations in which research is co-produced in processes that include trust-building based on principles of mutuality and equality **[44]**. Early feedback in response to the COVID-19 pandemic suggests that those partnerships might have had an important role in supporting an evidence-informed approach in response to the pandemic **[45]**.

### **Conclusion**

The policy response to the COVID-19 pandemic has focused on responding to the most immediate pressures, which were centred around providing adequate financial protection for those whose existence is most severely affected by lockdown measures or the physical health consequences of the pandemic. However, experiences from past health emergencies and economic crises show that mental health can become a priority of system reform during those times and that there are opportunities for change and for 'building back better' **[46]**. This includes designing public sector systems that are fit for purpose for future health emergencies. The LSE-Lancet Commission on the future of the NHS after COVID-19 recommends the incorporation of mental health strategies into plans to responses for future health emergencies and highlights the importance of mental health evidence in informing such responses **[47]**.

This chapter provides examples of how mental health and wellbeing research can potentially inform policy responses that tackle complex societal problems, including those posed during and after health emergencies. This included research that generates knowledge about the root causes of poor mental health; mechanisms and factors that matter the most for addressing mental health problems; and examples of economic research that informed resource allocations from a long-term perspective and from the perspective of different parts of society. As argued in this chapter, economic research in mental health has an important role in informing the difficult trade-off decisions between health, economic and social priorities that are typical for health emergencies. In order for relevant research to be produced and disseminated effectively and efficiently during health emergencies, government and non-government institutions should invest in building, developing and maintaining partnerships and networks between policy, practice and research.

### **References**


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during the COVID-19 pandemic. *BMC Psychology*. 2021; 9(1): 81. DOI: https://doi.org/10.1186/s40359-021-00589-4


## **8. Health, Wellbeing, and Democratic Citizenship: A Review and Research Agenda**

Christopher J. Anderson, Sara Hagemann, and Robert Klemmensen

Social scientists have examined the causes and consequences of people's engagement with politics for many decades, yet we have only just begun to understand the roles that health and wellbeing play in people's involvement as members of the body politic. Findings from a nascent body of research suggest that health predicts people's decision to turn out to vote and whether they feel they can have a say in political decisions more broadly, but we still lack a systematic understanding of the variable, as well as specific, ways in which health and feelings of wellbeing shape people's interactions with political life. We also know little about how – and if – these patterns vary across groups in society, regions, countries, or over time. In this contribution, we present a framework for analysing the ways in which specific health conditions may shape the connection between citizens' wellbeing and their interactions with politics and how research should endeavour to trace the consequences of these links for people's lives as citizens and their full participation in the democratic political process.

In surveys collected in 29 European countries between 2018 and 2020, one in three (34.7%) indicated that their health was 'fair', 'bad', or even 'very bad', while 65.3% rated their health as 'good' or 'very good' (The European Social Survey, www.euro peansocialsurvey.org, Round 9). In the same surveys, over 1 in 4 (26.7%) indicated that they were hampered in their daily activities by illness, disability, infirmity, or mental problems. Hence, depending on how we define physical or mental wellbeing and the strains associated with them, between one quarter and one third of Europeans report that they are coping with less than perfect health.1 Not only do these numbers constitute significant proportions of European societies, but as the negative correlations of indicators of individual health with measures of subjective wellbeing in **Figure 8.1** show, they shape how people feel about their lives: those who say they are in ill health or are hampered in their daily activities because of illness are also significantly more likely to say that they are unhappy or dissatisfied with their lives.

The fact that significant proportions of democratic electorates report less than perfect health at any given point in time is interesting and important in its own right, but how does it impact our societies? The politics and economics of health are well documented, and health policy, of course, is a long-standing and prominent concern across all contemporary democracies.

As a result, we know that inequalities in health conditions are systematic and considerable both within and across countries **[1]**. Long recognised as an important and costly public issue, health concerns have received attention from researchers and policy-makers interested in how government action can redress

*Source:* European Social Survey (ESS, Round 9).

current inequalities and the potential to reduce future ones **[2]**. 2 Political choices and policy designs matter for health outcomes.

In a different corner of the social sciences, political scientists for many decades have sought to understand inequalities in democratic political participation. How and why citizens engage with politics is a cornerstone of the study of politics; decades' worth of scholarship have established that people participate in different ways and at different rates because of unequal access to resources like time, money, and civic skills or differences in the motivation to engage with democratic politics. At the level of countries, socio-demographic heterogeneity and economic inequality are key drivers of inequalities in political demand and democratic representation, alongside differences in the formal political institutions that facilitate or hamper people's access to and engagement with political processes and institutions (e.g., **[3, 4]**).

For much of their existence, scholarship in these areas of health policy on one hand and political participation on the other has proceeded on parallel tracks. Yet, there are good reasons to connect them by examining the nexus between 1) inequalities in health and wellbeing and 2) inequalities in political participation and representation. First, while focusing on the political determinants of health and health inequalities is important, we know comparatively little about the flipside of the coin, namely whether and how differences in health and wellbeing matter for politics and civic life (cf. **[5, 6]**). Modern democracies devote significant resources to the wellbeing of their members to ensure full and equal participation in social and economic life, and yet, we have limited knowledge about how health and wellbeing in fact shape the ways in which people exercise their rights and responsibilities as citizens. Put simply, do policies that are designed to produce healthier populations also produce healthier democracies?

