Trust: the foundation of health systems

Health Policy Series No. 58 http://eurohealthobservatory.who.int H ea lt h Po lic y S er ie s 58?? 60 ?? ?? This study looks at the critical role of trust within health systems, exploring its impact on healthcare quality, functionality, and health outcomes. Trust is foundational for patients to seek timely help, share information, and adhere to treatment plans. For the public, trust in the health system’s ability to provide care, act in their best interest, and adapt to changing needs is essential. Policymakers must trust that the resources they provide for health systems will be used well. This book stands out by integrating perspectives from philosophy, sociology, economics, psychology, and medicine. It is forward-looking, exploring how new health technologies, data privacy, and artificial intelligence impact trust. It emphasizes the need for transparency, accountability, and combating misinformation to build and protect trust. It calls for active engagement of a diverse range of stakeholders and fostering of collaboration if we are to maintain trust and address power imbalances. The study underscores trust’s role in health system transformation, stressing that effective, equitable care is impossible without it. It advocates for trustworthy leadership, based on transparency and communication and for better measurement and understanding of the dynamic nature of trust if we are to sustain the legitimacy and functionality of health systems. Discover why trust is the cornerstone of effective health systems in this important new assessment. Dive into the complexities of trust, its impact on healthcare quality, and the necessity for transparency and accountability. With insights from multiple disciplines, this book is a vital guide for anyone invested in the future of health care. The editors Martin McKee – European Observatory on Health Systems and Policies and London School of Hygiene & Tropical Medicine, London, United Kingdom May C. I. van Schalkwyk – Department of Health Services Research and Policy, London School of Hygiene & Tropical Medicine, London, United Kingdom Rachel Greenley – Department of Health Services Research and Policy, London School of Hygiene & Tropical Medicine, London, United Kingdom Govin Permanand – Division of Country Health Policies and Systems, WHO Regional Office for Europe, Copenhagen, Denmark Trust The foundation of health systems Martin McKee May C.I. van Schalkwyk Rachel Greenley Govin Permanand Cover_OBS_60_TRUST_02072024.qxp_Mise en page 1 02/07/2024 13:24 Page 1 Trust: the foundation of health systems The European Observatory on Health Systems and Policies is a partnership, hosted by WHO Regional Office for Europe, which includes other international organizations (the European Commission); national and regional governments (Austria, Belgium, Finland, Ireland, the Netherlands, Norway, Slovenia, Spain, Sweden, Switzerland, the United Kingdom and the Veneto Region of Italy (with Agenas)); other health system organizations (the French National Union of Health Insurance Funds (UNCAM), the Health Foundation); and academia (the London School of Economics and Political Science (LSE) and the London School of Hygiene & Tropical Medicine (LSHTM)). The Observatory has a secretariat in Brussels and it has hubs in London (at LSE and LSHTM) and at the Berlin University of Technology. Trust: the foundation of health systems Martin McKee European Observatory on Health Systems and Policies and London School of Hygiene & Tropical Medicine, London, United Kingdom May C. I. van Schalkwyk Department of Health Services Research and Policy, London School of Hygiene & Tropical Medicine, London, United Kingdom Rachel Greenley Department of Health Services Research and Policy, London School of Hygiene & Tropical Medicine, London, United Kingdom Govin Permanand Division of Country Health Policies and Systems, WHO Regional Office for Europe, Copenhagen, Denmark Keywords: HEALTH SYSTEM TRUST HEALTH CARE OUTCOMES PATIENT TRUST HEALTH WORKFORCE PUBLIC OPINION HEALTH SYSTEM TRANSFORMATION © World Health Organization 2024 (acting as the host organization for, and secretariat of, the European Observatory on Health Systems and Policies) Some rights reserved. This work is available under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 IGO licence (CC BY-NC-SA 3.0 IGO; https://creativecommons.org/licenses/by-nc-sa/3.0/igo). 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The views and opinions expressed in Observatory publications do not necessarily represent the official policy of the Participating Organizations. ISBN 9789289059992 (electronic version) ISBN 9789289059657 (print version) Printed in the United Kingdom. Contents Foreword vii List of figures and boxes ix Acknowledgements xi 1. Introduction 1 1.1 What is trust in the context of health systems? 1 1.2 Why health systems need to focus attention on trust if they are to transform in ways that respond to changing circumstances 4 2. Trust and health systems 11 2.1 The importance of trust in health systems 11 2.2 Social trust versus institutional trust 15 2.3 Trust of patients in the health system 17 2.4 Trust of health workers in the health system 19 2.5 Trust of politicians in the health system 20 2.6 Trust of politicians in the public 21 2.7 What are the threats to trust in health systems? 22 2.7.1 Misinformation and disinformation 23 2.7.2 Marginalization and discrimination 24 2.7.3 Lack of transparency 24 3. A cross-disciplinary perspective on trust and the relevance for health and health systems 27 3.1 Different disciplinary perspectives on trust in health systems 30 3.1.1 Philosophical perspectives 30 3.1.2 Sociological perspectives 34 3.1.3 Economic perspectives 35 3.1.4 Psychological perspectives 37 3.2 Taking a holistic view 39 4. Trust, technology, artificial intelligence, health and health systems 41 4.1 Trust in algorithms 41 4.2 Trust in information 44 Trust: the foundation of health systemsvi 4.3 Trust in data systems 45 5. Policy implications and future directions 47 5.1 Building and sustaining trust 48 5.2 Widening participation in policymaking and implementation 51 5.3 Focusing on trust as an opportunity 54 Appendix I: Measuring trust in European health systems 55 Measuring trust 55 Is trust in health systems measured in Europe? 56 References 47 Foreword vii Foreword As populations and their health needs change, so must the health care that is available to them. People accumulate more medical conditions as they age, which require ever more complex treatment. And the opportunities to treat them have expanded beyond anything that we could have imagined even a few decades ago. Yet many governments have struggled to achieve the transformations which are needed to meet the increased demand. How do we create the models of care that ensure that we have the right health workers, with the right skills and equipment, in the right place, at the right time? We can design these models of care on paper, but the challenge is to translate them into reality. When we ask why this challenge is so hard to meet, one answer comes up time and again. Unfortunately, too often, there is a lack of trust among all those involved. Patients need to trust that the new models of care will prioritize their needs and expectations. Health workers need to trust that the changes are going to make a positive difference. And politicians need to trust that the additional resources required will be used effectively. I was delighted that so many ministers and senior officials came together in Tallinn, Estonia, in December 2023 to discuss trust and transformation in health systems, and I am grateful to the Estonian government for hosting the meeting. This book is one of the main products of that meeting. Initially prepared as a discussion document, it provided a solid basis for the exchange of ideas and good practice that took place. Subsequently the authors incorporated the results of those discussions into this book, that stands out for bringing together the differing disciplinary perspectives on the concept of trust and their applications to health systems. I see this as an excellent example of how the WHO Regional Office for Europe and its partners in the European Observatory on Health Systems and Policies are pushing the boundaries of our thinking on health systems, preparing us for the challenges that we all face going forward. Dr Hans Henri P. Kluge Regional Director WHO Regional Office for Europe

List of figures and boxes ix List of figures and boxes Figures Fig. 1 Relations involving trust, health and health systems 6 Fig. 2 The necessary transformation 9 Fig. 3 Trust in institutions in selected countries, 2021 57 Fig. 4 Percentage of respondents saying it is likely that their personal data will be used for legitimate purposes 57 Fig. 5 Share of individuals who trust the health care system in their country to provide them with the best treatment in selected European countries in 2023 58 Fig. 6 Share of respondents who answered “a lot” to the question: “How much do you trust scientists in this country?” 59 Fig. 7 Share of respondents who answered “a lot” to the question: “How much do you trust doctors and nurses in this country?” 60 Boxes Box 1 What is trust? 2 Box 2 The trust game 37

Acknowledgements xi Acknowledgements We are grateful to Professor Steve Reicher for valuable advice on aspects of trust, to Natasha Azzopardi Muscat, Suszy Lessof and Josep Figueras for reviewing the text, to Andrew Rzepa from Gallup for providing data from the Wellcome Global Monitor Survey, to Jon Clifton, CEO of Gallup, for his advice and copies of his book Blind spot: the global rise of unhappiness and how leaders missed it; and to David Stuckler, Olivier Wouters and Rikard Rosenbacke for advice on trust and artificial intelligence. An initial version of this document served as an introductory review to the concepts of trust and health to inform the 12–13 December 2023 Tallinn Health Systems Conference, Trust and Transformation: Resilient and Sustainable Health Systems for the Future, where it was presented as a draft for consultation. This version includes feedback received from conference participants and a wider engagement with relevant literature. We are especially grateful to our peer reviewers, Stephen Reicher (University of St Andrews) and Margaret Kruk (Harvard University) for their valuable comments.

1. Introduction This book is concerned with the concept of trust as it is relevant to promoting the health of individuals and ensuring health systems that are trustworthy, fit for purpose and able to address current and future challenges. This introductory chapter provides a simple overview of what is meant by trust, the different ways we can conceptualize trust, and its role in human interactions and social practices. This overview provides a working understanding for the purposes of this book of the concept of trust from a health systems perspective. The book is intended to introduce the reader to the role and importance of trust in the optimal functioning of health systems and its intimate relationship with health system transformation. It does not purport to provide a definitive definition of trust, nor a comprehensive engagement with the literature, which is vast and spans centuries of scholarly thought and research, and encompasses varying cultural interpretations and applications. Based on the working understanding of trust outlined below, this chapter explores some of the key trust relationships that are core to functioning health systems, setting the scene for the following chapters which explore in greater detail what is known about these relationships. The book explores: how these relationships are studied; how different disciplines approach the theorization and empirical analysis of trust; what is known about levels of trust in health systems and their components; what builds or undermines trust; and what can be done to ensure trust is valued and given more attention in health policymaking and health system transformation. 1.1 What is trust in the context of health systems? Health systems are, at their heart, a means of organizing many sets of human relationships and interactions to achieve a goal: the health of the population that they serve. All human relationships are, at one level, transactional. One person exchanges something with another and gets something else back in return, for themselves or for others. In many cases, therefore, transactions between people are straightforward and easily verifiable. A customer visiting a shop exchanges money for a product. Customers often know what they want to buy and can judge whether they have Trust: the foundation of health systems2 received it and whether it is at a fair price. However, in all but the simplest cases, a transaction requires a degree of trust (Box 1). When buying food, can the customer trust that it has been prepared in conditions that prevent bacterial or toxin contamination? When buying a part for their car, can they trust that it has been manufactured in a way that will prevent it from failing and causing an collision or injury (Reynolds & McKee, 2010)? If they feel unable to trust the provider of these goods, then they will be reluctant to purchase from them. The concerns that may arise in any relationship can be addressed through trust and trustworthiness. A consumer can trust the provider, believing that people are fundamentally honest or, at least, bound by the wish to create and maintain a reputation for acting honestly. Alternatively, regulation can seek to impose quality control systems along the supply chain and to ensure that standards are upheld, with sanctions for failures, although customers know that unscrupulous providers can often get around these measures. With or without regulation, providers often Box 1 What is trust? There is no universally agreed definition of trust. However, a widely used conceptualization sees trust as the belief that an object of trust (which can be a person or institution) will act in ways that produce positive outcomes, even if one cannot ensure it (Easton, 1975). It relates to vulnerability. A person demonstrates trust when they are willing to make themselves vulnerable, expecting that something good will be done by the object of trust, a person or institution that could also do them harm. Thus, trust is seen as an acceptance of some risk when faced with uncertain outcomes (Citrin & Stoker, 2018). Trust is usually relational in that “A trusts B to do X” (Hardin, 2002), although it is also possible to have general trust that is not linked to a specific action but rather the belief that the object of trust will do the right thing whatever it is (Nannestad, 2008). Trust is related to but different from reliance. Faulkner & Simpson cite the example that one may rely on one’s car to start but not trust it to do so, as that would imply that the car had one’s best interests at heart (Faulkner & Simpson, 2017). This is not limited to inanimate objects. Hardin cites the example of the philosopher Immanuel Kant, whose neighbours could rely upon him to walk past their windows at eight each morning (Hardin, 2002). However, as Kant did not do so for the benefit of those neighbours, they had no reason to trust him. Similarly, though again without necessarily implying positive intent, trust can be seen as “an attitude one takes towards the trustworthiness of another”; that is, believing that they, whether person or institution, will do what they say they will do (O’Hara, 2012). But it is by returning to the variable of positive intent that Hardin (2006) provides a simple description of trust that is useful for illuminating why it is so integral to health systems functioning and the provision of care: “To say we trust you means we believe you have the right intentions towards us and that you are competent to do what we trust you to do”. Chapter 3 explores different disciplinary concepts of trust in more detail. Introduction 3 take measures to develop and maintain public trust, not least as a means to achieve a competitive advantage because they recognize that trust has a value. Health is not a simple commodity, even if it has been commodified in many settings. As such, the transactional and trust relationship between parties around health and health care is somewhat less straightforward than in other spheres. At its simplest, a patient gives a health worker information about their health condition (and money sometimes directly or through their taxes) and (hopefully) receives, in return, a diagnosis and a plan of treatment. A health manager provides a salary to that health worker in return for their expertise and the provision of care to the patients attending the facility for which they are responsible. A policymaker may invest money into a particular policy direction or health project (such as a new hospital), expecting patients and health workers to play their part in implementing that policy in ways that bring about positive outcomes, or for that hospital to deliver quality care. Nevertheless the challenges around trust are especially great in health care. First, there is a major asymmetry in the knowledge held by the two parties to the transaction (Arrow, 1978). The health worker will often be much better informed about the nature and severity of the range of conditions that the patient presents with and the treatments that can be provided. This means that the patient must trust the health worker and the treatment they receive. As with all products and services, they can also look to the many safeguards that health systems have put in place, such as those that specify which qualifications the health worker should possess and whether they have taken measures to keep up to date with emerging knowledge. The patient will wish to be reassured that the services they are given are evidence-based and that the medicines they are prescribed are safe and not counterfeit or otherwise unsafe (Attaran et al., 2012). In turn, their trust has a value to care providers, because when patients trust the health system, they are more likely to follow the guidance given. The health manager too is in a trust-based relationship with the health workers given their lack of direct involvement in the provision of the care they are paying for through salaries. And policymakers, meanwhile, often have no expertise relevant to health care and no way of verifying that their policy decisions will have the desired impact. Indeed, these impacts, whether positive or negative, are only likely to manifest at a much later stage, often well after the individual has moved on. Finally, it is important to note that while trust in the health worker and in the health system must be earned and maintained over time, it is easily lost. The COVID-19 pandemic provides a case in point where numerous surveys indicated a precipitous loss of trust among the general public in countries across the world. In some cases, individuals or organizations may even be motivated to undermine that trust, such as for commercial or political gain (McKee et al., 2024b). Trust: the foundation of health systems4 Trustworthiness is a key characteristic of a well-performing health system, built up over time, but it should not be assumed. Sometimes mistrust of the health system is well placed and helps to expose systems that are unsafe, prejudiced and lacking in appropriate governance and resources. As the Socratic tradition suggests, asking questions and not blindly conferring trust or trustworthiness is crucial for the improvement or advancement of society. 1.2 Why health systems need to focus attention on trust if they are to transform in ways that respond to changing circumstances Originally conceived as a working document to inform a World Health Organization (WHO) European Region conference held in December 2023 on the themes of trust and transformation in health systems (Kluge et al., 2023; World Health Organization, 2023), this book takes as its starting point the experience of the COVID-19 pandemic and, in particular, the insights gained from the evidence reviewed for the report of the Pan-European Commission on Health and Sustainable Development (the Monti Report) (McKee, 2021). Our focus, therefore, is primarily on the WHO European Region with most examples and literature drawn from Europe, with additional references and examples from other countries where relevant. The COVID-19 pandemic underscored the need for health systems everywhere to adapt and evolve to changing realities. Not only do they need to be able to respond to new issues, but they must also embrace a wider scope than the primarily medicalized model they have traditionally been based on. Health security, emergency preparedness and resilience are now part of the health system vocabulary. Individual and population health and well-being are increasingly part of their remit. This requires new ways of delivering care, as well new approaches to the design and implementation of policies. As the conference highlighted, co-creation by three key stakeholder groups in particular – individuals and patients, health and care workers, and policymakers – is central to this new vision of health systems (WHO Regional Office for Europe, 2023) and is the focus of our discussion here. Health systems in the European Region responded to COVID-19 in different ways and achieved different outcomes. Some were able to use the pandemic as an opportunity and a springboard for adopting new ways of working, especially at primary care level (Kumpunen et al., 2022), often taking advantage of technological advances that accelerated during the pandemic, such as rapid diagnostics and innovative means of online engagement (Green et al., 2022). Health workers developed new roles and individuals took on more responsibility for their own health, facilitated by digital communication such as remote sensing Introduction 5 using wearables or near-patient testing, as exemplified in the development of the lateral flow tests that transformed management of the pandemic. But some countries also struggled and continue to struggle, unable to rebuild workforces already depleted by underinvestment, and with the additional burden of burnout and illness, including long COVID (Rajan et al., 2021). This situation, in part, reflects and exacerbates a crisis of trust. Indeed, none of the positive examples will succeed in benefitting people, far less in an equitable way, if those involved lack trust in these new measures and innovations, in the motive behind their design and adoption, and in each other. This is apparent in a series of critical relationships between patients, health care workers and politicians set out in Fig. 1. In this book we do not seek to capture all the relationships that underpin health systems and require trust. Rather, we focus on these three stakeholder groups and use examples to illustrate the importance of trust and its role in enabling health system transformation (the dark arrows in Fig. 1). There are other relationships, such as the trust of the public and health workers in politicians, with health worker strikes an example of where the latter has broken down (Weil et al., 2013). We do not ignore their importance, or the role of issues such as inadequate pay and poor conditions in undermining trust, but the specifics of these largely fall outside the scope of this book (the lighter arrows in Fig. 1). Indeed, no single publication can aim to capture or examine the multitude of trusting relationships that contribute to the protection, promotion and provision of health. What we are seeing, especially in the post-COVID-19 context, is that trust is a diminishing feature of, and in, the relationships depicted in Fig. 1. First, there is a loss of trust among the public that the health system will be there when they need it. In some countries, people are struggling to access care due to overcrowded health facilities, long waiting lists, insufficient health worker numbers, and substantial out-of-pocket payments, with evidence that this is leading to avoidable deaths (Jones et al., 2022). The People’s Voice Survey, a novel population survey that gathers data from 15 low-income, middle-income and high-income countries globally, estimated that less than 50% of respondents experience health security (that is, a judgement that the health system can meet one’s care needs and that that care is affordable). Only a quarter were supportive of their current health system, assessing it as functioning well and requiring no major reform (Kruk et al., 2024). The lowest support was measured among respondents in Peru, the United Kingdom and Greece, the latter two being Member States of the WHO European Region. People’s experiences leave them vulnerable to the arguments by some that universal health coverage, to which governments have committed in the United Nations’ Sustainable Development Goals and a dedicated United Nations General Assembly resolution, is somehow unaffordable or unsustainable, which exacerbates the sense that people cannot rely on their health system. Trust: the foundation of health systems6 Fig. 1 Relations involving trust, health and health systems Politicians and political institutions Public and patients Health workers HEALTH SYSTEMS Staff retention Solidarity Return on investm ent Trust in the people Trust in politiciansTru st in po lit ici an s Tru st in he alt h w or ke rs Note: Dark areas represent the relationships examined in this book. Lighter arrows represent other important relationships for health and health systems. Source: Authors’ compilation Loss of trust has been further fuelled during and since the COVID-19 pandemic by a discourse that attacks health workers and health systems, typically from those opposed to the measures that were necessary to interrupt transmission of SARS-CoV-2 (van Stekelenburg et al., 2022). This has been facilitated by the use of social media to spread disinformation seeking to undermine trust in science and the health workers who use this science to inform the delivery of evidence- based care (Wang et al., 2022). Moreover, an increasing distrust of the so-called establishment or elite has emerged in recent times, exacerbated by the pandemic, but often fuelled by politicians seeking to create a divide between “them” and “us”. A growing populist agenda in many countries, in Europe as well as globally, has seen the medical establishment (and “experts”) cast as part of “them”, with health now part of partisan politicking. If the public is to regain and retain trust in science, in the health community and in the health system, they must be confident that the system can meet their needs now and in the future. This is not a given. In the context of the European Union and the June 2024 European elections, for example, citizens have deemed public health their second most important issue (after the fight against poverty and exclusion) (European Union, 2024). This underscores just how important trust is to achieving the necessary transformations required to address these challenges. Introduction 7 Second, there is a loss of trust among health workers, who often work in difficult conditions and may feel uncared for by their employers and those setting health system policy. Many are exhausted and demoralized and have seen too many colleagues become severely ill or die, especially in the context of COVID-19. They feel neglected, leading some to look to other countries that offer improved conditions, while others reassess their work-life balance, a process that can lead them to leave the health workforce prematurely and often suddenly. The rise in partisan politics and othering of health and care professionals in many settings also contributes to an increasingly fragile health workforce (WHO Regional Office for Europe, 2022). These factors soon create a vicious cycle as the work still has to be done by a now depleted workforce which in turn leads to the loss of more staff. If they are to stay, health and care professionals will need confidence that their working conditions can improve in ways that reflect their changing needs and enable them to deliver their desired level of care to those they are responsible for. All health care workers need to feel valued and trusted and must themselves be able to trust the health system and those taking decisions at a policy level. Third, there is a loss of trust among politicians at all levels of government in the ability of health systems: to transform in ways that respond to the changing health needs of the population, particularly in the context of emerging and concurrent crises; to adapt to new opportunities to intervene, in particular digital innovations; and to meet increasing public expectations. Without this trust, politicians are understandably reluctant to make the case for the investments that are needed to address and overcome the challenges ahead. This also applies across different arms of the executive, with finance decision-makers perhaps reluctant to free up resources for their health counterparts to use for the health system, not trusting that it will be well used or provide a measurable return. The rise of populist politics and political leaders represents a threat from within, as many directly undermine trust in health and health systems, and actively look to cut public funds rather than invest in the transformation agenda required to strengthen health systems. The growing influence of private providers in many settings, often offering a lower standard of care and delivering worse health outcomes (Goodair & Reeves, 2024), in turn only serves to further diminish the trust of the public in the health system and in science (not to mention in policymakers and the political process as well). Fourth, the COVID-19 pandemic highlighted another relationship of trust, that of politicians in the public. In a crisis, people may be asked to surrender some liberties. But can they be trusted to do so without punitive sanctions? During the pandemic, many governments doubted that the public could be trusted in this way. But, as will be discussed, the evidence is somewhat more encouraging and suggests that there is scope for more co-production of health and of health system transformation. This is particularly relevant given the urgent need to Trust: the foundation of health systems8 mount effective responses to climate change, which will require mass behaviour change among populations and substantial health systems transformation (Marteau et al., 2021; Romanello et al., 2022). None of these issues is new (even if the last has only started to be discussed recently). The problems associated with them have been building up for many years, but a combination of developments means that these problems can no longer be ignored. This is because health systems need to change to meet both existing and upcoming challenges (and be prepared for unforeseen crises) and, we argue, they will only be able to do so if all those who must work together to bring about this transformation can trust each other. Some of the challenges include: ageing of populations; a reduction in potential recruits to the health workforce and increasing numbers of older people with complex health needs requiring their care; geopolitical developments that fuel inflation and disrupt supply chains, adding to the pressures on health systems; advances in areas such as artificial intelligence; and problems of governance in health and other sectors in many countries. There are many others, not least of which is climate change, as previously mentioned. Although this book cannot examine the nature of the transformation needed in any detail, it is important to briefly outline the overall vision given how central trust is to its development. The health system of the future must be truly person- centred, engaging with the public, health workers and politicians in policy and system design as well as in transactional health interactions. It must take account of how clinical work and the promotion and protection of public health are becoming ever more complex, with the changing nature of disease and growth of multimorbidity. Health care itself is also becoming more complex, with multidisciplinary teams bridging home and hospital, and bed and laboratory bench. It must recognize the unprecedented environmental challenges, to which health care is a major contributor. In this situation, the task can be put simply as being to support those delivering and receiving care to ensure that the right mix of health workers, with the right skills and technology (including medicines), are in the right facilities, in the right place, at the right time to meet the needs of the (potential) patient or population (Fig. 2). However, all change is unsettling. It disrupts relationships and hierarchies. Consequently, it will only be achieved if it is based on trusted relationships among the public, health professionals and politicians (Gille, 2023). Introduction 9 Fig. 2 The necessary transformation INCLUDE Tackle social determinants to reduce demand for care Empower patients, maximizing digital potential INNOVATE To build flexible systems To integrate technology INVEST In people: recruiting, retaining and reinvigorating In capital: making best use of technology and flexible facilities The right people (health workers, expert patients), with the right skills (task shifting), in the right place, at the right time (responding to patient need) Source: Authors’ compilation * * * Based on Fig. 2, this book asks a series of questions. Why is trust important for health systems, and how does it impact their functioning? How do different types of trust and specific trust relationships affect the health system? How can different disciplinary perspectives enhance our understanding of trust in health systems? How does trust interact with technology, artificial intelligence and data systems in health systems? What are the policy implications for building and sustaining trust in health systems, and what future directions should be considered? It then concludes with reflections on policy implications and future directions.

