uk essay biopsychosocial model

The Biopsychosocial Model of Mental Health

One of the most important questions many people have regarding mental-health is what influences it. Why does one person have good mental health while another person’s is poor? What triggers an episode of poor mental health and what are the root causes? The biopsychosocial model helps us understand all of this and more.

Background: The biomedical model

Before we dive into an explanation of the biopsychosocial model, you need to know a bit about something called the biomedical model of mental health. We won’t go into great detail here, but let’s take a quick look at the essentials.

The biomedical model

In the past, psychiatrists, who are trained as medical doctors, saw people who have mental health conditions as being ill in the same way that someone can be physically ill. They saw conditions as a result of disturbances in the brain to be treated with drugs, surgery or other physical means. They reasoned that if something was physically wrong with your brain, it needed a physical cure.

The biomedical approach was challenged in 1977 by George Engel because it didn’t take into account the many other factors that can influence mental health, and health in general. Factors such as upbringing, beliefs, coping skills, trauma and relationships did not enter the equation. It just didn’t seem right to Engel. So he proposed a new way of thinking about mental health that encapsulated social and psychological determinants to health as well as just simply a person’s biology. This was the biopsychosocial model.

The biopsychosocial model

Engel’s biospychosocial model went on to become very influention. Most medical professionals now consider mental health to be affected by three main areas that are encapsulated in the biopsychosocial model:

Biological (e.g. genetics, brain chemistry and brain damage)
Social (e.g. life traumas and stresses, early life experiences and family relationships)
Psychological (e.g. how we interpret events as signifying something negative about ourselves)

These factors interact with each other in complex ways to produce the final result that is a person’s overall mental health. The graphic above is a simplified summary of how the factors work together. In reality, it is a complex web with many connections across the different areas. As we continue on in our lives, new events enter the model and impact on existing factors. It is in flux, not fixed.

Mental health conditions the complex result of several factors

According to the biopsychosocial model, mental health is the result of many forces occurring at different which have a cumulative effect on the individual. These forces can be positive or negative. If the negatives outway the positives then a person could develop a mental illness.

It’s unlikely to be one specific thing that causes mental ill-health, but rather a mixture of negative circumstances that have built up. There might be one thing that pushes a person too far, but it’s unlikely to be this alone that caused a disorder.

Negative factors add up

Imagine you’re having a bad day at work. You had a stressful morning at home, you’ve dealt with more problems than normal from clients and you have just got out of an exhausting meeting you had half forgotten about. You sit back down at your desk and promptly knock your coffee over.

This might bring you to tears, send you into a rage or make you feel that you hate your job. A colleague watching this scene might be justified in thinking that you are so emotional because you knocked your drink over. But it wasn’t knocking your drink over that was the real issue. It was all the other things that happened before that created a situation where, when you did knock your drink over, it was too much.

This is just a simple example. We’ve probably all been there though. Those days when nothing seems to go right come along now and then and it’s infuriating. But the point is that we can all recognise how events can add up to the point where something small can tip us over the edge.

In a similar way, biological, psychological and social factors can add up across a person’s life to lead to times of mental ill-health.

For example it is now well established that schizophrenia has a genetic component. However the condition can be triggered by certain traumatic or stressful life events, such as a pattern of poor and chaotic family relationships in childhood. It is more than one factor that caused the condition.

Depression may be caused by a mixture of life events (such as emotional abuse in childhood or traumas in adulthood such as divorce) and a person’s habitual ways of judging themselves and their experiences. Again, it is not one factor alone that caused the issue.

The biopsychosocial model applies to us all

The biopsychosocial model is great for helping us understand how mental health conditions might develop. However, we shouldn’t only think of it as being useful for people who are not mentally well. It applies to us all. We can its three areas as postive forces to improve our mental health.

Your mental health, mine, your friend’s, your family’s and your colleagues’ is created by an interplay of biological, psychological and social factors. This is important to understand. It means that ‘healthy’ people are not separate from ‘unhealthy’ people.

The mind of someone who has a mental health condition is not entirely different to yours. There’s just a different combination of factors that have come together to create a state where the person is mentally unwell.

As with the mental health continuum , we all have the potential to be mentally well or unwell. We cannot see people with mental health conditions as different in some fundamental way. This is one excellent way to confront the stigma surrounding mental health issues.

The biopsychosocial model in the workplace

The biopsychosocial model has another advantage. As well as being able to explain mental health in terms beyond the purely biomedical, it shows us there is potential to positively influence a person’s mental health in the workplace.

As a manager, you should use the biopsychosocial model to help you find ways you can positively influence your team.

For example, you could influence biological factors by creating lunchtime exercise habits. Or you could promote healthy eating initiatives. In this way, you can positively impact on another’s mental wellbeing.

You should also examine what can be done to improve the social and psychological aspects of your work. Some things will be beyond your control, but other small changes can be made. What training can be given to build resilience? Can you use praise to raise self-esteem? What can you do to foster strong relationships between colleagues?

The positives add up too

Remember, just like negative factors, positive factors add up. A day where you’ve had some positives such as enjoying going for a walk with colleagues over lunch, feeling good because you ate something healthy might mean that when you do knock that cup of coffee over, you are able to see it for what it really is. An annoying accident, but nothing more.

Again, if we apply this logic to our whole lives, then we see that to be more mentally healthy and resilient, we need to ensure we focus on increasing the positive factors in our lives.

What if you’re too busy to do all this?

There’s no getting away from the fact that it can be challenging and time-consuming to work through the biopsychosocial model and identify where changes can be made. But it will be time well spent. The long-term benefits far outweigh the short-term efforts. Check out this article to see why.

Conclusions from the biopsychosocial model

The causes of mental health disorders are complex and varied. Biological factors have a role but they are not the only influence. Social and psychological factors are crucial too.
We are all unique. Some people may be more disposed to develop a mental health issue than others, but we can all improve our mental health by seeing the biopsychosocial model as three positive forces for mental health.
Focussing on the psychological aspects of the biopsychosocial model can empower people to take control of their thoughts and improve their mental health.
Work is a social activity and it can be a positive or negative influence on a person’s mental health.

If you’d like to learn more about mental health, you can get started with our bite-size Mental Health Awareness online course .

Delphis also offers on-site mental health workshops delivered and developed by highly educated business managers, academics and teachers. We guide companies along the path to creating mentally healthy, productive and rewarding working environments for their staff. The financial argument is compelling and caring for your employees is the right thing to do.

One major multi-national client says this about our workshops:

“Very relevant and informative with an engaging and inclusive style. Worth spending a whole day on. Loved the takeaway workbook, pretty much perfect, we need to roll out to whole company.”

Get in touch to discuss how we can provide customised mental health training for your organisation that fits your needs.

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A revitalized biopsychosocial model: core theory, research paradigms, and clinical implications

Derek bolton.

Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK

The biopsychosocial model (BPSM) was proposed by George Engel in 1977 as an improvement to the biomedical model (BMM), to take account of psychological and social as well as biological factors relevant to health and disease. Since then the BPSM has had a mixed reputation, as the overarching framework for psychiatry, perhaps for medicine generally, while also being criticized for being theoretically and empirically vacuous. Over the past few decades, substantial evidence has accumulated supporting the BPSM but its theory remains less clear. The first part of this paper reviews recent well-known, general theories in the relevant sciences that can provide a theoretical framework of the model, constituting a revitalized BPSM capable of theorizing causal interactions within and between biological, psychological, and social domains. Fundamental concepts in this new framework include causation as regulation and dysfunction as dysregulation. Associated research paradigms are outlined in Part 2. Research in psychological therapies and social epidemiology are major examples of programs that have produced results anomalous for the BMM and consistent with the BPSM. Theorized models of causal mechanisms enrich empirical data and two biopsychosocial examples are models of chronic stress and pain perception. Clinical implications are reviewed in Part 3. The BPSM accommodates psychological and social as well as biological treatment effects evident in the clinical trials literature. Personal, interpersonal, and institutional aspects of clinical care are out of the scope of the BMM, assigned to the art of healthcare rather than the science, but can be accommodated and theorized in the BPSM.

Introduction: the problem area and a proposal

The biopsychosocial model (BPSM) was proposed by George Engel in 1977 as an improvement to the biomedical model (BMM), necessary to account for psychological and social factors in health and disease as well as biological (Engel, 1977 ). This proposal remains critical in science and in service planning (Wade & Halligan, 2017 ). However, the BPSM has a mixed reputation: it has been regarded as the overarching, dominant framework for psychiatry, perhaps for medicine generally, while on the other hand, and often at the same time, it has been roundly criticized for being scientifically, theoretically vacuous (Ghaemi, 2009 ; McManus, 2005 ). This is the problem area to be addressed in this paper: what is the science of the BPSM?

At the level of the empirical data, there is reason to think now that this supports the broad BPSM. Over the past few decades, substantial evidence has accumulated that psychosocial as well as biological factors are implicated in the etiology and course of a wide range of health conditions, supporting the BPSM, reviewed, for example, in Novack et al. ( 2007 ), Bolton and Gillett ( 2019 ), and in a recent edited volume on biopsychosocial psychiatry (Savulescu, Roache, Davies, & Loebel, 2020 ). There remains, however, the problem of theory, identified by authoritative critics as cited above: the BPSM seems to have no clear scientific theoretical content. Put another way, the criticisms of the BPSM are typically not reviews of the evidence base, but are doubts about whether the ‘model’ really has anything to say – any content.

Drawing on previous work (Bolton & Gillett, 2019 ), I will present a case that Engel's main idea – that a BPSM was required to replace the BMM – was visionary but programmatic. It was visionary in anticipating radical changes in the ways that health and disease were becoming theorized and researched, but programmatic because the radical changes were in their early stages, still in progress and not yet widely implemented. However, I suggest, the position has changed by now, and theories that can underpin a broader BPSM are well-known and can be drawn upon to revitalize the model.

To explain the background and the proposal further, Engel's 1977 paper implicates two foundational underpinnings of the BMM, the model for biomedicine as conceived at that time: one is that biology, as physiology, is reducible to physics and chemistry, and the other is the assumption of mind/body dualism (Engel, 1977 , p. 379). Dualism notoriously offers no scientific account of how immaterial mental processes can causally influence the material body, and, with this assumption, there is no role for psychological causes in the scientific explanation of behavior unless they are somehow reducible to biological causes. Engel implies that these two foundational underpinnings of the BMM will be abandoned. As to what the replacements are and how they work in a new BPSM, Engel refers to von Bertallanfy's then relatively new General System Theory (Engel, 1977 , pp. 391–392; Von Bertalanffy, 1968 ), but there is no detailed account. However, there were paradigm shifts underway in the biological and psychological sciences at around that time, the emergence of information-based models in biology and the so-called cognitive revolution in psychology, which subsequently have become mainstream science. I will present a case that these new paradigms changed the reductionist assumptions that Engel attributed to the BMM, paving the way for theoretical content for the BPSM.

A defining feature of the BPSM is its interdisciplinarity. High levels of interdisciplinarity require a unified theoretical perspective and integration around shared themes and questions (Boden, 1999 ; Committee on Facilitating Interdisciplinary Research, 2004 ; Strijbos, 2010 ). For the BPSM, shared themes and questions are straightforwardly specifiable about the causes and cures of illness. The substantial task for the BPSM is to explicate a unified theoretical perspective and integration across the three relevant sciences. It turns out, I will propose in what follows, that the required shared theoretical perspectives is systems theoretic, as Engel anticipated, in which concepts such as regulation and control, information and communication, function and dysfunction, play critical roles across the whole biopsychosocial domain.

To make the case for the proposal that the BPSM can be revitalized in terms of current scientific theory I will review, in Part 1, well-known general theories in the three relevant sciences, associated with many research groups, which can provide theoretical content to the model. None of these well-known general theories are, I believe, currently controversial; their competitors are not so much in the current science but in the paradigms being replaced, particularly versions of biological reductionism. In this sense, the revitalized version of the BPSM outlined here is, I suggest, a plausible representation of an overarching model currently in the health sciences. Research paradigms and examples of research programs that implicate the broad range of biopsychosocial factors and which are consistent with the BPSM (regardless whether or not they explicitly invoke the model), are considered in Part 2, and clinical implications will be considered in Part 3.

BPSM core theory

The new biology.

Engel supposed that the BMM supposed biology was or was reducible to physics and chemistry (Engel, 1977 ). This reductionist supposition was pretty much orthodoxy at that time, but is now history. Biology (as physiology) has transformed itself in the last few decades, in a revolution largely driven in fact by biomedicine. Biology (as physiology), with biomedicine, is now a closely integrated combination of two kinds of science: one is the physics and chemistry of energy exchanges and transformations (quantified in enthalpy change equations, for example), but there is in addition something new: models of mechanisms for the regulation and control of the physics and chemistry, and of other systems, maintaining functions, typically using feedback by information-transfer. The new ‘regulatory’ paradigm, also known as the ‘information-processing’ revolution, appeared clearly in molecular biology in the 1960s and 1970s, such as Jacob and Monod's ground-breaking work on genetic regulatory mechanisms in the synthesis of proteins (Jacob & Monod, 1961 ; Lewis, 2013 ).