Second, health and wellbeing as determinants of political action are important for the study of politics for normative as well as empirical reasons. Commonly viewed as foundational to a well-functioning democracy, citizenship behaviours and attitudes are shaped – whether sustained and enhanced or interrupted and hindered – by the wellbeing of its citizens. It is an especially compelling argument from the perspective of democratic representation: if some groups in society are systematically underrepresented among those who make political claims and for reasons that are remediable, the democratic edifice is lacking.

Below, we begin by reviewing scholarship in health and health inequality on one hand and research on political behaviour and representation on the other to delineate the intersections between people's physical and psychological wellbeing and their cognitive and physical engagement with politics. Because wellbeing and political engagement take many intersecting and variable forms, the links between individual health and wellbeing and political attitudes and behaviours are complex and not always apparent. Moreover, these vary across countries, across different population groups, and over time.

More specifically, to understand how health shapes the quality of democratic life, we need to differentiate among specific types of health conditions and how these, in turn, affect particular kinds of citizenship behaviours. **[7, 8]** Moreover, we will want to know how these relationships vary as a function of individual characteristics, such as age, gender, income groups, and levels of education, that endow citizens with resources or motivations to engage in politics. For example, well-documented skews in political engagement show that older, better-off, and more educated citizens participate more fully in democratic life. As a result, older citizens' voices are heard more consistently and their preferences are represented more reliably. At the same time, we know that different groups of people have variable odds of experiencing distinct health-related problems for different kinds of reasons (e.g., lifestyle, working conditions, or access to preventive and diagnostic care).

Do these patterns go hand in hand or are they, as the example of older citizens may imply, at odds with one another? Does it matter what the nature of the health condition is? For example, do muscular and back pain or heart disease and diabetes have the same effect on political engagement, and are they consequential for the preferences of different groups of people or how these preferences are expressed? Put simply, do health problems cut across the currently documented inequalities in political participation or do they serve to exacerbate them, and do the sources of good and ill health matter differently? These questions are important, but their answers are likely to be found only in careful analyses of rich data, with the help of different methodological approaches.

Finally, we want to understand whether welfare systems and access to health care or treatments enhance access to the political arena or skew political demand **[9]**. Health policy is at the core of modern welfare states, often a central feature of political debates, and its design and operation affect people in ways that shape their resources and how they think about themselves as individuals and citizens. Given existing inequalities in the quality of care, access to care, and treatment, do citizens who need, seek, and subsequently receive treatment for particular conditions participate more fully or differently in politics than those who do not or cannot? Do these groups hold systematically different views about their country's health care policies and practices, and to what degree do we detect variance between the groups in their behaviours?

### **Understanding Health and Political Behaviour in Democracies**

What citizens want from government and what they do to get it is one of the core concerns of the study of politics. Political scientists have spent decades studying this question and we can summarise their insights with the help of some stylised facts. First, people's socio-economic status (SES) – often proxied by income, education, and social class – correlates positively with becoming involved with politics: higher status individuals participate more. Second, the mechanisms that underlie the basic correlation between SES and political action revolve around high SES individuals possessing the necessary resources – both material and otherwise – to engage with politics in various ways **[10]**. Indeed, the classic studies of participation suggest that financial resources and civic skills in particular are key to understanding why some people participate more than others **[11]**. In addition to these resources, the so-called 'Civic Volunteerism Model' developed by Verba, Schlozman, and Brady argues that participation also requires social connectedness and psychological engagement **[11]**. Taken altogether, individual resources, mobilising networks, and motivation are at the heart of what makes people participate.

While research on inequalities in citizen politics and access to the necessary resources has therefore been a core concern in the study of politics, it has surprisingly little to say about the connection between health and political cognitions and behaviours. In stark contrast to long-standing literatures linking health and participation in education, work, and family life, standard texts on political participation and voter turnout like Milbrath and Goel **[12]** or Wolfinger and Rosenstone **[13]** barely mention health, and Verba, Schlozman, and Brady's **[12]** by now classic analysis of political participation completely ignores health as a factor that influences involvement in civic life (see also Burns, Schlozman, and Verba 2001 **[14]**). Similarly, even the most prominent analysis of political activism among older adults in America, which focuses on the importance of resources, does not include any mention of health as a key ingredient **[15]**. And Schlozman, Brady, and Verba's **[16]** most recent book *Unequal and Unrepresented: Political Inequality and the People's Voice in the New Gilded Age* – a summary of three decades of work into political participation in America by some of the most distinguished political scientists of our time – references the health of citizens exactly once, and only in passing, noting that the most politically active citizens also tend to be healthier. As Burden et al. **[17 p167]** summarise this literature: when it comes to the question of whether health influences political participation, 'the link between the two is often overlooked, sometimes assumed, and poorly documented.'

Political scientists' neglect of health as a determinant of civic engagement has been as notable as it has been regrettable. A nascent body of research has begun to address this gap by examining how various health conditions may affect how people think about and actively participate in democratic politics (e.g., **[18–23]**). The most frequent starting point for these studies is a 'health gap hypothesis', which assumes that there is a positive relationship between a person's health and the quantity of their political involvement **[5, 6, 24]**. Echoing the civic volunteerism model foundational to research on political participation, the idea of such a health gap or health bias between more and less healthy individuals is rooted in the idea that engaging with politics has a psychological as well as a physical component and therefore requires resources that are linked to health. As Gollust and Rahn **[18]** note, 'The experience of illness … reduces the nonfinancial resources – including physical, cognitive, and social/ emotional resources – that could promote civic participation.'

