Category: Prevention

We have counted loneliness. Now we need to change it.

Our new research examines loneliness and social capital in more than 135,000 adults. The challenge now is to turn those findings into better questions – and interventions worth investing in.

A loneliness score can tell us something important about someone’s life, but it cannot tell us what would make that life less lonely. That gap is where I believe the next chapter of loneliness research belongs. In our new paper in BMC Global and Public Health, we analysed data from 135,725 adults participating in the INTERACT study in England. We examined factors associated with loneliness using two established measures, alongside a separate analysis of social capital: people’s perceptions of neighbourhood trust, cohesion and reciprocity.

Among respondents, younger age, being single, unemployment and disability were consistently associated with greater loneliness. Larger friendship networks were associated with lower loneliness. Older, married and retired respondents more frequently reported high social capital, while people with disability or long-term conditions had lower adjusted odds of reporting it. These findings give us questions to pursue but they do not give us a ready-made intervention.

That distinction should shape everything we do next. The study used a volunteer sample and measured people’s circumstances at one point in time. It cannot establish what causes loneliness, estimate how common it is across England, or tell us which intervention would work. A large sample does not remove those limitations.

For me, this is the starting point for a more demanding research agenda: what would we actually change, for whom, and how would we know it helped? Consider the association between friendship networks and loneliness. It would be tempting to translate it into a simple instruction: help people make more friends. But an association cannot tell us whether expanding someone’s network will reduce their loneliness, whether loneliness makes relationships harder to sustain, or how other circumstances influence both. “More friends” is also an outcome to aspire to, rather than a sufficiently specified intervention. Who makes the introduction? Where does the first meeting happen? What helps someone return? What makes an encounter develop into a relationship that matters? Those are intervention-development questions. They deserve the same intellectual attention as the statistical models that bring them into view.

Imagine, as a design exercise, a community programme offering weekly group activities. Before commissioning it, I would want to ask what problem it is intended to address. A shortage of opportunities to meet people? Difficulty entering unfamiliar social settings? The loss of a close relationship? Practical barriers to leaving home?

Each answer points towards a different proposition to test. For someone who wants to attend but cannot reach the venue, transport support could be a candidate component. For someone apprehensive about arriving alone, a familiar person accompanying them might be worth testing. For someone seeking a close, dependable relationship, attendance at a large group may be the wrong primary outcome. These are hypotheses, not findings from our study… but their value lies in making the proposed route to benefit explicit – and therefore open to challenge!

Social capital adds another set of questions. Our paper examined it as a separate outcome; it did not establish that increasing neighbourhood trust reduces loneliness. Nevertheless, I would argue that intervention development should ask what happens beyond the individual referral. What kind of community is someone being invited into? Who feels welcome there? Can participants influence what happens? Are there opportunities to contribute as well as receive support? What resources would a local organisation need to sustain relationships beyond a short funding period?

I want self-care to sit within that discussion. Any call for people to strengthen their own social connections should be accompanied by serious questions about the opportunities and support available to them. “Take action” is an incomplete offer unless we also examine what makes action possible.

The next step should be a programme of co-designed, explicitly testable interventions. People experiencing loneliness should help define the problem, choose outcomes that matter and identify features that make participation acceptable. Their involvement should extend to interpreting why an approach succeeds, disappoints or reaches only some of its intended participants. Evaluation then needs to follow the whole journey.

Counting invitations, referrals and attendance can describe delivery. To establish benefit, we need to examine changes in loneliness and wellbeing, whether those changes last, and how outcomes compare with what would have happened without the intervention. Randomised evaluations should be used where feasible, with credible alternatives where they are not. We should also examine who never takes up the offer, who leaves, and whose circumstances make participation difficult. I would want a commissioner to see those findings alongside the average outcome and the cost. An intervention’s reach is part of its practical value.

Our study also offers a reason to think carefully about measurement. Educational attainment showed different associations depending on which loneliness measure we used. That finding cautions against treating different instruments as interchangeable. Future evaluations should specify what they seek to change and combine appropriate measures with accounts of participants’ experiences.

None of this requires abandoning observational research. It requires giving its findings a purposeful next step.

For the Prevention Lab, my challenge is to researchers, funders and commissioners alike: make room for the difficult work between identifying a pattern and delivering a useful intervention. Fund development, refinement and rigorous evaluation. Specify the benefit being sought. Be willing to adapt or stop an approach when the evidence disappoints.