The new paradigm in biology can be dated to the physicist Ernst Schrödinger ( 1944 ) ground-breaking definition of life as local areas in which the overall direction of the 2nd law of thermodynamics is reversed – life decreases entropy, temporarily (Morange, 2020 ; Schrödinger, 1944 ). Schrödinger saw that this would have to involve control of energy production, and he further hypothesized that this was done by genes. An intellectual pathway can be traced from Schrödinger's new conceptualization of biological systems to von Bertalanffy's general system theory (Von Bertalanffy, 1968 ) to Engel's 1997 paper. Von Bertalanffy proposed that negative entropy was achieved in open systems, in biology and in wider domains including the psychological and the social, and Engel refers to von Bertalanffy's general system theory as a key theoretical driver for the new BPSM, anticipating impacts on healthcare science and practice (Engel, 1977 , pp. 391–392). The paradigm shift was, however, still in the early stages in the 1970s – the detailed work in theory development and new associated research paradigms has been underway in the decades since and continues.

The regulatory mechanisms that are central in the new biology have several core features that change the theoretical foundations of the life sciences in ways critical to explicating the BPSM. First, they are causal, but they are not, and are not reducible to, the energy-related equations of physics and chemistry. Second, and connected, regulatory mechanisms can break down, allowing foundational distinctions between life and death, health and disease, that are unavailable in physics and chemistry. Third, the same kind of theoretical apparatus used in biology (function, organization, regulation and dysregulation, information, production, and distribution) is also used in the psychological and social sciences – as reviewed below.

The new psychology

As noted in the Introduction, Engel supposed that the BMM assumed body/mind dualism and that this was an obstacle to accounting for psychological factors in health and disease. I outline in this section two general ways in which post-dualist, cross-disciplinary theories have been developed over recent decades, critical to formulating a biopsychological model.

Post-dualist models can be characterized as having two working assumptions: one is that mental processes regulate behavior and the other is that mental processing is a function of brain processing. The first point underpins cognitive psychology, while the second merges psychology with neuroscience. Both points are connected with the theoretical innovations in biology in the 1960s and 1970s outlined in the previous section: biology, psychology, and neuroscience all shared interests in new information-based models of the regulation of biological systems and behavior – the paradigm shift went across the life sciences.

The clearest expression of dualist assumptions in psychology was in behaviorism, which explicitly excluded mental processes from explanations of behavior – a position much like Engel attributed to the BMM. From around the 1960s onwards, however, behaviorism was swept away in the cognitive revolution (Miller, 2003 ; Xiong & Proctor, 2018 ).

The cognitive revolution influenced many specialties in psychology, not only learning theory. Cognitive models in clinical psychology emphasized the causal role of personal beliefs in the regulation of affect and behavior, such as Beck's cognitive model of depression (Beck, Rush, Shaw, & Emery, 1979 ). Further, there emerged around this period a class of psychological models focused on the role of expectancies and beliefs about personal control over events – or personal agency – and their implications for well-being. Main examples include Julian Rotter's locus of control theory (Rotter, 1966 ), Martin Seligman and colleagues’ learned helplessness theory (Seligman & Maier, 1967 ) and associated model of depression (Miller & Seligman, 1975 ), Albert Bandura's self-efficacy theory (Bandura, 1982 , 2006 ), and Richard Lazarus and Susan Folkman's work on stress, appraisal, and coping (Lazarus & Folkman, 1984 ).

Importantly, this class of models spanned many psychology specialty areas, across many domains – physiology, learning, personality, and social – and interactions between them. In this sense, they already constituted a theorized BPSM within the broad psychological tent.

The appearance of personal processes in the new psychological science – beliefs, about the world and our agency, personal goals, emotions, and behavior – has substantial relevance to the question whether a broader BPSM is needed in health science and healthcare. Engel gave a long list of important issues the BMM could not account for, and top of the list was ‘the person who has the illness’ (Engel, 1977 , p. 131). Here the point is, at least, that biomedicine can theorize diseased or otherwise dysfunctional organs or systems, but has nothing to say, over and above that, about the person who has the illness. Equally, it can be added, cognitive psychological models of specific systems such as memory and attention, need a wider, person-level framework to theorize how lowered function affects the person, for example, or typically, by compromising agency.

To sum up, the cognitive revolution in psychology endorsed the relevance of mind to science by constructing causal explanatory models of behavior in terms of mental (or cognitive-affective) states. Within that overall framework, diverse psychology specialty areas focused on personal processes – beliefs, about the world and their own agency, personal goals, emotions, and behavior – in interaction with biological and social processes. These developments in psychology have wide implications and they surface again when considering biopsychosocial models, such as of impacts of social disadvantages on health, and of pain and service use, considered in Part 2, and models of clinical care, in Part 3.

The second aspect of post-dualism models mentioned above is that psychological processing is regarded as a function of, or implemented by, brain processing, hence merging psychology with neuroscience. Cognitive (or cognitive-affective) neuroscience (as the merger can be called) has developed alongside cognitive psychology (Albright, Kandel, & Posner, 2000 ).

The new post-dualist constructs of mind and body, further, accommodate crosstalk between neuroscience/psychology and biomedicine, in both directions. This is evident in the new fields of psychoneuroendocrinology (Fink, Pfaff, & Levine, 2012 ) and psychoneuroimmunology (Moraes, Miranda, Loures, Mainieri, & Mármora, 2018 ), as well as in specific models such as of chronic stress and pain to be considered later. These interdisciplinary research programs, involving neuroscience, psychology, and biomedicine, were inconceivable in mind–body dualism. They are examples of the rationale for expanding the BMM to the BPSM, in effect contributing content to the concept of ‘biopsychology’ or ‘psychological medicine’ within the BPSM.

A relatively new class of theories known as ‘embodied mind’, ‘embodied cognition’, or ‘4E cognition’, explicitly overturns dualism and are, therefore, potentially relevant to a revitalized BPSM. They are less familiar than theories discussed above, however, and for reasons of space I do not consider them here – for details of the theories and controversies, see e.g. Newen, Gallagher, and De Bruin ( 2018 ), Carney ( 2020 ), and for current applications in clinical psychology and psychiatry (e.g. Allen & Friston, 2018 ; Gjelsvik, Lovric, & Williams, 2018 ).

Social determinants of health

Social factors can be accommodated within the conceptual framework of the new biopsychology because the social sciences have always employed comparable concepts, such as organization, rules and regulations, control (power), communication, and production and distribution of resources (e.g. Lasswell, 1936 ). In this sense, it is psychology and biology that made the theory changes critical to the BPSM, thereby becoming more aligned with concepts familiar in the social sciences.

The concept of socioeconomic status is closely connected to an individual's or group's access to resources, and the immediate relevance to health is that resources include what promotes good health (Bickel, Moody, Quisenberry, Ramey, & Sheffer, 2014 ; McGowan & Shahab, 2019 ). Over the past few decades, a substantial range of epidemiological studies have established that there are social determinants of health, that is, a positive correlation between higher social status and better health, the so-called social gradient in health, which underpins health inequalities (Marmot, 2006 ). This applies to both physical health and mental health (Bell & Marmot, 2022 ).

The resources that we need for biological health are well-known. Consistent with Schrödinger's insight into what life is, they include conditions of biological energy production. What we need for good psychological health is less well understood, probably because mind/body dualism never provided a useful definition of psychological life. In the new conceptualization of psychological life reviewed in the previous section, its conditions may be framed in terms of having sufficient agency (or autonomy). The extent of agency, like access to the conditions of physical well-being, depends on socioeconomic status. As Michael Marmot puts it: ‘The lower individuals are in the social hierarchy, the less likely it is that their fundamental human needs for autonomy and to be integrated into society will be met’ (Marmot, 2006 , p. 1304). Autonomy is facilitated by social integration especially into dominant power structures, and conversely is downgraded by exclusion, by denial of voice, civil rights and protections, and other means of oppression. These issues have been explored mainly in and across feminist (Biana, 2020 ), postcolonial (Fanon, 1968 ), critical race theory (Delgado & Stefancic, 2001 ), and increasingly in Lesbian, Gay, Bisexual, Trans, and Queer (LGBTQ) literatures (Lee & Brotman, 2013 ). Possible pathways linking social factors to health outcomes will be reviewed below as examples of models of biopsychosocial causal mechanisms.

BPSM research paradigms

Investigating psychological and social impacts on health.

Research designs relevant to the BPSM are those that examine the effects of psychological and social, as well as biological factors, on health outcomes (e.g. Lacombe, Armstrong, Wright, & Foster, 2019 ). Immediate findings are typically of correlations or associations, and control conditions of varying levels of stringency increase confidence in inference to causation. Large-scale group studies are necessary to identify small effects, and the methodology relies on statistical analytic methods such as regression that can estimate the effects of one or more variables on a health condition-dependent variable, estimating independent effects, and interactions moderating the effects of one independent variable by another. Multivariable regression models are applicable within the BMM, including biological variables only, but the expanded BPSM framework also accommodates inclusion of psychological and social variables, estimating their independent, additive, and interaction effects (e.g. Guloksuz et al., 2019 ).

BPSM compatible research studies were barely available when Engel proposed the new model in 1977. In fact, they began to appear at around the same time. The first clinical trials of psychological therapies appeared in the 1970s, heralding what has become a very large-scale research program of developing and evaluating psychological interventions for a wide range of health conditions and their complications. The early finding that cognitive therapy for depression was effective, and moreover, more effective than an antidepressant medication (Rush, Beck, Kovacs, & Hollon, 1977 ), reinforced the signal that the BMM was not enough, at least not for modeling and treating depression. At the same time, there was another major anomaly for the BMM, the emerging findings of social epidemiology, noted in the previous section, that social status affects a wide range of physical health and mental health outcomes, in the Whitehall Studies by Michael Marmot and colleagues (Marmot, Rose, Shipley, & Hamilton, 1978 ; Marmot et al., 1991 ).

The findings that are anomalous for the BMM but consistent with the BPSM are empirical data, related to specific influences on specific conditions at specific stages. There is nothing a priori in the empirical data. It is possible that a specific health condition at a particular stage may turn out to be primarily caused by only one kind of factor – biological, psychological, or social – and of course biomedical models of infectious diseases have had stunning successes in exactly this way. Such findings may be called a scientific-explanatory reduction to biological processes. This type of ‘reduction’ is different from theory-reduction of, for example, biology to physics and chemistry. Both types of ‘reduction’ are relevant to the relation between the BMM and the BPSM and both are in play in Engel's 1977 paper. The BMM would predict scientific-explanatory reduction to primary biological causes only across the whole of health, like the biomedical models of infectious diseases (or of effects of lesions or of genes of major effect). But this is an empirical, not a theoretical matter, and the emerging picture across health is that, especially for the noncommunicable diseases, and including all or practically all mental health conditions, the etiological picture is of at most a ‘patchy’ reductionism, and is more typically diverse, with multiple causal factors (Kendler, 2005 , 2012 ).

Notwithstanding evidence of influence of psychological and social factors on health and disease, there remains a tendency, possibly attributable to long-standing reductionist assumptions in the science, to roll everything up into the biological. There are several examples of this option in the theoretical psychiatry literature. Samuel Guze's highly influential paper over 30 years ago, ‘Biological psychiatry – is there any other kind?’ (Guze, 1989 ) is an example, as indicated by the rhetorical nature of the title question. More recently, Peter White and colleagues proposed that mental disorders are brain disorders, without for a moment being unaware of the research showing the influence of psychosocial factors in the onset and course of many psychiatric conditions (White, Rickards, & Zeman, 2012 ). Likewise National Institute of Mental Health (NIMH's) Research Domains Criteria framework, which regards psychiatric conditions as disorders of brain circuitry (Insel et al., 2010 ).

To the extent that biology, neurology, and neuroscience are being broadly conceived to acknowledge the causal role psychosocial factors in some conditions, in etiology and course, and in prevention and intervention, these theoretical proposals are not reductionist and, albeit unhelpfully expressed, they are compatible with a broad biopsychosocial framework. However, proposals to roll the psychosocial up into the biological appear to be, in name, a kind of reductionism, so far by-passing the need to theorize the acknowledged causal role of psychosocial factors or biopsychosocial causal mechanisms.

Theorized models of causal mechanisms

As well as findings of correlations (or associations) in well-controlled studies, the scientific picture benefits from also having a plausible theory that would explain apparent causal connections. Empiricism in science, relying on observation alone, controlled or otherwise, is well-known to be so far theory-free. In the present case of determining psychological and social causal connections, however, the problem has long been at exactly this point: the absence of a plausible theory of either psychological or social causation, still less theory as to how either could have material effects on biological processes, which were assumed determined by physics and chemistry alone. The assumed impossibility of psychological and social causation and the resulting downwards reductionist pressure inevitably encouraged skepticism toward any apparent empirical demonstration of the impossible. So while empirical evidence for psychosocial causes may accumulate, still, the theory problem is not yet solved and skepticism can persist.

Theory is necessary as well as data, of the sort outlined in the first part of the paper. In brief, psychological causation, implemented in brain processes, involves regulation of behavioral functioning toward attaining or maintaining some state. Social factors can causally interact with psychological processes, for example by regulating task demands and available resources. Psychological and social causal processes are both causal in the sense of regulatory, as is one kind of causation in biology, the other being energy transformations and exchanges covered by physicochemical laws. As to dysfunction, this has to involve disruption to regulation (however caused), because physicochemical laws cannot be disrupted. Models in which regulation/dysregulation are prominent are now to be found not only in biomedicine, but also in clinical psychology and psychiatry (Kendler & Woodward, 2021 ; Liu, Chua, Chong, Subramaniam, & Mahendran, 2020 ). Two well-known illustrations of theorized biopsychosocial causal mechanisms are given below.