As a consequence, health should affect political participation in various ways. For example, it impacts people's ability to engage in physical and mental tasks – consider, for example, the cognitive task of deciding who to vote for and then the physical task of casting a ballot – thus shaping their ability and skills to participate fully in democratic politics **[18, 25]**. In addition, if concerns about illness overwhelm a person's attention to other domains in life, including politics, ill health can reduce the motivation to become or remain involved. Or, given that physical and mental health contribute to the creation and maintenance of social networks and participation in social institutions, such as the workplace or religion, it can affect participation via the likelihood of mobilisation and recruitment by social others into political activity. Consistent with the health gap hypothesis, one general conclusion arising from existing studies is that poor health impedes the full participation of citizens in the political process. Moreover, the effect seems to be independent of other important socio-demographic or psychological factors associated with full and active citizenship behaviours **[5]**.

While such baseline findings about the deleterious effects of ill health may be intuitive, they have not been documented universally. Instead, the studies are generally limited in terms of scope and significance, focusing on different groups in society, with most research in this area still being early in the scientific lifecycle and exhibiting several notable limitations. Some of these limitations are empirical and others are conceptual and theoretical. For example, it is not exactly clear as to why particular health conditions alter the ways people engage in specific kinds of political acts and cognitions, or whether they do so consistently across different populations. In addition, important methodological issues and data-related challenges require clarification and examination. Taken together, despite a promising and emergent body of evidence, we are still some distance from fully exploring, let alone understanding, the various ways in which health-related factors shape how and how much citizens engage with democratic politics across countries and across populations and why. At the same time, because the provision of health care is increasingly the responsibility of government, it is important for both normative democratic theorists and empirical social scientists to fully understand whether and how the voices of the healthy or unhealthy are translated into public policy.

### **Taking Stock: Existing Data and Research**

On the whole, then, our knowledge about the link between health status and the way individuals think about and engage with politics – namely, that ill health seems to be associated with lower levels of engagement – is currently based on studies that examine the connection between health and participation in very specific ways. For example, to date, most studies measure wellbeing with the help of self-reported health; they also most commonly examine electoral participation (voter turnout) to measure political engagement. Both make sense for theoretical and practical reasons, as voting is the most common political activity most people engage in during their lifetimes, while self-reported health is a reliable and readily available indicator of wellbeing.3

At the same time, we do not know if other acts of participation are affected by health in the same way as voting is. Moreover, the finding that ill health demobilises citizens is not uniformly corroborated by the data. In fact, some studies have found that, rather than diminish people's motivation to be engaged, ill health can serve to politicise them (cf. **[19, 26]**). This politicisation arises from self-interest, with the increased activism hypothesis (or what some have called the reversed health gap) predicting that ill health motivates political involvement because the stakes of public policies and the provision of healthcare are higher for those highly dependent on health services **[5]**. Thus, people with specific health conditions may be more, not less, active in work that involves political parties, contact with policy-makers, and political demonstrations to make their voice heard to express grievances or needs **[19]**. Second, as a matter of social identity, illness and disease patterns may produce a shared experience and social identity, with mobilising networks and political entrepreneurs organising affected individuals to make demands on policy-makers **[27–30]**. Good examples of such mobilising identities are networks of cancer survivors or associations devoted to raising funding and awareness for particular kinds of diseases.

While research into and thus evidence in favour of this politicisation hypothesis has been much more limited than research on the health gap, it offers a clue that there may be alternative channels for political engagement among some subsets of people with specific conditions. Turned on its head, the politicisation hypothesis may also be useful for capturing a theoretically curious, but empirically well-documented, phenomenon: that younger (predominantly healthy) voters are more likely to abstain from participating in political life. In line with the politicisation hypothesis, younger voters in good health may well have fewer incentives to take political action, believing that the system can be relied upon and serves their interests. Hence, the politicisation hypothesis, while plausible, requires more rigorous and complete testing than has previously been the case.

**Figure 8.2** summarises the current literature linking health and political engagement, with our added suggestion of a reverse politicisation hypothesis in the top left corner.

Beyond the two stylised conclusions – that ill health is debilitating for political engagement and that some forms of ill health


**Figure 8.2: Hypotheses in the literature regarding health and political engagement**

*Source:* European Social Survey (ESS, Round 9).

hold the potential to politicise citizens – we know of few results in this emerging literature that would qualify as uncontested. For example, looking at the correlations of health and various forms of political participation and the attitudes about politics in the sample of European citizens we mentioned at the outset, we see that they can indeed be found in the data. **Figure 8.3**, which shows correlations between health and political engagement, reveals that Europeans who report higher levels of ill health and being hampered by illness in their daily lives are, by and large, significantly less engaged with politics: they participate less and exhibit lower levels of happiness with the political system.4

**Figure 8.3: Correlations between political behaviour and political attitudes by those experiencing ill health or feel hampered in their daily activities**

However, these conclusions are not uniformly supported by the data. While reports of health ('ill health') are strongly and negatively correlated with trust in the political system, satisfaction with the government, or a sense of being able to participate in politics (so-called political efficacy), feeling hampered in one's daily activities is essentially uncorrelated with reports of attending demonstrations or working for political parties. Importantly, those who report being hampered are just as interested in politics as other citizens, while correlations of being hampered and turnout in the last elections are modest at best.