I want the next paper to answer a harder question: what did we change, who benefited, and was the difference worth sustaining? The people behind our data deserve that next chapter – and a meaningful role in writing it. Through our ongoing qualitative research, we are exploring personal stories and journeys to understand what connection, belonging and support mean in everyday life. These accounts will inform the co-production of interventions grounded in people’s experiences, ready to be tested for the difference they make to their lives.

The Future of Self-Care: Emerging technologies, public trust & personal autonomy

Who should be in control when technology becomes part of how we look after ourselves? That question belongs at the centre of the digital self-care agenda. In my view, emerging technologies should be judged by the understanding and practical capability people gain, and by the control they retain over decisions affecting their lives.

The World Health Organization’s account of self-care includes maintaining health and coping with illness, with or without professional support. For me, the purpose of innovation is to make those activities more manageable within the realities of people’s lives.

Emerging technologies offer different ways to access information and assistance. Virtual reality (VR) creates an immersive digital environment; augmented reality (AR) adds digital information to a view of the physical world. Smart glasses offer functions that vary by device, including cameras, audio and, in some models, visual displays. Brain–computer interfaces (BCIs) translate brain signals into commands for external devices. Because their mechanisms and risks differ, each needs evaluation suited to its purpose.

Starting with the self-carer’s goals

My starting point is the self-carer’s goal. They may want an explanation they can understand, support with a difficult task or a way to communicate their needs. The design question is whether a particular technology helps them pursue that goal, under conditions they find acceptable. Our work on Self-Driven Healthcare proposed connecting people’s own health information and monitoring tools with professional care. That vision depends on accessible support and integration with health services, with people able to influence decisions about their care.

Our BMJ Open study of spatial computing in health and self-care explored these issues with UK adults, including healthcare professionals. Respondents identified possible value for self-care and patient education alongside barriers involving cost, training and privacy. These findings reflect perceptions rather than evidence of clinical benefit.

Smart glasses illustrate both the promise and the open questions. Be My Eyes connects blind and low-vision users of supported Meta glasses with sighted volunteers who can view the camera feed and provide spoken assistance. Its value, however, should be assessed against users’ goals and the alternatives available to them. This is why we launched the SMART EYES study to examine public views on AI-enabled smart glasses, including privacy, accessibility and possible support for health and self-care. To be meaningful, evaluations must start with people’s experiences, concerns and expectations. They should also account for the time needed to learn a tool, maintain it and resolve problems. The practical test is whether the overall experience becomes easier for the person using it.

In an earlier Prevention Lab article on health literacy, I argued that people need to understand information, judge its relevance and decide what to do next. Digital assistance should support those capabilities. Our UK symptom-checker survey found that respondents wanted help understanding symptoms and deciding whether to seek care, alongside concerns about privacy and losing face-to-face consultations. At the same time, our 2023 systematic review of symptom checkers found variable diagnostic and triage accuracy in the studies available at that time.

Earning public trust

Public trust also needs to be framed with care. SCARU’s RADIANT Voices research on AI and software as a medical device (SaMD) examined trust in clinical decision-making. We found higher trust in AI-assisted decisions than in AI-only decisions, alongside strong support for disclosure and professional oversight. These findings describe preferences, not evidence of safety or effectiveness.

Trust in individual pieces of advice matters as well. Our Trust in AI-Generated Health Advice (TAIGHA) scale and its four-item short form, TAIGHA-S, focus on trust in a specific piece of advice. Initially validated with 385 UK adults in a symptom-assessment scenario, they measure trust and distrust as related but distinct dimensions.

Our PLOS Digital Health study of community perspectives on BCIs likewise found concerns about implantation risks and cost, with participants emphasising regulation and public education. Those concerns belong in the decisions that set research priorities. Public engagement should give people a meaningful opportunity to influence development, including the option to question whether an application is desirable.

Because public trust has to be earned through evidence and accountability, developers and health services should explain the evidence for a proposed use, its limitations and who is accountable when something goes wrong. People should also have a practical way to challenge advice or report harm. The WHO’s guidance on generative AI in health supports clear tasks, appropriate accuracy and reliability, and involvement of patients and other affected groups in development.

Regulation and intended purpose

SaMD refers to software intended to perform a medical purpose without being part of a hardware medical device. Its increasing pervasiveness makes the intended purpose especially important. The MHRA’s guidance emphasises specifying that purpose and matching it to supporting evidence. Whether an application is accessed through a phone, headset or glasses, assessment should address its intended users, clinical function and setting. Determining regulatory status therefore requires attention to the specific features and claims of health-related software.