2. Trust and health systems There are many elaborations around the importance of trust in the sphere of health and health care, although trust itself is often described as poorly defined and vague given differing interpretations and underlying theoretical logic and assumptions. However, as it is important for the purposes of this book to make this more concrete and provide a way of engaging with the concept of trust, we adopt the view here that trust in the health system is an indispensable cornerstone that upholds the foundations of effective health care functioning (Beller et al., 2022; Gille, 2023). Trust creates the intricate web of relationships within the health care ecosystem, from the bond between clinicians and patients, through the cohesion within clinical teams, to the transparent communication between the health system and the public. As noted in Fig. 1, it is equally important in the relationship between the health and care workers and policymakers. In the evidence we assemble and discuss below, its importance resonates profoundly in myriad ways. Building on the concepts and relationships presented in the introduction, the following sections in this chapter examine: the importance of trust in health systems; types of trust (social versus institutional); what is known about trust relationships which are important for health system functioning (recalling Fig.1, between patients, health workers and politicians); and evidence on what builds or erodes trust. 2.1 The importance of trust in health systems Trust plays a pivotal role in the functioning, effectiveness and sustainability of health systems. Trust is integral to meaningful and beneficial relationships between patients and their clinicians and more broadly between the public and their health system. Trust is key to building health systems that foster public participation and legitimacy. These are essential for better health outcomes (Gille, 2023). Serving as a catalyst for social cohesion, trust underpins cooperation and the equitable sharing of resources within societies. Trust instils confidence among individuals, promoting a sense of unity and a collective commitment to the well-being of all. Moreover, trust is necessary if economies are to succeed in generating the necessary resources to support health care systems and if the public is willing to provide these resources, through their taxes and other contributions (Dann, 2022). Trust: the foundation of health systems12 Collaboration and teamwork thrive in environments characterized by high levels of trust, laying the foundation for robust health care infrastructure. Innovative solutions to emerging challenges often involve task-shifting, with health workers developing new roles, facilitated by technological advances, such as digital communication and remote sensing using wearables or near-patient testing. However, none of these can succeed if those involved lack trust in them and each other. This aspect becomes even more critical in today’s increasingly digital and interconnected world, where strong and trusted institutions are essential safeguards against exploitation. Government policies on health govern the allocation of resources, regulation of health care providers, and the overall structure of health care delivery. For these policies to be effective and accepted by society, they must command the trust of many stakeholders, including a diverse range of politicians, health care providers and the general public. When individuals and communities trust their health system, they are more likely to engage with health care services and adhere to public health recommendations, ultimately leading to better health outcomes. Health care providers, such as physicians and nurses, must also trust the policies and regulations governing their practice. Trust in these regulations fosters a conducive environment for health care professionals to deliver care effectively, knowing that their actions align with established standards and guidelines. As noted earlier, the delivery of such care must continue to transform. A health system that fosters trust among the public and political leaders must be able to show that it can do so. It must demonstrate that it can respond to the changing needs of patients, while anticipating the challenges posed by unfolding crises and novel threats. Effective transformation is thus core to maintaining trust that a health system will be there when needed and will provide quality and equitable care now and into the future. However, transformation involves change, vision and risk, and the public and health workers need to have trust that such transformation is being undertaken with the core aim of protecting and promoting the public’s interest. Successful transformation is only possible with trust, and trust can only be earned by involving and listening to those who are being asked to give their trust. This will involve listening, especially, to marginalized and underserved groups and those whose voice and role within the health system has historically been undervalued. It will involve transformation of engrained hierarchies, challenging deeply held assumptions and addressing practices that have eroded the trust of some groups, defined for example by their gender, ethnicity, diagnosis, or social situation. Only then can trust among everyone be fostered and retained. Without trust health systems cannot transform in a positive way, and without transformation that benefits all, they cannot garner trust or remain trustworthy. Trust and health systems 13 Perhaps the most widely studied example of the importance of trust in health systems is its role in the establishment of effective vaccination programmes (Badur et al., 2020). In countries where there is a high level of trust in the health care system, vaccine uptake rates tend to be higher. For instance, Denmark (Nielsen & Lindvall, 2021) and Finland (OECD, 2021) consistently report high levels of trust in their health care systems and also have robust vaccination rates and successful control of vaccine-preventable diseases. In contrast, countries with low levels of trust experience vaccine hesitancy and lower vaccination rates. These were not explained by barriers to access as seen in some eastern European regions during the COVID-19 pandemic (Beller et al., 2022). Recalling the point above about actively engaging with and listening to minority groups, a systematic review of COVID-19 vaccine hesitancy in ethnic minority groups found the main challenges related to institutional mistrust, lack of confidence in the vaccine and its development process, and lack of reliable information or messengers (Shearn & Krockow, 2023). It was not only with regard to vaccination that the COVID-19 pandemic brought trust to the forefront. A meta-analysis of 67 studies found that most COVID-related outcomes were associated with trust, but it also mattered who was being trusted (Devine et al., 2023). In general, trust in health authorities was associated with greater vaccine uptake while trust in government was associated with greater adherence to measures such as mobility restrictions. The PsyCorona study, using data from 23 countries, found that higher trust in government about COVID-19 was significantly associated with greater adoption of a range of positive health behaviours, including handwashing, avoiding crowded spaces, and self-quarantine (Han et al., 2023). A study from the United States found trust in government sources of information was associated with greater knowledge about COVID-19 and greater adherence to social distancing, while trust in social media was negatively associated with both (Fridman et al., 2020). A European study found a positive association between political trust and reductions in mobility during the first COVID-19 lockdowns (Bargain & Aminjonov, 2020) and another found that trust in institutions led to a greater willingness to follow societal restrictions (Lalot et al., 2020). Other studies, such as one using data on incidence and mortality from the European Centre for Disease Prevention and Control, found higher trust to be associated with lower COVID-19 incidence and mortality (Farzanegan & Hofmann, 2022). A study comparing Canada, Denmark and the United States concluded that trust in government was more important than resources in terms of vaccine uptake and adherence to protective measures (Falkenbach & Willison, 2022). These findings are supported by other research by Lenton et al. (2022), showing that resilience to COVID-19, measured as the rate of decline from the initial peak, correlated with levels of trust in other people in a study of over 150 countries. A paper by Sulik at al. Trust: the foundation of health systems14 (2021) found a correlation between trust in science and adherence to rules on social distancing. More detailed analyses such as by Costa-Font and Vilaplana- Prieto (2023), looking at 28 European countries, found that persons living in areas that suffered high rates of relative COVID-19 mortality during the first wave of the pandemic increased both their trust in the health system and their compliance with pandemic restrictions. However, this was not the case among younger persons. Older persons, they note, were the ones primarily affected in health terms, and had a higher ease of compliance with restrictions than younger persons. While the authors do not examine in detail younger persons’ motivations or behaviours, they note the differential impact of COVID-19 restrictions by age group. But younger people’s lower trust and rate of compliance may also have been related to how and where they sourced their information, the nature of that information, and so-called ‘pandemic fatigue’ (see Section 2.3 below). Taking this evidence together, one group of authors has argued that high trust in government contributed to success in reducing the spread of COVID-19 during the pandemic. They concluded that: “perhaps this pandemic can be a catalyst for the societal reforms needed to earn and nurture public confidence and social solidarity. COVID-19 has shown that the democracies that can mobilize public trust are best placed to survive and thrive even in the face of great adversity” (Bollyky et al., 2022). But as the differential in trust between age cohorts indicates, understanding how to tailor those reforms will be an important challenge. Beyond the pandemic, trust also plays a critical role in health policy implementation. Policies aimed at improving public health, such as smoking cessation (Lindström et al., 2000), programmes to tackle the harm caused by gambling (van Schalkwyk et al., 2021), or campaigns to combat infectious diseases, rely heavily on public cooperation. When individuals trust that these policies (or their authors) are guided by their best interests and are implemented transparently and fairly, they are more likely to support and adhere to them. Conversely, in settings where trust in the health care system is low, adherence may be undermined, hindering the achievement of the intended goals. Trust in health systems also reflects resource allocation and equitable access to health care services. In countries where there is a high level of trust in the government’s ability to distribute resources fairly, health care resources are more likely to be allocated in an equitable manner. For example, in the Nordic countries, there is both more equal access to health care services regardless of socioeconomic status (Baroudi et al., 2022) and high trust in public institutions. In contrast, regions with low trust experience disparities in health care access and outcomes. Beyond individual well-being the erosion of trust can damage public willingness to uphold the principle of solidarity, which is foundational to many health care Trust and health systems 15 systems, particularly in Europe. Trust in the health care system is essential to maintain the social contract that underpins these systems. Bor and colleagues (2023) report findings from a series of surveys that tracked public opinion throughout 2020, the first year of the COVID-19 pandemic, in four countries: the United States, Denmark, Hungary and Italy. This, it will be recalled, was a time when politicians were calling on the public to trust them when they asked for unprecedented sacrifices in terms of personal freedom to go about daily activities. The findings were complex, but the headline result is that social solidarity remained remarkably similar when they compared their findings with those from surveys conducted prior to the pandemic. However, there were some differences in the detailed findings. There were decreases in tolerance towards immigrants among Danes and Americans, but these negative changes were counterbalanced by smaller movements in the opposite direction in some other variables and in support for redistribution among Americans. By April 2020, social solidarity had slightly increased in Hungary and Italy and decreased in Denmark and the United States, but there was no evidence that social solidarity had been eroding throughout 2020. This study makes two other important contributions. First, due to its panel design following the same people over time, it suggested that some previously described associations from cross-sectional studies were artefacts. Second, it found an association between individual levels of anomie (or a sense of meaninglessness) and extreme discontent, a finding that could have longer term political consequences. Further work by some of the same researchers in a larger group of countries linked the discontent that is associated with what they describe as “pandemic fatigue” to support for protests and conspiratorial thinking (Jørgensen et al., 2022). Finally, measures that increase trust in health systems have spillover effects. Research from low- and middle-income countries has shown that having trusted, well performing health care systems that provide equitable, quality care is associated with increased trust in government. That is, among the populations surveyed, indicators of well performing health systems – specifically higher technical quality of health services, more responsive service delivery, greater fairness, improved health outcomes, and financial risk protection – were associated with a 13 percentage point increase in the probability of expressing trust in government (Rockers et al., 2012). This should be an important consideration for politicians seeking re-election, beyond any wider benefits to society. 2.2 Social trust versus institutional trust It is important to differentiate between social and institutional trust. Social trust reflects an optimistic perspective on the world and encourages interactions Trust: the foundation of health systems16 among strangers, predicated on the belief that they are sincere and do not set out to harm you. Institutional trust is characterized by the expectation that, in general, governmental authorities, law enforcement and public institutions act in the best interests of the community. Trust in institutions is not unconditional. Researchers have tested a series of hypotheses about how institutional trust develops (Mishler & Rose, 1997). Institutional theories see trust as driven by the characteristics of those institutions as they are viewed by individuals, while cultural theories see trust in institutions as an extension of each individual’s general trust in society, often learned when young and subsequently projected onto the institutions they interact with. These can be divided into macro and micro level theories. Macro-cultural theories emphasize the role of national culture in shaping trust. Micro-cultural theories consider how each person’s trust has been shaped by their previous experiences. Macro- institutional theories base trust on the overall ability of institutions to perform, while micro-institutional theories base it on the sum of personal experiences. The political transitions in eastern European and central Asian countries in recent decades provide a rich source of data for research using multilevel models. The results support the micro level theories, finding marked variations in institutional trust according to individual characteristics, but also some support for macro- institutional theories, specifically in an inverse association between trust and perceived levels of corruption (McKee et al., 2013). Trust in institutions is readily damaged. Surveys by Transparency International find that the health sector is viewed as among the most corrupt in many countries (Hutchinson et al., 2019), with corrupt practices taking a variety of forms including informal payments and unauthorized absences and procurement. Widespread abuses in several countries during the COVID-19 pandemic undermined confidence (García-Altés et al., 2023). Trust also plays a crucial role in ensuring adherence to societal norms, regulations and rules within health care systems. Individuals are more likely to comply with prescribed medical procedures and protocols when they have confidence in the institutions overseeing their care. However, it too is easily lost. A well publicized breach of COVID-19 regulations by a senior figure in the United Kingdom was associated with a marked fall in confidence in the government’s ability to handle the pandemic (Fancourt et al., 2020). Trust also fosters an atmosphere of innovation, where individuals feel secure in taking calculated risks to drive improvements in health care practices and outcomes. This emphasizes the importance of trust for any health system transformation agenda which inevitably involves uncertainty and some level of risk-taking. Additionally, communities with high levels of trust are better equipped to respond effectively to crises, resulting in faster recovery and greater Trust and health systems 17 resilience. In essence, trust in health systems is not merely a desirable attribute but a fundamental pillar upon which the success and resilience of health systems rest. In many countries, institutional trust has experienced a noticeable decline over recent decades despite objective improvements in public services, although there have been some exceptions, with increases in the early 2000s in some former Soviet countries (McKee et al., 2013). Also called the delivery paradox, this phenomenon of a decline in trust while services are improving challenges the conventional belief that improving the quality and efficiency of public services inevitably leads to increased trust in the institutions delivering them. Several factors contribute to this paradox. Improved services result in rising expectations, making citizens more critical of institutions that fail to meet higher standards, and potentially eroding trust. Complex and opaque bureaucracies can hinder accountability, leading to perceptions of inefficiency and corruption. Historical failures, external influences on public opinion, diverse societal priorities, and a gap between expectations and outcomes further complicate trust-building efforts. Addressing this paradox necessitates a multifaceted approach, including measures to increase transparency, accountability and public engagement, alongside management of evolving expectations. This is discussed in a later section on building and maintaining trust in health systems. At its most basic, the delivery paradox underscores the need for institutions to not only enhance services but also cultivate a model of trust inspired by social collaboration. This model recognizes citizens as active partners in the relationship, respecting their competence and agency, particularly in matters such as health management, where individuals are increasingly informed and discerning. 2.3 Trust of patients in the health system The relationship between clinicians and patients lies at the heart of the health system, and trust is its bedrock (Goold, 2001). Patients entrust their well-being to the hands of health care professionals. In return, clinicians rely on patients to provide accurate information about their health and circumstances. This mutual trust is pivotal; without it, the efficacy of medical treatments and the quality of care diminish significantly. Trust has been linked to treatment adherence and predicts continuity of care (Thom et al., 2004). Trust enables patients to confide in their health care providers, sharing their symptoms, concerns and fears openly, which is crucial for accurate diagnoses and effective treatment plans (Mechanic & Meyer, 2000). Trust is a reciprocal process and fosters mutual understanding and empathy (Hojat et al., 2013), two indispensable components for building deeper and more meaningful relationships within the health care system. Clinicians who trust Trust: the foundation of health systems18 their patients are better equipped to understand their unique needs, preferences and values (Street et al., 2009). This empathy facilitates patient-centred care (Eklund et al., 2019; Kwame & Petrucka, 2021), where health care decisions are made with consideration for the individual patient’s circumstances, promoting both a higher quality of care and patient satisfaction (Walsh et al., 2019). Trust also encourages individuals to seek medical care promptly, preventing conditions from deteriorating. When patients trust the health care system and their health care providers, they are more likely to act proactively to address their health concerns, leading to earlier intervention and better outcomes. Trust also profoundly impacts the patient experience. Positive encounters built on trust enhance patients’ experiences, making them feel heard, respected and cared for. This in turn contributes to one of the primary objectives of health systems: responsiveness to patients’ needs and expectations (World Health Organization, 2000). Trust in the health care system is thus not a luxury but a necessity and underpins all of the building blocks of health systems. Trust elevates the quality of care, enhances patient outcomes and ultimately underpins the very essence of health care itself: the well-being of patients (Berger-Schmitt, 2002). Trust takes time and investment to build and maintain, and the eliciting of trust must be warranted by ensuring that health systems are trustworthy. Trust is also key during times of crisis. As Cairney and Wellstead (2021) point out in their work on developments during the COVID-19 pandemic in the United Kingdom and the United States, in a pandemic “people need to trust experts to help them understand and respond to the problem, governments to coordinate policy instruments and make choices about levels of coercion, and citizens as they cooperate to minimize infection” (emphasis in original). The authors document important dynamics in and influences on trust, demonstrating the need for nuanced approaches to understanding the role of trust and distrust during times of crisis. They explain that: In the UK, ministers invested high trust in their closest science advisors. However, the development of trust via regular interaction between a small group of people in an insulated environment produced unintended consequences in relation to distrust of expert outsiders, which undermined useful challenges to key mistakes. (Cairney & Wellstead, 2021) A lack of reliance on science at the federal level in the United States led to fragmented policy responses, with individual states then tending to lead on responses, many of which were not consistent with those of other states. The trust that both governments displayed towards the public differed and changed during the pandemic, with a shift to stricter government intervention and away from Trust and health systems 19 trust based approaches. The relationship between public trust in government and health behaviour is not straightforward and varies by context, personal beliefs, motivators and political alliances, and wider embedded cultural norms and values. Thus, public trust or distrust in government, while important, is not a straightforward predictor of public behaviour. However, what is clear is that any explanation of the role of trust during the COVID-19 pandemic is incomplete without considering the types of trust (individual, institutional, societal) and the political system context, if lessons are to be learned (Cairney & Wellstead, 2021). Finally, mention must be made of the particular importance of securing and maintaining the trust of young people during crises (Aksoy et al., 2022), given how trust built or lost during youth persists into adulthood. The mishandling of health and other crises can fuel the erosion of young people’s trust in politicians and their decisions for years after the event (Aksoy et al., 2022). The same appears true of science, where a study of young people’s experience of COVID-19 across 138 countries revealed a loss of trust in science more generally (Eichengreen et al., 2021). At the same time, a study of younger persons in the United Kingdom and the United States found that trust in government leaders played a critical role in COVID-19 public health messaging for adolescents. Both the British prime minister (Boris Johnson) and the American president (Donald Trump) displayed distrust of the COVID-19 science. As a result, despite access to traditional sources of information about the pandemic, those who placed their trust in these leaders were less likely to accept the science around COVID-19 (Mathews et al., 2021). Thus, trust building activities must take into account the unique needs of young people, including a better understanding of the ways in which they access, consume and understand science and health information. Such activities must create effective mechanisms to engage meaningfully with young people. This is of particular relevance given that young people today are going to be called upon repeatedly to respond to crises such as climate change and other environmental threats progress. 2.4 Trust of health workers in the health system Workforce shortages, driven substantially by failures to retain skilled staff, are already among the greatest threats to the sustainability of European health systems (Zapata et al., 2023). If these health workers are to stay, they need: fair incomes, reflecting what they could earn in other sectors; supportive working environments, such as well designed facilities and access to technology; equitable and safe working conditions, free from discrimination, bullying and other forms of mistreatment; and opportunities to progress in their careers. More than that, they must trust that the health system cares about them and will provide these conditions in the long term. Regrettably, some or all of these conditions are Trust: the foundation of health systems20 lacking in many health systems, as is the trust that the system will address the gaps in provision. The consequence is that health workers leave health systems, take early retirement, seek other ways to use their skills, such as in information technology, or emigrate to countries offering better conditions. Thus, one in three medical students in the United Kingdom does not intend to remain in its National Health Service (Ferreira et al., 2023), with so-called brain drain an increasing problem for many countries in Europe and globally (WHO Regional Office for Europe, 2022). The situation has been exacerbated by the experience of the COVID-19 pandemic. Burnout and moral injury (the term most often used in military parlance where an individual experiences psychological trauma because of their inability to help others) were widespread in the United Kingdom (Williamson et al., 2023). This situation was not helped by shortages of essential personal protective equipment, coupled with widespread accounts of procurement scandals and profiteering that prevented the equipment being delivered (McKee, 2020). This loss of trust (and health system trustworthiness) has consequences that go beyond retention of health workers. It is seen in the breakdown of relations between health workers and governments that has contributed to strikes in some countries (Deakin, 2023). Strikes by health workers are normally extremely rare and should be seen as a signal that there is a major problem in the health system necessitating decisive action (Weil et al., 2013). This loss of trust also creates a reluctance by health workers to innovate and thus take forward the transformations that are needed to strengthen health systems and ensure their sustainability. 