We speculate that part of the reason for why findings in the emerging literature on individual health and political engagement are mixed is conceptual. In particular, there is a need to specify the cognitive and physical requirements and antecedents of specific behaviours and opinions more precisely in order to subsequently establish which dimensions of health matter and in what way. For example, are the critical dividing lines between physical and cognitive requirements, chronic and acute ailments, the social meaning of diseases and disease identities, or differential treatment via the health care system? Answering these questions requires a framework for specifying what we mean by health and political behaviour and to conceive exactly how we believe the two to be connected.

### **Healthy Citizens: Connecting Health and Wellbeing in the Study of Politics**

We start by defining health as a personal property or asset5 and political engagement as an individual-level activity that involves concrete and observable acts (e.g, voting, demonstrating, joining a group) as well as political orientations, including motivations (e.g., political interest), policy preferences (e.g., left-right orientations), feelings of political efficacy and trust, satisfaction with incumbents, and the like **[5]**. If political engagement, then, has physical and psychological manifestations and requires the necessary resources, motivations, and mobilising networks, our conceptualisations of individual health and wellbeing need to be defined relative to the political acts we are studying: some aspects of health status involve the ability to perform physical tasks and some involve emotion, others cognition. Importantly, perhaps, there also are blurry conceptual lines between, say, chronic diseases and disability. Moreover, some forms of action, such as casting a ballot, require different kinds of physical resources than others, such as making an online donation to a political organisation, while some attitudes are more heavily cognitive in nature with others being more related to affective states.

In combination, then, health and political acts need to be seen in relation to one another. Similar to Mattila et al.'s **[5]** discussion of the notion of 'accessibility' of political behaviour, we ask, 'What does this type of engagement require?' Once we can answer that question, we can define a particular kind of health status as potentially being facilitating or debilitating with regard to specific political actions or the formation of particular attitudes. That is, we think of political acts as being hindered or enabled, depending on the specific health concern involved and depending on the person's experience of how their wellbeing is thus affected.

Our generic individual-level model hence links health status and engagement, where the effects of health on behaviour are likely to be conditional on a) the specific attitude or action to be explained, b) the specific health issue(s) at hand, and c) intervening factors, such as demographic factors, socio-economic resources, attitudes (like identity), and mobilising agents and networks. In the aggregate, inequalities arise because individual-level physical and psychological resources necessary for political engagement are distributed unevenly across social groups in a population.

In this way, we expect the influence of health on engagement to be conditional, and in several ways. For one, ill health manifests in different ways and in ways that are differentially relevant to specific actions. Moreover, there are likely to be significant differences between somatic and psychological wellbeing – differences that do not necessarily point in the same direction of more or less involvement. In fact, absent the need to perform a physical task, physical wellbeing may serve to produce countervailing effects on civic attitudes. For example, as discussed above, good health may induce people to believe that all is well and thus produce more positive attitudes about government and politics, while ill health may have the opposite effect and mobilise to action.

These direct effects are interesting but only the beginning of the story. As mentioned above, it is likely that they are conditional on individual traits, characteristics, and attitudes. Thus, political ideology may moderate these effects, as may politically and psychologically relevant identities like gender or socioeconomic status. To complicate matters even further, the logic of physical resources and political engagement may not translate neatly to the effects that cognitive resources and abilities may have on people's involvement with politics. While education has long been a potent predictor of physical and psychological involvement with politics, it is yet to be determined if the availability of cognitive resources functions in the same way that physical ones do.

As a last point in this complex chain of relations whose logic we seek to unravel, we expect these relationships to be embedded in particular political, institutional, and cultural contexts and thus to vary as a function of differences across countries. Hence, aggregated to the level of countries, we should see cross-national differences in the strength of the individual-level associations as well as aggregate correlations that are contingent on national factors (such as formal political institutions, political culture, or characteristics of the social policy and health care policy systems).

**Figure 8.4** above illustrates our main argument: that health and wellbeing directly, as well as in conjunction with other identifiable factors, affect political action on a sustained basis.

**Figure 8.4: Relationship between individual health status, social context and a person's political engagement**

### **A Brief Look at Some Data**

In this section we conduct a brief empirical probability probe to see if some of these patterns can be detected in the European Social Survey data mentioned above. The intention is merely to establish whether the overall picture of these correlations holds true in order for future research to then engage with these relationships more rigorously and more in-depth.

In **Figure 8.6** we correlate reports of political action and attitudes with reports of subjective health and wellbeing hampered in daily activities. Importantly we subset these by gender, education, and income, given that they are well known antecedents of

political engagement and because they are likely to proxy for differences in the availability of resources to compensate for difficulties arising from bad health outcomes. **Figure 8.5** summarises these factors – health, institutional and socio-economic factors – and their impact on a person's political engagement.

The top row of **Figure 8.6** shows correlations of health with political engagement for women and men, the second row shows

#### **Figure 8.6: Effects of health on political engagement dependent on gender, income, and education, respectively**

*Source:* European Social Survey (ESS, Round 9).

these correlations for respondents with low and high levels of education, and the third row for high- and low-income earners.