The developer’s experience deserves attention too. Our study of medical-software developers’ experiences of regulation, available as a preprint, describes participants’ difficulties obtaining reliable advice and navigating requirements. Clear guidance, accessible expertise and proportionate evidence requirements should form part of responsible innovation.

Autonomy in everyday use

Personal autonomy also needs to be built into everyday use. Who chooses the goal behind a reminder or recommendation? Who can change it? People should understand the purpose of the support they receive and be able to pause or decline it. Commercial interests should be visible, especially where advice is connected to the sale of a product or service. Delegating a task should leave the individual able to influence the terms of that delegation.

For smart glasses, autonomy also concerns the relationship between the wearer and people nearby. Using a camera to assist with a task, retaining a recording and sharing it are distinct activities. Each deserves a clear explanation and an appropriate decision about permission.

That discussion should also respect the dignity of people using assistive technology. Someone should not have to disclose a diagnosis to justify their device to a stranger. Equally, the people around them should have meaningful ways to understand and influence what happens to their information. Good safeguards need to address both concerns in practice.

Equity and shared responsibility

Equitable access should be considered from the outset and meaningful evaluations need to address affordability, language, disability-related requirements and the support needed to use a technology. People should retain an accessible route to care if a device is unsuitable or they choose not to use it. A service should also plan for interruptions, software changes and the point at which a product is no longer supported.

Health systems and wider society retain responsibilities of their own. A self-care strategy needs accessible professional advice and practical support, alongside attention to housing, working conditions and other constraints on daily choices. Digital tools should be assessed within that context and should not become a justification for transferring responsibilities to people without considering the resources available to them.

Evaluating what matters

For researchers and commissioners, this calls for evaluation beyond stated willingness to adopt a product. Relevant outcomes include understanding, appropriate action, wellbeing and harms, with results examined across different groups. We should measure the work expected of users and carers, compare realistic alternatives and study use over time. A successful demonstration is only the starting point for that work. Ultimately, the future of self-care must be shaped with the people expected to use these technologies. They should help define the problems worth solving, the evidence that matters and the boundaries they want respected. The measure of progress should be whether people have more meaningful choices, stronger capabilities and dependable support in looking after their health. These principles guide our work in practice. Through our patient and public involvement and engagement PPIE activities, self-carers regularly share their feedback with us, and their insights shape our projects. Their perspectives keep our research grounded in the realities of looking after one’s health, and we are grateful for the time and candour they bring. We will continue to build our work with them, rather than for them.

Building the future together

In my next blog, I will reflect on the importance of PPIE and adopting a team science approach in driving our work, and on what bringing together lived experience and diverse expertise contributes to research on self-care.

Health Literacy is the Operating System of Self-Care

Imagine receiving a blood pressure monitor without understanding the readings. A medicine without clear instructions. Or advice to “live more healthily” without knowing where to begin.

These examples raise a question that should sit at the centre of prevention: what does someone need to turn health information into a decision they can use?

Every year, on International Literacy Day celebrated the world over on 8 September, is an opportunity to reinforce health literacy as the operating system of self-care: the capability that helps people interpret information, judge its relevance and decide what to do next.

What is health literacy? 

WHO describes health literacy as the ability to find, understand, critically assess and use health information and services. It also recognises that these abilities depend on how organisations communicate and what resources people can access. Health literacy therefore involves both individual capability and the conditions in which people make decisions.

The operating system metaphor helps explain why this matters. We can think of self-care practices – taking medicines, preparing food, being physically active or monitoring symptoms -as applications. Health literacy helps connect those activities to understanding: Why am I doing this? What should I expect? How do I know whether it is helping? When should I seek support?

WHO also explicitly identifies health literacy as a foundation for people’s active participation in their own health. Its account of self-care includes everyday health practices and the use of medicines, devices and tests, within an environment that provides appropriate support and access to professional care.

This has an important implication for how we judge successful self-care. We should indeed value someone recognising their limits and asking for help just as much as their ability to manage independently. A useful question for any self-care intervention is whether people understand both what they can do themselves and when they need someone else.