The first example is a set of models of chronic stress, applied to epidemiological findings on the social determinants of health, aiming to explain pathways between unfavorable social status and unfavorable health outcomes. The key point for the present context is that the hypothesized causal mechanisms are biopsychosocial, indeed they have to be because the pathways implicated by the epidemiological research run across the three domains. Common hypothesized causal mechanisms and pathways include the following: low levels of social resources (e.g. working poverty and other forms of social exclusion) lead to chronic lack of control over salient outcomes, leading to chronic psychological stress, raising risk of anxiety and depression, while the chronic physiological arousal associated with chronic psychological stress raises the risk of dysregulation and damage across multiple biological systems and hence poor health outcomes. There is not space here nor is it the intention to review the large literature on chronic stress models (O'Connor, Thayer, & Vedhara, 2021 ; Roberts & Karatsoreos, 2021 ), but simply to give an illustration of a substantial research program on biopsychosocial causal mechanisms.

The second example of a new causal explanatory biopsychosocial theory with wide application comprises new models of pain perception, implicating neurobiological–psychological processing as well as peripheral physiological or structural damage. The new models implicate the person's negative appraisals of the meaning of pain and expected adverse effects on their lives and task demands, and associated Central Nervous System (CNS) pain-processing mechanisms (Garland, 2012 ; Ong, Stohler, & Herr, 2019 ).

This new understanding of pain perception is directly relevant to conditions dominated by pain, but there is a broader point that is relevant to the health sector as a whole, specifically to drivers of service use. The complex of pain, distress about pain, with associated impairment of functioning, is close to ‘feeling unwell’ and is a main driver of referral and service use. It is increasingly recognized that significant proportions of patients with such presentations turn out to have medically unexplained symptoms. ‘Medically unexplained’ here actually means biomedically unexplained, and biomedically orientated clinics typically have no biopsychosocial management protocols in place; consequently needs are not met, and the patient journey can be potentially long and costly; for example, in general practice and medical clinics (Jadhakhan, Lindner, Blakemore, & Guthrie, 2019 ), cardiology (Lenderink & Balkestein, 2019 ), neurology (Carson et al., 2003 ), and surgery for some pain presentations (Louw, Diener, Fernández-de-Las-Peñas, & Puentedura, 2017 ).

Neuroscience and genetics are biopsychosocial

This overview of BPSM research paradigms with examples of major research programs has to briefly mention that the two life sciences that have accelerated the most in recent decades – genetics and neuroscience – are suited to a biopsychosocial theoretical framework. Indeed, it's more than that; they have been instrumental in making the new BPSM compatible core theory reviewed in Part 1.

It was advanced in genetics that introduced into biology theoretical ideas of a new kind of science involving coding, information-transfer, error, regulation and control, additional to energy-transfer and -exchanges covered by physical–chemical laws (equations). Further, theories of genetics have always been thoroughly interactional across domains, in evolutionary theory, and recently in the new field of epigenetics, including in psychiatry (Campanile, Fanelli, Fabbri, Serretti, & Mendlewicz, 2022 ; Cecil, 2020 ).

The same theory-shift that transformed biology also transformed neuroscience and cognitive psychology, enabling a coherent biopsychology. As to the domain of social interactions, there is no shortage of research programs on its major importance to our biopsychology in phylogenesis (Barrett, Henzi, & Barton, 2022 ) and ontogenesis (Blakemore, 2008 ).

Clinical implications

Clinical trials and guidelines.

The clearest clinical implications of the BPSM, in contrast as always with the narrower BMM, is accommodation of psychological and social factors as well as biological factors relevant to clinical management and treatment. The importance of this broader scope has been substantially supported in the clinical trials literature, appearing mainly after Engel wrote his 1977 main paper. Large-scale clinical therapeutics research programs in the decades since have studied and shown the effectiveness of some psychological therapies for a large range of health conditions (Barkham & Lambert, 2021 ), of combination therapy, medication plus psychotherapy, for some conditions such as depression (Breedvelt et al., 2021 ), and of social treatments such as social support (Brown et al., 2020 ; Wang, Mann, Lloyd-Evans, Ma, & Johnson, 2018 ). The details of exactly what helps what are always specific to details of treatment, condition(s) and stage, but the overall picture that has emerged from the clinical trials literature is consistent with the broad biopsychosocial framework, in the precise sense that any narrower framework – envisaging treatments that are biological only, psychological only, or social only – omits some effective treatments for some health conditions at particular stages.

Now that there is a substantial clinical trials literature, summarized and adapted in clinical guidelines, it is of major importance in clinical decision making. And the broad message, as above, is that the broad biopsychosocial framework is required to accommodate it.

Like the BMM, the BPSM covers not only causes of onset (etiology) and treatments, but also post-onset maintaining causes that adversely affect prognosis. The models of chronic stress and of pain outlined above are examples of maintaining mechanisms across the biopsychosocial domains. Social determinants of health associated with chronic stress, for example, are typically on-going, affecting not only illness onset but also prognosis, for example, by adversely affecting access to treatment (Schneider, Roots, & Rathmann, 2021 ).

Theorizing personal, interpersonal, and institutional factors in clinical care

A lot more is going on in clinical care than decisions as to what treatments to recommend, including personal, interpersonal, and institutional processes. Specific issues include the role of the person as patient – in determining what is wrong, whether anything is wrong, in collaborating on a treatment plan – the imperative of ‘compassionate’ care (Hodges, Paech, & Bennett, 2020 ), and institutional/professional factors supporting or jeopardizing good clinical care (Mannion et al., 2019 ). Engel says a lot of interesting things about all these things in his 1997 paper and others around that time (Engel, 1980 , 1982 ), and they can be considered as part of what is covered by the BPSM.

While persons, interpersonal relations, and institutions can be accommodated within the BPSM, the contrast with the BMM is, as always, clear. These matters are simply out of the scope of the narrower BMM: they are not in its ontology, and therefore, it has no idea of them at all, still less their causes and effects. Therefore, adherence to the BMM (or to any model or line of thought, by whatever name, which regards biological processes alone as being causally relevant to health and disease) will have to construe these other matters in another way, broadly not as science, but as ‘art’. There is of course a grand tradition of this approach in medical theorizing – see, for example, Nassir Ghaemi (Ghaemi, 2010 ) – and Engel argued against it, favoring rather a broadly scientific-investigatory approach to understanding and improving, for example, receptive and expressive clinical communication skills, and institutional supports of clinical professional care (Bolton, 2020 ; Engel, 1978 , 1980 ).

The revitalized, cross-disciplinary BPSM proposed here can be used to theorize personal and institutional factors relevant to clinical care and highlight their role as critical and not merely discretionary considerations. For example, the fundamental importance of personal agency in psychology is consistent with the central role of the person as patient, and the fundamental importance of socio-political factors in regulating recognition and access to resources can help theorize and highlight interpersonal, institutional, and wider political processes that affect clinical care.

The key added value of the BPSM, in contrast with BMM, is that it accommodates personal, interpersonal, and institutional factors in clinical care within the causal systems affecting health and disease. That said, it should be noted that these issues have been most theorized by other models of care, for example patient or person-centered models (Epstein & Street, 2011 ; Nolte, 2017 ), and the more recent Recovery Model (Hare-Duke, Ng, & Slade, 2022 ), and in reports and studies on healthcare institutional failure (Reader & Gillespie, 2013 ). There is the further important point that the increasing voice of the person as patient has been substantially a consequence of activism and wider socio-political movements, not a matter of healthcare theory and research (Brown, 1981 ; Rashed, 2019 ).

Engel's proposal in the late 1970s that a new model was needed to take account of not only biological factors affecting health and disease, but also psychological and social factors, was made at a time when the theoretical and empirical backing for it was not established but was rather in construction. The proposed new BPSM can be regarded as being, at the time in the late 1970s, a general empirical hypothesis that psychosocial as well as biological factors are implicated in the causes and cures of illness, and as such, it could have turned out false. As things have turned out, however, the model as a general empirical hypothesis has been confirmed. The determination of relevant evidence in the intervening decades has required the development of new research methodologies capable of determining multifactorial influences on onset, course, complications, and treatments. The overall picture of causes and cures that has emerged, comprising specifics on many particular health conditions and treatments, is broadly biopsychosocial rather than narrowly biological, which is why the terms ‘biopsychosocial’ or ‘biopsychosocial model’ have established extensive application in the clinical literature and in healthcare classrooms. Regarding theory and mechanisms, Engel recognized that reductionism of various sorts in the basic sciences of biology and psychology stood in the way of conceptualizing biopsychosocial causation, and that radical new nonreductive theories were required. As outlined in this paper, these radical changes required to theorize the BPSM were in fact already in their early stages by the late 1970s and are now standard science. Empirical findings, new research paradigms, and theories developed in the last few decades effectively update and revitalize the BPSM.

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Understanding the Biopsychosocial Model of Health and Wellness

A holistic approach to well-being

Dr. Amy Marschall is an autistic clinical psychologist with ADHD, working with children and adolescents who also identify with these neurotypes among others. She is certified in TF-CBT and telemental health.

Steven Gans, MD is board-certified in psychiatry and is an active supervisor, teacher, and mentor at Massachusetts General Hospital.

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The Three Aspects of the Biopsychosocial Model

How the Biopsychosocial Model Impacts Mental Health

Criticism of the Model

How Healthcare Professionals Use the Biopsychosocial Model

How clients and patients can use the biopsychosocial model.

The biopsychosocial model is an approach to understanding mental and physical health through a multi-systems lens, understanding the influence of biology, psychology, and social environment. Dr. George Engel and Dr. John Romano developed this model in the 1970s, but the concept of this has existed in medicine for centuries.

A biopsychosocial approach to healthcare understands that these systems overlap and interact to impact each individual’s well-being and risk for illness, and understanding these systems can lead to more effective treatment. It also recognizes the importance of patient self-awareness , relationships with providers in the healthcare system, and individual life context.

Dr. Akeem Marsh, MD , physician and author of Not Just Bad Kids , described the biopsychosocial model as “at its core, centering around social determinants of mental health in connection with the ‘standard’ biomedical and psychological models. One of the more common ways in which it is represented when using the model is through the four ‘Ps’ of case formulation: predisposing, precipitating, perpetuating, and protective factors.”

Learn more about how providers can use the biopsychosocial model to offer holistic care and how clients and patients can benefit from this approach.

What Are the Three Aspects of the Biopsychosocial Model?

When understanding an individual’s physical and mental health through the biopsychosocial model, we consider physiological factors such as genetics and illness pathology (biological); thoughts, emotions, and behavior (psychological); and socioeconomic components, social support, and culture (social). How do each of these components inform the model as a whole?

“Biology” refers to our genetics , physical health, and the functioning of our organ systems. Our physical well-being impacts our mental health for multiple reasons. First, our brain is an organ and can become unwell just like any other organ. Second, physical health conditions can wear on mental health. For example, chronic pain can lead to symptoms of depression.

Additionally, just like we can have genetic predisposition to a physical disability, mental health has genetic roots as well. According to Dr. Marsh, “Genetics are the most basic level by which mental health is influenced, and on some level has an impact for everyone.” In other words, “Whatever the phenotypical expression, genetics does play a role to some degree.” The expression is in turn influenced by the environment.

Psychological

Mental health is health, and one’s psychological well-being impacts both mental and physical health. Unhealthy and maladaptive moods, thoughts, and behaviors can all be symptoms of mental health conditions, and in turn can contribute to our overall health. Mental health and behavior can be cyclical; for example, an individual who self-isolates as a symptom of depression may experience increased depressive symptoms as a result of isolation.

Routine physical activity is known to promote positive mental wellness, while inadequate or excessive physical activity can contribute to different types of mental health struggles.

Addressing these symptoms is key in improving mental health.

Dr. Marsh shares the impact of external factors on health: “The expression [of genetics] is in turn influenced by environment.” Changes in one’s environment can impact mental health, both positively and negatively. In the previous example of depression and isolation , individuals who have appropriate social support experience fewer mental health issues compared to those without this support.

An individual who is struggling with their mental health might need social support and environmental changes just as much as they need therapy or medication intervention for their symptoms.

Traditionally, healthcare has focused primarily on the medical and biological side of the patient’s needs, and mental health care has focused on the psychological side. While it makes logical sense to address manifesting symptoms, a holistic approach to care that aims to address the social as well as the psychological and biological contributions to illness can be more health-promoting.

Sometimes, for instance, addressing an underlying social need or environmental stressor can improve mental health more effectively than other psychological or biological treatments. This may allow for less-invasive treatments and interventions, and it can improve the individual’s well-being in a way that non-holistic models overlook.

Criticism of the Biopsychosocial Model

Although many providers support a holistic approach to care and implement the biopsychosocial model in practice, like any model it has limitations. Dr. Marsh notes that there are concerns about its evidence backing: “Some people believe that [the biopsychosocial model] is not scientific, as in it has not quite met the ‘gold standard’ of being validated through multiple randomized trials, as it is a uniquely challenging study prospect.” How can researchers study controlled variables in a model that requires holistic care that takes individual needs into account?

At the same time, the model has many strengths and can benefit patients in the healthcare and mental health systems: “It has been researched extensively and shown positive results when applied in different ways,” Dr. Marsh said.

Mental health professionals who utilize the biopsychosocial model in practice include extensive medical history, family history, genetics, and social factors in assessments in addition to psychological information.

Additionally, they use this information to ensure that all of the client’s needs are met , as many medical issues can manifest with mental health symptoms. Therapy services to treat, for example, depression caused by an under-functioning thyroid is unlikely to be effective.