The patterns are as interesting as they are straightforward. Generally speaking, reports of ill health are negatively correlated with measures of physical and psychological political engagement, particularly when it comes to attitudinal measures of political engagement, including political trust, satisfaction, and a sense of being able to participate in politics. In contrast, correlations with actual reported political activities are significantly lower. Thus, the data show that reported health status is indeed a significant factor in people's engagement with politics, but even more so is a person's subjective sense of wellbeing.

Just as importantly for our purposes of demonstrating the complexity of the relations between health and political engagements, there are consistent differences in the strength of these correlations across the different demographic groups. Specifically, we see that ill health has a significantly more debilitating effect on attitudes and behaviours among women and individuals with lower levels of education and income. At the same time, we also see that our measure of reported (subjective) health has significantly stronger correlations with the various outcomes than reports of actually being hampered in daily life because of illness.

On the flipside, we also see that ill health appears to have the potential to be a positive driver of political motivation, especially among the highly educated and individuals with higher incomes. Among these two groups, we see a positive correlation between ill health and political interest, as well as a positive but more modest correlation with reports of having worked for a political party. Taken together, these correlations suggest that the health gap hypothesis has broad applicability, but that health status has different correlations with attitudes and actions as well as across groups of individuals with more or fewer political resources. In particular, it is striking that being hampered in their daily lives appears to mobilise and motivate people of higher socioeconomic status to be politically involved to a greater extent than those of lower socio-economic status.

### **Looking Ahead: Some Suggestions**

While these correlations only scratch the very surface of what may lie underneath the relationships between health and political engagement, they point to some of the key challenges to be addressed as part of future research in this area. On a theoretical level, they highlight differences between the dependent variables under examination – action versus attitudes – and why we may see them. More importantly, perhaps, they remind us of the importance to conceptualise and specify the physical and cognitive demands they put on people with different kinds of health experiences. Moreover, on the independent variable side, they raise the question of why subjective health has stronger effects on engagement variables than reported health; this suggests the need to specify how to capture the different kinds of limits that physical and cognitive abilities impose on citizens.

Among the various ways of categorising these, we would imagine there to be important disparities, depending on whether differences in health are due to chronic or acute ailments, different kinds of chronic ailments, disease identities and stigmas, or how we categorise and incorporate the study of disabilities into the study of wellbeing and political engagement. On the cognitive resources side of the ledger, too, we will need to understand variation across different kinds of mental health conditions, for instance, and the extent to which they may or may not impede cognitive engagement with politics.

Aside from important conceptual and definitional issues, there are important empirical considerations to bear in mind. For one, the more specific and finely grained the disease patterns or impairments we are looking to study, the bigger and more precise our datasets need to be in order to achieve sufficient empirical leverage to tease apart how the different manifestations of ill health matter. Aside from the need for rich and plentiful data, there also is the need to move beyond purely correlational evidence in order to pin down the consequences of ill health for political behaviours. Causality is difficult to establish with existing data sources. Outside the laboratory, longitudinal panel data that trace people's wellbeing and political engagement over the life course may allow us to track changes in individual outcomes. Alternatively, certain statistical techniques can be helpful, provided the data are rich and samples sizeable, to draw inferences at the level of individuals. In particular, so-called matching methods, where we match individuals on all relevant characteristics except for the statistical treatment of interest – here, an individual's health status **[31, 32]** – may be especially useful.

Aside from allowing richer, more comprehensive, and more extensive cross-nationally valid measurement of health status as well as political behaviour, comparing individuals across countries will allow us to establish with greater precision whether the impact of health varies across different health care systems. Do differences in health care systems shape and moderate the connection between health inequality and political inequality? Given the considerable cross-national variation in terms of how health care is funded or the nature and extent of provision **[33]**, it will be important to establish whether people across specific social groups (e.g., age, income, and education) are systematically advantaged or disadvantaged when it comes to the formation and expression of political preferences, depending on the provision of healthcare in a society. Together, these building blocks will allow us to establish whether there is a connection between health and democracy, what form it takes, and whether that connection is spurious or causal. Of course, what policy-makers are likely to do about these findings and whether they can serve to articulate proposals to address inequalities of participation resulting from differences in health outcomes has to remain an open question for another day.

### **Notes**

1 The number of respondents across these surveys was 49,320. There are cross-national differences, with Lithuanians and Latvians most likely to say they feel healthy and the Swiss and the Irish least likely to do so, or Lithuanians and Latvians least likely to say they are hampered in their daily activities and Italians and Spaniards most likely to say so.

2 Thus, researchers have found, for example, that inequalities in population health are lower in the more generous and universal welfare states of Scandinavia **[34]** or that the choices governments make when it comes to designing health, education, and social policies are systematic drivers of health outcomes that mediate the impact of people's socioeconomic position on their wellbeing **[35]**.

3 Often examined in the context of age and lifecycle effects in health and voting, researchers have found that ill health reduces turnout, and this effect is especially pronounced later in life.

4 European Social Survey data have been used in some of the most prominent European studies of health and wellbeing and political engagement (www.europeansocialsurvey.org). Here, we look at political actions and attitudes asked repeatedly over a number of years. Actions include voting, attending demonstrations, and working for a political party; attitudes include people's trust in political institutions and satisfaction with the government, political interest, and political efficacy.

5 We acknowledge that people can also be affected by the health challenges of social others, such as family members or friends.