Consider a hypothetical heatwave. A person might understand the advice to keep their home cool yet have little control over an overheated rented flat. They might know they should reduce exertion but work outdoors. They might recognise concerning symptoms yet be uncertain where to seek advice. We should distinguish these problems. Understanding, practical opportunity and access to support each deserve attention. A leaflet cannot change a tenancy agreement or a working condition

Delimiting self-care

That is also where the operating system metaphor reaches its limit. People need resources, relationships and services alongside knowledge. Any prevention strategy built around self-care should ask what makes the recommended action feasible.

There is a corresponding responsibility for organisations. WHO emphasises that health literacy is shaped by social conditions and that information providers should make trustworthy information understandable and actionable.

For the Prevention Lab, I would translate this into a practical design principle: every recommendation should come with a usable route to action. “Be more active” should open a conversation about an achievable starting point. A monitoring device should come with an explanation of its readings and a clear route to advice. A digital service should make it easy to find help when its instructions are unclear. We should also make room for critical judgement. When someone encounters a compelling health claim, useful questions include: Who produced it? What evidence supports it? What are they selling? What remains uncertain? Does this apply to my circumstances?

It is arguable that asking these questions is itself a form of self-care and our evaluation methods should reflect that ambition. Alongside counting views, downloads or leaflets distributed, we should examine whether people can explain the next step, assess a claim, use a tool appropriately and obtain support. We should ask whose needs the intervention meets and who still faces barriers.

Evey year, International Literacy Day offers an opportunity to put these questions into the prevention agenda. The proposal is simple: treat health literacy as a core requirement whenever we ask people to take an active role in their health. And given that health literacy is the operating system of self-care, building it belongs in the design of every self-care intervention.

PRE-ACT: From prediction to prevention & making risk intelligence actionable in primary care

Health systems are becoming increasingly good at predicting risk. Routinely collected health data, machine learning, clinical risk scores, remote monitoring and digital technologies can identify people who may be at increased risk of disease or adverse health outcomes – sometimes well before those outcomes occur.

But prediction is not prevention.

Knowing that someone is at increased risk only creates value if that information can be translated into an appropriate response: something understandable to the person, clinically meaningful to professionals, feasible within routine care, and capable of supporting action. This is the problem that the Prediction-Enabled Action for Self-care in Primary Care (PRE-ACT) consortium sets out to address.

The PRE-ACT consortium is a collaboration between Imperial College London Self-Care Academic Research Unit (SCARU) and the Research Unit OPEN, University of Southern Denmark, bringing together researchers, clinicians and implementation partners with expertise spanning primary care, public health, risk prediction, digital health, behavioural science and self-care.

Closing the gap between risk and action

Much of the innovation in predictive healthcare has understandably concentrated on improving model performance: identifying the right variables, improving discrimination and calibration, and determining whether an algorithm can accurately classify risk. These are necessary questions. But they are not sufficient:

Between a risk estimate and an improved health outcome lies an important translational pathway. Risk must be interpreted. It must be communicated appropriately. Decisions need to follow. Patients may need support to act. Primary care teams need workable pathways through which to respond. And all of this must occur without widening existing inequalities.

PRE-ACT starts from the proposition that prediction should be viewed as the beginning of a preventive pathway, rather than its endpoint.

The initiative therefore brings together predictive analytics, decision support, primary care and self-care within a single translational framework. Its focus is not simply on whether we can identify risk, but on what should happen next.

Why self-care matters

This question is particularly important as healthcare moves towards earlier intervention and greater participation by patients in managing their own health.

The 2018 Declaration of Astana on Primary Health Care provides an important foundation. It renewed the global commitment to primary health care as a route to universal health coverage and emphasised, among other principles, the importance of prevention and health promotion, empowering individuals and communities, and enabling people to acquire the knowledge, skills and resources required to maintain their health.

PRE-ACT takes this principle into an increasingly data-driven healthcare environment. If predictive technologies can identify an opportunity to prevent deterioration, then we should also ask how individuals can be meaningfully supported to respond. That may involve self-monitoring, behavioural change, appropriate use of digital tools, supported self-management, or timely engagement with healthcare services.

Self-care in this context does not mean shifting responsibility from health systems to individuals. It means designing systems in which people are equipped and supported to participate in prevention, with appropriate professional oversight and clear routes into care.

 

Prediction-enabled prevention must also be responsible

There are important safeguards. A technically sophisticated predictive system may still have limited value if clinicians cannot interpret its output, patients do not understand what the result means, actionable services are unavailable, or those with lower digital access are systematically disadvantaged. PRE-ACT therefore places issues such as equity, human oversight, transparency, evidence, privacy, clinical governance and implementation readiness alongside predictive performance.