2.5 Trust of politicians in the health system Health systems will only be able to transform to meet changing needs and expectations and to foster trust if they receive adequate investment and are enabled to use these investments effectively to provide quality and equitable care. This is often dependent on politicians making the necessary resources available. Yet they will only do so if they trust the health system to use those resources wisely. Without this trust, politicians will understandably be reluctant to make the case for the investments in health and health systems that are needed to address and overcome the challenges ahead. Addressing this lack of trust has two aspects. The first involves providing reassurance that the resources are indeed being used appropriately, for example by having robust health technology assessment systems and systems for assessing overall health system functioning. The second is to challenge the frequent characterization of all forms of variation in the use of resources as waste. Some Trust and health systems 21 variations may be legitimate, as when facilities serving disadvantaged populations must do more to address the health consequences of failings in other sectors (although more often these populations are actually underserved in relation to need, illustrating what is termed the inverse care law [Tudor Hart, 1971]). Some variations may also reflect a failure to recognize the necessity of a degree of redundancy in a system in case of emergencies. Thus, some European health systems that had long been accused of profligacy prior to the COVID-19 pandemic (for example because of high levels of intensive care facilities) were better able to respond to the pandemic, with one analysis suggesting that, even at low occupancy rates in normal times, this may be a cost-effective element of pandemic preparedness (Gandjour, 2021). This aspect of trust is, however, the least understood of those examined in this book. Insights are at present more likely to be found in political biographies and other historical studies than in empirical research (although these need to be understood in context). These sources can offer inspiration, valuable explanations of policy change or inertia, and topic suggestions for future research. It is also possible to draw on the literature on agenda setting for ideas and suggestions of wider relevance, such as Kingdon’s model of policy streams (Kingdon & Stano, 1984) or Jenkins’ (2013) practical guide to getting politicians to prioritize mental health. 2.6 Trust of politicians in the public As we have noted earlier, there are many other relationships that have implications for health and where trust is important. They include trust of the public in politicians and in the organs of government (such as the civil service, the judiciary and scientific institutions). There is an extensive political science literature on this topic. There is also interpersonal trust, the trust that each individual has in others they encounter in their everyday life. This may be especially important where formal health systems are weak and where patients rely on advice from friends and relatives. For example, a study that used the same methodology in countries at all levels of development found that having people one can trust was associated with improved hypertension control, but only in countries where investment in health systems was low (Palafox et al., 2017). Another study from the same research group found that packages of care that included peer support alongside other measures improved hypertension control in Colombia and Malaysia (Schwalm et al., 2019). In this section we will, however, look at another relationship involving trust. This is the trust that politicians have in the public, something that came to the fore as a consequence of experience during the COVID-19 pandemic. For example, in the United Kingdom some politicians and their advisers hesitated to impose Trust: the foundation of health systems22 major restrictions in its early stages, based on the erroneous view that the public would not comply or would become fatigued (Reicher, 2021). This perspective has been linked to delays in introducing restrictions on mobility, even though at the time it was clear that any delay would have severe consequences with a novel virus that was spreading rapidly and exponentially (Arnold et al., 2022). Reicher and Bauld (2021) have described how governments tend to view the public as psychologically flawed, subject to biases, and unable to deal with complex, uncertain or probabilistic information. From this perspective, the individual is seen as what they describe as a “fragile rationalist”. Reicher (2023) has linked this to the concept of nudge, which he characterizes as the idea that individuals must be helped to make the right decision by changing the choice architecture. If this is indeed the case, then it is even more important that people are guided to particular decisions during a crisis. However, he questions this assumption, noting that the main explanations why people do not make what are established at the time to be the right choices often lie in areas outside their control. Moreover, as Drury has noted, panic is very rare and people tend to support one another in emergencies, even if they are strangers, and where disasters do happen it is rarely due to psychological dysfunctionality (Drury, 2018). Rather, it is more likely to be due to failures by those in charge, such as the blocking of exits at public venues in case of fire, or having too little information rather than too much (Drury et al., 2020). The COVID-19 pandemic has offered a wealth of empirical evidence on this issue. Tracking data from mobile phones showed how people changed their behaviour rapidly in the early stages, including in Sweden where legal restrictions were much less stringent than in other European countries (Vannoni et al., 2020). There was no evidence of significant fatigue, with adherence remaining high as long as a threat remained (Reicher & Drury, 2021). Overall, the experience of the pandemic reinforces the view that people should be trusted, that most breaches of rules are a consequence of necessity, and that punitive measures, such as fines, are often counterproductive. Instead, measures that strengthen communities and mutual support are more likely to be effective. 2.7 What are the threats to trust in health systems? If trust is a cornerstone of effective health systems, its erosion can have far reaching consequences. Several threats pose significant challenges to trust in health systems, with each carrying its own unique implications. They include misinformation and disinformation, marginalization and discrimination, and a lack of transparency, meaningful engagement and effective communication. Trust and health systems 23 2.7.1 Misinformation and disinformation One of the greatest contemporary threats to trust in health systems is the proliferation of misinformation and disinformation, particularly in the context of health care. It is important to differentiate these concepts. Misinformation is a passive or inadvertent spread of misleading and false information, whereas disinformation is the deliberate and concerted spread of such information (Wang et al., 2022). However, the boundaries between the two are often blurred. Misinformation proliferates partly because people often accept advice and information from friends, family and people they feel their community trusts above official sources (Rodgers & Massac, 2020). Misleading or false information about vaccines has been associated with decreased vaccination rates and heightened risks of preventable disease outbreaks. During the COVID-19 pandemic, the rapid spread of misinformation about the virus, treatments and vaccines on social media platforms contributed to vaccine hesitancy and undermined trust in public health agencies (Roozenbeek et al., 2020). However, vaccine hesitancy long predates the most recent pandemic, with disinformation relating to the alleged and false association between the MMR (measles, mumps, rubella) vaccine and autism being perhaps the most widely studied example (Sadiq & Saji, 2022). Many internet and social media platforms have become breeding grounds for misleading health content (Buchanan, 2020), as shown in a review of access to social media and population health decisions (Swire-Thompson & Lazer, 2020). The prevalence of health misinformation was the highest on Twitter and on issues related to smoking products and drugs. Not just smoking and drugs – misinformation on other major public health issues, such as vaccines and diseases, was also found to be high, leading individuals to question the credibility of health authorities and institutions (Suarez-Lledo & Alvarez-Galvez, 2021). (We have not found a detailed study of the impact of Twitter’s takeover by Elon Musk and rebranding as X in July 2023 on health information available on the platform, but as the amount of general misinformation and disinformation has been shown to have significantly increased (Chan, 2023), and X has since stepped out of the European Union’s Code of Practice on Disinformation, there is no reason to suggest that health information has not also been similarly affected.) Another study found some American physicians (more typically male and specializing in alternative medicine) spreading a variety of misinformation related to COVID-19 using Facebook, Twitter and YouTube (Sule et al., 2023). Politicians in some countries were also responsible for disinformation, undermining scientific sources for personal or political gain. Commercial actors from health-harming industries and those in receipt of their funding have also been documented spreading disinformation about the health harms of their products and undermining the legitimacy of government public health policies and regulatory agencies Trust: the foundation of health systems24 (Gilmore et al., 2023). The implications of these practices for maintaining public trust in health systems remain largely unexplored. 2.7.2 Marginalization and discrimination Marginalization and discrimination present a formidable threat to trust in health systems (Wesson et al., 2019). There is extensive empirical evidence that members of a group, defined according to characteristics such as race, ethnicity or socioeconomic status, tend to favour other members of that group (Balliet et al., 2014), and that this is mediated to a considerable extent by different degrees of trust (McKeown & Psaltis, 2017; Montoya & Pittinsky, 2011). When marginalized communities experience unequal access to health care, lower quality of care and worse health outcomes, their trust in the health care system can erode, leading for example to delayed presentation and consequently poorer outcomes. There is, however, evidence that intergroup trust can be increased using methods that address unconscious bias (Duncan et al., 2023). The absence, in many countries, of health and social data disaggregated by ethnicity is a major barrier to understanding these associations (Routen et al., 2022). This can be addressed to a very limited extent by one-off surveys, such as research showing markedly lower vaccine uptake among Roma in central Europe, a population that has often well founded distrust in state institutions (Duval et al., 2016). The importance of having such data is apparent from the experience of those few countries that do collect it, especially the United Kingdom, where certain ethnic minority populations fared far worse during the COVID-19 pandemic (Katikireddi et al., 2021). 2.7.3 Lack of transparency A lack of transparency within health care institutions and policies can also erode trust. When the basis of health care costs is opaque, where medical errors are not openly acknowledged, or where conflicts of interest are not disclosed, patients and the public perceive a lack of accountability and ethical behaviour within the health care system. One example is distrust of the pharmaceutical industry, seen as profiteering from the pricing of essential medications such as insulin (Knox, 2020), or in the publishing of fallacious clinical trial data (Van Noorden, 2023). This lack of transparency regarding essential drug pricing has resulted in calls for greater accountability and disclosure (Mossialos & McKee, 2003) as patients and the public seek to understand the reasons behind such cost increases and their impact on health care access. In the United States, trust in the industry has also been eroded by evidence of the role of the Sackler family in driving the opioid epidemic (Keefe, 2021). The relationship between for-profit actors providing Trust and health systems 25 health or health care, and public trust in health systems and policymakers, is a complex issue and one that is beyond the scope of this book. Cammett et al. (2015) provide an introductory discussion. Similarly, close relationships between the medical product industry and the medical profession and health systems, and the conflicts of interest that these interactions and influences create, have been identified as important potential threats to building and maintaining public trust in medicine (Chimonas et al., 2021). These issues deserve greater attention and more research is needed to understand the impacts of conflicts of interest and commercial influence on public trust in health systems. Transparency is especially important in relation to medical errors, whether they actually occur or are perceived as being common. They can lead to patient harm or even loss of life and have the capacity to shatter trust in health care providers, institutions and the overall health system. One example from the United Kingdom, a scandal at the Mid Staffordshire NHS Foundation Trust, exemplified how widespread neglect and poor standards of care can leave patients and their families feeling that their safety and well-being have been compromised and severely erode trust in the health care system more widely (Holmes, 2013). Even the perception that medical errors are commonplace can be detrimental. In France, reports of medication errors in hospitals have led to concerns that individuals have become wary of seeking medical care due to fears of becoming the next victim of a mistake (Azar et al., 2021). Public health errors can similarly lead to the erosion of trust. Bavli (2023) provides a comprehensive and inclusive definition of public health errors based on a review of the relevant literature, defining them “as an action or omission, by public health officials, whose consequences for population health were substantially worse than those of an alternative that could have been chosen, regardless of the causal processes involved in the consequences”. Bavli explains that “this definition suggests that a decision is a public health error when a different decision would have enabled more people to have lived longer or been healthier. It also implies that both culpable errors and non-culpable errors should be considered as public health errors”. The latter is important as there is evidence suggesting that both culpable errors and non-culpable errors can lead to an erosion of public trust and that this is influenced by context (Bavli, 2023). Further, the manner in which providers respond to error has also been shown to affect public trust in the health system (Shore, 2006)dD . Transparency and accountability are thus fundamental to ensuring trust in health care and the trustworthiness of the health system. Health care providers and institutions must openly acknowledge errors or investigate their causes, although medical errors, if given a high profile by the media (which tend to prioritize the coverage of rare and shocking events as opposed to the delivery of daily and safe care) can significantly impact public perceptions and thus trust Trust: the foundation of health systems26 in the health care system. This was the case in Germany when incidents such as wrong-site surgeries or medication mix-ups involving well known hospitals gained extensive media attention and had negative consequences for trust (Stauch, 2011). This highlights the importance of preventing such events from happening in the first place. * * * Having so far examined concrete examples and applications of the key trust relationships in health systems, the next chapter is concerned with the more theoretical understandings of trust as applied to the health sphere. Reviewing different disciplinary perspectives provides a wider understanding of not just the issues at hand in viewing trust as a key driver of health system transformation, but also the reasons for the different views on its role, how it can be studied, and how best to benefit from it. 3. A cross-disciplinary perspective on trust and the relevance for health and health systems Having thus far introduced the reader to the importance of trust to health systems and some of the key trust relationships within health systems, we now present a picture of the state of the literature more widely, how different disciplines theorize and conceptualize trust, and an understanding of the factors that shape these key trust relationships and the health impacts of a strengthening or a loss of trust. This chapter draws predominantly on a recent review by Taylor and colleagues, which examined the literature on trust in health systems spanning the last 50 years (Taylor et al., 2023). Taylor et al. begin by noting how the experience of the COVID-19 pandemic “has clarified the role that trust played in virtually every element of health care delivery”. Thus, lack of trust delayed care and reduced vaccine uptake, adversely affecting health. Health workers realized how much their safety and that of their families relied on trusting colleagues, employers and patients. Taylor et al. identified five broad groupings within the literature: patients’ trust in clinicians; clinicians’ trust in patients; clinicians’ trust in other clinicians; patients’ and clinicians’ trust in organizations (which they combined as this literature was sparse); and general trust in health care systems by patients, clinicians and the general public. However, they also note that the literature on trust “can be as frustrating as it is voluminous”, with simple questions being met with complicated answers. Research on the first of these groupings, trust of patients in clinicians, is the most extensive. Referring to a seminal systematic review published in 2004, which said that the “evidence base to support the claims about the impact of trust on therapeutic outcomes is in short supply” (Calnan & Rowe, 2006), Taylor et al. noted limitations in much of the subsequent work, which was dominated by cross-sectional surveys or qualitative interviews, with a few intervention studies. However, they also cited a recent systematic review which, although only looking at general trust rather than trust by the patient in the specific clinician, did identify 13 randomized controlled trials. The interventions were all intended to increase trust and included measures designed to improve communication, motivational interviewing, shared decision-making, patient centred care, empathic care, and Trust: the foundation of health systems28 cultural competency training. Together, they found a small but significant effect on health care outcomes, including pain and anxiety, and markers of diabetes control (Kelley et al., 2014). The authors note how most studies use validated scales to measure trust. These typically include concepts of honesty, communication, confidence and competence, although fidelity, system trust, confidentiality and fairness also featured, but less often (Ozawa & Sripad, 2013). The most widely used now are the Group-Based Medical Mistrust Scale, the Medical Mistrust Index, and the Health Care System Distrust Scale. However, they note that research on the psychometric properties of these measures is limited (Müller et al., 2014). The authors make three recommendations. First, they call for improved instruments for measuring trust, with additional validation of their psychometric features. They call for measures that assess trust in clinicians other than physicians, and in the teams that are increasingly involved in providing health care. Second, they note the challenges involved in taking account of reciprocity, whereby the quality of the clinical interaction is influenced by both the trust of the patient in the clinician and of the clinician in the patient. Here, they also highlight the challenges that arise whereby trust in the clinician is related to trust in the health facility that employs them and in the health system more generally. Third, and noting that their focus is on the United States health system, they call for research that seeks to understand differences in patients’ trust in doctors and nurses. Taylor et al. find fewer studies looking at clinicians’ trust in patients. One scoping review of articles examining physicians’ trust concluded that “rigorous investigations of trust are rare, narrowly focused, and imprecise in their discussion of trust” (Wilk & Platt, 2016). In contrast to the literature on patients’ trust in clinicians, these studies tend to consider the reciprocity involved in the relationship. However, this is a relationship based on two different types of vulnerability. The patient is vulnerable to harm caused by the clinician, whereas the vulnerability of the clinician relates to their reputation and professional standing. Here, the authors call for innovative designs, such as those that examine how trust changes over the course of what, for chronic conditions, can be a long-term relationship. Taylor et al. found that many of the papers about relations between clinicians and other clinicians that included the word “trust” in the title did not really focus on it. Where they did, trust was seen as an aspect of clinical competence, although one conceptualized trustworthiness as a function of both competence and integrity (Duijn et al., 2018). One study identified high autonomy and an emphasis on quality rather than productivity as predictors of trust in physicians by colleagues from a range of professional backgrounds (Linzer et al., 2019). Another saw trust as being justified where the individual or organization is perceived to have “the A cross-disciplinary perspective on trust and the relevance for health and health systems 29 competence, willingness, integrity, and capacity … to perform a specified task under particular conditions” (Lundh et al., 2019). The authors call for more research on trust among clinicians with different professional backgrounds and in hierarchies where there are formal power differentials (Umoren et al., 2022). The sparse literature on patients’ and clinicians’ trust in health organizations is also dominated by research from the United States, and thus might not easily be generalized to a European context. In particular, it has been noted that the growth of managed competition and with it the creation of a consumer mindset has undermined trust, as patients “question the motives and decisions of these organizers and providers of care” (Mechanic, 1996). This is increasingly recognized as a problem, with evidence linking mistrust to underuse of services (Taber et al., 2015). This literature also invokes the concept of institutional betrayal, where health organizations fail to act to protect those dependent on them, calling into question their trustworthiness. A recent example was the response by managers in a hospital in the United Kingdom to a series of unexplained deaths among babies where paediatricians had raised concerns about a nurse but were rebuffed and were even required to apologize to her. She was later convicted of multiple murders (Alexander, 2023). The authors note the scarcity of research on trust in health institutions and, especially, the lack of research on trust of clinicians in their employing organizations. The final type of trust is general trust in health care systems by patients, clinicians and the general public. This literature is reasonably large, with many studies using data from surveys of public opinion. A 2013 systematic review identified 45 measures of trust within the health system (Ozawa & Sripad, 2013). A 2019 systematic review examined mistrust, defined as “a tendency to distrust medical systems and personnel believed to represent the dominant culture” (Benkert et al., 2019). The authors found that medical mistrust was often associated with earlier negative interpersonal experiences with health care personnel, and while medical mistrust predicted a number of outcomes associated with service delivery, they found no clear link to health outcomes. In summary, the review by Taylor and colleagues stresses the importance of trust and shows how the term is widely used but often inadequately defined or poorly understood (Taylor et al., 2023). It sets out an ambitious agenda for research. However, it also highlights two important issues that must be addressed. First is that definitions of key terms, including trust and trustworthiness, vary among and within disciplines. Second, both trust and trustworthiness are dynamic and even those whose trust is being studied may be struggling to resolve conflicting perceptions and emotions and cannot easily be observed by the researchers seeking to understand these phenomena. Thus, although a patient may reasonably expect that their physician will treat them well, they cannot anticipate the future. This means their perception will also be influenced by their attitude to risk and to the Trust: the foundation of health systems30 range of possible outcomes (McKee et al., 2024a). Another problem is, simply, that trust is a complex phenomenon, involving many different decisions, types of interactions and relationships, and interpretations of concepts that seek to capture trust (McKee, van Schalkwyk, Greenley, et al., 2024). It can be difficult to know whether two people recording the same scores on a scale purportedly measuring trust actually mean the same thing. Finally, the authors suggest that researchers working in this field should draw on insights from other disciplines, such as philosophy, sociology, economics and psychology. How these fields conceptualize and research trust as relevant to health and health systems is summarized in the next section. 3.1 Different disciplinary perspectives on trust in health systems Superficially, the concept of trust seems quite simple: I can be confident that, in any exchange, I will get what I expect. Mechanic (1998) defined it as a belief “that individuals and institutions will act appropriately and perform competently, responsibly, and in a manner considerate of our interests”. Yet the concept of trust has generated much disagreement about its nature, its role in transactions, and its value within and between several disciplines, including philosophy, sociology, economics and psychology. 