## **References**


*politics, policy and law*. 2015; 40(6): 1115–1155. DOI: https://doi .org/10.1215/03616878-3424450


## **9. Health and Disability Gaps in Political Engagement: A Short Review**

## Mikko Mattila

This review presents a short overview of the current state of research in the field of health, disability, and political engagement. I focus on the individual-level relationship between health and political behaviour or political attitudes. Most of the existing studies have analysed the effects of health or disability on electoral turnout, and almost all of these studies have found a negative association between poor health, disability, and turnout. The relationships between health and other forms of political participation are more complex; poor health and disability can actually promote certain types of participation (e.g., signing petitions or participation in social media). However, studies of political attitudes show that poor health and disability are connected to lower levels of trust and external political efficacy and that this disengagement may even lead, for example, to increased support for right-wing populist parties. In general, political actors and researchers need to be encouraged to implement new, more inclusive solutions to bridge the health and disability gaps in political engagement.

In this review, I present a short overview of the current state of research in the field of health and political engagement. The overall aim is to provide an easily accessible evaluation of the main concepts and empirical contributions for readers interested in the rapidly expanding field. I focus on the individual-level relationship between health and political behaviour or attitudes, that is, on what we know about the effect that individuals' health status has on their engagement with democratic politics. Given the briefness of this review, it is impossible to do justice to all of the research in this rapidly growing field. However, I try to present a balanced view by highlighting the most important research results and developments in the field.

I start by briefly discussing the definitions of health and disability, because it is important to acknowledge the differences and similarities between these two concepts for two reasons. First, political science researchers often do not make a distinction between the two. Although health and disability are two separate concepts, they can sometimes overlap empirically. Second, if we acknowledge the similarities between these concepts, there is much that political scientists can learn from the disability studies field, particularly when it comes to policies that aim to bring the voice of these disadvantaged groups into political decision-making.

After this conceptual part, I will turn to a discussion of the existing state of knowledge in the field of health, disability, and political engagement, starting by reviewing what we know about the health implications for politics and then discussing the policy implications of this accumulated knowledge.

### **Health and Disability**

The concepts of health and disability are related, but the exact nature and overlap between the concepts is rather difficult to define because the nature of both is contested, with little consensus on their substance. One of the most frequent definitions of health is that provided by the World Health Organization (WHO), which defines health as 'a state of complete physical, mental, and social well-being and not merely the absence of disease or infirmity' **[1]**. But compared with health, defining disability is even harder. Depending on the approach, disability can be defined as an impairment (medical definition), a functional limitation that prevents participation in work life (administrative or legal definition), or barriers in society that restrict the lives of people with disabilities (social definition).

Turning once more to WHO, they define disability as an umbrella term incorporating three dimensions: (1) impairment, (2) activity limitation, and (3) participation restriction **[2]**. The first dimension refers to a problem with bodily functions or structure, whereas an activity limitation is a difficulty encountered by an individual when executing a task or action. From the perspective of democratic government, the third dimension is perhaps the most interesting. Participation restrictions are defined as problems affecting individuals' involvement in life situations. This dimension is particularly important for political scientists, as participation in democratic politics is one of the most central subjects of study in the field.

The concepts of health and disability are thus distinct, but overlap in part. For instance, not all persons in poor health belong to the group of disabled persons, but those with chronic illnesses may fall into this category. For example, diabetes may cause blood-flow problems in feet, which may lead to amputation and permanent movement restrictions. Likewise, a person with a disability may otherwise be in excellent health, but others may have health concerns beyond their disabilities. The essential point here is that both conditions may restrict or disable people's participation in democratic life.

For political scientists, it is possible that when they say they are analysing the relationship between health and politics, they often mean they are interested in how disabilities affect people's engagement with politics. Here, the term *disabilities* incorporates the standard definition discussed earlier but also includes chronic health problems. Short-term health problems are not, in and of themselves, challenging for democracies. If a person catches a common cold just before election day and does not vote because of this condition, it will not be a problem for democracy as long as these short-term conditions are dispersed relatively randomly in the population. However, chronic health conditions are different. They are long-lasting by definition, and we know that they are not randomly distributed among different socio-economic groups in the population. They affect less well-off people to a greater extent than other groups, and this group also often has other difficulties in their lives that affect their political participation. These kinds of health differences produce health gaps in democratic participation between those in good health and those in poor health, which in turn are likely to result in bias in policies, because the voices of all groups are not equally heard in the decision-making process **[3]**.

Therefore, it appears that political scientists are in fact more interested in participation limitations in democratic politics brought about by long-term impairments than in the effects of health conditions. This would imply that they are interested in not only the effects of health but also disability. Because there already exists a large body of literature studying societal participation in the field of disability studies, political scientists should certainly engage with this literature more in their own studies as the issues confronted by people with health problems are often similar to those limitations faced by people with disabilities.

### **Health and Disability Gaps in Politics**

Health and disability gaps in politics refer to differences in political engagement between those in good health and those in poor health, or between those with disabilities and those without. The gaps may be related to participation or to differences in political attitudes, values, or identifications. Most studies have focused on different forms of political participation, and studies analysing the effects of health **[4]** or disability **[5]** on electoral turnout have been particularly popular. Almost all of these have found a negative association between health and turnout, with a scoping review of 40 studies showing that this negative relationship is robust, has electoral consequences, may shape policies, and may deepen existing health inequalities **[6]**. Theoretically, researchers have attributed this negative effect to a lower sense of political efficacy, lower levels of social and financial resources, or diminished social networks amongst people with poor health. However, more information is needed about condition-specific effects on turnout, because it seems that although the relationship is usually negative, some conditions increase the likelihood of turning out **[7]**.