When adopted appropriately, health professionals conceptualize patients that they work with in a broad context that attempts to understand and see patients as a whole person—complex human being with nuance, so much more than just a cluster of symptoms or diagnosis.

This model lets providers see the whole person beyond their presenting symptoms.

While the biopsychosocial model has its place in the healthcare and mental healthcare systems, individuals might also implement tenants of this model in their own lives. This means being aware of how environmental factors impact their mental and physical health, as well as how their genetics and medical history in turn influence behaviors, thoughts, and emotions.

It can help individuals better understand themselves as complex, whole beings as well. “I believe that [the biopsychosocial model] could enhance their self-awareness and understanding of themselves, along with broadening their personal sense of what issues or challenges may be going on with them," says Dr. Marsh.

Engel GL. The need for a new medical model: a challenge for biomedicine . Science . 1977;196(4286):129-136. doi:10.1126/science.847460

Soltani S, Kopala-Sibley DC, Noel M. The co-occurrence of pediatric chronic pain and depression: a narrative review and conceptualization of mutual maintenance . The Clinical Journal of Pain . 2019;35(7):633-643. doi:10.1097/AJP.0000000000000723

Alsubaie MM, Stain HJ, Webster LAD, Wadman R. The role of sources of social support on depression and quality of life for university students . International Journal of Adolescence and Youth . 2019;24(4):484-496. doi:10.1080/02673843.2019.1568887

By Amy Marschall, PsyD Dr. Amy Marschall is an autistic clinical psychologist with ADHD, working with children and adolescents who also identify with these neurotypes among others. She is certified in TF-CBT and telemental health.

IResearchNet

Mental Health and the Biopsychosocial Perspective

This article explores the intricate relationship between mental health and the biopsychosocial perspective within the field of health psychology . The introduction delineates the significance of mental health in overall well-being and provides an overview of the holistic biopsychosocial perspective. The subsequent sections delve into the biological factors, scrutinizing neurobiological influences, genetic factors, and physiological aspects. The psychological factors section dissects cognitive, emotional, and behavioral dimensions, emphasizing the role of cognitive behavioral therapy and emotional intelligence. Social and environmental factors follow, examining the impact of social support, cultural influences, and environmental stressors on mental health. The article integrates these factors in the biopsychosocial model, presenting case studies to exemplify its application and addressing challenges and criticisms. The conclusion emphasizes the interconnectedness of biological, psychological, and social factors, advocates for holistic approaches in mental health care, and suggests future directions in Biopsychosocial research.

Introduction

Mental health, an integral component of overall well-being, constitutes a multifaceted domain encompassing emotional, psychological, and social dimensions. Defined as a state of cognitive and emotional balance, mental health goes beyond the absence of mental disorders, encapsulating the ability to cope with life’s challenges, form meaningful relationships, and contribute to society. The paramount significance of mental health in influencing one’s quality of life and functioning cannot be overstated, as it intricately intertwines with physical health, productivity, and social interactions. Neglecting mental health not only jeopardizes individual welfare but also has far-reaching societal implications. This article provides a nuanced exploration of mental health through the lens of the Biopsychosocial Perspective, a conceptual framework that acknowledges the interplay of biological, psychological, and social factors. 1. Tracing its origins and development, this section highlights the evolution of the Biopsychosocial Perspective, underscoring its emergence as a holistic approach to understanding mental health. 2. By adopting a comprehensive viewpoint, the Biopsychosocial Perspective recognizes that mental health is not solely determined by biological factors but is profoundly influenced by psychological and social dimensions, fostering a more encompassing understanding of mental well-being.

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The intricate relationship between neurobiology and mental health is a central focus within the Biopsychosocial Perspective. 1. The role of brain structure and function is pivotal in understanding mental health dynamics. Brain regions such as the prefrontal cortex, amygdala, and hippocampus play crucial roles in regulating emotions, decision-making, and memory. Disruptions in these structures have been linked to various mental health conditions, providing insights into the neural basis of psychiatric disorders. 2. Neurotransmitters, acting as messengers within the brain, significantly influence mental health. Alterations in neurotransmitter levels, such as serotonin, dopamine, and norepinephrine, have been associated with mood disorders and schizophrenia, elucidating the neurochemical underpinnings of mental health conditions.

Genetic contributions to mental health underscore the complex interplay between genes and environment. 1. The heritability of mental health disorders suggests a genetic predisposition to certain conditions. Twin, family, and adoption studies have provided evidence for the heritability of disorders like depression, bipolar disorder, and schizophrenia. Understanding the genetic component enhances our comprehension of the risk factors and susceptibility inherent in mental health. 2. Identifying genetic markers associated with mental health conditions is an ongoing area of research. Genome-wide association studies (GWAS) and molecular genetics techniques are unraveling specific genes and variations that contribute to vulnerability or resilience in the face of environmental stressors, paving the way for targeted interventions.

The influence of physiological factors on mental health extends beyond neural processes to encompass hormonal and physical aspects. 1. Hormonal influences on mental health, particularly involving stress hormones like cortisol, are critical in the body’s response to challenges. Dysregulation of the stress response system has been linked to anxiety disorders and post-traumatic stress disorder, highlighting the intricate connection between hormonal imbalances and mental well-being. 2. The impact of physical health on mental well-being emphasizes the bidirectional relationship between physical and mental health. Chronic illnesses, lifestyle factors, and overall health status contribute to mental health outcomes, underscoring the importance of a holistic approach that considers both biological and lifestyle elements in mental health assessments and interventions.

Psychological Factors in Mental Health

Understanding the intricate interplay between cognition and mental health is essential within the Biopsychosocial Perspective. 1. Thought patterns and their impact on mental health elucidate the significance of cognitive processes. Dysfunctional thought patterns, such as negative self-talk and cognitive distortions, are associated with various mental health disorders, influencing emotions and behaviors. Recognizing and altering maladaptive thought patterns are key components in cognitive-behavioral models of therapy. 2. Cognitive Behavioral Therapy (CBT) approaches represent a cornerstone in psychological interventions. CBT focuses on identifying and modifying distorted thought patterns and behaviors, promoting adaptive coping strategies. With empirical support for its efficacy, CBT has become a widely utilized therapeutic modality for a spectrum of mental health conditions.

The intricate relationship between emotions and mental health is a central aspect of the Biopsychosocial Perspective. 1. Emotion regulation, the ability to manage and modulate emotional responses, plays a pivotal role in mental health. Difficulties in emotion regulation are observed in various disorders, including mood disorders and borderline personality disorder. Interventions targeting emotion regulation skills have shown promise in ameliorating symptoms and improving overall well-being. 2. The impact of emotional intelligence on mental health underscores the importance of recognizing, understanding, and effectively managing emotions. Individuals with higher emotional intelligence exhibit better mental health outcomes, as they navigate interpersonal relationships, cope with stressors, and adapt to challenges more effectively.

Behavioral dimensions contribute significantly to our understanding of mental health within the Biopsychosocial Perspective. 1. Behavioral models in mental health emphasize the role of learned behaviors in the development and maintenance of psychological disorders. Behavioral approaches, rooted in principles of conditioning and reinforcement, provide insights into maladaptive behaviors and inform therapeutic interventions. 2. Behavioral interventions and therapies offer practical strategies for modifying behaviors associated with mental health challenges. Techniques such as exposure therapy, behavioral activation, and contingency management target specific behaviors, fostering positive change and symptom relief. The integration of behavioral approaches within the broader context of the Biopsychosocial Perspective highlights the importance of addressing behavioral factors in comprehensive mental health care.

Social and Environmental Factors in Mental Health

The social context is integral to understanding mental health, emphasizing the impact of social support and relationships. 1. The importance of social networks in mental health cannot be overstated. Strong social connections and supportive relationships serve as buffers against stress, providing emotional aid and fostering a sense of belonging. The quality of social interactions influences mental well-being, with positive relationships correlating with better mental health outcomes. 2. Conversely, the impact of social isolation on mental health underscores the detrimental effects of loneliness and lack of social connections. Social isolation is associated with increased risk of depression, anxiety, and other mental health disorders, emphasizing the need to address social factors in mental health interventions.

Recognizing the cultural dimensions of mental health is crucial within the Biopsychosocial Perspective. 1. Cultural variations in mental health highlight the diversity of expressions and experiences of psychological distress across different cultural contexts. Beliefs, norms, and cultural practices shape individuals’ perceptions and coping mechanisms, influencing the manifestation and interpretation of mental health symptoms. 2. Cultural competence in mental health care is imperative to ensure effective and sensitive treatment. Mental health professionals must be attuned to cultural nuances, respecting diverse worldviews, and adapting interventions to align with cultural values. Culturally competent care enhances treatment engagement and effectiveness, acknowledging the impact of cultural factors on mental health outcomes.

The broader environmental context plays a significant role in shaping mental health outcomes within the Biopsychosocial Perspective. 1. The impact of socioeconomic factors on mental health elucidates the link between economic disparities and psychological well-being. Socioeconomic status influences access to resources, education, and healthcare, contributing to disparities in mental health outcomes. Addressing social determinants of mental health is crucial for promoting equity and reducing the burden of mental health disorders. 2. Urbanization and its effects on mental health underscore the challenges posed by modern living environments. Factors such as noise, pollution, and social density in urban settings have been associated with increased stress and mental health issues, necessitating urban planning strategies that prioritize mental well-being. Understanding and addressing environmental stressors are integral components of a comprehensive Biopsychosocial Perspective on mental health.

Integration of the Biopsychosocial Model

The integration of the Biopsychosocial Model underscores the dynamic interplay between biological, psychological, and social dimensions in shaping mental health outcomes. The interconnectedness of biological factors is evident as neurobiological, genetic, and physiological influences mutually inform and influence one another. Biological processes, such as neurotransmitter functioning or genetic predispositions, interact with psychological and social factors to shape an individual’s mental health. Psychological factors are intricately connected to both biological and social elements. Cognitive processes, emotional regulation, and behavioral patterns intertwine with biological mechanisms and social contexts, forming a complex web that shapes mental health experiences. Social factors, encompassing social support, cultural influences, and environmental stressors, interact with biological and psychological factors to impact mental health. The Biopsychosocial Model recognizes that understanding mental health necessitates a holistic examination of these interconnected dimensions.

Examining case studies provides concrete examples of how the Biopsychosocial Model operates in real-world scenarios, elucidating the holistic nature of mental health. Case studies illustrating the interplay of biological factors delve into instances where genetic predispositions, neurobiological functioning, and physiological aspects collectively contribute to the manifestation and progression of mental health disorders. Psychological case studies showcase how cognitive, emotional, and behavioral factors interact with biological elements, providing insights into the holistic nature of psychological functioning. Social case studies demonstrate the influence of social support, cultural factors, and environmental stressors on mental health, highlighting the need for comprehensive, contextually sensitive interventions. These cases underscore the value of considering the entirety of the Biopsychosocial Model in understanding and addressing mental health challenges.

While the Biopsychosocial Perspective offers a comprehensive framework for understanding mental health, it is not without challenges and criticisms. Challenges include the difficulty in precisely quantifying and delineating the relative contributions of biological, psychological, and social factors in any given mental health condition. The complex interplay among these dimensions often complicates research designs and treatment strategies. Criticisms of the Biopsychosocial Perspective range from concerns about its broad scope potentially leading to overcomplexity to debates regarding the relative emphasis given to each factor. Striking a balance between comprehensive understanding and practical applicability remains a persistent challenge. Addressing these challenges and criticisms is essential for refining and advancing the Biopsychosocial Model, ensuring its continued relevance and effectiveness in the field of mental health.

In summarizing the exploration of mental health through the Biopsychosocial Perspective, several key points emerge. The definition of mental health goes beyond the absence of disorders, encompassing cognitive and emotional balance, and is integral to overall well-being. The Biopsychosocial Perspective provides a holistic framework acknowledging the interplay of biological, psychological, and social factors in shaping mental health. Biological factors, including neurobiological influences, genetic factors, and physiological elements, interact with psychological factors such as cognition, emotion, and behavior, while social and environmental factors further contribute to the complexity of mental health dynamics.

This comprehensive understanding of mental health calls for a paradigm shift towards holistic approaches in mental health care. Integrating biological, psychological, and social perspectives in assessment, diagnosis, and treatment is essential. Mental health interventions should consider the interconnectedness of these factors, recognizing that effective care extends beyond symptom management to address the root causes within the broader context of an individual’s life. Collaborative efforts among healthcare professionals, researchers, and policymakers are necessary to develop and implement integrated, person-centered approaches that prioritize the diverse needs and experiences of individuals seeking mental health support.

As we look towards the future, continued research is essential to refine and expand our understanding of mental health within the Biopsychosocial Perspective. Advances in technology and neuroscience offer opportunities to deepen our understanding of biological factors, including genetics, neurobiology, and physiological processes. Further exploration of cultural nuances, social determinants, and environmental influences will enhance cultural competence in mental health care and guide interventions that are sensitive to diverse contexts. Longitudinal studies and interdisciplinary collaborations will contribute to unraveling the complexities of the Biopsychosocial Model, addressing challenges, and refining the framework for more precise applications in research and clinical practice. Embracing these future directions will propel the field toward more effective, personalized, and holistic approaches to promoting mental health and well-being.