3.1.1 Philosophical perspectives We begin with a series of issues that concern the nature of trust. The first of these issues is the relationship between reliance and interpersonal trust (an outline of the concept can be found in Box 1). While a patient may rely on a doctor to get their diagnosis right, several writers have argued that this is not sufficient to count as trust. By analogy, one might rely on a shelf not to fall down and shatter a precious ornament, but one would not usually say that one trusted it not to. Jones has argued that while one can rely on many things, such as the shelf not falling down, one can only trust someone that has a will and can thus decide whether or not to act in a way that is trustworthy (Jones, 1996). Thus, extending the shelf analogy, the trust is in the person who fixed it to the wall or who selected the material from which it was constructed, but not the shelf itself. Baier has argued that trust involves goodwill (Baier, 1986). There is an expectation that the person being trusted acts in a certain way because they have your interests at heart, not that they are doing it begrudgingly, accidentally or because they are being forced to do so. In contrast, Hawley rejects the view that goodwill is necessary for reliance to become trust, instead arguing that commitment is (Hawley, 2014). She uses an example where a work colleague who is a poor A cross-disciplinary perspective on trust and the relevance for health and health systems 31 judge of quantities reliably brings extra food to work, so that one can depend on being able to eat their leftovers. This only becomes trust when they commit to doing so, perhaps because they enjoy eating with you. Hawley (2014) distinguishes between the consequences of failures by things that have will or do not have will. To return to the earlier example, should the shelf fall down one would be disappointed, whereas should an individual act contrary to what was expected, for example saving money by not using the right fixings, it would be seen as betrayal. Faulkner invokes ideas of predictive and affective trust (Faulkner, 2011). The former simply involves relying on someone to do the right thing because they usually do. When they fail to do so, then the response is disappointment. However, in the latter case there is not just a sense of reliance but also a normative expectation that the person ought to be dependable so, if they are not, it is seen as betrayal. In summary, trust is more than being reliable. It involves a commitment and societal expectation to behave in ways that lead to one’s actions being reliable. A second issue relates to the question of trust to do what? Scholars on trust distinguish between three-place and two-place trust. In the former A trusts B to do X (for example to water your plant when on holiday) but not to do Y (such as look after your child), whereas in the latter A trusts B generally. While the practical difference is obvious, the philosophical discussion has centred on which derives from the other. Most writers argue that two-place trust derives from three-place trust. In other words, if A trusts B to do enough things, then the relationship becomes one of two-place trust. Critics of this view argue that it fails to take account of the nature of other aspects of relationships that influence trust that are typically unconditional, such as love and friendship, (Domenicucci & Holton, 2017). The importance for the present purposes is that trust in, for example, health workers can derive either from the view that they can be trusted because, for example, they have certain skills (thus, one would trust a surgeon to remove an appendix but not necessarily to paint a portrait, even if some of the skills, such as manual dexterity, are the same) or because they have shown the commitment and vocation to become health workers and so, should they take to portraiture, they can be trusted to do it to the best of their ability. A third issue introduces the question of whether one’s beliefs are relevant to considerations of trust (often employing the philosophical term doxastic, which simply means relating to an individual’s beliefs) (Adler, 1994; Hieronymi, 2008). Doxastic accounts of trust, at their most basic, see trust as where A believes that B will do something, while Hawley (2014) develops this to see trust as where A believes that B will not just do it but is committed to doing so. Meanwhile, non-doxastic accounts recognize that such a belief can be present but is not essential for trust, for example where there is respect that they will try to do it but Trust: the foundation of health systems32 no belief that they will always succeed (Baker, 1987). Others invoke optimism that they will do the right thing, even if one does not believe with certainty that they will (Jones, 1996). These questions have relevance to how one approaches trust in health care. A doxastic approach has the advantage of simplicity. The patient trusts the health worker because they believe they are competent. Without such belief, they will require other evidence that this is the case. This could take the form, for example, of a public report of their clinical success rate, a measure fraught with problems, including methodological ones (McKee & Hunter, 1995). Doxastic accounts also distinguish trust that someone will do something well from the optimism that arises from desperation where a patient clutches at straws (causing themselves to believe in an outcome that is very unlikely) lest they lose hope. This issue is also relevant to the other side of the health worker–patient relationship, where the health worker trusts the patient to adhere to the therapy they have been prescribed. Given the extensive literature on non-adherence to many long-term treatments, the health worker may trust the patient to take their tablets but not necessarily believe that they will (non-doxastic). However, this can develop into therapeutic trust, whereby trust is seen as a means to promote trustworthiness (Frost-Arnold, 2014). Thus, rather than castigate the patient, the health worker will emphasize the trust they have that the patient will do all they can. A further issue to be considered is how trust relates to the risk that is inherent in health care. Thus, the patient recognizes that there is always a risk that something could go wrong with their treatment. The question then becomes how they respond to it. They could accept it, thereby preserving the therapeutic relationship with the health worker, or they could seek to minimize it, for example by getting second and third opinions or demanding to see the health worker’s qualifications. However, that could undermine the trust on which the relationship is based (Faulkner, 2011). Like so many of the issues so far discussed, this is subject to changing norms. In the United Kingdom, a failure by a clinical team to seek specialist advice gave rise to a movement (Martha’s Rule, named after the young girl who died) that has attracted widespread political support to give patients in hospitals and their relatives the right to seek a second opinion (Mills, 2023). A second set of issues relates to norms in trusted relationships. There are two norms to be considered: the first, that one will trust someone who invites you to trust them, and the second, that someone who is trusted should be trustworthy (Fricker, 2018). Carter argues that when deciding to trust someone, one should consider three evaluative assessments: success, competence and aptness. Trust can be justified if the trusted person succeeds in what they should do or if they display competence A cross-disciplinary perspective on trust and the relevance for health and health systems 33 that allows one to rely on them doing the right thing. However, while these two considerations will often coincide, someone can be competent but not succeed, for example due to a lack of judgement at some point. The third is therefore aptness, where their success is explicitly derived from their competence (Carter, 2020). While these considerations relate to whether someone is entitled to trust another, Fricker has asked whether we have an obligation to do so, examining the situation that arises when someone who merits trust is dismissed because of prejudice on the part of the person being asked to trust them (Fricker, 2007). She illustrates this by reference to the book To kill a mockingbird, where a black man on trial before a white jury for a crime of which he is innocent has his testimony dismissed. This is relevant in health care where, for example, a patient distrusts their health worker on the grounds of their ethnicity rather than their competence. The literature on trustworthiness is complex but, to simplify it, debate arises around issues such as whether it relates to trust in general or in a particular matter (the two- and three-place issue discussed above) and whether it is sufficient to be reliable or requires something else such as goodwill, also discussed above. So far, this section has focussed on trust. However, there is also debate about the opposite of trust. Three terms – low trust, distrust and mistrust – are commonly used, each with potentially different meanings. Low trust is arguably the easiest to understand. It arises where someone is willing to make themself vulnerable in an interaction with someone they might trust, albeit with limited enthusiasm. This differs from distrust, where they will be reluctant to do so because they expect that the person being trusted will be incompetent or actually seek to harm them (Hillen et al., 2011). Thus, Mechanic (1996) has argued that distrust is not the opposite of trust but is an alternative to it. It is the difference between mistrust and distrust that is more problematic. Griffith and colleagues have suggested that distrust relates to the perception of a specific person or organization, while mistrust is a more general scepticism, arising for example from experience of historical injustice or systemic racism (Griffith et al., 2021). This is consistent with an earlier review that noted how, although the two terms are often used interchangeably, distrust refers to a lack of trust based on prior experience in a particular context while mistrust refers to a general sense of global unease (Brennan et al., 2013).  Related to both trust and distrust is the concept of misplacement. In the context of debates surrounding the ethical use of artificial intelligence (AI) and the legitimacy of the idea of placing trust in a non-human entity, Starke and Ienca (2022) propose a framework of misplaced trust and distrust. Using this framework, they demonstrate that actors can place trust in trustworthy systems or other actors based on flawed and/or ethically unjustified beliefs or motivations, and similarly, that distrust of an untrustworthy system or actor can be applied for an Trust: the foundation of health systems34 incorrect and/or unjustifiable reason. Thus, placing trust in the trustworthy and being distrustful of the untrustworthy do not constitute sufficient conditions for establishing ethically justifiable trust relationships such as between humans and AI systems. Such a deeper understanding of the reasonings, beliefs or motivations underpinning the placement or withholding of trust can help inform policies that prevent the unwarranted placement of trust in AI and, conversely, withholding of trust when it is otherwise warranted (Starke & Ienca, 2022). 3.1.2 Sociological perspectives Consistent with other disciplines, sociological research differentiates between trust in general and trust in specific individuals or organizations (Fukuyama, 1996). Much of the literature has focused on its antecedents and determinants (Schilke et al., 2021). In particular, it examines how characteristics such as social position, prior experiences and opinions can influence levels of trust. As with much of the literature on trust and health systems, there is a distinctly American focus. This tends to emphasize the growing distrust associated with the increasing commercialization of American medicine (Imber, 2008), with evidence that clinicians have lower trust in for-profit health plans (Schlesinger et al., 2005). However, there is other literature; for example, a Swedish study found that poor self-rated health was mediated in part by underuse of the system by those who lacked trust in it (Mohseni & Lindstrom, 2007). Seligman’s seminal book, The problem of trust, distinguishes trust in systems from confidence in them (Seligman, 2000). Confidence stems from knowing that systems will perform well, while trust comes into play where that knowledge is lacking. Consequently, trust becomes more relevant in a situation where institutions and systems are perceived to be weakening. An important body of sociological literature addresses the relationship between trust and social capital. Social capital comprises the networks and norms that facilitate coordination and cooperation for mutual benefit. It encompasses connections among individuals and the social networks and norms of reciprocity and trustworthiness that arise from them. Trust is often seen as a key element of social capital, acting as the glue that holds networks together. In this literature, trust has several important benefits. First, it reduces transaction costs. High levels of trust mean that people spend less time and resources verifying information or guarding against potential exploitation. Second, it facilitates cooperation. When trust is widespread, individuals are more likely to engage in collective action and community endeavours. Third, it promotes economic growth. Societies with high social capital, characterized by trust and reciprocity, often perform better economically due to smoother transactions and reduced need for rigorous regulations. A cross-disciplinary perspective on trust and the relevance for health and health systems 35 The relationship between social capital and trust is bi-directional. High levels of trust can lead to greater social capital and, in turn, a rich stock of social capital can further enhance and sustain trust within a society. This mutual reinforcement creates a feedback loop where societies with high trust and social capital can continue to thrive and grow stronger over time. However, breakdowns in trust can erode social capital. Events like financial crises, political scandals or episodes of societal unrest can diminish trust among individuals or between the public and institutions. Once depleted, trust can be challenging to rebuild, leading to a weakening of social capital and its associated benefits. This has clear parallels and relevance to our discussion on trust and health system transformation where the latter is dependent on the former, but the former will not be built or sustained without the latter. The need is for a virtuous rather than a vicious cycle. However, the evidence on social capital and trust is contested, as is the role that social capital plays in health. Pearce and Davey Smith have questioned what they described as a “vague, popular concept”, arguing that the evidence linking social capital and health was often conflicting (Pearce & Davey Smith, 2003). One problem is that, as with trust, there are problems of definition and terminology. Thus, while a 1916 paper argued that interactions based on goodwill, fellowship and mutual sympathy led to the accumulation of social capital, which satisfied both the needs of the individuals involved and the whole community (Hanifan, 1916), later writers have differed in which of these levels they see as most important. Is social capital primarily an attribute of the individual or of the community, or of both? Wacquant and Bourdieu (1992) take the former position, arguing that an individual benefits as a consequence of their social networks by virtue of the power they can exert within them, power that is determined by context and social norms. Meanwhile, Putnam (1993) sees social capital as “features of social organizations, such as networks, norms and trust that facilitate action and cooperation for mutual benefit”. Others, however, have argued that both are important. Szreter and Woolcock (2004) argued, just after Pearce and Davey Smith published their paper, that there was already an extensive body of research showing positive associations between different aspects of health and social capital. Shiell and colleagues, writing in 2020, identified 28 further systematic reviews, all but one finding positive associations with at least one aspect of health, even if the results can be inconsistent (Shiell et al., 2020). 3.1.3 Economic perspectives Economics offers several perspectives on trust relevant to health care. One is the importance of trust in situations where there is uncertainty and asymmetry of information (a situation that characterizes many clinical interactions) as described Trust: the foundation of health systems36 in a seminal work by Arrow (1978). He emphasized the importance of professional ethics as a means of building trust, exemplified by the Hippocratic oath. Another is the use of game theory (Blake & Carroll, 2016), and in particular the prisoner’s dilemma, which examines the rational approach to an interaction that is potentially risky, such as a clinical encounter (Nay & Vorobeychik, 2016). Where one party distrusts the other, they may act in ways that lead to a worse outcome than if each trusted the another. This has also been used in its iterative form to compare responses in circumstances where the encounter is either one-off or one of many in a long-term relationship, such as arises with a chronic disease (Tarrant et al., 2010). Individuals engaged in the latter who are acting rationally are less likely to exploit one another. Game theory also offers insights, through the use of bargaining scenarios, into decisions made at the end of life, when trust is especially important (Slomka, 1992). It has also been employed to understand vaccine uptake and, in particular, the way that free riders can prevent achievement of herd immunity (Chapman et al., 2012). Other applications relate to building trust between multiple providers contributing to the care of a patient with multimorbidity or providers colluding in a health care market to prevent the entry of another provider that might be a competitor (Bettinger, 2016). A third addresses the problem that no one can know another person’s value set. Thus, the patient cannot know whether the clinician will exploit them. In these circumstances, the patient will rely on signals that the clinician is trustworthy (Hampshire et al., 2017). This can take several forms. One is credential display, where physicians’ qualifications and awards feature prominently in their offices, serving as a signal of their competence and expertise. Ratings on online comparison sites now play a similar role. Another is physical appearance and demeanour demonstrated, for example, by wearing a white coat or carrying a stethoscope. Diagnostic tests can also act as a signal, being used not only to gather essential information but also to reassure patients and signify thoroughness. Therapeutic regimen signalling occurs where a health care provider prescribes a certain treatment that indicates the severity or nature of the condition to the patient, for example, when they refer them to a specialist. However, signalling can also have adverse consequences, for example, when it leads to overtreatment. Economics has also contributed some methodological innovations, in particular the trust game (Berg et al., 1995). This is used to study trust and reciprocity in economic and social interactions. Researchers analyse the decisions made by players to understand factors influencing trust, cooperation, and risk-taking behaviour. The game can reveal insights into how individuals perceive and respond to trustworthiness and how they balance self-interest with cooperation in various situations. Box 2 The trust game The trust game is an exercise commonly used in psychology and behavioural economics to study trust and reciprocity in human interactions. The game typically involves two participants. They are usually anonymous to each other and cannot communicate directly. The first player is often referred to as the “Sender” or “Trustor”, and the second player is known as the “Receiver” or “Trustee”. Both are given a certain amount of money (or points, or another form of currency). The Sender then decides how much of their money to send to the Receiver. The amount sent is tripled (or multiplied by another factor) as it is transferred to the Receiver. The Receiver, knowing that the transfer is tripled, now knows how much the Sender transferred, though not how much the Sender had to begin with. The Receiver then decides how much of their total to send back to the Sender. The game ends after this exchange, and both players keep the money they have at this point. The trust game is insightful because it reveals how individuals perceive and respond to trust. The Sender’s decision to send money can be seen as an act of trust, betting that the Receiver will reciprocate. The Receiver’s decision to send money back can be interpreted as an act of reciprocity or trustworthiness for the future – if it were a one-off the Sender may send nothing for fear that they may get nothing back and, indeed, the Receiver would have no incentive to send anything back. Researchers use variations of this game to understand how factors like communication, reputation, group identity and past experiences influence trust and cooperation. The game provides a simplified model to observe and analyse human behaviour in a controlled setting, offering valuable insights into social, economic and psychological dynamics. A cross-disciplinary perspective on trust and the relevance for health and health systems 37 3.1.4 Psychological perspectives Psychology provides a rich framework to understand the dynamics of trust in health care. Linked inherently to emotions, perceptions and experiences, trust is influenced by a variety of psychological processes. This literature often focuses on how an individual who is party to an encounter decides whether it is safe to expose their vulnerability. Often, they make use of subconscious clues and heuristics to decide whether the person they are interacting with is trustworthy. The ability to do so is seen as an evolutionary adaptation, as being able to decide who can be trusted makes it less likely that one will be exploited (DeSteno, 2014; DeSteno et al., 2012). There is a body of research in laboratories and in real life settings showing how people derive clues from body language and demeanour that help them make these decisions, even though there is no obvious reason why these should be linked to trustworthiness (Krumhuber et al., 2013). However, based on an extensive review of the literature, Lorié and colleagues have shown that while some non-verbal expressions have universal meanings, others are culturally specific (Lorié et al., 2017). A classic example from history was when in a seminal work by Arrow (1978). He emphasized the importance of professional ethics as a means of building trust, exemplified by the Hippocratic oath. Another is the use of game theory (Blake & Carroll, 2016), and in particular the prisoner’s dilemma, which examines the rational approach to an interaction that is potentially risky, such as a clinical encounter (Nay & Vorobeychik, 2016). Where one party distrusts the other, they may act in ways that lead to a worse outcome than if each trusted the another. This has also been used in its iterative form to compare responses in circumstances where the encounter is either one-off or one of many in a long-term relationship, such as arises with a chronic disease (Tarrant et al., 2010). Individuals engaged in the latter who are acting rationally are less likely to exploit one another. Game theory also offers insights, through the use of bargaining scenarios, into decisions made at the end of life, when trust is especially important (Slomka, 1992). It has also been employed to understand vaccine uptake and, in particular, the way that free riders can prevent achievement of herd immunity (Chapman et al., 2012). Other applications relate to building trust between multiple providers contributing to the care of a patient with multimorbidity or providers colluding in a health care market to prevent the entry of another provider that might be a competitor (Bettinger, 2016). A third addresses the problem that no one can know another person’s value set. Thus, the patient cannot know whether the clinician will exploit them. In these circumstances, the patient will rely on signals that the clinician is trustworthy (Hampshire et al., 2017). This can take several forms. One is credential display, where physicians’ qualifications and awards feature prominently in their offices, serving as a signal of their competence and expertise. Ratings on online comparison sites now play a similar role. Another is physical appearance and demeanour demonstrated, for example, by wearing a white coat or carrying a stethoscope. Diagnostic tests can also act as a signal, being used not only to gather essential information but also to reassure patients and signify thoroughness. Therapeutic regimen signalling occurs where a health care provider prescribes a certain treatment that indicates the severity or nature of the condition to the patient, for example, when they refer them to a specialist. However, signalling can also have adverse consequences, for example, when it leads to overtreatment. Economics has also contributed some methodological innovations, in particular the trust game (Berg et al., 1995). This is used to study trust and reciprocity in economic and social interactions. Researchers analyse the decisions made by players to understand factors influencing trust, cooperation, and risk-taking behaviour. The game can reveal insights into how individuals perceive and respond to trustworthiness and how they balance self-interest with cooperation in various situations. Box 2 The trust game The trust game is an exercise commonly used in psychology and behavioural economics to study trust and reciprocity in human interactions. The game typically involves two participants. They are usually anonymous to each other and cannot communicate directly. The first player is often referred to as the “Sender” or “Trustor”, and the second player is known as the “Receiver” or “Trustee”. Both are given a certain amount of money (or points, or another form of currency). The Sender then decides how much of their money to send to the Receiver. The amount sent is tripled (or multiplied by another factor) as it is transferred to the Receiver. The Receiver, knowing that the transfer is tripled, now knows how much the Sender transferred, though not how much the Sender had to begin with. The Receiver then decides how much of their total to send back to the Sender. The game ends after this exchange, and both players keep the money they have at this point. The trust game is insightful because it reveals how individuals perceive and respond to trust. The Sender’s decision to send money can be seen as an act of trust, betting that the Receiver will reciprocate. The Receiver’s decision to send money back can be interpreted as an act of reciprocity or trustworthiness for the future – if it were a one-off the Sender may send nothing for fear that they may get nothing back and, indeed, the Receiver would have no incentive to send anything back. Researchers use variations of this game to understand how factors like communication, reputation, group identity and past experiences influence trust and cooperation. The game provides a simplified model to observe and analyse human behaviour in a controlled setting, offering valuable insights into social, economic and psychological dynamics. Trust: the foundation of health systems38 Frances Younghusband, leading an armed British incursion in Tibet, believed that the Tibetans lining the streets clapping his progress through villages were welcoming him, unaware that it was what they did to drive out demons (French, 2016). Elbaum (2020) has argued that clinicians have a moral responsibility to ensure that they are aware of cultural differences, especially when interacting with groups that have previously suffered discrimination in their encounters with the health system. Trust deepens when there is consistency in behaviour. If patients experience consistently high-quality care and feel they are treated with respect and consideration, their trust in the health care system grows. The psychological literature emphasizes the role of integrity in deciding about trustworthiness and, in particular, how clinicians reconcile conflicts between selfishness and selflessness, with the latter an indication of being trustworthy. Other insights draw on evidence on the role of expectation. Trust develops when there is a belief that a person or an organization will act in our best interest. Previous positive past experiences with health care providers can establish and reinforce such expectations, leading to increased trust, while negative experiences, which may relate to other health systems as is the case with migrants, can undermine trust (O’Donnell et al., 2008). Perceptions of trust are also important. Trust is more likely to develop if patients perceive their health care providers as competent. As discussed above, this perception can be influenced by the provider’s communication skills, credentials, demeanour and even the environment of the health care facility. Effective communication, where information is conveyed clearly and questions are addressed, can enhance trust. Conversely, perceived secrecy or withholding of information can erode trust. Similarly, demonstrating a commitment to patient autonomy, whereby they have a voice in decisions about their care, can foster trust, while feeling coerced or having a lack of agency can reduce trust. Good communication skills can support a therapeutic alliance (Elbaum, 2020), a term used to signify a partnership between the patient and clinician, and which has been shown to improve outcomes (Kinney et al., 2020; Sulaman et al., 2023). Empathy is an important aspect of communication, manifested as the ability to listen actively and build rapport, a crucial skill for health workers. Feeling understood and cared for on a personal level can significantly bolster a patient’s trust. Cognitive biases are important because they can shape trust in health care. For example, confirmation bias might cause patients to seek out information that aligns with their existing beliefs about a treatment, which can either enhance or diminish trust in medical advice (Kappes et al., 2020). They also affect how people weigh the perceived risks and benefits of medical decisions. If the perceived risk is high (for example with invasive procedures), trust becomes A cross-disciplinary perspective on trust and the relevance for health and health systems 39 even more crucial. Clinical practice can also be shaped by cognitive biases undermining the provision of optimal and equitable care (Doherty & Carroll, 2020). Diagnostic and treatment errors are often in part due to cognitive biases. Many forms of cognitive biases exist, each affecting clinical practice in difference ways, demonstrating the importance of identifying effective debiasing strategies or ways to mitigate against their impacts (Doherty & Carroll, 2020). Notably, in some circumstances disclosure of biases, such as a clinician’s bias towards recommending a treatment plan based on their speciality of interest, has been found to increase patients’ reported trust and the likelihood of them consenting to a treatment that aligns with the physician’s area of specialization (Sah et al., 2016). Such bias disclosers also led physicians to increase the strength of their advice to undergo their specialty treatment. Self-disclosure of a speciality bias could therefore lead advisees to perceive their advisors as more competent or trustworthy with important implications for disclosure policies and the handling of advisor biases (Sah et al., 2016). 