These considerations matter because the future of prevention will increasingly involve interactions between people, professionals, health systems and intelligent technologies. Success cannot be judged solely by the accuracy of an algorithm. We also need to ask whether an intervention is understandable, actionable, acceptable, equitable and capable of being integrated into real-world care.

From predicting risk to changing outcomes

One way of expressing the PRE-ACT pathway is: Prediction → Interpretation → Decision support → Activation → Self-care & clinical action → Outcomes

Each transition matters. A failure at any point can break the chain between recognising risk and preventing harm. Conversely, designing these elements together creates an opportunity to move predictive technologies away from passive risk stratification and towards genuinely preventive healthcare. This is the broader ambition of PRE-ACT: to help define what responsible, human-centred and actionable prediction should look like in primary care.

As predictive technologies become more powerful, the central question may therefore become less “How accurately can we predict what happens next?” and more: “What can we enable people and health systems to do differently because we know?” That is the point at which prediction becomes prevention.

When Does Prevention Become Medicine? Trust, legitimacy & the future of lifestyle medicine

At what point does something we do every day become medicine? Eating. Moving. Sleeping. Managing stress. Connecting with other people are among the most ordinary acts of human life. They happen largely beyond hospitals, clinics and consultation rooms. Yet they are also intimately connected with health.

And therein lies an intriguing tension: we readily accept that medicines prescribed for hypertension, diabetes or depression belong within healthcare. But what happens when the therapeutic proposition is not principally a tablet, procedure or device, but a different way of living? Who should deliver that intervention? What qualifications should they possess? Who do people trust? And perhaps most importantly: what makes an approach feel sufficiently legitimate to belong within medicine at all? These questions sit at the heart of our recently published study in BMJ Open, Legitimacy, trust and readiness for implementing lifestyle medicine in England.

The paradox of the unfamiliar familiar

One of the most striking findings was a paradox; most people were not particularly familiar with the term lifestyle medicine. Among 733 participants, only 26% of the overall sample had previously heard of it. Among healthcare professionals, awareness was considerably higher, at 62%. And yet, when we moved beyond the label, people largely recognised its substance. Nutrition. Physical activity. Sleep. Stress management. These were readily understood as legitimate components of health. In other words, lifestyle medicine appears to suffer from an unusual problem: its constituent ideas may be more familiar than the discipline that brings them together.

This matters, because public health frequently assumes that if an intervention is evidence-informed, useful and available, people will engage with it. But healthcare does not operate through evidence alone. It also operates through meaning, expectation, professional authority and trust. Before a person asks, “Does this work?”, another question may already be operating beneath the surface: “Is this really medicine?”

Legitimacy is not an abstract concept

Our findings suggest that this question has practical consequences. Perceived legitimacy was strongly associated with participants’ stated intention to use a lifestyle medicine service delivered through the NHS. Nearly half of participants said they would use such a service if it were available through the NHS, rising to around two-thirds of healthcare professionals. Because the study was cross-sectional, we cannot conclude that perceiving lifestyle medicine as legitimate causes people to use it. But the association raises an important implementation question. Perhaps prevention cannot simply be offered, but must instead also be socially and institutionally authorised.

That distinction is more important than it first appears. The same advice (eat differently, move more, sleep better, reduce harmful exposures, strengthen social connection) can be interpreted very differently depending on who gives it, where it is given and the institutional framework surrounding it.

Advice from a friend is advice. Advice from an influencer is content. Advice from a clinician may be interpreted as healthcare. The behaviour being discussed may be identical, but meaning attached to it is not.

Trust follows more than knowledge

Our findings make this particularly visible. Participants reported high levels of trust in lifestyle advice delivered by clinicians who had formal lifestyle medicine training: 73% expressed high trust. Trust was substantially lower for non-medical professionals, at 42%, even when those professionals possessed lifestyle medicine qualifications. This presents a difficult but important question for prevention.

What exactly are people trusting?

Is it knowledge? Credentials? Professional regulation?  Clinical accountability? The symbolic authority of medicine? Or some combination of all four? There is no simple answer in our data. Nor should these findings be interpreted as evidence that one professional group necessarily provides better lifestyle support than another. But they reveal something that implementation science cannot afford to ignore: the credibility of an intervention and the credibility of its messenger may be inseparable in the minds of those being asked to act upon it.