References:

Adler, N. E., & Stewart, J. (2010). Health disparities across the lifespan: Meaning, methods, and mechanisms. Annals of the New York Academy of Sciences, 1186(1), 5-23.
Beck, A. T., & Dozois, D. J. (2011). Cognitive therapy: Current status and future directions. Annual Review of Medicine, 62, 397-409.
Caspi, A., & Moffitt, T. E. (2006). Gene–environment interactions in psychiatry: Joining forces with neuroscience. Nature Reviews Neuroscience, 7(7), 583-590.
Cohen, S., & Wills, T. A. (1985). Stress, social support, and the buffering hypothesis. Psychological Bulletin, 98(2), 310-357.
Engel, G. L. (1977). The need for a new medical model: A challenge for biomedicine. Science, 196(4286), 129-136.
Galderisi, S., Heinz, A., Kastrup, M., Beezhold, J., & Sartorius, N. (2015). Toward a new definition of mental health. World Psychiatry, 14(2), 231-233.
Gross, J. J. (2015). Emotion regulation: Current status and future prospects. Psychological Inquiry, 26(1), 1-26.
Hofstede, G. (2001). Culture’s consequences: Comparing values, behaviors, institutions, and organizations across nations. Sage Publications.
Holmes, T. H., & Rahe, R. H. (1967). The Social Readjustment Rating Scale. Journal of Psychosomatic Research, 11(2), 213-218.
House, J. S., Landis, K. R., & Umberson, D. (1988). Social relationships and health. Science, 241(4865), 540-545.
Kandel, E. R., Schwartz, J. H., & Jessell, T. M. (2000). Principles of neural science (4th ed.). McGraw-Hill.
Kendler, K. S., & Gardner, C. O. (2016). Dependent stressful life events and prior depressive episodes in the prediction of major depression: The problem of causal inference in psychiatric epidemiology. Archives of General Psychiatry, 69(5), 513-519.
Kendler, K. S., Karkowski, L. M., & Prescott, C. A. (1999). Causal relationship between stressful life events and the onset of major depression. The American Journal of Psychiatry, 156(6), 837-841.
Kessler, R. C., & Bromet, E. J. (2013). The epidemiology of depression across cultures. Annual Review of Public Health, 34, 119-138.
Linehan, M. M. (2015). DBT® Skills Training Manual (2nd ed.). Guilford Press.
Marmot, M. (2005). Social determinants of health inequalities. The Lancet, 365(9464), 1099-1104.
McEwen, B. S. (2017). Neurobiological and systemic effects of chronic stress. Chronic Stress, 1, 2470547017692328.
Rutter, M. (2006). Genes and behavior: Nature-nurture interplay explained. Blackwell Publishing.
Sarason, I. G., Levine, H. M., Basham, R. B., & Sarason, B. R. (1983). Assessing social support: The Social Support Questionnaire. Journal of Personality and Social Psychology, 44(1), 127-139.
World Health Organization. (2018). Mental health: Strengthening our response. Retrieved from https://www.who.int/news-room/fact-sheets/detail/mental-health-strengthening-our-response

The Biopsychosocial Model 40 Years On

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First Online: 29 March 2019

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Derek Bolton 3 &
Grant Gillett 4

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The first chapter outlines George Engel’s proposal of a new biopsychosocial model for medicine and healthcare in papers 40 years ago and reviews its current status. The model is popular and much invoked in clinical and health education settings and has claim to be the overarching framework for contemporary healthcare. On the other hand, the model has been increasingly criticised for being vague, useless, and even incoherent—clinically, scientifically and philosophically. The combination of these two points signifies something of a crisis in the conceptual foundations of medicine and healthcare. We outline some of the emerging evidence implicating psychosocial as well as biological factors in health and disease, and propose the following solution to the vagueness problem: that the scientific and clinical content of the model relates to specific conditions and stages of conditions, so that there is, for example, a biopsychosocial model of cardiovascular disease, diabetes or depression. Much the same point applies to the narrower biomedical model. However this raises the question: what is the point of having a general model? Our response is that it is needed to theorise biopsychosocial interactions in health and disease. In the light of historical prejudices against psychosocial causation deriving from physicalist reductionism and dualism, recognised by Engel and current commentators on the biopsychosocial model, this is a non-trivial task that occupies subsequent chapters.

Biomedical model
Biopsychosocial model
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1.1 Doing Well—But with Underlying Problems

1.1.1 engel’s proposed improvement on the biomedical model.

In his classic paper published in 1977 George Engel proposed a new model for medicine, the biopsychosocial model, contrasted with the existing biomedical model [ 1 ]. While recognising the great advances in biomedicine, Engel argued that nevertheless the biomedical model was limited, and insufficient for many aspects of medical science and healthcare. These limitations were extensive, comprising failure to take account of the following: the person who has the illness, the person’s experience of, account of and attitude towards the illness ; whether the person or others in fact regard the condition as an illness; care of the patient as a person; for some conditions such as schizophrenia and diabetes, the effect of conditions of living on onset, presentation and course; and finally, the healthcare system itself also cannot be conceptualised solely in biomedical terms but rather involves social factors such as professionalisation ([ 1 ], pp. 131–135). Engel argued that a broadening of the biomedical approach, a new biopsychosocial model, was needed to take account of all these factors ‘contributing to both illness and patienthood’ ([ 1 ], p. 133).

1.1.2 The Presumed ‘Overarching Framework’

In his review of a recent book on the biopsychosocial model by Nassir Ghaemi [ 2 ], in The American Journal of Psychiatry , Kenneth Kendler starts with the sentence: “This book is about a very important topic—the overarching conceptual framework of our field of psychiatry” ([ 3 ], p. 999).

Whether the biopsychosocial model has this status for the rest of medicine is less clear, given the prominence of biomedicine and its biomedical model. Nevertheless, ‘the rest of medicine’ is not one thing, and the various medical specialities differ in their relative involvement with the biological, the psychological and the social. Primary care, also known as general practice or family medicine, is well-known to be much involved in psychological and social factors, and another clear example is public health. The relevant contrast here is with biomedicine, but biomedicine is not itself a medical speciality, but a particular kind of biological science-based medicine that can be applied across medical specialities, in some more than in others. Although Engel starts his paper referring to the ‘medical model’, he soon switches to ‘biomedical model’ and this is the term he uses for the contrast with his new proposed ‘biopsychosocial model’. In short it is not only psychiatry but also all the other non-biomedical aspects of medicine and its specialities that apparently require the broader biopsychosocial model.

We will review some of the health science suggesting the need for a biopsychosocial model in the next section, but first let us consider some current major trends in health, disease and healthcare that point to the same conclusion.

Engel was primarily concerned with psychosocial aspects of managing illness within hospitals, complementing the biomedical approach in hospital care. The example he discussed in detail in his 1980 ‘clinical applications’ paper was of myocardial infarction [ 4 ]. However, it has become clear in the intervening decades that managing illnesses in hospital is a particular and expensive way of providing healthcare. Illness severe enough to require hospital admission has high burden of suffering and disability, and high costs of hospital care, including biomedical investigations and treatments. It would be better all round to prevent illness altogether, or to detect and manage it earlier to prevent worsening, and also better to provide community and social care where possible to avoid or shorten hospital admissions. Implementing this last strategy involves practical psychological and social factors, such as availability of social supports or social care. The first two strategies, primary and secondary prevention, interact with psychosocial factors such as lifestyle, social capital and health literacy.

At the same time the importance of many of the areas of neglect that Engel conveniently listed under one heading—as shortcomings of the biomedical model—have been ratcheted up by diverse trends including socio-cultural changes, economics and globalisation. The voice of the service user has gained strength from civil rights and general emancipatory social changes; rising costs of healthcare in economically developed countries have focussed minds on containing costs by service reorganisations of diverse kinds; health has become globalised in many ways, such as improving health services in economically developing countries, or in the need for international policy to manage epidemics that can now spread more rapidly worldwide.

Other trends since Engel wrote that have also broadened the focus to include more than the biomedical model have to do with changing patterns of population health. Among the greatest achievements of biomedicine have been the identification, treatment and control of infectious diseases. However, and connected, the current burden of ill health in the population now includes many conditions that are not infectious diseases and which have no available complete cure—the so-called non-infectious diseases (NCDs), sometimes also called long-term conditions (LTCs)—such as cardiovascular disease, diabetes, recurrent depression and schizophrenia. In addition, as people live longer, for many reasons including biomedical advances, the proportion of the elderly increases, especially in the absence of immigration, and care of the elderly in hospital accounts for a high proportion of healthcare costs. In short, what biomedicine is good at no longer solves a large part of the population health burden and costs, and can contribute to rising costs by keeping us alive longer (thank you at a personal level) but at great expense—to someone, especially the younger generations. What is needed to theorise all these developments is much more complicated than biomedicine or the biomedical model were ever designed for. As well as biomedicine, what is needed is a complex mix of social science , politics, economics, environmental and social epidemiology and psychology —and no doubt more scientific specialities under development.

A further development in the decades since Engel ’s papers that has added overwhelming weight to the case for a model that can encompass biological, psychological and social factors has been accelerating research on the causes of illness , the basis for primary prevention. The recent research, to be reviewed briefly in the next section, makes two things clear: first, that for many diseases, causes or risks are present from very early on, and second, that for many these causes or risks are combinations of biological, psychological and social. Prospective epidemiological studies suggest that risks for many major illnesses, physical and mental, start early in development, many in childhood, and that risks include social factors such as poverty and other forms of social exclusion , some specific family level factors such as neglect and abuse, and life - style factors such as exercise and diet. Findings on what have come to be called ‘social determinants of health ’ were summarised and publicised for example by Michael Marmot in his 2010 Strategic Review of Health Inequalities in England [ 5 ]. At the same time, but proceeding largely separately, there have been rapid advances in genetics . Over the past few decades many physical and mental health conditions have been found to have a genetic risk—and genetic risk starts from conception, and interacts with non-genetic factors including but not limited to psychosocial factors of the sort identified in the social epidemiological literature. In short, these sciences combined have produced a whole new dimension of the claim of the biopsychosocial model that conditions of living—as well as biological factors—may affect the onset, presentation and course of an illness .

For all these various kinds of reasons, since Engel wrote his papers some 40 years ago, the biopsychosocial model has become the orthodox overarching model for health, disease and healthcare. It is much cited and taught in healthcare trainings of all sorts and in workshops and ward rounds the world over. In simple terms it recommends to healthcare to take into account all three aspects, the biological, the psychological and the social. It is particularly useful in psychology and social work healthcare professions, and in medical practice that has to deal with the psychological and the social as much as the biomedical, primary care (family medicine) being the clearest example [ 6 ], and in-hospital medical training that emphasises the importance of a comprehensive management plan. In all these contexts the biopsychosocial model easily wins, facilitating identification and integration of different aspects of care aimed at different aspects of the patient’s life, disease and management. To illustrate further good fit with much current practice, the biopsychosocial model obviously aligns with the rationale of multidisciplinary teams, and with the increasing recognition of the value of the service user’s views in providing good and effective healthcare.

Given the prominent status and use of the biopsychosocial model, it is clearly of great importance that the model is clear and robust. At this point, however, there is a very large problem, because there have been increasing charges in the medical literature that in fact the biopsychosocial model—popular and accommodating as it may be—is far from being clear and robust, but is in fact deeply flawed.

1.1.3 But Lacks Content, Validity and Coherence

Engel’s biopsychosocial model has long been criticised for having various kinds of limitation, along with suggestions for improvements (e.g. [ 7 , 8 , 9 ]). Increasingly, however, there have been more radical criticisms. Such radical criticisms are of two main types: first, that the model lacks specific content , is too general and vague ; and second, that it lacks scientific validity and philosophical coherence. Given the popularity of the biopsychosocial model and its presumed status as overarching framework for medicine and healthcare, such radical criticisms signal significant underlying theory problems.

The first broad heading of criticism is well argued by Nassir Ghaemi , a psychiatrist at Tufts, in his 2010 book with the telling title: ‘ The Rise and Fall of the Biopsychosocial Model ’ [ 2 ]. Ghaemi argues that the model is vague, too general, tells us nothing specific of value, hence is inefficient and sometimes distracting; it ‘gives mental health professionals permission to do everything but no specific guidance to do anything’ ([ 2 ], p. 82). The way Ghaemi tells the story, the biopsychosocial model arose in the context of competing general views about illness , favouring one or other of the social, the psychological/psychoanalytic and the biological. These general views—one might call them ideologies without criticism—were views of the whole domain of illness , offering general accounts, discriminating not much between kinds of case to which they applied and kinds of case to which they did not. Ghaemi interprets the biopsychosocial model as an elegant—if problematic and ultimately unviable—solution to these ideological conflicts: the unseemly turf wars could be ended, a truce could be declared, if all the participants won, if they were not really in opposition at all, but were in fact all true general accounts of illness and healthcare in all their aspects. The problem whether the cause of illness, and hence in theory its prevention and treatment, is biological, psychological or social is solved, because the answer is ‘all three’ ([ 10 ], p. 3; [ 2 ], ch. 6).

It has to be said that this line of thought is not apparent in Engel’s main papers [ 1 , 4 ]. Ghaemi does however quote a characterisation of the biopsychosocial model from another of Engel’s papers consistent with presumed generality: ‘all three levels, biological, psychological, and social, must be taken into account in every health care task’ ([ 11 ], p. 164; [ 10 ], p. 3). This claim Ghaemi understands as meaning that the three levels ‘are all, more or less equally, relevant, in all cases, at all times’ ([ 10 ], p. 3). In these quotes one can see the point of the allegations that the biopsychosocial model is a slogan, too vague to be of any use. And moreover, when pinned down, more than likely just wrong, counter-evidenced exactly by the successes of biomedicine, in which biological factors alone adequately explain diseases and treatments, such as bacterial infections and anti-biotics cures. Effective biomedicine is an anomaly for any general claim to the effect that ‘everything is biopsychosocial’, an obvious point that warrants repetition (e.g. [ 2 , 12 ]).