3.2 Taking a holistic view Taylor and colleagues (2023) argue that each of the disciplines discussed in this chapter can be seen as pairs of glasses, helping the wearer to see unique features of what they are observing. This means that a philosopher may study trust and interpret the evidence in a different way from, say, an economist. As a consequence, they are likely to speak past one another as it is difficult for someone to wear more than one pair of glasses at the same time. Taylor et al. make a series of recommendations to strengthen studies on trust by health services researchers. First, trust should be studied as an outcome and not just as an input to the delivery of health care, with a specific call for research that explores how trust can be rebuilt once it is lost, drawing on ideas of moral repair (Walker, 2006). Second, they call for more experimental or quasi-experimental studies to evaluate interventions. Third, they argue for more longitudinal studies to complement the existing body of evidence dominated by cross-sectional ones, noting the particular importance of this approach for conditions that involve repeated interactions (Rotenberg & Petrocchi, 2018). Fourth, they note how trust arises from the relationship between two people, such as patients and clinicians, but very little research looks in both directions. As they point out, “a patient’s trust in a clinician can be influenced not only by what that patient thinks about the clinician but also what the patient thinks the clinician thinks of them”. This is important especially in the context of minority or marginalized groups who may already be sceptical about how they are regarded by health professionals or the health service, leading to lower levels of health care utilization, diminished access and lower health outcomes. A survey of five countries (including France and Trust: the foundation of health systems40 the United Kingdom) found that individuals who identify as ethnic minorities or persons of colour, or as LGBTQ+, or who experience a disability, have had negative health care experiences leading to considerably lower levels of trust than others (Sanofi, 2023). Fifth, they call for studies that consider spillovers of trust between clinicians, health facilities and plans, and health systems. Sixth, while recognizing that many studies have looked at trust and characteristics such as race or sexuality, they identify a need to make more use of participants’ lived experiences, with mixed methods offering considerable potential. Seventh, echoing an issue that will be discussed in the next chapter on explainable AI (XAI), they propose further discussion about the pursuit of maximal or optimal trust and, in particular, how the latter might be measured. Finally, they argue that researchers studying trust should adopt a reflexive stance, recognizing that trust is built over time through analysis and testing of assumptions rather than being granted impulsively or instinctively, noting how their presence and worldview is likely to influence the information they obtain. * * * Thus far this book has examined the importance of trust for health system functioning and transformation, described key trust relationships that help in explaining trust’s critical role, summarized key factors that can build or erode trust, and provided an overview of the state of the literature on trust in health systems and different disciplinary perspectives on trust. The next chapter discusses the relationship between trust and other key elements of functioning health systems, namely, technology, information, data and how these are used and disseminated. Trust, technology, artificial intelligence, health and health systems 41 4. Trust, technology, artificial intelligence, health and health systems Much of this book is concerned with trust between patients and health workers (or more broadly, the health system). However, the delivery of health care is changing, driven largely by the pace of technological advances. The response to the COVID-19 pandemic was transformed by the widespread availability of lateral flow tests, allowing individuals to conduct diagnostic tests that would previously have required transporting a sample to a laboratory. Many people with long term conditions now manage them using wearable equipment that can monitor parameters such as blood glucose or heart rhythm in real time. The potential of these devices is expanding rapidly with developments in machine learning or artificial intelligence (AI) more generally. These developments have many consequences for trust. Patients should have confidence that the equipment they are using is accurate, and that the data it produces are protected and used in their best interests and the public’s best interest more broadly. Providers need to trust their patients and have confidence that they are using the equipment effectively. This requires the development and implementation of quality standards and their enforcement by consumer protection authorities. These are under-resourced in some countries, limiting their ability to regulate effectively, and can be susceptible to corruption or corporate capture. Another area raising concern is the availability of online resources that offer advice to patients which can be difficult to regulate, because they may be based in another jurisdiction. Finally, AI has given rise to some complex issues related to trust. 4.1 Trust in algorithms Artificial intelligence, powered by complex algorithms, is a rapidly developing field, with profound implications for trust in general and for health care in particular. Areas of particular concern include the use of AI in the clinical encounter, its use to generate and propagate disinformation, and concerns about privacy. Artificial intelligence systems can perform close to, or in some cases as well as, trained clinicians, especially in areas that depend on pattern recognition, such as Trust: the foundation of health systems42 detection of abnormalities in images (in areas such as radiology, histopathology or dermatology) (Rajpurkar et al., 2022; Schwalbe & Wahl, 2020). AI-learning chatbots are increasingly being used in health care, and various studies point to positive results in some areas such as: accuracy of answers to clinical questions (Goodman et al., 2023); patients preferring chatbot answers over those provided by physicians (Ayers et al., 2023); in encouraging early access to health care (especially for embarrassing conditions [Branley-Bell et al., 2023]); in improving referrals for mental health conditions (Williams, 2024). However, the overall picture remains equivocal, with one horizon scanning review undertaken in Canada noting that “there have been times when chatbots have provided information that could be considered harmful to the user” (Clark & Severn, 2023), and a recent study in Australia finding that evidence prompts can lead ChatGPT to produce biased and potentially misleading responses based on the evidence included in the question (Koopman & Zuccon, 2023). As such, some caution is needed (McKee & Wouters, 2023). A further important concern is that algorithms trained on data from one population may generate misleading results when applied to another (Wadden, 2021). Algorithms may also reproduce existing biases in treatment when, for example, they use subtle clues to determine a patient’s race in a setting where there are already racial biases in treatment decisions (Gichoya et al., 2022; Obermeyer et al., 2019). Over time, dependence on AI may lead to deskilling and loss of experience among the current generation of trained clinicians, so that it may be more difficult to identify when algorithms do go wrong. This is especially problematic given that AI, and chatbots specifically, are being touted as potential solutions to insufficient workforce numbers. Finally, there is inherent uncertainty in health care. However, when two clinicians disagree, they can often resolve the issue by discussion. This is so far not yet possible with a machine (Grote & Berens, 2020). Trust is important in this relationship between clinician and machine. If clinicians do not have sufficient trust, they will not use it. Conversely, if they have too much trust they may allow the output of the algorithms to override what might be their own correct clinical judgement (Asan et al., 2020). This can be difficult to address because machine learning models often function as black boxes, with workings that are difficult or impossible to interpret and understand. There are three main reasons for this: corporate secrecy designed to protect manufacturers’ intellectual property, technical illiteracy of users, and the intrinsic complexity of the algorithms being used (Burrell, 2016). The problems that arise from not knowing how the algorithms function was illustrated in a study where AI could identify pictures of horses, not because of their equine characteristics but rather because the pictures used bore a small copyright tag Trust, technology, artificial intelligence, health and health systems 43 (Lapuschkin et al., 2016). When this was attached to other objects, such as cars, it identified them as horses. While this is a dated example given the speed at which AI is advancing, according to a systematic survey (Lin et al., 2023), the complexity and non-linearity of deep learning models make them difficult to interpret, thereby reducing trust among users. The survey highlights that improving the accuracy, reliability and explainability of machine learning models is crucial for improving human–machine trust. An example of how machine learning can err is the case of IBM Watson Health (Strickland, 2019), which at times provided incorrect recommendations for cancer treatment, such as prescribing drugs that could cause bleeding in patients who were already experiencing heavy bleeding. This error demonstrates the potential dangers of relying on opaque machine learning systems in medical contexts. One possible solution is explainable AI (XAI), where models are made more transparent so that decisions can be explained to humans interacting with them (Arrieta et al., 2020). This can take at least five forms. First, there can be local, or specific, explanations of an individual prediction (Ribeiro et al., 2016). Second, global explanations present the model’s general logic (Wu et al., 2020). Third, counterfactual explanations report a threshold at which the algorithm could change its recommendations. Fourth, confidence explanations report the probability that the prediction is correct (Zhang et al., 2020). Finally, example- based solutions involve the algorithm justifying its decision by providing examples from the same dataset with similar characteristics to assist the observer to understand what factors are being taken into account (Liao et al., 2020). So far, the evidence on whether XAI can achieve an appropriate level of trust is mixed. Starting with medical imaging, a study from Taiwan found that physicians were more likely to trust and implement AI in clinical practice if results were perceived as explainable, with higher levels of explainability associated with higher levels of trust (Liu et al., 2022). Another study found that 70% of pathologists agreed that their trust increased when the algorithm indicated those areas of images associated with high or low confidence, although 10% disagreed and 20% were undecided (Evans et al., 2022). Yet another study found that adding counterfactual explanations, which indicate how much change would be required in an image to lead to a different conclusion, further increased trust (Mertes et al., 2022). However, other studies have found no association between use of XAI and trust when interpreting images (Cabitza et al., 2020; Gaube et al., 2023). Mixed results have also been found in studies where XAI was used to interpret complex data (Martínez-Agüero et al., 2022; Naiseh et al., 2021). In thinking about trust and AI it is important to differentiate between cognition- based trust (where trust is derived from the perceived understandability, reliability and technical competence of XAI, rooted in reasoning) and affect-based trust Trust: the foundation of health systems44 (involving emotional attachment and faith). Most research so far has focused on the former but the limited research available suggests that both play a role, with use of counterfactuals promoting relaxation and reducing anger (Mertes et al., 2022). In summary, those involved in implementing AI solutions must consider how they will be received by those who must use them, and especially whether they will engender the appropriate level of trust – neither too much nor too little. There is some evidence that XAI can help but much more research is needed to understand how it can be most effective and in what circumstances, and therefore when it should be seen as trustworthy (and trusted to the extent that is appropriate). 4.2 Trust in information Health systems will often have to communicate crucial public health messages to the population, as happened during the COVID-19 pandemic. However, as soon became clear, they often struggled against others who were promoting disinformation which, as noted earlier, differs from misinformation, the former designed to mislead while the latter is inadvertently false (Wang et al., 2019). Previous research had shown how disinformation often spreads more rapidly than factually correct information (Donzelli et al., 2018). In their 1947 basic law of rumour, Allport and Postman proposed that the amount of rumour circulating reflected the importance of the subject to the individuals concerned and the ambiguity of the evidence (Allport & Postman, 1947). Artificial intelligence can reduce trust in messaging by generating misleading content. Those involved can have a variety of motives. Some believe in the messages they are creating but others are using them as clickbait, to monetize interactions with web pages or to spread malware. Others, in particular state actors, have political objectives to undermine trust in other governments (Broniatowski et al., 2018). This false messaging can take many forms, including misleading images (for example, a stock picture purporting to have been taken somewhere it was not), a doctored newspaper headline or, increasingly, so-called deep fakes, where the image of a well known and trusted individual is manipulated to say something that is false (Chesney & Citron, 2019). The impact of disinformation can be increased by selective targeting. For example, the scope for so-called microtargeting was demonstrated when the advocacy group ProPublica showed that it could use Facebook’s algorithms to restrict certain groups, such as African Americans, Jews and disabled people, from viewing advertisements for property in a desirable area (Angwin et al., 2017). Facebook (now called Meta) has subsequently limited the ability to identify people based on certain protected characteristics, but it is possible to circumvent this restriction. Trust, technology, artificial intelligence, health and health systems 45 Ways to combat the use of AI to spread disinformation and thus undermine trust in health messaging go beyond the scope of this book. The challenges are considerable, not least because there may be reluctance by officials to challenge those politicians that are spreading disinformation in what has come to be known as a post-truth world, where some politicians know that they can lie with impunity (Higgins, 2016). In addition in some countries (most notably the United States) concepts such as trust in science have become politically highly polarized (Bruine de Bruin et al., 2020; Rao et al., 2022). A further complication is that everyone is subject to cognitive biases, including those where strong prior beliefs may not only make authoritative corrections ineffective but may even render them counterproductive (McKee & Stuckler, 2015). There is now a strong case for all health organizations that make use of public messaging to have processes to actively combat disinformation and misinformation, employing both traditional methods to tackle false information, including corrective messages and fact checking, and novel ones that tackle the creators of this information, employing evidence from psychology and communication science (Wang et al., 2022). Importantly, when used for the public’s interest, AI could prove to be a powerful tool in efforts to track and counter misinformation and disinformation and redress their impacts on trust, for example in vaccines and other public health measures (Larson & Lin, 2024). 4.3 Trust in data systems Effective functioning of health systems depends on access to clinical information. It is intuitive that clinicians will make better decisions if they have comprehensive and accurate medical records. Moreover, legitimate surveillance activities, such as cancer registration, can be compromised where people opt out or where data linkage is not possible (Rahu et al., 2020). Yet in some places there has been a backlash against the collection of such information, in part reflecting a lack of trust that the patient’s data will be adequately safeguarded (Gille et al., 2022). Some groups may have well founded concerns about the use of their data, based on previous experience. Ethnic minority populations may fear the potential for discrimination (López et al., 2011). Migrants may have concerns if their health data is linked to immigration enforcement (Hiam et al., 2018). Artificial intelligence complicates this issue because of its ability to deanonymize data, combining disparate items in ways that can identify individual patients (Murdoch, 2021). Concerns are further exacerbated by other developments that compromise individuals’ expectations of privacy, such as facial recognition technology (Van Noorden, 2020). Similar concerns are arising in the relationship between staff and employers. Thus in some areas, such as warehouse and delivery operations, staff are tracked Trust: the foundation of health systems46 and their productivity monitored. So far this is less common in health care but there is some potential, for example in tracking those working in the community. This also risks eroding trust and exacerbating shortages in a sector that already struggles to recruit and retain staff in many countries. Finally, trust in information systems can be damaged by hacking or cyberattacks which, like the generation of disinformation, can have many motives, from the use of ransomware to deeds by hostile actors. * * * In summary, trust building and health system transformation that is both trusted and trustworthy will involve engaging with the challenges and opportunities brought by advances in technology and access to data. The following and final chapter draws conclusions on policy implications and potential future directions. Recalling that the focus of the discussion is about trust (between people and patients, health and care workers, and policymakers) as key to driving the health system transformations that are needed in Europe and beyond, this chapter will offer some thoughts on how to take this agenda forward. 5. Policy implications and future directions The previous chapters have set out the case for taking measures to restore and sustain trusted relationships throughout health systems. So what needs to happen next? This final chapter cannot hope to offer a definitive way forward, for two principal reasons. First, trust is strongly influenced by context. Even though the evidence is fragmentary, levels of trust in governments, in health systems, in health workers and in science itself vary markedly among countries. It also varies within countries, shaped by the previous experiences of groups within society and their expectations about how they will be treated. Trust can also change rapidly, as happened on occasions during the COVID-19 pandemic. It varies according to what or who is being trusted to carry out what task or fulfil what role (McKee et al., 2024b). Trust in one set of state institutions, such as the health system, does not necessarily translate into trust in another, such as the police. Second, as noted earlier, the evidence is limited on what works to increase trust, either in general or in different circumstances. What can be said, however, is that even if trust is complex and multifaceted, it matters. Trust serves to bind communities and ensures their smooth operation (Delhey et al., 2018). It fosters cooperation and the sharing of resources, promoting social cohesion and harmony. Trust is critical when responding to crises. When individuals trust one another, they are more likely to work together for the greater good, leading to the collective benefit of all. This trust extends to governance and institutions which also ensure that societal norms, regulations and rules are upheld, contributing to order and stability (Gilson, 2003). People are more willing to pool their resources and efforts when they trust that their contributions will be valued and reciprocated (Schiefer & Van der Noll, 2017). On an individual level, trust is a fundamental pillar of emotional and mental well-being. Trusting bonds with friends, family and colleagues provides a sense of security and support, fostering mental resilience and happiness. Organizing services around understandings of trust rather than risk may be more effective at both meeting need and managing risk (Brown et al., 2009). Finally, trust is critical to the functioning of health systems, underpinning the legitimacy that is needed by health system actors to undertake their activities Trust: the foundation of health systems48 and people’s willingness to engage with health system facilities and public health measures. A lack of trust reduces service utilization, worsens treatment outcomes, and creates stigmatized and strained relationships between individuals seeking care and health providers, especially in mental health. As Gille summarizes: To build public trust, we need to understand public trust as an integral part of health policy making and health care activities. Without a sustained focus on and engagement with public trust during the planning, implementation, provision and evaluation phases of health system activities, it is difficult to meaningfully increase and curate public trust. (Gille, 2023) However, trust and its importance to health system functioning and health policymaking continue to receive too little attention. There is a pressing need to elevate the importance of trust to health and health system functioning and transformation, and build greater recognition of how precious trust is and the time and investment that is needed to build and maintain it, including ensuring that trust is earned and warranted. Continuing to undervalue and overlook trust risks its erosion beyond repair. 