Poor health seems to affect voting choices as well. In terms of the traditional left-right dimension, people with poor health or disabilities are more likely to identify themselves with the political left **[8]**. Most studies of actual party choices in elections have been conducted in countries using the first-past-thepost electoral system, with results from the UK showing that people in poor health in general **[9]** or people with depression **[10]** are more likely to favour Labour over the Conservatives, and in the United States, results show that the Republicans are similarly favoured by those in good health **[11]**. However, more recent studies of European multiparty systems indicate that poor health is associated with a higher likelihood of voting for right-wing populist parties **[12]**. Finally, there are also some results indicating that mental health issues may affect voting choices in referendums as well, as was the case with the Brexit referendum **[13]**.

Regarding forms of political participation other than voting, the results are more varied and depend on the context, type of illness, and participation form. The pioneering study by Söderlund and Rapeli found that among Nordic citizens, poor health can actually motivate people to participate **[14]**. Poor health can intensify the importance of politics for individuals because welfare policies, particularly those related to healthcare services and transfers, become more important for people with health problems. Similar results were subsequently found in a wider European comparison and also in other contexts **[15]**. For instance, contacting politicians, signing petitions or initiatives, being politically active in social media, and boycotting certain products were found to be typical forms of participation in which people with poor health were more active than those in good health.

Interest in politics is a key indicator of citizens' attitudes towards politics. Interest is usually quite a stable trait that is developed in adolescence and is generally relatively consistent over the individual's life course. Findings relating to the correlation between health and interest are somewhat mixed. Analyses with cross-sectional data have shown that depression and disabilities are associated with lower levels of interest in politics **[16]**, but a longitudinal study of the effects of general health on interest levels found evidence of a relatively weak connection **[17]**.

One of the main attitudes promoting political participation is political efficacy, which is typically broken down by political scientists into two subcomponents. The first, internal political efficacy, refers to individuals' evaluation of their own competence in terms of understanding and analysing politics. The second, external efficacy, refers to beliefs that politicians and the political system in general are responsive to demands from citizens. For those with high political participation, this engagement is typically preceded by the belief that one is capable of acting politically (internal efficacy) and that it is possible to make a difference through one's actions (external efficacy). Available results on how health is related to political efficacy vary. In one study, data collected from Finland showed that poor health was associated with lower levels of external efficacy but was unrelated to internal efficacy **[18]**. However, a later European-wide study suggested that in addition to external efficacy, low internal political efficacy is also related to people's poor health status **[19]**. Disability is also linked with lower levels of both types of efficacy, although the gap in internal efficacy disappears after controlling for education and certain other socioeconomic factors **[20]**.

Another important predictor of political participation is political trust. Data on how health is related to trust show stronger patterns than results concerning efficacy. People in poor health have lower levels of trust in policy-makers and in the functioning of the political system **[21]**. However, the effects of low levels of trust on actual political participation are not necessarily obvious. Research from Finland shows that poor health leads to lower levels of trust, which in turn depresses traditional forms of participation (such as voting), but that it has the opposite the effect on non-institutional participation. Health problems in combination with low levels of trust motivate people to engage in participatory forms that bypass traditional party-based institutions (e.g., demonstrating, boycotting products and political participation in social media) **[22]**. This poor-health-related disengagement from traditional forms of participation may also be related to the observation that when people become ill, their identification with political parties also decreases **[23]**.

To sum up, we know quite a lot about how health or disability affects political engagement in general. Poor health or disabilities affect both the amount of participation and the way people participate. They depress traditional partybased participation (such as turnout) and are linked to disappointment with the political system (low levels of trust and external efficacy). In contrast, this disappointment also encourages certain types of political activities. Poor health often motivates people to engage in actions that are directly relevant to their needs, such as participating in demonstrations related to insufficient public health care policies, or contacting politicians to try to affect decisions that go to local level health services. Hence, it is difficult to say whether poor health or disabilities reduce participation in general (except in self-evident cases of extreme impairments), but it certainly transforms the way people participate in politics.

Obviously, there are still several important topics not covered by the existing research. First, the literature does not inform us enough on the relative importance of health problems in comparison to the main indicators of individuals' socioeconomic status. For instance, questions such as 'How significant is the effect of poor health or disabilities on political engagement when compared to low income, unemployment or low education?' have not yet been sufficiently answered. Furthermore, we do not know if and how health problems interact with socioeconomic status or life habits, although there are some results indicating that the health effect is independent of persons' social class **[24]**.

Second, we do not know enough of the potential context specificity of the health gaps. It is probable that the effects of health are heterogeneous; that is, they vary in different cultures and political systems, or amongst different groups of people. Few studies have looked comparatively at health or disability gaps in different welfare state regimes. The hypothesis that differences between health groups should be smaller in societies where public healthcare services (combined with extensive social support networks) are widely available makes sense. Nevertheless, available analyses only partially support this idea. Comparisons of health gaps in trust and political efficacy show that both political trust and political efficacy are higher in more encompassing European welfare states, but the differences between those in good and poor health are also largest in these strong welfare states **[25]**. One explanation for this observation could be the 'Nordic paradox', which suggests that the Nordic welfare model has been unsuccessful in reducing health inequalities between socioeconomic groups, and that these inequalities 'spill over' to affect the health-political engagement relationship as well **[26]**.