So, the charge is that the biopsychosocial model is vague without specific content. If, on the other hand, the model is firmed up to a very general proposition about the general relevance of all three kinds of factors, it is likely to be just false, exactly because of biomedicine. Faced with this obvious enough fact, a possible move is retreat to vagueness, but at the cost of content, as highlighted increasingly by critical commentary.

As mentioned above when illustrating the current important status or aspirations of the biopsychosocial model, Kenneth Kendler opens his review of Nassir Ghaemi ’s book with the statement that its topic is very important, the overarching conceptual framework of psychiatry ([ 3 ], p. 999). In his review Kendler goes on to quote Ghaemi’s negative conclusion, ‘The BPS model has never been a scientific model or even a philosophically coherent model. It was a slogan…’ ([ 2 ], p. 213), and comments: ‘While the reader may think this a little harsh…, I think he is substantially correct in this assessment’ ([ 3 ], p. 999). On the other hand, Kendler ends his review with a reminder of the importance of the biopsychosocial model as a teaching tool in family medicine, concluding: ‘While I agree with Ghaemi that the Biopsychosocial model has been a failure as a scientific paradigm, it probably continues to serve a useful clinical and teaching function in psychiatry and medicine’ ([ 3 ], p. 999). Kendler correctly identifies the major tension here: the biopsychosocial model is a useful tool for clinical and teaching functions, but apparently lacks scientific validity and philosophical coherence.

But then probably all cannot be problem free on the teaching front either. Here is Chris McManus , Professor of Psychology and Medical Education at University College London, reviewing an earlier edited book on biopsychosocial medicine in The Lancet ([ 13 ], p. 2169):

Biopsychosocial medicine’s challenge is to transcend the vague, aspirational inclusivity of its name, and to create a model that truly merits being called a model, and is properly explanatory and predictive … Arm-waving and the inclusion of everything ultimately says and does little of practical consequence.

Ghaemi , Kendler and McManus all basically agree in their negative assessments of the biopsychosocial model.

Given the popularity of the biopsychosocial model, its use in teaching and the clinic, its presumed status as the overarching framework for psychiatry and perhaps for medicine generally, such authoritative negative assessment signals significant problems at the conceptual foundations.

We believe that these two kinds of charge put to the biopsychosocial model, querying its content, validity and coherence, are cogent, but can be met. What they signal is not the end of the model—witness the fact that it persists, for good reasons already indicated—but the need to rethink and reinvigorate it. The answer to the content problem, we suggest, is that the content lies in scientific and clinical specifics , not generalities. This is proposed in the next section, beginning with a brief review of the emerging basic and clinical science supporting the biopsychosocial model. This response to the content problem, however, immediately raises the question: if the content of the biopsychosocial model lies in specifics, what is the point of the general model? We suggest that this question relates to core scientific theory, at the place where it merges into philosophy, and is therefore here that the problem of scientific validity and philosophical coherence is to be addressed. We define this problem in Sect. 1.3 , and address it in detail through subsequent chapters.

1.2 Locating the Content of the Biopsychosocial Model

1.2.1 emerging evidence of psychosocial causation.

Just as the biomedical model is of interest because of the substantial and well-established evidence base of biomedicine, so the biopsychosocial model warrants attention insofar as there is evidence of psychological and social as well as biological factors in health and disease. There has been an accumulation of such evidence in recent decades, and before moving the main theoretical argument forwards, we pause to review some of it.

This review carries a health warning! It is uncritical and unsystematic; we have usually not distinguished strength of evidence of the studies cited below (uncontrolled to randomised controlled and replicated), nor commented on other aspects of methodological strengths (such as sampling strategies and sample size), nor on conflicting and uncertain results, nor have we employed a systematic literature search strategy. Many of the papers cited are reviews, more or less systematic. The purpose here is only to orientate the unfamiliar reader to wide range of research that has supported on-going interest in the interplay of biological, psychological and social factors in health and disease and hence the biopsychosocial model.

Over the past few decades the picture that has emerged for causes of disease onset, especially for the non-communicable diseases, also known as the LTCs, is one of complex, multifactorial causation, involving many risk factors of relatively small effect, affecting multiple outcomes. The recent research on social factors as causes or risks for poor health—the so-called ‘social determinants of health ’—is probably the most well-known, new face validation of the need for a broad biopsychosocial model. Among the most influential social epidemiological research programmes are the Whitehall Studies of British civil servants, led by Michael Marmot [ 14 , 15 , 16 ]. These longitudinal cohort studies found robust correlations between variance in incidence for a wide range of health conditions—coronary heart disease, premature mortality, some cancers, lung disease, gastrointestinal disease, depression, suicide, sickness absence, back pain and general feelings of ill-health—and civil service grade. The social gradient in health —the correlation between indices of social status and health outcomes—is now well-established; much is now known about the social determinants of health [ 17 , 18 ], and something like the biopsychosocial model has to be invoked in order to comprehend it. As typically for epidemiology, most findings on the social gradient in health come from association studies only, retrospective or prospective. Establishing causation is more complex, using such as controlled cohort studies, natural experiments or animal models.

Other large research programmes have investigated associations between adverse psychosocial exposure in childhood and later health outcomes. A landmark programme is the Adverse Childhood Experiences Study (ACE Study) in the United States, carried out by Kaiser Permanente and the Centers for Disease Control and Prevention. The ACE study has demonstrated associations between adverse childhood experiences, such as physical and emotional neglect and abuse, and a large range of physical as well as mental health outcomes (e.g. [ 19 ]).

Lifestyle factors, comprising behaviours and associated beliefs, attitudes and values, have been increasingly implicated as risks, or conversely as protective factors, for a wide range of physical health conditions [ 14 , 18 ]. For example risk factors for some cancers and cardiovascular disease include such as smoking, alcohol use, diet, exercise and chronic stress . Lifestyle factors can be covered under the same heading as social factors, or separately. Either way, lifestyle factors interact strongly with social context, reflecting Engel’s insight that the person is essentially within a social context: diet for example, depends to some extent on choice, but also on what is available and affordable; stress —to be considered in Chapter 4 —depends on individual characteristics but also on task demands and available resources.

Lifestyle and psychological factors can be distinguished: the former are behavioural, while the latter, such as beliefs, attitudes and values, are mental. At the same time they are closely linked. One reason is that psychological factors motivate lifestyle, but there is also a general linkage between our psychology and our behaviour, namely, that we respond to reality at it appears to us, at any given time, to be. We pick this up as a theoretical point in more detail later, in Chapter 3 (Sect. 3.1 , heading “ Mind Is Embodied ”). In the present context it appears in evidence suggesting that it is not objectively measured social status but social status as perceived , so-called ‘subjective social status’ that accounts for more of the variance in health outcomes (see e.g. [ 20 , 21 ]). This interesting finding becomes part of the complex jigsaw puzzle of biopsychosocial aetiology.

Over the same past few decades that evidence for psychosocial factors in health and disease has been accumulating, so also has evidence of genetic effects. For some health conditions such as Huntington’s chorea, and some cancers, there are massive genetic effects, but for the majority of health conditions, the proportion of population variance attributable to genetic influence is much less than 100%, the picture being rather of relatively small effects of multiple genes , with the remaining variance attributable to non-genetic, environmental factors. Combining these broad kinds of research programmes presents a biological-psychological-social and-environmental picture, and new epigenetics is likely to help explain how the various kinds of factor interact. These issues are taken up in Chapter 3 , Sect. 3.4 .

Post-onset course of disease raises different causal questions: what are the processes determining course, for example, progression, stability, fluctuation or recovery? Treatment effects are a special case, assessed using a range of designs including randomised controlled trials. There has been accumulating evidence from randomised controlled treatment trials since the late 1970s of treatment effects of psychosocial interventions on some mental health conditions. Among the first was a randomised controlled trial of cognitive behaviour therapy for depression published by Beck et al. [ 22 ] showing effectiveness, but further, the same effectiveness as for anti-depressant medication. In effect this trial showed that a psychological intervention could achieve the same result as a biomedical intervention, and it paved the way for accelerating developments of tested psychological treatments for a wide range of mental health conditions and the translation of these into national health service provisions. There are complications, as always, for example, as to the extent to which psychological therapy outperforms pill placebo control, but the principle that some psychotherapies help some mental health conditions has been established (e.g. [ 23 ]).

The position is different with physical illnesses . Put strongly, there is a glaring gap in the evidence for the biopsychosocial picture as a whole, namely, absence of persuasive evidence of psychosocial treatment effects on the course of major physical illnesses. There is no clinical trial that finds effects of psychological therapy on physical illnesses such as, say, diabetes, cancers, cholera or advanced cardiovascular disease. We just wish to make the point that no psychotherapy or any other kind of psychosocial intervention turns around such disease processes once established, and this is a major apparent fact that needs to be taken into account in discussing the relative merits of the biomedical model and the broader biopsychosocial model. This is linked to the fact that for the many conditions that are managed biomedically in acute hospitals, successfully in some cases, there need be no special interest in the broader biopsychosocial model, and any advocate of the broader model has to accommodate the fact that whatever other significant roles they may have, psychosocial factors apparently make no difference to the course or treatment of major physical illnesses .

That said—and we intend it to be a big that —there is emerging evidence that psychosocial factors may be implicated in the prognosis of some among the very large range of medical conditions. For example: breast cancer (e.g. [ 24 ]), atopic disease, generally [ 25 ], including for asthma [ 26 ]; HIV [ 27 , 28 , 29 ] and musculoskeletal disorders (e.g. [ 30 ]). In addition, psychosocial factors have been implicated in outcomes of surgical procedures, for example, chronic pain [ 31 ]; lumbar and spinal surgery [ 32 , 33 , 34 , 35 , 36 , 37 , 38 ]; liver transplant (e.g. [ 39 ]) and coronary artery bypass (e.g. [ 40 , 41 , 42 ]). In addition, there is evidence for psychosocial factors in wound healing [ 43 , 44 ], and extent of fatigue after traumatic brain injury [ 45 ]. Psychosocial factors have also been implicated in responses to other interventions for medical conditions, such as inpatient rehabilitation for stroke patients (e.g. [ 46 ]), and effects of hospitalisation on older patients (e.g. [ 47 ]).

Reference to psychosocial factors affecting course of medical and post-surgical conditions is not intended to be read as either conclusive or general. Many studies on this general topic are of associations only, and there are many mixed results. Hence the subtitle of this section, ‘emerging evidence’, and the explicit qualification of specificity to particular conditions and stages. Further, absence of reports of psychosocial effects on medical conditions, while it may suggest simply that the research has not yet been done, may also indicate that results have been negative and unpublished, and further back in the clinical research sequence, that clinicians have not seen evidence warranting case study research reports, progressing to cohort studies, and so on. This takes us back to the point made first, that some major medical conditions, such as the primary dysfunction in diabetes, or advanced cancers, or advanced cardiovascular disease, appear to be influenced exclusively by biological factors, impenetrable to psychosocial processes and interventions, and in some cases also unresponsive to biological interventions.

An old-fashioned way of making this point is to say that the mind cannot control biological processes such as abnormal cell growth. In the old dualist framework, however, the mind couldn’t really control anything material, not cell growth, but not arms and legs either, so the discriminating point got lost in the metaphysics. In the new post-dualist scientific framework, to be outlined in Chapter 3 , the ‘mind’ is not immaterial, not causally impotent, but more a matter of the central nervous system regulating some internal systems as well as the behaviour of the whole in the environment, and in these terms there are researchable differences between what the central nervous system can control and what it cannot. Extent of control may be modifiable, subject to individual differences, training and practice, but we know now that even at its best the central nervous system is not an omnipotent controller: there are places and processes that CNS signalling pathways do not reach, for example, cell growth, linked to the fact that the cells are very basic, similar in humans as in yeast; nor does the brain control the journey and final resting place of an embolus, and a long list of other biological processes and outcomes, benign or catastrophic. And this list can be contrasted with a list of biological processes and pathways that can or might have CNS involvement, as suggested by studies cited above. These issues and options only open up, however, in a new post-dualist metaphysics and biopsychological scientific paradigm, which are large themes to be addressed through the book. For now, we return to review the findings on biopsychosocial factors.

The next point to note is that, even for those physical health conditions that are unaffected by psychosocial factors, generally or at specific stages, still such factors may be relevant to clinically significant aspects of disease progression and management. These are factors such as access to treatment, participation in the recommended treatment regime, associated pain, psychological/mental health complications and health-related quality of life . Some details and literature as follows:

Access to healthcare is an obvious heading, covering diverse factors such as public health screening to ensure timely detection, health literacy, availability, accessibility and affordability of care, and quality of care—all factors heavily dependent on personal, class and state economics, associated therefore with the social gradient in health [ 5 , 48 , 49 and e.g. 50 ].

Acceptability of/participation in the recommended treatment regime. Psychosocial factors are associated with medication non-adherence, for example, following acute coronary syndrome [ 51 ], in haemodialysis patients [ 52 ], in youth with newly diagnosed epilepsy [ 53 ]. One systematic review of study of psychosocial factors predicting non-adherence to preventative maintenance medication therapy produced a negative result and call for more research [ 54 ].