5.1 Building and sustaining trust What can the health system do to build and sustain trust? A first step is to systematically measure the different aspects of trust, conducting regular surveys that can capture both overall levels of trust and its distribution within populations. This should be coordinated internationally to ensure comparability of results and should be complemented by a range of qualitative and mixed methods measures that explore some of the aspects of trust discussed previously, and by a programme of research to improve the ability to measure trust. Readers seeking to integrate the measurement of trust into health policymaking and health system transformation and assessment are advised to refer to appendix I. This provides examples of what is currently being measured and how, and the key issues that need to be considered when measuring and monitoring trust and identifying what builds or undermines trust. This is presented from the perspective of those working in the European Region, reflecting both the provenance of the book and the area of work and expertise of the book’s authors. But measurement can only describe the problem. The next step is to solve it. This will not be easy. Those in the health sector, the intended readership of this book, must accept that they face constraints. Trust in the institutions that make up the health system and in those who work in it is influenced by many factors in the broader environment, such as the rule of law, the scrutiny that those in power are subject to, and much else. These lie outside the scope of health policymakers. Policy implications and future directions 49 That does not, however, mean that they should ignore them. Rather, as was set out in the evidence reviewed for the Pan-European Commission on Health and Sustainable Development, a comprehensive strategy for health and health system resilience and preparedness must include advocacy for action on things that reduce trust, such as corruption (recalling that health systems are often perceived as among the most corrupt), organized crime and access to justice, as well as collaboration across sectors and actions that can be taken within the health sector (McKee, 2021). This book explicitly does not prescribe a package of specific policies directed at building and sustaining trust. These must be developed on the basis of a detailed understanding of the reasons for lack of trust in a given context, an understanding that will require a range of study methods and disciplinary methods. It is particularly important to consider differences in levels and determinants of trust in different groups within a population. This will require high levels of cultural competence and a willingness to confront historical issues, such as the legacy of colonialism and discrimination. It is, however, important to incorporate some long-established principles into measures that are being considered. These are transparency and honesty, empathy and care, dedication and commitment, and competence and expertise (Covello, 1993), and they should underpin all interactions at all levels within health systems. There is a rich literature on institutional trust, from which certain principles emerge (Fuglsang & Jagd, 2015; Hudson, 2006; Sønderskov & Dinesen, 2016). This literature points to the importance of employing a combination of strategies and actions consistent with the principles above. These demonstrate reliability, integrity, transparency and a commitment to the well-being of stakeholders. A first step is to establish and pursue a clear mission and clear values. These should align with accepted ethical standards and be communicated effectively to stakeholders. Leadership is crucial. Leaders should exemplify ethical behaviour, placing integrity at the heart of their decisions and holding themselves accountable. Competence is also crucial, demonstrating the ability to deliver care of high quality to those whose trust is sought. This must be delivered consistently. As noted previously, reliability is not trust, but is a core element of it. Inconsistencies can erode trust quickly. There should be clear mechanisms for accountability within the institution. When mistakes or problems occur, those in charge must assume responsibility and take steps to rectify them. Resolute action is required when actions undermine trust. Perhaps the most pervasive example in some European countries is that of informal payments, used to obtain preferential treatment or even to access any care at all. Clearly, those involved in this practice are acting at best unethically and at worst illegally. However, it is important to recognize that they are often acting in this way because they are working in a dysfunctional system. One conceptualization of Trust: the foundation of health systems50 this phenomenon notes that it often arises where patients lack the conventional responses to poor quality care: exit (for example, going to the private sector) or voice (for example, complaining). Instead, such payments offer an informal exit (which they called INXIT) (Gaal & McKee, 2004). More recent work has viewed corruption from a developmental governance perspective, exploring the role of structures and networks, who benefits, and who is simply seeking to make a dysfunctional system work (Hutchinson et al., 2020). Sharing information about the activities of the health system has become much easier as a consequence of the internet. However, what is published must be honest and there should be no suspicion that information is being withheld. Freedom of information legislation can help but it is important to obey the spirit and not just the letter of the law. Laws to protect whistleblowers are important, although this can be difficult in societies characterized by widespread use of political patronage. Given the complex and multifaceted nature of trust, it can be challenging from a policymaking perspective to identify how to start building an agenda around fostering and maintaining trust within wider health system policies. Gille has developed evidence-based guidance and frameworks for considering the different elements and functions of trust and the factors that cultivate or undermine it (Gille, 2023). A simple conceptual framework provides a basis for thinking through and considering the different elements of trust, namely: 1) causal themes, that capture factors known to build public trust; 2) effect themes, that capture the outcome of establishing a trusting relationship between the public and health systems; and 3) framing themes, that capture what shapes public trust building (Gille, 2023). Taxonomies of the themes that fall within each of these elements are provided by Gille to complement the framework. All themes within these three elements need to be included when working with the framework, noting that it was developed in the context of researching how to build public trust in health system use of health data. Transference to other areas needs to be guided by careful modification using robust methods. Gille (2023) also outlines three core actions that are required to build public trust in health systems: 1. Develop a comprehensive understanding of public trust in the health system activity of focus. 2. Derive from point 1, develop: a. policy and governance actions that build public trust. b. communication strategies that build public trust. c. methods to collect reliable data about public trust. Policy implications and future directions 51 3. Collect data about public trust and evaluate if the public trust-building actions meet their targets. Policymakers, researchers and others are encouraged to refer to the guidance and frameworks developed by Gille (2023) when taking action to build public trust in health systems. 5.2 Widening participation in policymaking and implementation Trust will only be delivered if those affected can see that they are being listened to. This requires involvement of a wide range of stakeholders of all ages in key decisions. While many governments seek the views of stakeholders through formal consultations, these have limitations. They can be manipulated, especially in a world where it is possible to deluge websites with responses that give a misleading impression of the breadth of opinion. Responses to such consultations can also be shaped by the phrasing of the questions. There are better alternatives to static consultations, such as employing deliberative decision-making. One example is the use of citizens’ assemblies in which a group of individuals, say 100, are selected purposively to be representative of the range of views on a subject. They meet together over a period of time, alongside experts and others who can supply evidence and opinions and make recommendations. In some cases, these have been a valuable prelude to legislation on contentious issues, such as abortion in Ireland (Farrell et al., 2019) or choices around access to and coverage of medicines in Canada (Public Policy Forum, 2018). At the clinical front line there is enormous scope for co-production, an approach that is now informed by a rapidly growing literature. Co-production allows those most affected, whether patients, carers or clinicians, to find solutions that are practical in a given context (Turk et al., 2021). An example was a cluster randomized trial seeking optimal packages of care for hypertension in two middle-income countries (Schwalm et al., 2019). Although the packages shared certain features such as the use of simplified treatment regimes, mid-level health workers and peer support, the actual packages were developed by working with the communities over a year, and they both achieved significant improvements in outcomes. This requires trust, built through shared values, mutual respect and open communication, but just as important, acknowledging and addressing power imbalances in co-production, which can undermine trust and lead to unequal outcomes (Romsland et al., 2019). It is axiomatic that democratic principles and values are the foundation of a participatory space. Such a space for health, especially one where visible efforts are being made to equalize the balance of power, requires inclusion of voices Trust: the foundation of health systems52 heard through demonstrations, protests, strikes, petitions and other campaigns. Taking unsolicited public engagement seriously can help to overcome social and political power barriers (Matos & Serapioni, 2017; Nelson et al., 2018). At the very least, acknowledging the messages that the population, communities and civil society put across to policymakers via such means increases the level of trust between population and government. Free and active media are also important, with many examples of activities that undermine trust being exposed by investigative journalists (O’Donovan et al., 2019). When this happens, the reaction should not be defensive. Rather, those in charge should make clear that they will learn from what happened and implement change to rebuild trust and trustworthiness. Similar principles apply to the other relationships involving trust. Given the challenges currently facing health workforces, measures that increase staff retention must be a high priority. These must include a commitment to build the trust of those whom the system seeks to retain. It is beyond the scope of this book to discuss the literature on industrial relations. It is, however, within its scope to note that strikes by health workers should never happen and, when they do, it is a sign that something has gone very badly wrong (Weil et al., 2013). It is therefore not coincidental that protests by health workers were seen across the world during the latter stages of the COVID-19 pandemic and since then (Brophy et al., 2022). There are, however, emerging examples of novel approaches to building or restoring trust among clinicians which draw on core elements of trust building, namely meaningful engagement based on listening with humility and providing constructive and transparent feedback (Khullar, 2019). A notable example is a programme implemented by an organization in Hawaii in the United States, named Getting Rid of Stupid Stuff (Ashton, 2018). Recognizing that electronic health records commonly fuel clinician discontent, health system leaders established an intranet email system dedicated to collecting reports from clinicians about processes they identified as being poorly designed or unnecessary. A small group of people were assigned to monitor the email reports, taking action by working with an information technology team to correct the issue and providing clinicians with a summary of what had been actioned. The programme, which was welcomed by clinicians, was extended to other frustrating or unnecessary health care delivery activities (Ashton, 2018). For patients and the public, we know that social participation (used as an encompassing term for public participation, deliberation and other modes of direct involvement) plays a crucial role in building trust within health systems, underpinning optimal relationships between governments, health care institutions, civil society and the community (World Health Organization, 2021). It is also Policy implications and future directions 53 fundamental to involving individuals and patients in the co-creation that genuine and trustworthy health system transformation necessitates. Social participation mechanisms seek to enable civil society and the public, including young people, to be informed and engaged in health care decision- making processes. Civil society organizations can play an important role in these processes and should be encouraged. There is now an extensive literature on social accountability, highlighting the importance of active and engaged civil society organizations, supportive interlocutors within institutions, and access to information. When people have access to information and can actively participate in discussions about health care policies, they are more likely to trust that decisions are being made transparently and accountably. For instance, in Sweden citizens participate in the planning and allocation of health care resources through local health councils, fostering trust in the health care system’s fairness and openness. Here, however, it is important to note that information is critical but not sufficient. The top down bombardment of individuals with information, often in a format and language they are unable to engage with, can be counterproductive when looking to build trust (Thiede, 2005). The engagement and better use of community health workers, especially in working with minority or marginalized groups who may traditionally not trust health workers or the health systems for whatever reason, can be a high-return investment at comparatively low cost (even if this is not always the case) – especially in ensuring that information is communicated and shared in a helpful manner (Capotescu et al., 2022). Additionally, social participation ensures that a diverse range of voices and perspectives are considered. Through a process of shared decision-making, a sense of ownership, power diffusion and responsibility for health outcomes is fostered. However, it is necessary to avoid engagement that is merely tokenistic, marginalizing individuals with experiential knowledge. This not only fails to influence policy but also carries significant risks, including erosion of trust between stakeholders and in the participatory process itself. It is much less clear what can be done to restore trust of politicians in health systems, reassuring them that any additional resources will be spent wisely. Robust health technology assessment functions and health system functioning assessment more generally may help but, ultimately, success is likely to emerge from shared visions and excellent communication, including when it is realistic to expect an impact. An area in need of greater attention and research is the proposal that strengthening of trust between policymakers and their health systems could be facilitated by creating opportunities for more high-quality, in person interactions between the policymakers who govern health systems, the health system administrators who manage health facilities and are responsible for health staff, and those who deliver care (Khullar, 2019). This includes providing Trust: the foundation of health systems54 them with opportunities to gain a greater appreciation of each other’s roles and the challenges they face by, for example, work place visits and shadowing experiences (Khullar, 2019). Finally, this book has discussed a series of more specialized issues, of which the most important is likely to be AI, given the pace of technological change. This will require those engaged in health policy to develop and continually transform governance and regulatory systems as technology advances and more is learned about the impacts and uses of AI, ensuring that policymakers and those within the health system are empowered with the knowledge and skills they need to work with AI to the benefit of patients and populations while preventing the harms. 5.3 Focusing on trust as an opportunity To conclude this chapter, we want to emphasize the opportunities offered by a focus on trust that recognizes its importance for health systems. Health systems across Europe are faced with the multiple challenges of recovering from the COVID-19 pandemic and addressing its ongoing impacts, responding to changing health care and public health needs, and transforming to ensure resilience and sustainability in a world facing concurrent environmental crises, unprecedented technological advances, and adverse geopolitical developments. While examples of progress have been observed, major inequities remain, with many people still unable to access or afford the care they need when they need it. In some places, health system responsiveness and quality are declining rather than improving, with inequalities and inequities widening, unmet needs growing and trust diminishing. Engaging with and working in partnership with those whose trust we seek to gain and protect points to novel, effective and just ways of health policymaking and health system transformation, with a view to ensuring that everyone receives the care they need, and that the health system is not only trusted but also trustworthy. The question is not should we focus on trust in health systems? Instead, we must ask what will it take to ensure trust in health systems and trustworthiness are afforded the priority and investment they deserve? Appendix I Measuring trust in European health systems This appendix provides an overview of initiatives conducted globally that assess levels of trust as one of their objectives. It aims to give the reader an introductory understanding of the types of programmes that capture some form of trust and of the types of challenges that may influence efforts to measure, compare and track levels of trust in diverse and dynamic contexts, and applies these to the European context. Measuring trust Despite its importance, there is no single source of data on trust in health systems and related issues in Europe. Instead, there are a variety of sources that track levels of interpersonal trust and trust in certain institutions. These collate data from household surveys using various methodologies. However, caution is needed. The methodological challenges involved have been reviewed in detail in a publication from the Organisation for Economic Co-operation and Development (OECD) (OECD, 2017). It showed that the best questions are those that are easily understood, unambiguous and place minimal burden on the respondent. It is also necessary to consider how words, concepts and meanings translate across languages and subgroups who use a given language, such as ethnic minorities, social classes or people with different levels of education. The OECD report emphasizes the importance of question wording, citing evidence, which mostly relates to questions on interpersonal trust, that relatively minor changes can have a large effect. When a caution rider is added, such as “Do you think most people can be trusted?” or “Do you need to be careful in dealing with people?”, the percentage expressing trust can fall substantially. Importantly, the effect is different for male and female respondents. The literature is less extensive on institutional trust, but the report cites evidence that expanding the question “Do you think x can be trusted?” to include the words “to act in the national interest” increases reported trust with national institutions, except for banks (noting that the research in question was conducted in the aftermath of the 2007–2008 financial crisis). Trust: the foundation of health systems56 Other considerations include response formats, with evidence that an 11-point scale (0-10), accompanied by scale anchors (completely, not at all, etc.) is optimal. The placement or order of questions within surveys is also important. In general, the report argues that asking questions on trust after ones that may cause the respondent to recall negative experiences yields lower reported trust. It therefore recommends placing them early in a survey and beginning with trust in general before moving on to more specific questions. Is trust in health systems measured in Europe? Although there are a number of cross-country surveys conducted regularly in Europe, such as the Eurobarometer (European Union, 2007) and EU-SILC (European Union statistics on income and living conditions) (Arora et al., 2015), they rarely ask about trust in health systems. Thus, recognizing the importance of trust in governance more generally, the OECD has begun to survey public trust in certain institutions. However, the number of countries in Europe that are included remains limited (Fig. 3). Moreover, there are so far no time series. The OECD also surveys trust that personal data will be used appropriately, an important concern given the increasing dependence of health systems on data. Again, the data are limited in coverage and time but do offer some insights (Fig. 4). Other surveys that capture selected characteristics of health systems in smaller groups of countries could be used to measure trust. One is the Commonwealth Fund International Health Policy Survey (Commonwealth Fund, 2024), which is regularly updated and seeks insights into public opinions on health care. This survey examines issues such as access to care and health care costs, although it tends to focus on questions that are of most interest to American audiences. Perhaps the most relevant, for the purposes of this book, is data published commercially by Statista, which covers a small number of European countries (Fig. 5). Recently the Edelman Trust Barometer, which claims to be the “world’s leading authority on trust”, began looking at trust and health in the context of COVID-19. In 2022 it conducted its first survey spanning 10 countries and 10 000 respondents (1000 per country). Based on a binary question as to whether the pandemic had increased or decreased their trust in the health system, 52% said it had decreased their trust. In the European countries this was 57% in France, 50% in Germany and 49% in the United Kingdom. Japan at 71% and China at 30% were at the poles (Edelman, 2023a). In 2023 they undertook another survey, this time focusing more on individuals and their own health management, asking more specific questions about trust in health care providers, professionals and employers, and what the broader health ecosystem can do (Edelman, 2023b). The headline finding was that “Good health feels further out of reach”, a 14% increase from the 2022 report but, given the different questions asked, this reflected economic 57Appendix I: Measuring trust in European health systems concerns, inflation and the cost of living, and a growing burden of poor mental health, rather than a declining degree of trust in the health system. Fig. 3 Trust in institutions in selected countries, 2021 0 25 50 75 100 Courts and legal systemCivil serviceLocal governmentNational government Pe rc en ta ge re po rti ng tr us t No rw ay Fin lan d Lu xe m bo ur g Ire lan d Ice lan d Ne th er lan ds De nm ar k Es to nia Po rtu ga l Sw ed en Un ite d Ki ng do m Be lgi um Fr an ce Au str ia La tvi a Source: OECD (2023) Fig. 4 Percentage of respondents saying it is likely that their personal data will be used for legitimate purposes 0% 25% 50% 75% 100% IrelandDenmarkIcelandNetherlandsNorwayEstoniaLuxembourgAustriaSwedenUnited Kingdom PortugalBelgiumFranceLatvia Source: OECD (2023) Trust: the foundation of health systems58 Fig. 5. Share of individuals who trust the health care system in their country to provide them with the best treatment in selected European countries in 2023 0% 25% 50% 75% 100% Strongly/tend to disagree Not sure Strongly/tend to agree Hungary Poland Italy Türkiye Germany Sweden United Kingdom France Spain Netherlands (Kingdom of) Belgium Switzerland Strongly / tend to disagreeNot sureStrongly / tend to agree Notes: Responses to question “To what extent do you agree or disagree with the following statement? I trust the health care system in my country to provide me with the best treatment.” Sample size: 1000 per country. Fieldwork July/August 2023. Source: Statista (2023) The Wellcome Trust Global Monitor, conducted by Gallup, is the world’s largest study into how people around the world think and feel about science and major health challenges (Wellcome Trust, 2020). It surveys over 140 000 people from more than 140 countries, including over 40 000 from Europe. It includes important data on public trust in science and medicine, which emerged as a key issue during the COVID-19 pandemic. The findings reveal substantial variations, in some cases even between seemingly similar countries (Fig. 6 and Fig. 7). As discussed in Section 1.2, the People’s Voice Survey is a novel population survey that gathers data from 15 low-income, middle-income and high-income countries globally, including Greece, Italy and the United Kingdom. The survey captures public perceptions of their health systems, including their experience of care, their confidence in the health system’s ability to provide them with the care they need, and their confidence that such care is affordable (Kruk et al., 2024). There are, however, many important gaps in data on trust in European countries. One example is trust in particular institutions. Although there are examples of 59Appendix I: Measuring trust in European health systems surveys of public perceptions, such as that on the United Kingdom’s National Health Service conducted by the Health Foundation (Wise, 2023), they have not been standardized and brought together in one place. The importance of regular monitoring is apparent from analyses using data from the RAND American Life Panel that showed declining trust in the United States Centers for Disease Control during the COVID-19 pandemic (Pollard & Davis, 2022). This noted the known low level of trust among the African American population but also that levels of trust among Hispanics and non-Hispanic whites declined to the level seen in African Americans. This decline was closely aligned with political affiliation, reflecting the tenor of political discourse at the time. In summary, the state of knowledge on trust in health systems in Europe remains fragmentary. Given its importance for health systems, especially as they seek to implement the transformations that will be necessary to adapt to future challenges, there is a need to collect appropriate data with sufficient granularity to assess differences within populations and with sufficient regularity to track changes over time. Fig. 6 Share of respondents who answered “a lot” to the question: “How much do you trust scientists in this country?” COUNTRY VALUE (%) Albania 12 Austria 47 Belarus 16 Belgium 64 Bosnia and Herzegovina 10 Bulgaria 23 Croatia 28 Cyprus 35 Czechia 40 Denmark 60 Estonia 28 Finland 62 France 54 Germany 56 Greece 27 Hungary 29 Iceland 54 Ireland 58 Italy 45 Norway 52 Poland 29 Portugal 50 Romania 43 Russian Federation 29 Serbia 24 Slovakia 24 Slovenia 48 Spain 71 Sweden 52 Switzerland 46 Ukraine 19 United Kingdom 50 60%+ 50–59% 40–49% 30–39% 20–29% <20% Latvia Lithuania Luxembourg Macedonia Malta Republic of Moldova Montenegro Netherlands 53 16 34 39 12 36 9 8 Source: Authors’ analysis of data from Wellcome Trust (2020) Trust: the foundation of health systems60 Fig. 7 Share of respondents who answered “a lot” to the question: “How much do you trust doctors and nurses in this country?” Albania 30 Austria 65 Belarus 18 Belgium 77 Bosnia and Herzegovina 21 Bulgaria 27 Croatia 54 Cyprus 29 Czechia 56 Denmark 74 Estonia 34 Finland 73 France 68 Germany 66 Greece 30 Hungary 32 Iceland 71 Ireland 65 Italy 27 Netherlands 74 Latvia 19 Lithuania 39 Luxembourg 67 Macedonia 29 Malta 73 Republic of Moldova 20 Montenegro 18 Norway 78 Poland 32 Portugal 54 Romania 43 Russian Federation 22 Serbia 28 Slovakia 30 Slovenia 47 Spain 78 Sweden 67 Switzerland 63 Ukraine 14 United Kingdom 66 70%+ 60–69% 50–59% 40–49% 30–39% <30% COUNTRY VALUE (%) Source: Authors’ analysis of data from Wellcome Trust (2020) References Adler, J. E. (1994). Testimony, trust, knowing. The Journal of Philosophy, 91(5):264–275. Aksoy, C., Eichengreen, B., & Saka, O. (2022). COVID-19 and Trust among the young. Washington, DC, International Monetary Fund, F&D June 2022 issue (https://www.imf. org/en/Publications/fandd/issues/2022/06/COVID-19-and-trust-among-the-young-aksoy- eichengreen-saka). Alexander, M. (2023). Could Lucy Letby have been stopped sooner? Look at the timeline – and NHS history. The Guardian (London), 18 August 2023 (https://www.theguardian.com/ commentisfree/2023/aug/18/lucy-letby-stopped-sooner-nhs-deaths, accessed 21 August 2023). Allport, G. W., & Postman, L. (1947). The Psychology of Rumor. New York, NY, Henry Holt. Angwin, J., Tobin, A., & Varner, M. (2017). Facebook (Still) Letting Housing Advertisers Exclude Users by Race. New York, NY, ProPublica (https://www.propublica.org/article/facebook- advertising-discrimination-housing-race-sex-national-origin, accessed 11 June 2023). Arnold, K. F., Gilthorpe, M. S., Alwan, N. A., Heppenstall, A. J., Tomova, G. D., McKee, M., & Tennant, P. W. G. (2022). Estimating the effects of lockdown timing on COVID-19 cases and deaths in England: A counterfactual modelling study. PLoS One, 17(4):e0263432. https:// doi.org/10.1371/journal.pone.0263432 Arora, V. S., Karanikolos, M., Clair, A., Reeves, A., Stuckler, D., & McKee, M. (2015). Data Resource Profile: The European Union Statistics on Income and Living Conditions (EU-SILC). International Journal of Epidemiology, 44(2):451–461. https://doi.org/10.1093/ije/dyv069 Arrieta, A. B., Díaz-Rodríguez, N., Del Ser, J., Bennetot, A., Tabik, S., Barbado, A., García, S., Gil-López, S., Molina, D., & Benjamins, R. (2020). Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI. Information Fusion, 58:82–115. Arrow, K. J. (1978). Uncertainty and the welfare economics of medical care. In: Diamond, P. & Rothschild, M., eds. Uncertainty in Economics. Amsterdam, Elsevier:345–375. Asan, O., Bayrak, A. E., & Choudhury, A. (2020). Artificial Intelligence and Human Trust in Healthcare: Focus on Clinicians. Journal of Medical Internet Research, 22(6):e15154. https:// doi.org/10.2196/15154 Ashton, M. (2018). Getting Rid of Stupid Stuff. New England Journal of Medicine, 379(19):1789– 1791. https://doi.org/10.1056/NEJMp1809698 Attaran, A., Barry, D., Basheer, S., Bate, R., Benton, D., Chauvin, J., Garrett, L., Kickbusch, I., Kohler, J. C., Midha, K., Newton, P. N., Nishtar, S., Orhii, P., & McKee, M. (2012). How to achieve international action on falsified and substandard medicines. BMJ, 345:e7381. https://doi.org/10.1136/bmj.e7381 Trust: the foundation of health systems62 Ayers, J. W., Poliak, A., Dredze, M., Leas, E. C., Zhu, Z., Kelley, J. B., Faix, D. J., Goodman, A. M., Longhurst, C. A., & Hogarth, M. (2023). Comparing physician and artificial intelligence chatbot responses to patient questions posted to a public social media forum. JAMA Internal Medicine, 183(6):589–596. Azar, C., Allué, D., Valnet-Rabier, M. B., Chouchana, L., Rocher, F., Durand, D., Grené-Lerouge, N., Saleh, N., & Maison, P. (2021). Patterns of medication errors involving pediatric population reported to the French Medication Error Guichet. Pharmacy Practice (Granada), 19(2). Badur, S., Ota, M., Öztürk, S., Adegbola, R., & Dutta, A. (2020). Vaccine confidence: the keys to restoring trust. Human Vaccines & Immunotherapeutics, 16(5):1007–1017. Baier, A. (1986). Trust and antitrust. Ethics, 96(2):231–260. Baker, J. (1987). Trust and rationality. Pacific Philosophical Quarterly, 68(1):1–13. Balliet, D., Wu, J., & De Dreu, C. K. (2014). Ingroup favoritism in cooperation: a meta-analysis. Psychological Bulletin, 140(6):1556–1581. https://doi.org/10.1037/a0037737 Bargain, O., & Aminjonov, U. (2020). Trust and compliance to public health policies in times of COVID-19. Journal of Public Economics, 192:104316. Baroudi, M., Goicolea, I., Hurtig, A.-K., & San-Sebastian, M. (2022). Social factors associated with trust in the health system in northern Sweden: a cross-sectional study. BMC Public Health, 22(1):1–8. Bavli, I. (2023). When Public Health Goes Wrong: Toward a New Concept of Public Health Error. Journal of Law, Medicine & Ethics, 51(2):385-402. https://doi.org/10.1017/jme.2023.67 Beller, J., Schäfers, J., Haier, J., Geyer, S., & Epping, J. (2022). Trust in Healthcare during COVID-19 in Europe: Vulnerable groups trust the least. Journal of Public Health, 31:1495– 1504. Benkert, R., Cuevas, A., Thompson, H. S., Dove-Meadows, E., & Knuckles, D. (2019). Ubiquitous Yet Unclear: A Systematic Review of Medical Mistrust. Behavioral Medicine, 45(2):86–101. https://doi.org/10.1080/08964289.2019.1588220 Berg, J., Dickhaut, J., & McCabe, K. (1995). Trust, reciprocity, and social history. Games and Economic Behavior, 10(1):122–142. Berger-Schmitt, R. (2002). Considering social cohesion in quality of life assessments: Concept and measurement. Social Indicators Research, 58(1–3):403–428. Bettinger, B. M. (2016). Game theory and mechanism design for cooperative competition dilemmas between healthcare providers [doctoral dissertation]. Boston, MA, Northeastern University. Blake, A., & Carroll, B. T. (2016). Game theory and strategy in medical training. Medical Education, 50(11):1094–1106. Bollyky, T. J., Angelino, O., Wigley, S., & Dieleman, J. L. (2022). Trust made the difference for democracies in COVID-19. Lancet, 400(10353):657. https://doi.org/10.1016/s0140- 6736(22)01532-x Bor, A., Jørgensen, F., & Petersen, M. B. (2023). The COVID-19 pandemic eroded system support but not social solidarity. PLoS One, 18(8):e0288644. Branley-Bell, D., Brown, R., Coventry, L., & Sillence, E. (2023). Chatbots for embarrassing and stigmatizing conditions: could chatbots encourage users to seek medical advice? Frontiers in Communication, 8:1275127. Brennan, N., Barnes, R., Calnan, M., Corrigan, O., Dieppe, P., & Entwistle, V. (2013). Trust in the health-care provider-patient relationship: a systematic mapping review of the evidence base. International Journal for Quality in Health Care, 25(6):682–688. https://doi.org/10.1093/ intqhc/mzt063 References 63 Broniatowski, D. A., Jamison, A. M., Qi, S., AlKulaib, L., Chen, T., Benton, A., Quinn, S. C., & Dredze, M. (2018). Weaponized Health Communication: Twitter Bots and Russian Trolls Amplify the Vaccine Debate. American Journal of Public Health, 108(10):1378–1384. https:// doi.org/10.2105/ajph.2018.304567 Brophy, S. A., Sriram, V., Zong, H., Andres, C., Mawyin, M. P., & Lakshmi, N. G. (2022). Heroes on strike: Trends in global health worker protests during COVID-19. Washington, DC, Accountability Research Centre (Accountability Note) (https://accountabilityresearch. org/publication/heroes-on-strike-trends-in-global-health-worker-protests-during-COVID-19/, accessed 7 May 2024). Brown, P., Calnan, M., Scrivener, A., & Szmukler, G. (2009). Trust in mental health services: A neglected concept. Journal of Mental Health, 18(5):449–458. Bruine de Bruin, W., Saw, H. W., & Goldman, D. P. (2020). Political polarization in US residents’ COVID-19 risk perceptions, policy preferences, and protective behaviors. Journal of Risk and Uncertainty, 61(2):177–194. https://doi.org/10.1007/s11166-020-09336-3 Buchanan, M. (2020). Managing the infodemic. Nature Physics, 16(9):894–894. Burrell, J. (2016). How the machine ‘thinks’: Understanding opacity in machine learning algorithms. Big Data & Society, 3(1):2053951715622512. Cabitza, F., Campagner, A., & Sconfienza, L. M. (2020). As if sand were stone. New concepts and metrics to probe the ground on which to build trustable AI. BMC Medical Informatics and Decision Making, 20(1):219. https://doi.org/10.1186/s12911-020-01224-9 Cairney, P., & Wellstead, A. (2021). COVID-19: effective policymaking depends on trust in experts, politicians, and the public. Policy Design and Practice, 4(1):1–14. https://doi.org /10.1080/25741292.2020.1837466 Calnan, M., & Rowe, R. (2006). Researching trust relations in health care: conceptual and methodological challenges--introduction. Journal of Health Organization and Management, 20(5):349–358. https://doi.org/10.1108/14777260610701759 Cammett, M., Lynch, J., & Bilev, G. (2015). The Influence of Private Health Care Financing on Citizen Trust in Government. Perspectives on Politics, 13(4):938–957. https://doi.org/10.1017/ S1537592715002248 Capotescu, C., Chodon, T., Chu, J., Cohn, E., Eyal, G., Goyal, R., Ige, O., LaViolette, J., Mallik, S., Phillips, L. M., Spencer, P., & Tomson, D. L. (2022). Community health workers’ critical role in trust building between the medical system and communities of color. American Journal of Managed Care, 28(10):497–499. https://doi.org/10.37765/ajmc.2022.89247 Carter, J. A. (2020). On behalf of a bi-level account of trust. Philosophical Studies, 177(8):2299–2322. Chan, K. (2023). Musk’s X is the biggest purveyor of disinformation, EU official says. New York, NY, The Associated Press (https://apnews.com/article/disinformation-musk-x-twitter-european- union-9f7823726f812bb357ee4225b884354f, accessed 7 May 2024). Chapman, G. B., Li, M., Vietri, J., Ibuka, Y., Thomas, D., Yoon, H., & Galvani, A. P. (2012). Using game theory to examine incentives in influenza vaccination behavior. Psychological Science, 23(9):1008–1015. Chesney, B., & Citron, D. (2019). Deep fakes: A looming challenge for privacy, democracy, and national security. California Law Review, 107:1753. Chimonas, S., Mamoor, M., Zimbalist, S. A., Barrow, B., Bach, P. B., & Korenstein, D. (2021). Mapping conflict of interests: scoping review. BMJ, 375:e066576. https://doi.org/10.1136/ bmj-2021-066576 Citrin, J., & Stoker, L. (2018). Political trust in a cynical age. Annual Review of Political Science, 21:49–70. Trust: the foundation of health systems64 Clark, M., & Severn, M. (2023). Artificial Intelligence in Prehospital Emergency Health Care: CADTH Horizon Scan. Ottawa, ON, Canadian Agency for Drugs and Technologies in Health (https://www.ncbi.nlm.nih.gov/books/NBK596747/, accessed 7 May 2024). Commonwealth Fund. (2024). Commonwealth Fund international health policy survey. New York, NY, Commonwealth Fund (https://www.commonwealthfund.org/trending/international- health-policy-survey, accessed 27 May 2024). Costa-Font, J., & Vilaplana-Prieto, C. (2023). Trusting the Health System and COVID 19 Restriction Compliance. Economics & Human Biology, 49:101235. https://doi.org/https:// doi.org/10.1016/j.ehb.2023.101235 Covello, V. T. (1993). Risk communication and occupational medicine. Journal of Occupational Medicine, 35(1):18–19. Dann, C. (2022). Does public trust in government matter for effective policy-making? Bristol, UK, Economics Observatory (https://www.economicsobservatory.com/does-public-trust-in- government-matter-for-effective-policy-making, accessed 26 October 2023). Deakin, M. (2023). Doctors’ strikes: the NHS faces its toughest test yet. BMJ, 382:2143. https:// doi.org/10.1136/bmj.p2143 Delhey, J., Dragolov, G., & Boehnke, K. (2018). Social cohesion and well-being in Europe. Dublin, Eurofound (https://www.eurofound.europa.eu/en/publications/2018/social-cohesion-and- well-being-europe, accessed 7 June 2024). DeSteno, D. (2014). The truth about trust: How it determines success in life, love, learning, and more. s.l., Penguin. DeSteno, D., Breazeal, C., Frank, R. H., Pizarro, D., Baumann, J., Dickens, L., & Lee, J. J. (2012). Detecting the trustworthiness of novel partners in economic exchange. Psychological Science, 23(12):1549–1556. https://doi.org/10.1177/0956797612448793 Devine, D., Valgarðsson, V., Smith, J., Jennings, W., Scotto di Vettimo, M., Bunting, H., & McKay, L. (2023). Political trust in the first year of the COVID-19 pandemic: a meta-analysis of 67 studies. Journal of European Public Policy, 31(3):657–679. Doherty, T. S., & Carroll, A. E. (2020). Believing in Overcoming Cognitive Biases. AMA Journal of Ethics, 22(9):E773–778. https://doi.org/10.1001/amajethics.2020.773 Domenicucci, J., & Holton, R. (2017). Trust as a two-place relation. In: Faulkner, P. & Simpson, T., eds. The philosophy of trust. Oxford, Oxford University Press:149–160. Donzelli, G., Palomba, G., Federigi, I., Aquino, F., Cioni, L., Verani, M., Carducci, A., & Lopalco, P. (2018). Misinformation on vaccination: A quantitative analysis of YouTube videos. Human Vaccines & Immunotherapeutics, 14(7):1654–1659. https://doi.org/10.1080/21645515.20 18.1454572 Drury, J. (2018). The role of social identity processes in mass emergency behaviour: An integrative review. European Review of Social Psychology, 29(1):38–81. Drury, J., Reicher, S., & Stott, C. (2020). COVID‐19 in context: Why do people die in emergencies? It’s probably not because of collective psychology. British Journal of Social Psychology, 59(3):686–693. Duijn, C. C. M. A., Welink, L. S., Bok, H. G. J., & Ten Cate, O. T. J. (2018). When to trust our learners? Clinical teachers’ perceptions of decision variables in the entrustment process. Perspectives on Medical Education, 7(3):192–199. https://doi.org/10.1007/s40037-018- 0430-0 Duncan, C., Tölch, U., Walter, H., & Dziobek, I. (2023). Ethnic discrimination unlearned: experience in the repeated Trust Game reduces trust bias. Frontiers in Psychology, 14:1139128. https://doi.org/10.3389/fpsyg.2023.1139128 References 65 Duval, L., Wolff, F. C., McKee, M., & Roberts, B. (2016). The Roma vaccination gap: Evidence from twelve countries in Central and South-East Europe. Vaccine, 34(46):5524–5530. https:// doi.org/10.1016/j.vaccine.2016.10.003 Easton, D. (1975). A re-assessment of the concept of political support. British Journal of Political Science, 5(4):435–457. Edelman. (2023a). 2022 Edelman Trust Barometer. Special Report: Trust and Health. s.l., Edelman (https://www.edelman.com/trust/22/special-report-trust-in-health, accessed 6 May 2024). Edelman. (2023b). 2023 Edelman Trust Barometer. Special Report: Trust and Health. s.l., Edelman (https://www.edelman.com/trust/2023/trust-barometer/special-report-health, accessed 6 May 2024). Eichengreen, B., Aksoy, C. G., & Saka, O. (2021). Revenge of the experts: Will COVID-19 renew or diminish public trust in science? Journal of Public Economics, 193:104343. https://doi. org/https://doi.org/10.1016/j.jpubeco.2020.104343 Eklund, J. H., Holmström, I. K., Kumlin, T., Kaminsky, E., Skoglund, K., Höglander, J., Sundler, A. J., Condén, E., & Meranius, M. S. (2019). “Same same or different?” A review of reviews of person-centered and patient-centered care. Patient Education and Counseling, 102(1):3–11. Elbaum, A. (2020). Earning Patient Trust: More Than a Question of Signaling. Hastings Center Report, 50(1):29–31. https://doi.org/10.1002/hast.1082 European Union. (2007). Eurobarometer 68. Brussels, European Commission Directorate-General for Communication (https://europa.eu/eurobarometer/surveys/detail/664, accessed 27 May 2024). European Union. (2024). EP Spring 2024 Survey: Use your vote - Countdown to the European elections. Brussels, European Commission Directorate-General for Communication (https:// europa.eu/eurobarometer/surveys/detail/3272, accessed 7 May 2024). Evans, T., Retzlaff, C. O., Geißler, C., Kargl, M., Plass, M., Müller, H., Kiehl, T.-R., Zerbe, N., & Holzinger, A. (2022). The explainability paradox: Challenges for xAI in digital pathology. Future Generation Computer Systems, 133:281–296. Falkenbach, M., & Willison, C. (2022). Resources or trust: What matters more in the vaccination strategies of high-income liberal democracies? Health Policy and Technology, 11(2):100618. https://doi.org/10.1016/j.hlpt.2022.100618 Fancourt, D., Steptoe, A., & Wright, L. (2020). The Cummings effect: politics, trust, and behaviours during the COVID-19 pandemic. Lancet, 396(10249):464–465. https://doi.org/10.1016/ s0140-6736(20)31690-1 Farrell, D. M., Suiter, J., & Harris, C. (2019). ‘Systematizing’constitutional deliberation: the 2016–18 citizens’ assembly in Ireland. Irish Political Studies, 34(1):113–123. Farzanegan, M. R., & Hofmann, H. P. (2022). A matter of trust? Political trust and the COVID-19 pandemic. International Journal of Sociology, 52(6):476–499. Faulkner, P. (2011). Knowledge on Trust. Oxford, Oxford University Press. Faulkner, P., & Simpson, T. (2017). The problem of trust. In: Faulkner, P. & Simpson, T., eds. The philosophy of trust. Oxford, Oxford University Press:109–128. Ferreira, T., Collins, A. M., Feng, O., Samworth, R. J., & Horvath, R. (2023). Career intentions of medical students in the UK: a national, cross-sectional study (AIMS study). BMJ Open, 13(9):e075598. https://doi.org/10.1136/bmjopen-2023-075598 French, P. (2016). Younghusband: The last great imperial adventurer. s.l., Vintage. Fricker, E. (2018). Trust and Testimonial Justification. Midwest Epistemology Workshop, Notre Dame University, IN, 19-20 October. Fricker, M. (2007). Epistemic Injustice–Power and the Ethics of Knowing. Oxford, Oxford University Press. Trust: the foundation of health systems66 Fridman, I., Lucas, N., Henke, D., & Zigler, C. K. (2020). Association Between Public Knowledge About COVID-19, Trust in Information Sources, and Adherence to Social Distancing: Cross-Sectional Survey. JMIR Public Health and Surveillance, 6(3):e22060. https://doi. org/10.2196/22060 Frost-Arnold, K. (2014). The cognitive attitude of rational trust. Synthese, 191(9):1957–1974. Fuglsang, L., & Jagd, S. (2015). Making sense of institutional trust in organizations: Bridging institutional context and trust. Organization, 22(1):23–39. Fukuyama, F. (1996). Trust: The social virtues and the creation of prosperity. s.l., Simon and Schuster. Gaal, P., & McKee, M. (2004). Informal payment for health care and the theory of ‘INXIT’. International Journal of Health Planning and Management, 19(2):163–178. https://doi. org/10.1002/hpm.751 Gandjour, A. (2021). How Many Intensive Care Beds are Justifiable for Hospital Pandemic Preparedness? A Cost-effectiveness Analysis for COVID-19 in Germany. Applied Health Economics and Health Policy, 19(2):181–190. https://doi.org/10.1007/s40258-020-00632-2 García-Altés, A., McKee, M., Siciliani, L., Barros, P. P., Lehtonen, L., Rogers, H., Kringos, D., Zaletel, J., & De Maeseneer, J. (2023). Understanding public procurement within the health sector: a priority in a post-COVID-19 world. Health Economics, Policy and Law, 18(2):172–185. https://doi.org/10.1017/s1744133122000184 Gaube, S., Suresh, H., Raue, M., Lermer, E., Koch, T. K., Hudecek, M. F. C., Ackery, A. D., Grover, S. C., Coughlin, J. F., Frey, D., Kitamura, F. C., Ghassemi, M., & Colak, E. (2023). Non-task expert physicians benefit from correct explainable AI advice when reviewing X-rays. Scientific Reports, 13(1):1383. https://doi.org/10.1038/s41598-023-28633-w Gichoya, J. W., Banerjee, I., Bhimireddy, A. R., Burns, J. L., Celi, L. A., Chen, L. C., Correa, R., Dullerud, N., Ghassemi, M., Huang, S. C., Kuo, P. C., Lungren, M. P., Palmer, L. J., Price, B. J., Purkayastha, S., Pyrros, A. T., Oakden-Rayner, L., Okechukwu, C., Seyyed-Kalantari, L., . . . Zhang, H. (2022). AI recognition of patient race in medical imaging: a modelling study. Lancet Digital Health, 4(6):e406–e414. https://doi.org/10.1016/s2589-7500(22)00063-2 Gille, F. (2023). What is public trust in the health system? In: Gille, F. What Is Public Trust in the Health System? Bristol, UK, Policy Press:35–38. Gille, F., Smith, S., & Mays, N. (2022). Evidence-based guiding principles to build public trust in personal data use in health systems. Digital Health, 8:20552076221111947. https://doi. org/10.1177/20552076221111947 Gilmore, A. B., Fabbri, A., Baum, F., Bertscher, A., Bondy, K., Chang, H.-J., Demaio, S., Erzse, A., Freudenberg, N., Friel, S., Hofman, K. J., Johns, P., Abdool Karim, S., Lacy-Nichols, J., de Carvalho, C. M. P., Marten, R., McKee, M., Petticrew, M., Robertson, L., . . . Thow, A. M. (2023). Defining and conceptualising the commercial determinants of health. Lancet, 401(10383):1194–1213. https://doi.org/10.1016/S0140-6736(23)00013-2 Gilson, L. (2003). Trust and the development of health care as a social institution. Social Science & Medicine, 56(7):1453–1468. Goodair, B., & Reeves, A. (2024). The effect of health-care privatisation on the quality of care. Lancet Public Health, 9(3):e199–e206. https://doi.org/10.1016/S2468-2667(24)00003-3 Goodman, R. S., Patrinely, J. R., Stone, C. A., Jr., Zimmerman, E., Donald, R. R., Chang, S. S., Berkowitz, S. T., Finn, A. P., Jahangir, E., Scoville, E. A., Reese, T. S., Friedman, D. L., Bastarache, J. A., van der Heijden, Y. F., Wright, J. J., Ye, F., Carter, N., Alexander, M. R., Choe, J. H., . . . Johnson, D. B. (2023). Accuracy and Reliability of Chatbot Responses to Physician Questions. JAMA Network Open, 6(10):e2336483. https://doi.org/10.1001/ jamanetworkopen.2023.36483 References 67 Goold, S. D. (2001). Trust and the ethics of health care institutions. Hastings Center Report, 31(6):26–33. Green, M. A., McKee, M., & Katikireddi, S. V. (2022). Remote general practitioner consultations during COVID-19. Lancet Digital Health, 4(1):e7. https://doi.org/10.1016/s2589- 7500(21)00279-x Griffith, D. M., Bergner, E. M., Fair, A. S., & Wilkins, C. H. (2021). Using Mistrust, Distrust, and Low Trust Precisely in Medical Care and Medical Research Advances Health Equity. American Journal of Preventive Medicine, 60(3), 442–445. https://doi.org/10.1016/j. amepre.2020.08.019 Grote, T., & Berens, P. (2020). On the ethics of algorithmic decision-making in healthcare. Journal of Medical Ethics, 46(3):205–211. https://doi.org/10.1136/medethics-2019-105586 Hampshire, K., Hamill, H., Mariwah, S., Mwanga, J., & Amoako-Sakyi, D. (2017). The application of signalling theory to health-related trust problems: the example of herbal clinics in Ghana and Tanzania. Social Science & Medicine, 188:109–118. Han, Q., Zheng, B., Cristea, M., Agostini, M., Bélanger, J. J., Gützkow, B., Kreienkamp, J., & Leander, N. P. (2023). Trust in government regarding COVID-19 and its associations with preventive health behaviour and prosocial behaviour during the pandemic: a cross-sectional and longitudinal study. Psychological Medicine, 53(1):149–159. https://doi.org/10.1017/s0033291721001306 Hanifan, L. J. (1916). The Rural School Community Centre. Annals of the American Academy of Political and Social Sciences, 67:130–138. Hardin, R. (2002). Trust and trustworthiness. New York, NY, Russell Sage Foundation. Hardin, R. (2006). Trust. Cambridge, Polity. https://books.google.co.uk/books?id=XWwpRhX1tdsC Hawley, K. (2014). Trust, distrust and commitment. Noûs, 48(1):1–20. Hiam, L., Steele, S., & McKee, M. (2018). Creating a ‘hostile environment for migrants’: the British government’s use of health service data to restrict immigration is a very bad idea. Health Economics, Policy and Law, 13(2):107–117. https://doi.org/10.1017/s1744133117000251 Hieronymi, P. (2008). The reasons of trust. Australasian Journal of Philosophy, 86(2):213–236. Higgins, K. (2016). Post-truth: a guide for the perplexed. Nature, 540(7631):9. https://doi. org/10.1038/540009a Hillen, M. A., de Haes, H. C., & Smets, E. M. (2011). Cancer patients’ trust in their physician-a review. Psychooncology, 20(3):227–241. https://doi.org/10.1002/pon.1745 Hojat, M., Louis, D. Z., Maio, V., & Gonnella, J. S. (2013). Empathy and health care quality. American Journal of Medical Quality, 28(1):6–7. Holmes, D. (2013). Mid Staffordshire scandal highlights NHS cultural crisis. Lancet, 381(9866):521–522. Hudson, J. (2006). Institutional trust and subjective well‐being across the EU. Kyklos, 59(1):43–62. Hutchinson, E., Balabanova, D., & McKee, M. (2019). We Need to Talk About Corruption in Health Systems. International Journal of Health Policy and Management, 8(4):191–194. https://doi.org/10.15171/ijhpm.2018.123 Hutchinson, E., Naher, N., Roy, P., McKee, M., Mayhew, S. H., Ahmed, S. M., & Balabanova, D. (2020). Targeting anticorruption interventions at the front line: developmental governance in health systems. BMJ Global Health, 5(12). https://doi.org/10.1136/bmjgh-2020-003092 Imber, J. B. (2008). Trusting doctors: The decline of moral authority in American medicine. Princeton, NJ, Princeton University Press. Jenkins, R. (2013). How to convince politicians that mental health is a priority. World Psychiatry, 12(3):266–268. https://doi.org/10.1002/wps.20073 Trust: the foundation of health systems68 Jones, K. (1996). Trust as an affective attitude. Ethics, 107(1):4–25. Jones, S., Moulton, C., Swift, S., Molyneux, P., Black, S., Mason, N., Oakley, R., & Mann, C. (2022). Association between delays to patient admission from the emergency department and all-cause 30-day mortality. Emergency Medical Journal, 39(3):168–173. https://doi. org/10.1136/emermed-2021-211572 Jørgensen, F., Bor, A., Rasmussen, M. S., Lindholt, M. F., & Petersen, M. B. (2022). Pandemic fatigue fueled political discontent during the COVID-19 pandemic. Proceedings of the National Academy of Sciences, 119(48):e2201266119. https://doi.org/10.1073/pnas.2201266119 Kappes, A., Harvey, A. H., Lohrenz, T., Montague, P. R., & Sharot, T. (2020). Confirmation bias in the utilization of others’ opinion strength. Nature Neuroscience, 23(1):130–137. https:// doi.org/10.1038/s41593-019-0549-2 Katikireddi, S. V., Lal, S., Carrol, E. D., Niedzwiedz, C. L., Khunti, K., Dundas, R., Diderichsen, F., & Barr, B. (2021). Unequal impact of the COVID-19 crisis on minority ethnic groups: a framework for understanding and addressing inequalities. Journal of Epidemiology and Community Health, 75(10):970–974. https://doi.org/10.1136/jech-2020-216061 Keefe, P. R. (2021). Empire of Pain: The Secret History of the Sackler Dynasty. s.l., Doubleday Books. Kelley, J. M., Kraft-Todd, G., Schapira, L., Kossowsky, J., & Riess, H. (2014). The influence of the patient- clinician relationship on healthcare outcomes: a systematic review and meta-analysis of randomized controlled trials. PLoS One, 9(4):e94207. https://doi.org/10.1371/journal.pone.0094207 Khullar, D. (2019). Building Trust in Health Care—Why, Where, and How. JAMA, 322(6):507– 509. https://doi.org/10.1001/jama.2019.4892 Kingdon, J. W., & Stano, E. (1984). Agendas, alternatives, and public policies (Vol. 45:165–169). Boston, Little, Brown. Kinney, M., Seider, J., Beaty, A. F., Coughlin, K., Dyal, M., & Clewley, D. (2020). The impact of therapeutic alliance in physical therapy for chronic musculoskeletal pain: A systematic review of the literature. Physiotherapy Theory and Practice, 36(8):886–898. https://doi.org /10.1080/09593985.2018.1516015 Kluge, H., Azzopardi-Muscat, N., Figueras, J., & McKee, M. (2023). Trust and transformation: an agenda for creating resilient and sustainable health systems. BMJ, 380:651. https://doi. org/10.1136/bmj.p651 Knox, R. (2020). Insulin insulated: barriers to competition and affordability in the United States insulin market. Journal of Law and the Biosciences, 7(1):lsaa061. Koopman, B., & Zuccon, G. (2023). Dr ChatGPT tell me what I want to hear: How different prompts impact health answer correctness. Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, Singapore, 6–10 December. Kruk, M. E., Kapoor, N. R., Lewis, T. P., Arsenault, C., Boutsikari, E. C., Breda, J., Carai, S., Croke, K., Dayalu, R., Fink, G., Garcia, P. J., Kassa, M., Mohan, S., Moshabela, M., Nzinga, J., Oh, J., Okiro, E. A., Prabhakaran, D., SteelFisher, G. K., . . . Garcia-Elorrio, E. (2024). Population confidence in the health system in 15 countries: results from the first round of the People’s Voice Survey. Lancet Global Health, 12(1):e100–e111. https://doi.org/10.1016/S2214-109X(23)00499-0 Krumhuber, E. G., Kappas, A., & Manstead, A. S. (2013). Effects of dynamic aspects of facial expressions: A review. Emotion Review, 5(1):41–46. Kumpunen, S., Webb, E., Permanand, G., Zheleznyakov, E., Edwards, N., van Ginneken, E., & Jakab, M. (2022). Transformations in the landscape of primary health care during COVID-19: Themes from the European region. Health Policy, 126(5):391–397. https://doi.org/10.1016/j.healthpol.2021.08.002 Kwame, A., & Petrucka, P. M. (2021). A literature-based study of patient-centered care and communication in nurse-patient interactions: barriers, facilitators, and the way forward. BMC Nursing, 20(1):1–10. References 69 Lalot, F., Heering, M. S., Rullo, M., Travaglino, G. A., & Abrams, D. (2020). The dangers of distrustful complacency: Low concern and low political trust combine to undermine compliance with governmental restrictions in the emerging COVID-19 pandemic. Group Processes & Intergroup Relations, 25(1):106–121. https://doi.org/10.1177/1368430220967986 Lapuschkin, S., Binder, A., Montavon, G., Muller, K.-R., & Samek, W. (2016). Analyzing classifiers: Fisher vectors and deep neural networks. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Las Vegas, 27–30 June. Larson, H. J., & Lin, L. (2024). Generative artificial intelligence can have a role in combating vaccine hesitancy. BMJ, 384:q69. https://doi.org/10.1136/bmj.q69 Lenton, T. M., Boulton, C. A., & Scheffer, M. (2022). Resilience of countries to COVID-19 correlated with trust. Scientific Reports, 12(1):75. https://doi.org/10.1038/s41598-021- 03358-w Liao, Q. V., Gruen, D., & Miller, S. (2020). Questioning the AI: informing design practices for explainable AI user experiences. Proceedings of the 2020 CHI conference on human factors in computing systems, Honolulu, HI, 25–30 April. Lin H, Han J, Wu P, Wang J, Tu J, Tang H, & Zhu L. (2024). Machine learning and human‐ machine trust in healthcare: A systematic survey. CAAI Transactions on Intelligence Technology, 9(2):286–302. Lindström, M., Hanson, B. S., Östergren, P.