For lifestyle medicine to scale, therefore, the challenge is not merely to identify effective interventions. It is to develop trusted systems through which those interventions can be delivered.

The prevention paradox inside healthcare

There was another tension in the findings in that healthcare professionals appeared interested in lifestyle medicine, yet the infrastructure surrounding them appeared much less mature.

Among the 58 healthcare professionals surveyed, 48% reported providing lifestyle-related advice to patients, while only 21% reported having received formal training in lifestyle medicine. Almost two-thirds wanted additional training or resources. The principal barriers they identified included patient readiness, limited time and insufficient training. Most strikingly, only 3% thought that the NHS currently supported lifestyle-based approaches “very well”. Because the healthcare professional subgroup was small, these estimates require appropriate caution, but they do generate questions that require further investigation.

We increasingly ask healthcare professionals to practise prevention while maintaining systems historically structured around the identification, treatment and management of established disease. We tell clinicians that lifestyle matters and encourage conversations about physical activity, food, sleep, stress and social connection. But if those conversations are to become a meaningful part of healthcare rather than an optional addition to it, clinicians also require time, competencies, referral pathways, professional standards and services to which patients can actually be directed. A health system cannot become preventive simply by asking its workforce to talk more about prevention. Prevention needs infrastructure.

Perhaps the question is larger than lifestyle medicine

This is where our study findings lead to a broader philosophical question. Modern medicine has become extraordinarily sophisticated at intervening once pathology is visible. We can image increasingly subtle abnormalities, quantify biological risk, stratify populations algorithmically and develop treatments targeted at increasingly specific molecular pathways. Yet many of the actions through which health is created or lost remain remarkably ordinary. They happen in supermarkets and kitchens, on pavements and playing fields, in workplaces and bedrooms, within families, friendships and communities. The future of prevention may therefore depend partly on whether healthcare can become more comfortable operating at the boundary between the clinical and the everyday.

Lifestyle medicine occupies precisely this boundary. Its proposition is not that ordinary life should become medicalised. Nor should structural determinants of health be reduced to individual responsibility. People do not make choices in a vacuum: income, housing, work, neighbourhoods, commercial environments, education and opportunity all constrain what is realistically possible. The more interesting proposition is that healthcare might take the conditions of everyday life more seriously without pretending that every determinant of health belongs inside the consultation room. That requires a different conception of prevention. Not prevention as instruction. Not prevention as telling people to “make better choices”.

But prevention as capability: that is, creating the knowledge, confidence, opportunities, professional support and environments that make healthier lives more achievable.

From lifestyle advice to prevention infrastructure

For that reason, the future of lifestyle medicine may depend less on defending the term and more on answering three practical questions: Can people trust it? Can professionals deliver it competently? Can health systems support it consistently and equitably?

Our findings suggest that these domains (legitimacy, capability and system readiness) are deeply interconnected. Awareness alone will not be enough. Enthusiasm alone will not be enough. Nor will simply adding another service to an already crowded healthcare landscape.

Training matters. Standards matter. Professional credibility matters. Institutional endorsement matters and implementation matters. There is also an important warning here for those of us interested in prevention and self-care. If lifestyle medicine becomes available primarily to people who already possess the resources, knowledge, confidence and time required to engage with it, it could reproduce rather than reduce existing inequalities. A credible model of lifestyle medicine must therefore be more than clinically plausible. It must also be accessible, trusted and equitable.

So when does prevention become medicine?

Perhaps there is no single moment… Perhaps prevention becomes medicine only when scientific evidence is translated into competent practice; when people trust the person delivering it; when health systems make room for it; and when individuals are given meaningful opportunities to participate in decisions about their own health.

The distinction between treatment and prevention may ultimately be less rigid than our institutions have made it appear.

After all, health is not produced only when we enter the healthcare system. It is being shaped long before we arrive. The challenge for the NHS and for health systems more broadly is therefore not simply to treat disease earlier. It is to decide how far upstream healthcare is prepared to travel. Lifestyle medicine offers one possible route.

Our study suggests that people may be more receptive to that journey than familiarity with the terminology alone would suggest. But for lifestyle medicine to move from an appealing idea to a credible component of prevention, it will have to earn something that cannot be manufactured through branding alone: trust.

And perhaps that is the larger lesson. The future of prevention will not be determined only by what we know can improve health. It will also depend on whether we can build institutions, professions and systems that people believe have the legitimacy to help them act on that knowledge.