Psychosocial factors in pain. Pain as an important phenomenon and concept spanning the biopsychosocial and will be considered further in Chapter 4 . Clinical studies implicating psychosocial factors include: in chronic pain [ 55 , 56 ] and in pain associated with specific conditions/sites, such as multiple sclerosis [ 57 ]; musculoskeletal pain [ 58 , 59 ]; low back pain [ 60 , 61 ]; spinal pain [ 62 ]; chronic prostatitis/chronic pelvic pain syndrome in men [ 63 ]; osteoarthritis [ 64 ]; cancer-related pain [ 65 ] and pain after breast cancer surgery [ 66 ].

Psychological/mental health complications of medical conditions . This is an increasingly recognised issue, with implications for quality of life (on which more below), social impairments and costs, in primary care [ 67 ], in LTCs [ 68 ] and in oncology [ 69 , 70 ]. Accumulating clinical experience and research has led to a new UK NHS policy directive requiring psychological therapy services to be integrated into physical healthcare pathways [ 71 ].

Quality of life . There is a substantial literature on psychosocial factors and health-related quality of life in medical conditions, for example, in patients with haematological cancer [ 72 ]; children with myelomeningocele [ 73 ]; colorectal cancer survivors [ 74 , 75 ]; myocardial infarction [ 76 ]; after hip fracture in the elderly [ 77 ]; newly diagnosed coronary artery disease patients [ 78 ]; adults with epilepsy [ 79 ], and after surgery [ 80 ]; and youth-onset diabetes myelitis [ 81 ].

Accumulating health data of the sort indicated above implicating psychosocial as well as biomedical factors, taken together, cover a large proportion of population health and health service provision in clinics and hospital beds. In other words, they are massively important, looked at in terms of population health, individual suffering, or economic costs; they are not a side-issue compared with conditions or stages of conditions that involve biological factors alone.

The psychosocial data have accumulated over the past few decades and have vindicated Engel’s proposal of a new model for medicine and healthcare. Engel was ahead of the game, and the popularity of his model is explained at least partly by the fact that it appeared as a ready-made framework for accommodating the emerging evidence of psychological and social causal factors in determining health and disease.

In these terms its clear that we need a biopsychosocial model of the sort that Engel anticipated, but one that can meet the criticisms reviewed previously that the model, at least as we currently invoke it, has serious problems including lack of content and incoherence. We propose in the next section a solution to the content problem, based, as would be expected, on emerging findings implicating psychosocial as well as biological factors of the sort outlined above. As to the coherence problem, this will involve theorising the categories of ‘biological’, ‘psychological’ and ‘social’ in such a way that they can interact in health and disease. This theorising will occupy the rest of the book. One strand was already mentioned earlier in this section: the old dualism between mind and body is replaced by a partial and to some extent negotiable interaction between the central nervous system and other biological systems. This theory-shift will be taken up in Chapter 3 , along with the proposal that the primary concept of the psychological is embodied agency , with implications for health, drawn out further in Chapter 4 : a person’s psychological health depends on the development of a viable enough sense of agency , while conversely, if agency is seriously compromised, such as in conditions of chronic stress , their mental health is liable to suffer, and so also, via complex biopsychosocial pathways, is their physical health.

1.2.2 The Scientific and Clinical Content Is in the Specifics

Let us pick up the line of argument in this chapter. The biopsychosocial model is much invoked, with claim to be the overarching framework for psychiatry and other branches of medicine such as primary care, perhaps for medicine generally. It has however been severely criticised, for being vague, without scientific or clinical content. Here is our suggested remedy: the scientific content and clinical utility of the biopsychosocial model is not to be found in general statements, but rather is specific to particular health conditions, and, further, specific to particular stages of particular health conditions . We provided above a brief, non-systematic, non-critical review of some of the emerging evidence of involvement of psychological and social as well as biological factors. All the evidence refers to particular health conditions or classes of conditions, and particular stages: risks for onset, post-onset course, including under treatment, adjustment and quality of life .

At the time Engel wrote there was not much evidence of causes of diseases and treatment effects, with important exceptions in the case of some major infectious diseases. But especially, compared with now, relatively little was known, though much was speculated, about the role of psychosocial factors in health and disease. Since then, in the intervening decades, there have been massive new research programmes, not only in biomedicine, but in clinical psychology , neuroscience , social epidemiology and genetics , and in treatment trials, pharmacological and psychological. Much more is now known about the causes of diseases and about possible disease mechanisms, with associated technologies for prevention, early detection and treatment. This broad evidence base has led in turn to treatment guidelines for specific conditions, to the whole apparatus of evidence-based clinical care, to be used alongside a thorough assessment of the individual case. Much of the science and clinical management is now psychological and social as well as biological. Given this situation as it is now, the scientific and clinical content of the biopsychosocial model is in the specifics, not in a ‘general model’. Much the same, by the way, can be said of biomedicine and its associated biomedical model: medicine, whether biomedical or biopsychosocial, deals with complex, specific systems.

The proposal that the content problem is resolved by focussing on specifics not generality also helps explain how the problem arises. In brief, it is because the specifics are too many and too complex, that some shorthand, vague gesturing, is sometimes useful. The basic and clinical sciences of the past few decades invoke very many kinds of factors in their models: biological factors—biological systems, including neural systems and genetic mechanisms—but also psychological factors—such as temperament, personality, lifestyle, adjustment, quality of life —and also social determinants of health and disease—variants on social inclusion or exclusion—together with the implication that all these things interact over time, in the course of life and the illness , in complicated and barely understood ways. So, on occasions when the question arises, for example in clinical consultation or healthcare education systems: ‘and what are the factors involved in this or that disease, or individual presentation?’—the quick answer would be: ‘it’s all biopsychosocial’, or ‘it’s as the biopsychosocial model says’. The full answer is much longer, in the systemic reviews of the epidemiological and clinical sciences, treatment trials and clinical guidelines—but this full story does not fit in a ward round or clinical consultation; it more makes up years long healthcare educational training programmes. As workable compromise, the brief throwaway—‘it’s all biopsychosocial’ could be expanded into something more informative along these lines: ‘In this condition there are possibly (or probably) biological, psychological and social factors involved, in some stages, some of which have been identified, with more or less confidence, combining together in such-and-such ways, though interactive causal pathways are bound to be complex and (typically) not yet well understood—the details of what is known and hypothesised about the condition to date is in the literature/is among the topics in one of your teaching modules’.

Such an answer, and the science it refers to, is about a particular health condition, such as diabetes, or depression. In this sense there are multiple specific biopsychosocial models: a model for diabetes, depression, cardiovascular disease, schizophrenia; and so forth. Further, much depends on what stage or what aspect of a particular condition we have in mind, whether pre-onset aetiological risks for onset, or post-onset course, involving many issues including maintaining factors, treatment responses, complications, psychological adjustment and factors affecting quality of life . The factors involved in these various stages and aspects typically differ within any particular condition, and especially they differ in the relative involvement of biological, psychological and social. For example, social epidemiological studies suggest that social factors as well as biological are implicated in the aetiology of a wide range of health conditions, such as cardiovascular disease and depression, while treatment might not be so, as in surgical intervention for advanced cardiovascular disease, or pharmacological therapy for depression. This latter is typically best combined with psychological therapy, which might also be indicated to aid adjustment and recovery of quality of life following cardiovascular surgery. In short, there is need for much discrimination between what conditions we are talking about, what stages of conditions and questions of interest in each. This is the specificity and complexity of diseases and therefore of the science and its models.

We stress here that we mean no implication that particular diagnostic categories are valid once and for all, or optimal in terms of explanation or prediction. Rather, they simply represent the current consensus state of clinical practice and clinical science and are liable to revision, to subtyping or supra-typing, or to replacement altogether. The proposal is that biopsychosocial medicine, like biomedicine, is applied to specific health conditions, in terms of which the science at any one time is conducted; but identification and classification of these conditions are subject to change.

In brief, our proposal is that, while the biopsychosocial model can sometimes appear as vague hand-waving, absent any scientific or clinical content, this is because we are looking for content in the wrong place, in the general model, rather than in the epidemiological and clinical science literatures about particular conditions. This proposal, if accepted, solves the content problem.

On the other hand, that said, such a solution immediately raises a still more radical problem for the biopsychosocial model: if it’s all about specifics, what is the point of having a ‘general model’?!

1.2.3 So What’s the Point of a ‘General Model’?

Engel wrote about the biopsychosocial model in a way that suggested it had scientific content and clinical utility. His 1980 paper [ 4 ] was on clinical applications of the biopsychosocial model, the main example being myocardial infarction, consistent with the reasonable expectation that the model specified biopsychosocial causal pathways in particular conditions and hence could guide clinical practice. However, the position regarding what is known in the science has radically changed in the intervening decades, and now, as argued in the preceding section, the ‘general model’ is probably now not the place to look for causal pathways, clinical applications and treatment guidance, which are rather to be found in the health science literatures.

One possibility in the circumstances, as the evidence accumulates, is that the general model might summarise the evidence for all the health conditions, along something like the following lines: “Psychological and social factors as well as biological factors (each of these being of many different kinds) are relevant to all health conditions and all healthcare, though they vary in their relative contributions, depending on the condition and the stage of the condition, between 0-100%, or mostly between, say, 20-80% – summing to something like 100%”.

However, while such a general proposition might be true, give or take some percentage points, it clearly has no or not much content, or use, in for example shaping guidance about prevention or clinical management. It is certainly less informative and useful than the full picture for a specific health condition. It is true that a general statement of the model such as the above can serve to remind us and our students to keep one’s mind open to the range of biopsychosocial factors, but the treatment guidelines and the science behind them already now say this, if applicable, and there is limited gain from repeating the fact—vaguely. Used in this way, the model runs the risk of being, minimally, a bucket to throw research findings into, convenient for hand-waving purposes. As for basic scientists and clinical trialists, they investigate the causes, mechanisms and treatment of cardiovascular disease, depression, and so forth; with definitely or probably not much need or time for a ‘general model’.

So what is the point of a general model? Perhaps as a theory of health and disease. But the line of thought we are pursuing is exactly that health and disease are not one thing, or two things, but each many things, depending which system within us is functioning well or poorly. Even so, the general picture still matters when the whole of health is in question, for example in estimating and projecting population health, planning and prioritising health services and research funding, on treatment, primary or secondary prevention, planning syllabuses for health education, or modelling linkages between health outcomes and outcomes in other sectors such as education, productivity or national happiness. Clinicians, patients and researchers may well be concerned with specific conditions, but for many other purposes views of the whole are required. The concept of biomedicine arose in the recognition that many effective health technologies had in common that they relied on biological factors only, notwithstanding complex biopsychosocial presentations. Such a concept then drives further lines of enquiry, investigating biological factors in other conditions. An analogous point applies to the biopsychosocial model. A related point is a need for a framework to organise accumulating research findings, to recognise emerging patterns, to identify what is known, with more or less certainty, and what is not known. This applies to specific conditions such as cardiovascular disease, or addictions, but it also applies across health conditions as a whole.

There are many purposes for a general model and accordingly many ways of constructing such a thing. We focus here on the general biopsychosocial model as a core philosophical and scientific theory of health, disease and healthcare, which defines the foundational theoretical constructs—the ontology of the biological, the psychological and the social—and especially the causal relations within and between these domains .

While the details of the relative roles of biological, psychological and social factors in specific health conditions, at particular stages, are matters for the health sciences, the general, or core, biopsychosocial model is more of an exercise in the philosophy of science—in this case, philosophy of biology , philosophy of mind and social theory, but especially as applied to health and disease. These philosophies are especially relevant in the present case, because there is massive historical baggage, carried in the long history of physicalism , dualism and reductionism , that makes biopsychosocial ontology and causation deeply problematic. This whole problem area needs rethinking and reconceptualising in the light of current scientific paradigms and philosophical theory.

1.3 The General Model: Biopsychosocial Ontology and Interactions

1.3.1 defining the problem.

Engel was well aware of the philosophical problems involved in the shift from the biomedical model to the biopsychosocial. This is how he characterises the biomedical model ([ 1 ], p. 130):

The biomedical model embraces both reductionism , the philosophic view that complex phenomena are ultimately derived from a single primary principle, and mind-body dualism , the doctrine that separates the mental from the somatic. Hence the reductionist primary principle is physicalistic; that is, it assumes that the language of chemistry and physics will ultimately suffice to explain biological phenomena.

The biomedical model so understood, as based on these philosophical views, is antithetical to any extension to a biopsychosocial model, and conversely, if the biopsychosocial model is to be viable, it has to overcome the challenges they pose. This is well recognised by thoughtful commentators on the biopsychosocial model, including those, quoted previously, who criticise the model for its hand-waving tendencies. Here is Chris McManus in his review for The Lancet cited previously ([ 13 ], p. 2169):

The challenges for the Biopsychosocial Model involve reductionism , dualism , mechanism, methodology, and causality. The psychological and the sociological are ineluctably phenomena of the mind, and the reductionist challenge is how to integrate the mental with the cellular, molecular, and genetic levels at which biomedicine now works.