### **Implications for Policies**

What are the policy implications of these results? What can be done to reduce the health and disability gaps? An obvious solution would be to reduce health inequalities, although this is something that should be done regardless of gaps in political engagement between those who are healthy and those who are not. However, as the results from the Nordic countries show, this is not a straightforward task because policies aimed at promoting general levels of health in the population do not necessarily diminish political engagement gaps between health groups. Thus, we need to focus both on general levels of political activity (which are only partly related to health differences) and the between-group differences.

One way to help the situation is by promoting awareness of health gaps in political engagement, and especially by emphasising how the subdued voice of people with poor health may bias decision-making in favour of those in good health. This effort should entail increased cooperation with various health and disability advocacy groups and organisations. Public advocacy work would also benefit from more research on the matter. Currently, the biggest obstacle for high-quality research into health gaps is the lack of suitable data. To uncover the often complex and intermingled mechanisms between health issues, socioeconomic status, and political engagement, better data are needed. In practice, this kind of analysis requires longitudinal panel data that track people's situation in terms of health and political engagement over several years or even decades. Unfortunately, existing panel data projects are not very suitable for these purposes. There are some excellent survey panel projects that include good measures of health, but these only consider a very limited range of indicators of political engagement (e.g., the UK Household Longitudinal Study). Political panel survey projects have also provided good data following changes in political engagement, but typically they do not include good measures of health or disability (if any at all). Suitable data would also encourage researchers to apply rigorous research designs to unravel the causal effects that health and disabilities have on political engagement. Currently, too much of the research is based on designs, methods, or data that can only reveal correlations without really being able to test the causal mechanisms connecting health to political engagement.

Building new or modifying existing social institutions to increase the voice of those with health issues could also alleviate the situation. Nowadays, for example, countries such as Finland require that all municipalities have compulsory disability councils, which should be consulted in all matters that could have consequences for the situation of people with disabilities. Often, however, the influence of these kinds of mandatory bodies is limited, and more research is needed into how these kinds of institutional setups can actually have a greater influence on political decision-making. Furthermore, as recent developments in party research have emphasised the importance of intraparty democracy and inclusiveness **[27]**, a way to strengthen the voice of disadvantaged health groups could be to build similar 'councils' within parties that are ultimately responsible for political decisions affecting the lives of people with health issues.

Equality in elections is considered to be one of the cornerstones of democracy, so special attention needs to be given to inclusive voting practices **[28]**. Hence, it is not a surprise that voting accessibility has been on the agenda in many countries. Voting has been made easier with various facilitation arrangements put in place, such as advance voting, e-voting, postal voting, or proxy voting, but the results – in terms of encouraging turnout – vary and are not always as helpful as expected. Comparative results from Europe indicate that health gaps are not smaller in countries which have these kinds of voter facilitation practices; in fact, the situation seems to be quite the reverse **[29]**. The reason for this may be that when new measures are not directly targeted specifically at people with poor health (such as advance voting), these measures may motivate other voter groups even more than those with health issues. It is also possible that countries have begun to implement voter facilitation instruments because of concern over existing health gaps. There is also contrary evidence relating to useful reforms, which has helped to close the turnout gap, at least to some extent. In the US context, allowing voting by mail has increased the turnout among people with disabilities **[30]**. Furthermore, providing more polling stations closer to where people live might help, because increasing physical distance from polling stations decreases the likelihood of voting among people in poor health **[31]**.

### **Conclusion**

In conclusion, although health and disability gaps do not exist in all areas of political engagement, they do so in many areas, and it is a matter of concern that such a situation can lead to partial political disempowerment of people in poor health and people with disabilities. Overall, the results point to increased political disengagement and disappointment with politics amongst people with poor health, as well as to an increased willingness to engage in political protest behaviour and participate in politics in ways that bypass the traditional party-based system. Hence, measures attempting to bridge turnout gaps between health groups are particularly important. However, focusing on turnout alone will not ensure that the voice of these disadvantaged groups is heard in political decision-making. More efforts to raise awareness are required, along with research on this topic and a focus on building accessible public institutions, in order to achieve more inclusive democracy.

## **References**


#### LSE Public Policy Review Series

## **Wellbeing:** Alternative Policy Perspectives **Edited by** Timothy Besley (LSE) and Irene Bucelli (LSE)

Governments in liberal democracies pursue social welfare, but in many different ways. The wellbeing approach instead asks: Why not focus directly on increasing measured human happiness? Why not try to improve people's overall quality of life, as it is subjectively seen by citizens themselves?

Timothy Besley Irene Bucelli

Alternative Policy Perspectives

**WELLBEING** 

**Editors**

The radical implications of this stance include shifting attention to previously neglected areas (such as mental health and 'social infrastructure' services) and developing defensible measures of overall wellbeing or quality of life indicators. Can one 'master' concept of wellbeing work to create more holism in policy-making? Or should we stick with multiple metrics? These debates have been live in relation to an alternative 'capacities' approaches, and they are well-developed in health policymaking. Most recently, the connections between wellbeing and political participation have come into sharper focus.

Wellbeing remains a contested concept, one that can be interpreted and used differently, with consequences for how it is incorporated into policy decisions. By bringing together scholars from economics, psychology and behavioural science, philosophy and political science, the authors explore how different disciplinary approaches can contribute to the study of wellbeing and how this can shape policy priorities.