-O., & Berglund, G. (2000). Socioeconomic differences in smoking cessation: the role of social participation. Scandinavian Journal of Public Health, 28(3):200–208. Linzer, M., Poplau, S., Prasad, K., Khullar, D., Brown, R., Varkey, A., Yale, S., Grossman, E., Williams, E., & Sinsky, C. (2019). Characteristics of Health Care Organizations Associated With Clinician Trust: Results From the Healthy Work Place Study. JAMA Network Open, 2(6):e196201. https://doi.org/10.1001/jamanetworkopen.2019.6201 Liu, C. F., Chen, Z. C., Kuo, S. C., & Lin, T. C. (2022). Does AI explainability affect physicians’ intention to use AI? International Journal of Medical Informatics, 168:104884. https://doi. org/10.1016/j.ijmedinf.2022.104884 López, L., Green, A. R., Tan-McGrory, A., King, R., & Betancourt, J. R. (2011). Bridging the digital divide in health care: the role of health information technology in addressing racial and ethnic disparities. Joint Commission Journal on Quality and Patient Safety, 37(10):437–445. https://doi.org/10.1016/s1553-7250(11)37055-9 Lorié, Á., Reinero, D. A., Phillips, M., Zhang, L., & Riess, H. (2017). Culture and nonverbal expressions of empathy in clinical settings: A systematic review. Patient Education and Counseling, 100(3):411–424. https://doi.org/10.1016/j.pec.2016.09.018 Lundh, P., Palmgren, P. J., & Stenfors, T. (2019). Perceptions about trust: a phenomenographic study of clinical supervisors in occupational therapy. BMC Medical Education, 19(1):404. https://doi.org/10.1186/s12909-019-1850-1 Marteau, T. M., Chater, N., & Garnett, E. E. (2021). Changing behaviour for net zero 2050. BMJ, 375:n2293. https://doi.org/10.1136/bmj.n2293 Martínez-Agüero, S., Soguero-Ruiz, C., Alonso-Moral, J. M., Mora-Jiménez, I., Álvarez-Rodríguez, J., & Marques, A. G. (2022). Interpretable clinical time-series modeling with intelligent feature selection for early prediction of antimicrobial multidrug resistance. Future Generation Computer Systems, 133:68–83. Mathews, C. J., McGuire, L., Joy, A., Law, F., Winterbottom, M., Rutland, A., Drews, M., Hoffman, A. J., Mulvey, K. L., & Hartstone-Rose, A. (2021). Assessing adolescents’ critical health literacy: How is trust in government leadership associated with knowledge of COVID-19? PLoS One, 16(11):e0259523. https://doi.org/10.1371/journal.pone.0259523 Trust: the foundation of health systems70 Matos, A. R., & Serapioni, M. (2017). O desafio da participação cidadã nos sistemas de saúde do Sul da Europa: uma revisão da literatura [The challenge of citizens’ participation in health systems in Southern Europe: a literature review]. Cadernos de Saude Publica, 33(1):e00066716. https://doi.org/10.1590/0102-311x00066716 McKee, M. (2020). England’s PPE procurement failures must never happen again. BMJ, 370:m2858. https://doi.org/10.1136/bmj.m2858 McKee, M. (2021). Drawing light from the pandemic: a new strategy for health and sustainable development. Copenhagen, European Observatory on Health Systems and Policies https:// iris.who.int/handle/10665/345027, accessed 1 October 2023). McKee, M., & Hunter, D. (1995). Mortality league tables: do they inform or mislead? Quality in Health Care, 4(1):5–12. https://doi.org/10.1136/qshc.4.1.5 McKee, M., & Stuckler, D. (2015). Reflective Practice: How the World Bank Explored Its Own Biases? International Journal of Health Policy and Management, 5(2):79–82. https://doi. org/10.15171/ijhpm.2015.216 McKee, M., van Schalkwyk, M. C., & Greenley, R. (2024a). Meeting the challenges of the 21st century: the fundamental importance of trust for transformation. Israel Journal of Health Policy Research, 13(1):21. https://doi.org/10.1186/s13584-024-00611-1 McKee, M., van Schalkwyk, M. C. I., Greenley, R., & Permanand, G. (2024b). Placing Trust at the Heart of Health Policy and Systems. International Journal of Health Policy and Management, 13:8410. https://doi.org/10.34172/ijhpm.2024.8410 McKee, M., & Wouters, O. J. (2023). The Challenges of Regulating Artificial Intelligence in Healthcare Comment on “Clinical Decision Support and New Regulatory Frameworks for Medical Devices: Are We Ready for It? - A Viewpoint Paper”. International Journal of Health Policy and Management, 12:7261. https://doi.org/10.34172/ijhpm.2022.7261 McKee, R., Murphy, A., Richardson, E., Roberts, B., Haerpfer, C., & McKee, M. (2013). Do citizens of the former Soviet Union trust state institutions, and why? East European Politics, 29(4):377–396. McKeown, S., & Psaltis, C. (2017). Intergroup contact and the mediating role of intergroup trust on outgroup evaluation and future contact intentions in Cyprus and Northern Ireland. Peace and Conflict: Journal of Peace Psychology, 23(4):392. Mechanic, D. (1996). Changing medical organization and the erosion of trust. Milbank Quarterly, 74(2):171–189. Mechanic, D. (1998). The functions and limitations of trust in the provision of medical care. Journal of Health Politics, Policy and Law, 23(4):661–686. https://doi.org/10.1215/03616878- 23-4-661 Mechanic, D., & Meyer, S. (2000). Concepts of trust among patients with serious illness. Social science & Medicine, 51(5):657–668. Mertes, S., Huber, T., Weitz, K., Heimerl, A., & André, E. (2022). Ganterfactual—counterfactual explanations for medical non-experts using generative adversarial learning. Frontiers in Artificial Intelligence, 5:825565. Mills, M. (2023). Martha’s rule: a hospital escalation system to save patients’ lives. BMJ, 383:2319. https://doi.org/10.1136/bmj.p2319 Mishler, W., & Rose, R. (1997). Trust, distrust and skepticism: Popular evaluations of civil and political institutions in post-communist societies. The Journal of Politics, 59(2):418–451. Mohseni, M., & Lindstrom, M. (2007). Social capital, trust in the health-care system and self- rated health: the role of access to health care in a population-based study. Social Science & Medicine, 64(7):1373–1383. https://doi.org/10.1016/j.socscimed.2006.11.023 References 71 Montoya, R. M., & Pittinsky, T. L. (2011). When increased group identification leads to outgroup liking and cooperation: the role of trust. Journal of Social Psychology, 151(6):784–806. https:// doi.org/10.1080/00224545.2010.538762 Mossialos, E., & McKee, M. (2003). Rationing treatment on the NHS—still a political issue. Journal of the Royal Society of Medicine, 96(8):372–373. Müller, E., Zill, J. M., Dirmaier, J., Härter, M., & Scholl, I. (2014). Assessment of trust in physician: a systematic review of measures. PLoS One, 9(9):e106844. https://doi.org/10.1371/ journal.pone.0106844 Murdoch, B. (2021). Privacy and artificial intelligence: challenges for protecting health information in a new era. BMC Medical Ethics, 22(1):122. https://doi.org/10.1186/s12910-021-00687-3 Naiseh, M., Al-Thani, D., Jiang, N., & Ali, R. (2021). Explainable recommendation: when design meets trust calibration. World Wide Web, 24(5):1857–1884. Nannestad, P. (2008). What have we learned about generalized trust, if anything? Annual Review of Political Science, 11:413–436. Nay, J. J., & Vorobeychik, Y. (2016). Predicting Human Cooperation. PLoS One, 11(5):e0155656. https://doi.org/10.1371/journal.pone.0155656 Nelson, E., Bloom, G., & Shankland, A. (2018). Introduction: Accountability for health equity: galvanising a movement for universal health coverage. IDS Bulletin – Institute of Development Studies, 49(2):1–16. https://doi.org/10.19088/1968-2018.131 Nielsen, J. H., & Lindvall, J. (2021). Trust in government in Sweden and Denmark during the COVID-19 epidemic. West European Politics, 44(5–6):1180–1204. O’Donnell, C. A., Higgins, M., Chauhan, R., & Mullen, K. (2008). Asylum seekers’ expectations of and trust in general practice: a qualitative study. British Journal of General Practice, 58(557):e1–11. https://doi.org/10.3399/bjgp08X376104 O’Hara, K. (2012). A general definition of trust. Southampton, University of Southampton (working paper) (https://eprints.soton.ac.uk/341800/1/ohara_trust_working_paper_aug_2012. pdf, accessed 7 May 2024). O’Donovan, J., Wagner, H. F., & Zeume, S. (2019). The value of offshore secrets: Evidence from the Panama Papers. The Review of Financial Studies, 32(11):4117–4155. Obermeyer, Z., Powers, B., Vogeli, C., & Mullainathan, S. (2019). Dissecting racial bias in an algorithm used to manage the health of populations. Science, 366(6464):447–453. https:// doi.org/10.1126/science.aax2342 OECD. (2017). Methodological considerations. Paris, OECD Publishing (https://www.oecd- ilibrary.org/content/component/9789264278219-6-en, accessed 23 October 2023). OECD. (2021). Drivers of Trust in Public Institutions in Finland. Paris, OECD Publishing. https://doi.org/10.1787/52600c9e-en OECD. (2023). Trust in government. Paris, OECD Publishing (https://www.oecd.org/governance/ trust-in-government/, accessed 7 December 2023). Ozawa, S., & Sripad, P. (2013). How do you measure trust in the health system? A systematic review of the literature. Social Science &i Medicine, 91:10–14. https://doi.org/10.1016/j. socscimed.2013.05.005 Palafox, B., Goryakin, Y., Stuckler, D., Suhrcke, M., Balabanova, D., Alhabib, K. F., Avezum, A., Bahonar, A., Bai, X., Chifamba, J., Dans, A. L., Diaz, R., Gupta, R., Iqbal, R., Ismail, N., Kaur, M., Keskinler, M. V., Khatib, R., Kruger, A., . . . McKee, M. (2017). Does greater individual social capital improve the management of hypertension? Cross-national analysis of 61 229 individuals in 21 countries. BMJ Global Health, 2(4):e000443. https://doi.org/10.1136/ bmjgh-2017-000443 Trust: the foundation of health systems72 Pearce, N., & Davey Smith, G. (2003). Is social capital the key to inequalities in health? American Journal of Public Health, 93(1):122–129. https://doi.org/10.2105/ajph.93.1.122 Pollard, M. S., & Davis, L. M. (2022). Decline in Trust in the Centers for Disease Control and Prevention During the COVID-19 Pandemic. Rand Health Quarterly, 9(3):23. Public Policy Forum. (2018). Pathways to Sustainable Access to Innovative Medicines for Canadians. Ottawa, Public Policy Forum (https://ppforum.ca/publications/pathways-sustainable-access- innovative-medicines-canadians/, accessed 23 January 2024). Putnam, R. (1993). The prosperous community: Social capital and public life. The American Prospect, 4:35–42. Rahu, K., McKee, M., Mägi, M., & Rahu, M. (2020). The fall and rise of cancer registration in Estonia: The dangers of overzealous application of data protection. Cancer Epidemiology, 66:101708. https://doi.org/10.1016/j.canep.2020.101708 Rajan, S., Khunti, K., Alwan, N., Steves, C., MacDermott, N., Morsella, A., Angulo, E., Winkelmann, J., Bryndová, L., Fronteira, I., Gandré, C., Or, Z., Gerkens, S., Sagan, A., Simões, J., Ricciardi, W., de Belvis, A. G., Silenzi, A., Bernal-Delgado, E., . . . McKee, M. (2021). In the wake of the pandemic: Preparing for Long COVID. Copenhagen, European Observatory on Health Systems and Policies. Rajpurkar, P., Chen, E., Banerjee, O., & Topol, E. J. (2022). AI in health and medicine. Nature Medicine, 28(1): 31–38. https://doi.org/10.1038/s41591-021-01614-0 Rao, A., Morstatter, F., & Lerman, K. (2022). Partisan asymmetries in exposure to misinformation. Scientific Reports, 12(1):15671. https://doi.org/10.1038/s41598-022-19837-7 Reicher, S. (2021). Pandemic fatigue? How adherence to COVID-19 regulations has been misrepresented and why it matters. London, BMJ (https://blogs.bmj.com/bmj/2021/01/07/ pandemic-fatigue-how-adherence-to-COVID-19-regulations-has-been-misrepresented-and- why-it-matters/, accessed 21 October 2023). Reicher, S. (2023). Trust the Public? How the UK Government Got the Psychology of COVID-19 Wrong and Why It Matters. In: Pasternak, C., ed. Evaluating a Pandemic. s.l., World Scientific Publishing:98–118. Reicher, S., & Bauld, L. (2021). From the ‘fragile rationalist’ to ‘collective resilience’: what human psychology has taught us about the COVID-19 pandemic and what the COVID-19 pandemic has taught us about human psychology. Journal of the Royal College of Physicians of Edinburgh, 51(S1):S12–s19. https://doi.org/10.4997/jrcpe.2021.236 Reicher, S., & Drury, J. (2021). Pandemic fatigue? How adherence to COVID-19 regulations has been misrepresented and why it matters. BMJ, 372:n137. https://doi.org/10.1136/bmj.n137 Reynolds, L., & McKee, M. (2010). Organised crime and the efforts to combat it: a concern for public health. Global Health, 6:21. https://doi.org/10.1186/1744-8603-6-21 Ribeiro, M. T., Singh, S., & Guestrin, C. (2016). “ Why should i trust you?” Explaining the predictions of any classifier. Proceedings of the 22nd ACM SIGKDD international conference on knowledge discovery and data mining, San Francisco, CA, 13-17 August. Rockers, P. C., Kruk, M. E., & Laugesen, M. J. (2012). Perceptions of the health system and public trust in government in low- and middle-income countries: evidence from the World Health Surveys. Journal of Health Politics, Policy and Law, 37(3):405–437. https://doi. org/10.1215/03616878-1573076 Rodgers, K., & Massac, N. (2020). Misinformation: a threat to the public’s health and the public health system. Journal of Public Health Management and Practice, 26(3):294–296. Romanello, M., Di Napoli, C., Drummond, P., Green, C., Kennard, H., Lampard, P., Scamman, D., Arnell, N., Ayeb-Karlsson, S., Ford, L. B., Belesova, K., Bowen, K., Cai, W., Callaghan, References 73 M., Campbell-Lendrum, D., Chambers, J., van Daalen, K. R., Dalin, C., Dasandi, N., . . . Costello, A. (2022). The 2022 report of the Lancet Countdown on health and climate change: health at the mercy of fossil fuels. Lancet, 400(10363):1619–1654. https://doi.org/10.1016/ S0140-6736(22)01540-9 Romsland, G. I., Milosavljevic, K. L., & Andreassen, T. A. (2019). Facilitating non-tokenistic user involvement in research. Research Involvment and Engagement, 5:18. https://doi. org/10.1186/s40900-019-0153-3 Roozenbeek, J., Schneider, C. R., Dryhurst, S., Kerr, J., Freeman, A. L., Recchia, G., Van Der Bles, A. M., & Van Der Linden, S. (2020). Susceptibility to misinformation about COVID-19 around the world. Royal Society Open Science, 7(10):201199. Rotenberg, K. J., & Petrocchi, S. (2018). A longitudinal investigation of trust beliefs in physicians by children with asthma and their mothers: Relations with children’s adherence to medical regimes and quality of life. Child: Care, Health and Development, 44(6):879–884. https:// doi.org/10.1111/cch.12604 Routen, A., Akbari, A., Banerjee, A., Katikireddi, S. V., Mathur, R., McKee, M., Nafilyan, V., & Khunti, K. (2022). Strategies to record and use ethnicity information in routine health data. Nature Medicine, 28(7):1338–1342. https://doi.org/10.1038/s41591-022-01842-y Sadiq, M. T., & Saji, M. K. (2022). The disaster of misinformation: a review of research in social media. International Journal of Data Science and Analytics, 13(4):271–285. Sah, S., Fagerlin, A., & Ubel, P. (2016). Effect of physician disclosure of specialty bias on patient trust and treatment choice. Proceedings of the National Academy of Sciences, 113(27):7465– 7469. https://doi.org/10.1073/pnas.1604908113 Sanofi. (2023). A Million Conversations: How we’re bridging the healthcare ‘trust gap’ with marginalized communities. s.l., Sanofi (https://www.sanofi.com/en/magazine/social-impact/ global-poll, accessed 7 May 2024). Schiefer, D., & Van der Noll, J. (2017). The essentials of social cohesion: A literature review. Social Indicators Research, 132:579–603. Schilke, O., Reimann, M., & Cook, K. S. (2021). Trust in social relations. Annual Review of Sociology, 47:239–259. Schlesinger, M., Quon, N., Wynia, M., Cummins, D., & Gray, B. (2005). Profit-seeking, corporate control, and the trustworthiness of health care organizations: assessments of health plan performance by their affiliated physicians. Health Services Research, 40(3):605–645. https:// doi.org/10.1111/j.1475-6773.2005.00377.x Schwalbe, N., & Wahl, B. (2020). Artificial intelligence and the future of global health. Lancet, 395(10236):1579–1586. https://doi.org/10.1016/s0140-6736(20)30226-9 Schwalm, J. D., McCready, T., Lopez-Jaramillo, P., Yusoff, K., Attaran, A., Lamelas, P., Camacho, P. A., Majid, F., Bangdiwala, S. I., Thabane, L., Islam, S., McKee, M., & Yusuf, S. (2019). A community-based comprehensive intervention to reduce cardiovascular risk in hypertension (HOPE 4): a cluster-randomised controlled trial. Lancet, 394(10205):1231–1242. https:// doi.org/10.1016/s0140-6736(19)31949-x Seligman, A. B. (2000). The problem of trust. Princeton, NJ, Princeton University Press. Shearn, C., & Krockow, E. M. (2023). Reasons for COVID-19 vaccine hesitancy in ethnic minority groups: A systematic review and thematic synthesis of initial attitudes in qualitative research. SSM - Qualitative Research in Health, 3:100210. https://doi.org/10.1016/j.ssmqr.2022.100210 Shiell, A., Hawe, P., & Kavanagh, S. (2020). Evidence suggests a need to rethink social capital and social capital interventions. Social Science & Medicine, 257:111930. https://doi.org/10.1016/j. socscimed.2018.09.006 Trust: the foundation of health systems74 Shore, D. A. (Ed.). (2006). The Trust Crisis in Healthcare: Causes, Consequences, and Cures. Oxford, Oxford University Press. https://doi.org/10.1093/acprof:oso/9780195176360.001.0001. Slomka, J. (1992). The negotiation of death: clinical decision making at the end of life. Social Science & Medicine, 35(3):251–259. Sønderskov, K. M., & Dinesen, P. T. (2016). Trusting the state, trusting each other? The effect of institutional trust on social trust. Political Behavior, 38:179–202. Starke, G., & Ienca, M. (2022). Misplaced Trust and Distrust: How Not to Engage with Medical Artificial Intelligence. Cambridge Quarterly of Healthcare Ethics, 1–10. https://doi. org/10.1017/S0963180122000445 Statista. (2023). Share of individuals who trust the healthcare system in their country to provide them with the best treatment in select European countries in 2023. s.l., Statista (https:// www.statista.com/statistics/889517/trust-in-healthcare-system-in-europe-by-country/, accessed 7 December 2023). Stauch, M. (2011). Patient safety and clinical risk management in Germany. In: Tingle, J., Bark, P., eds. Patient Safety, Law Policy and Practice. Abingdon, UK, Routledge:165–176. Street, R. L., Makoul, G., Arora, N. K., & Epstein, R. M. (2009). How does communication heal? Pathways linking clinician–patient communication to health outcomes. Patient Education and Counseling, 74(3):295–301. Strickland E. (2019). IBM Watson, heal thyself: How IBM overpromised and underdelivered on AI health care. IEEE Spectrum, 56(4):24–31. Suarez-Lledo, V., & Alvarez-Galvez, J. (2021). Prevalence of health misinformation on social media: systematic review. Journal Of Medical Internet Research, 23(1):e17187. Sulaman, I., Hartley, S., & Elvins, R. (2023). Therapeutic alliance in the treatment of adolescent substance misuse: a systematic review. Child and Adolescent Mental Health. https://doi. org/10.1111/camh.12671 Sule, S., DaCosta, M. C., DeCou, E., Gilson, C., Wallace, K., & Goff, S. L. (2023). Communication of COVID-19 Misinformation on Social Media by Physicians in the US. JAMA Network Open, 6(8):e2328928–e2328928. Sulik, J., Deroy, O., Dezecache, G., Newson, M., Zhao, Y., El Zein, M., & Tunçgenç, B. (2021). Facing the pandemic with trust in science. Humanities and Social Sciences Communications, 8(1):301. https://doi.org/10.1057/s41599-021-00982-9 Swire-Thompson, B., & Lazer, D. (2020). Public health and online misinformation: challenges and recommendations. Annual Review of Public Health, 41(1):433–451. Szreter, S., & Woolcock, M. (2004). Health by association? Social capital, social theory, and the political economy of public health. International Journal of Epidemiology, 33(4):650–667. https://doi.org/10.1093/ije/dyh013 Taber, J. M., Leyva, B., & Persoskie, A. (2015). Why do people avoid medical care? A qualitative study using national data. Journal of General Internal Medicine, 30(3):290–297. https://doi. org/10.1007/s11606-014-3089-1 Tarrant, C., Dixon-Woods, M., Colman, A. M., & Stokes, T. (2010). Continuity and trust in primary care: a qualitative study informed by game theory. The Annals of Family Medicine, 8(5):440–446. Taylor, L. A., Nong, P., & Platt, J. (2023). Fifty Years of Trust Research in Health Care: A Synthetic Review. Milbank Quarterly, 101(1):126–178. https://doi.org/10.1111/1468-0009.12598 Thiede, M. (2005). Information and access to health care: is there a role for trust? Social Science & Medicine, 61(7):1452–1462. https://doi.org/10.1016/j.socscimed.2004.11.076 References 75 Thom, D. H., Hall, M. A., & Pawlson, L. G. (2004). Measuring patients’ trust in physicians when assessing quality of care. Health Affairs, 23(4):124–132. Tudor Hart, J. (1971). The inverse care law. Lancet, 1(7696):405–412. https://doi.org/10.1016/ s0140-6736(71)92410-x Turk, E., Durrance-Bagale, A., Han, E., Bell, S., Rajan, S., Lota, M. M. M., Ochu, C., Porras, M. L., Mishra, P., Frumence, G., McKee, M., & Legido-Quigley, H. (2021). International experiences with co-production and people centredness offer lessons for COVID-19 responses. BMJ, 372:m4752. https://doi.org/10.1136/bmj.m4752 Umoren, R., Kim, S., Gray, M. M., Best, J. A., & Robins, L. (2022). Interprofessional model on speaking up behaviour in healthcare professionals: a qualitative study. BMJ Leader, 6(1):15. https://doi.org/10.1136/leader-2020-000407 Van Noorden, R. (2020). The ethical questions that haunt facial-recognition research. Nature, 587(7834):354–358. https://doi.org/10.1038/d41586-020-03187-3 Van Noorden, R. (2023). Medicine is plagued by untrustworthy clinical trials. How many studies are faked or flawed? Nature, 619(7970):454–458. https://doi.org/10.1038/d41586- 023-02299-w van Schalkwyk, M. C., Petticrew, M., Cassidy, R., Adams, P., McKee, M., Reynolds, J., & Orford, J. (2021). A public health approach to gambling regulation: countering powerful influences. Lancet Public Health, 6(8):e614–e619. van Stekelenburg, B. C. A., De Cauwer, H., Barten, D. G., & Mortelmans, L. J. (2022). Attacks on Health Care Workers in Historical Pandemics and COVID-19. Disaster Medicine and Public Health Preparedness, 17:e309. https://doi.org/10.1017/dmp.2022.275 Vannoni, M., McKee, M., Semenza, J. C., Bonell, C., & Stuckler, D. (2020). Using volunteered geographic information to assess mobility in the early phases of the COVID-19 pandemic: a cross-city time series analysis of 41 cities in 22 countries from March 2nd to 26th 2020. Global Health, 16(1):85. https://doi.org/10.1186/s12992-020-00598-9 Wacquant, L. J., & Bourdieu, P. (1992). An invitation to reflexive sociology. Cambridge, Polity. Wadden, J. J. (2021). Defining the undefinable: the black box problem in healthcare artificial intelligence. Journal of Medical Ethics, 48(10):764–768. https://doi.org/10.1136/ medethics-2021-107529 Walker, M. U. (2006). Moral repair: Reconstructing moral relations after wrongdoing. Cambridge, Cambridge University Press. Walsh, S., O’Neill, A., Hannigan, A., & Harmon, D. (2019). Patient-rated physician empathy and patient satisfaction during pain clinic consultations. Irish Journal of Medical Science (1971-), 188:1379–1384. Wang, Y., Bye, J., Bales, K., Gurdasani, D., Mehta, A., Abba-Aji, M., Stuckler, D., & McKee, M. (2022). Understanding and neutralising COVID-19 misinformation and disinformation. BMJ, 379:e070331. https://doi.org/10.1136/bmj-2022-070331 Wang, Y., McKee, M., Torbica, A., & Stuckler, D. (2019). Systematic Literature Review on the Spread of Health-related Misinformation on Social Media. Social Science & Medicine, 240:112552. https://doi.org/10.1016/j.socscimed.2019.112552 Weil, L. G., Nun, G. B., & McKee, M. (2013). Recent physician strike in Israel: a health system under stress? Israel Journal of Health Policy Research, 2(1), 33. https://doi.org/10.1186/2045-4015-2-33 Wellcome Trust. (2020). Wellcome Global Monitor. London, Wellcome Trust (https://wellcome. org/reports/wellcome-global-monitor-COVID-19/2020, access 26 October 2023). Wesson, D. E., Lucey, C. R., & Cooper, L. A. (2019). Building trust in health systems to eliminate health disparities. JAMA, 322(2):111–112. Trust: the foundation of health systems76 WHO Regional Office for Europe. (2022). Health and care workforce in Europe: time to act. Copenhagen, WHO Regional Office for Europe (https://www.who.int/europe/publications/i/ item/9789289058339, accessed 23 January 2024). WHO Regional Office for Europe. (2023). Tallinn Charter 15th Anniversary Health Systems Conference: Trust and transformation – resilient and sustainable health systems for the future: outcome statement. Copenhagen, WHO Regional Office for Europe, (https://www.who.int/ europe/publications/i/item/tallinn-charter-15th-anniversary-health-systems-conference-- trust-and-transformation---resilient-and-sustainable-health-systems-for-the-future--outcome- statement, accessed 7 May 2024). Wilk, A. S., & Platt, J. E. (2016). Measuring physicians’ trust: A scoping review with implications for public policy. Social Science & Medicine, 165:75–81. https://doi.org/10.1016/j. socscimed.2016.07.039 Williams, R. (2024). A chatbot helped more people access mental-health services. Cambridge, MA, MIT Technology Review (https://www.technologyreview.com/2024/02/05/1087690/a- chatbot-helped-more-people-access-mental-health-services/, accessed 7 May 2024). Williamson, V., Lamb, D., Hotopf, M., Raine, R., Stevelink, S., Wessely, S., Docherty, M., Madan, I., Murphy, D., & Greenberg, N. (2023). Moral injury and psychological wellbeing in UK healthcare staff. Journal of Mental Health, 32(5):890–898. https://doi.org/10.1080/09638 237.2023.2182414 Wise, J. (2023). Public confidence in government’s stewardship of NHS falls to new low, poll finds. BMJ, 380:436. https://doi.org/10.1136/bmj.p436 World Health Organization. (2000). The World Health Report 2000: health systems: improving performance. Geneva, World Health Organization. World Health Organization. (2021). Voice, agency, empowerment–handbook on social participation for universal health coverage. Geneva, World Health Organization. World Health Organization. (2023). Tallinn Charter 15th Anniversary Health Systems Conference: Trust and transformation – resilient and sustainable health systems for the future. Geneva, World Health Organization (https://www.who.int/europe/event/tallinn-charter-15th- anniversary-health-systems-conference--trust-and-transformation---resilient-and-sustainable- health-systems-for-the-future, accessed 24 January 2024). Wu, W., Su, Y., Chen, X., Zhao, S., King, I., Lyu, M. R., & Tai, Y.-W. (2020). Towards global explanations of convolutional neural networks with concept attribution. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, Seattle, WA, 13–19 June. Zapata, T., Azzopardi-Muscat, N., McKee, M., & Kluge, H. (2023). Fixing the health workforce crisis in Europe: retention must be the priority. BMJ, 381, 947. https://doi.org/10.1136/ bmj.p947 Zhang, Y., Liao, Q. V., & Bellamy, R. K. (2020). Effect of confidence and explanation on accuracy and trust calibration in AI-assisted decision making. Proceedings of the 2020 conference on fairness, accountability, and transparency, Barcelona, 27–30 January. Health Policy Series No. 58 http://eurohealthobservatory.who.int H ea lt h Po lic y S er ie s 58?? 58 ?? ?? This study looks at the critical role of trust within health systems, exploring its impact on health care quality, functionality, and health outcomes. Trust is foundational for patients to seek timely help, share information, and adhere to treatment plans. For the public, trust in the health system’s ability to provide care, act in their best interest, and adapt to changing needs is essential. Policymakers must trust that the resources they provide for health systems will be used well. This book stands out by integrating perspectives from philosophy, sociology, economics, psychology, and medicine. It is forward-looking, exploring how new health technologies, data privacy, and artificial intelligence impact trust. It emphasizes the need for transparency, accountability, and combating misinformation to build and protect trust. It calls for active engagement of a diverse range of stakeholders and fostering of collaboration if we are to maintain trust and address power imbalances. The study underscores trust’s role in health system transformation, stressing that effective, equitable care is impossible without it. It advocates for trustworthy leadership, based on transparency and communication and for better measurement and understanding of the dynamic nature of trust if we are to sustain the legitimacy and functionality of health systems. Discover why trust is the cornerstone of effective health systems in this important new assessment. Dive into the complexities of trust, its impact on health care quality, and the necessity for transparency and accountability. With insights from multiple disciplines, this book is a vital guide for anyone invested in the future of health care. The authors Martin McKee – European Observatory on Health Systems and Policies and London School of Hygiene & Tropical Medicine, London, United Kingdom May C. I. van Schalkwyk – Department of Health Services Research and Policy, London School of Hygiene & Tropical Medicine, London, United Kingdom Rachel Greenley – Department of Health Services Research and Policy, London School of Hygiene & Tropical Medicine, London, United Kingdom Govin Permanand – Division of Country Health Policies and Systems, WHO Regional Office for Europe, Copenhagen, Denmark Trust The foundation of health systems Martin McKee May C.I. van Schalkwyk Rachel Greenley Govin Permanand Cover_OBS_58_TRUST_03072024.qxp_Mise en page 1 03/07/2024 09:33 Page 1