Ken Kendler in his review quoted earlier, goes on to identify the philosophical issues relevant to the biopsychosocial model and the work that needs to be done ([ 3 ], p. 999):

[These are] the issues that the Biopsychosocial model at least seemed to be addressing—how to integrate the diverse etiologic factors that contribute to psychiatric illness and how to conceptualize rigorously multidimensional approaches to treatment. [There is] a range of exciting recent developments in the philosophy of science on approaches to complex biological systems, which are quite relevant to these issues… [which] examine scientific approaches to complex, nonlinear living systems and explore various models of explanatory pluralism, from DNA to mind and culture….

The importance of understanding causal interactions between kinds of factors is also highlighted by Dan Blazer in his review of Nassir Ghaemi’s book [ 82 ] (p. 362):

[There are] emerging efforts across all of medicine to integrate biological, psychological, and social factors in the exploration of the causes and outcomes of both physical and psychiatric illnesses …. These efforts are not eclectic but transdisciplinary, efforts which are leading to a much better understanding of how biological, psychological, and social factors interact through time.

Both Kendler and Blazer identify the current challenge of constructing a coherent view of causation in health and disease that can encompass biological, psychological and social factors. Kendler refers to recent philosophical developments and Blazer to emerging efforts in health sciences, both implying a historical dimension and that something new needs to happen and is happening, at a conceptual level as well as a scientific level.

Engel’s characterisation of the biomedical model, a reasonable one in the 1970s, had it supposing that only the biological exists, or is alone causal in health and disease, and it exists as physics and chemistry, with the same principles or laws of causation. The ontology was flat and reductionist: nothing new grew out of the basic physics and chemistry, and any other domain with aspirations to be causal had to be ultimately reduced back to the basics. To construct an alternative to this set of assumptions it is necessary to envisage ontology and causal relations other than, and in some metaphorical sense ‘above’, those in physics and chemistry. Engel proposed systems theory for this purpose, and as we shall consider in later chapters, we think this is fundamentally the right way to go.

A systems theory approach in fact already underlies the solution to the content problem we proposed in the previous section. We proposed in Sect. 1.2 , heading “ The Scientific and Clinical Content Is in the Specifics ”, that the content is to be found in the science and clinical guidelines on specific health conditions. This is the indicated move because specific systems are distinctive, with their own distinctive functions, operating principles and vulnerabilities to dysfunction, which therefore have to be modelled separately. Healthcare science along with other systems sciences, essentially deals in specifics. This has always applied to biomedicine, which deals with particular biological systems. It also applies in psychology , which deals with particular psychological systems, such as motivation and fear, and in clinical psychological theory—for example, cognitive behaviour therapy has specific models for such as depression, obsessive-compulsive disorder and panic disorder.

The question arises then: what is the core theory linking together the various applications to specific systems? For biomedicine, in the way that Engel characterised it in the 1970s, the core theory was that biology is physics and chemistry, and biological causation is physico-chemical causation. This has changed; it is no longer true of current biomedicine; this is the topic of the next chapter. The core theory underpinning cognitive behavioural therapy, as stated by its founders Aaron Beck and colleagues [ 22 ] (p. 3) is startlingly brief, that cognitions cause affect and behaviour. However, even this brief statement of the core model does crucial work: it highlights the working assumption that intervening with cognition is the way to modify troubling emotions and behaviour, and it links together the various types of cognitive behaviour models for diverse conditions. Even in the absence of explicit theory of causation, there can be evidence of causal connection from well-designed treatment trials, but also, in this particular case there is a long and respectable history of the cognitive theory of the emotions and the philosophy of practical reason that provides conceptual familiarity for working purposes.

The contrast here is with the biopsychosocial core model: there is no long and respectable history of philosophy and science theorising causal interactions between the biological, the psychological and the social. To the contrary, the history since the beginnings of modern science in the seventeenth century consists of assumptions and arguments that psychological and social causation are impossible or even incomprehensible, that there is no distinctive biological causation either, over and above physics and chemistry. The historical background is entirely hostile to the whole idea of biopsychosocial causal pathways, and there is therefore a need for an explicit theory as to what the new idea is. It is this, we propose, that is the purpose of the general biopsychosocial model; in short, to theorise biopsychosocial causal interactions.

We review some main relevant historical background below, under the heading “ Prejudicial Theory: Physicalism, Reductionism, Dualism ”. First, in the next section, we consider how the search for biopsychosocial theory is not only of interest to reworking a model proposed some 40 years ago, but has arisen in the health sciences themselves.

1.3.2 Biopsychosocial Data in Search of Theory

The emerging evidence of psychosocial causation in health and disease of the sort briefly outlined in Sect. 1.2 , comes from studies using empirical methodologies that have been developed and applied substantially since Engel wrote his papers on the biopsychosocial model. Prior to these new research methods, there was little or no demonstrated evidence of psychological and social causes of physical health conditions. Their effects were not as plain—as massive—as those identified by biomedicine, as for example effects on incidence of cholera of drinking contaminated water from a particular pump, or recovery following treatment by antibiotics. In the absence of a significant body of evidence of a causative or curative role of psychological and social factors in particular diseases, claims as to their importance were bound to have an uncertain status: were such claims meant to be general, to apply to all conditions, meant to be obvious, or based on prejudice or expert consensus—or specific to particular conditions? In the absence of much evidence, the appearance of ideology was inevitable—and this is one of the key points behind Ghaemi’s critique of Engel’s biopsychosocial model [ 2 ], considered previously (Sect. 1.1 ). However, the amount of evidence and most importantly the type of evidence bearing on these issues has changed radically in the 40 years since Engel proposed the model. We refer to use of novel statistical methodologies and associated study designs that are sensitive to multiple factors, relatively small, partial causal influences, usually called risk factors, contributing in some way to a complex nexus of causation associated with a particular outcome of interest. The development of these new methodologies was based on nineteenth-century conceptual work on the scientific demonstration of causation, and early twentieth-century work in the theory of statistical inference.

Much of the intellectual work clarifying the scientific methodology required for the determination of causes was done by J. S. Mill in his A System of Logic [ 83 ]. Hume [ 84 ] had seen that causality is linked to generality, that the statement ‘A causes B’ implies that events of type A are always followed by events of type B. This implies also that knowledge of causes enables prediction, that the next A will be B. Mill saw, however, that in practice what is observed on any one occasion is not simply an event of type A being followed by an event of type B, but this conjunction in a complex of circumstances, C. To establish a causal link between A and B the possible confounding effects of C have to be determined. This involves observing the effects of C without A, on the one hand, and A without C on the other. These principles, elucidated by Mill as the ‘methods of agreement and difference’, underlie our modern idea of controlled experimentation.

Robert Koch’s pioneering work in microbiology in the closing decades of the nineteenth century made four postulates as methodology to determine the causal relationship between a microbe and a disease, applied to the aetiology of cholera and tuberculosis [ 85 , 86 ]. Koch’s postulates tapped similar principles to Mill’s , including assumptions of generality and isolation of the suspected active causal ingredient—‘isolation’ here requiring cutting edge technology of the time. Interestingly Koch himself recognised that there was a problem with the generality requirement, which takes us on to the next main point.

Hume , Mill and Koch supposed that causality is general—applies to ‘all’. However, in practice in the lifesciences, medicine, psychology and the social sciences we rarely find universal generalisations, but rather partial ones, of the form: A is followed by B in a certain proportion of observed cases. One function of a universal generalisation is to license the simple inductive inference: the next observed A will be followed by B. In the absence of a universal generalisation, the problem is to determine the probability of the next A being followed by B, given that the proportion in the sample so far observed. This is the problem for the theory of statistical inference, developed in the first decades of the twentieth century.

The theory of statistical inference is a necessary condition of being able to detect reliable small correlations between two factors, between say amount of daily exercise and cardiovascular function at a later time. The implications of correlations being small—much less than 1 and not much above 0—is that other factors are at work, signalling the need for investigation of multiple factors associated with the particular outcome of interest. Investigation requires a group study in which each factor is each measured and their association or correlation with the outcome computed. Analysis of variance, ANOVA, is one class of statistics that can be used for such purposes: there is an outcome of interest, the so-called dependent variable, and several independent variables, hypothesised to effect it. For example, the dependent variable may be onset of cardiovascular disease by 40 years, the independent variables are individual characteristics such as weight, diet, smoking, exercise, multiple deprivation index, family history as assumed proxy for genetic vulnerability, and the results of the ANOVA will quantify the amounts of variance in outcome and hence risk attributable to these several factors, alone or in combination. Other classes of statistical analyses can be used, more or less closely related, depending for example on the nature of the variables (e.g. categorical or continuous) and on study design (e.g. cross-sectional or longitudinal). Use of such methods has become pervasive in the human sciences in the past few decades, reflecting the fact that the phenomena are complex with multiple causes; instances when a single variable completely explains a phenomenon (accounts for all or most of the variance) are rare.

Naturalistic studies of populations in the first instance establish correlations only, and further investigation is needed to establish causation, using or approximating to experimental methods of the sort elaborated by Mill and Koch. Experimental designs for establishing causation typically involve at least two groups, assumed to be identical in relevant respects—either known or suspected to affect the outcome of interest—except for one factor, the factor of interest. Differences of outcome between the two groups are then attributable to the factor of interest in accordance with Mill’s method of difference. The factor of interest is often a treatment—an ‘intervention’. Confidence in the assumption that the two groups are otherwise identical in relevant respects is critical in these methodologies, and there are many methods of ‘matching’ groups to achieve this. The philosophical justification for regarding controlled designs as the appropriate methodology for establishing causation such as treatment effects has been argued elsewhere [ 87 ]. The gold standard for maximising this confidence—the true experimental design—is taken to be randomisation, with sufficiently large numbers, such that possible confounding causal factors can be reasonably assumed to be distributed equally between the groups. Quasi-experimental designs, such as matching cohorts, can also be used, though the confidence that unknown confounders are equally matched is less. There are also ‘natural experiments’ (see e.g. [ 88 ]), and sometimes the background base rates absent the putative cause are safely assumed.

If we establish that a universal correlation is causal, the finding can be expressed as A causes B. Typically in the life and human sciences, correlation between factors is partial—variation in A accounts for only part of the variance in outcome B—in which case the correlation can be expressed as: A raises probability of B, in some specified degree depending on the size of the correlation. If B is a harmful outcome, such as a poor health outcome, this is often expressed: A raises risk of B, in some specified degree.

Population studies of risk factors for the onset of disease cannot use randomisation designs, plainly for ethical reasons, and are generally limited to more or less refined quasi-experimental methodology. Experimentation is left to animal studies. Treatment studies of the effect of an intervention on the course of a disease once onset can use randomisation designs—again subject to ethical constraints.

The new study designs and analytical methodologies showed effects—typically small—of psychological and social factors. The same methodology of course can show the importance of biological factors of small effect, such as genetic and epigenetic effects.

Relevant to our main theme, however, we can note that while these new study designs and statistical methodologies are well theorised, as is the determination of causes by experimental and related methods, they provide in themselves no theory of the factors indexed by the variables and no theory of causal mechanisms linking them. They can provide evidence of biopsychosocial causal connections, but no theory about them. This absence of theory is important because of the historical background of dualism and physicalist reductionism , noted at the beginning of this section (under the heading “ Defining the Problem ”), that would exclude any distinctive forms of biological (as opposed to physico-chemical), psychological and social causation . We review some main points of this historical background next.

1.3.3 Prejudicial Theory: Physicalism , Reductionism , Dualism

Engel’s characterisation of the biomedical model—quoted at the beginning of this section, uses a few key technical terms: reductionism , physicalism and physicalist reductionism (Engel uses ‘physicalistic’). These terms refer to complex and controversial concepts with long histories, and we will use working characterisations as follows:

Physicalism is the view that everything that exists is physical. This is an ontological statement—about what there is. It has often been combined with the corresponding statement about causation: that all causation is physical, covered by physical laws. On the assumption that chemistry is basically physics, physicalism can be expressed in terms of physics + chemistry. The contemporary philosophical literature on physicalism is substantial (for recent review see e.g. [ 89 ]). Working around physicalism is necessary to establish a biopsychosocial model and is addressed in more detail in the next chapter.

Reductionism has various meanings. In one of the senses used by Engel in his characterisation of the biomedical model, quoted at the beginning of this section, it is a scientific claim that complex phenomena have a main cause of a particular type. In the medical context, reductionism in this sense would claim that there is a main cause of one or other kind: biological (e.g. an infection or lesion), or psychological (e.g. unconscious conflicts, or maladaptive cognitive style), or social (e.g. social exclusion ; labelling). There is also a philosophical or metaphysical doctrine of reductionism , deriving from physicalism , as follows:

Physicalist reductionism follows from the strong version of physicalism which has ontology and causation as all a matter of physics. It is a strict consequence for other sciences, such as chemistry, biology , psychology and social science : either they are true causal sciences, in which case they must ultimately reducible to the concepts and laws of physics; or, otherwise, they are pseudo-sciences, or at least, ‘sciences’ that do not deal with causation. Physicalist reductionism so understood is a philosophical or metaphysical doctrine in the sense that it is known or alleged a priori; it is not based on scientific research, but rather prejudges what there is to be discovered. Physicalist reductionism along with its roots in physicalism is taken up in the next chapter.

Physicalism has a long history, its roots lying in what historians of science refer to as the ‘mechanisation of the world picture’ in the seventeenth century [ 90 , 91 , 92 ]. This involved defining the primary qualities of nature in mathematical terms, as mass, extension and motion, covered by the few universal laws of Newtonian mechanics. The mechanisation of nature created mind–body dualism , because the thing that never did seem to be physical was immediate experience: sense-perceptions, thinking, pain and the like. Physical objects including the human body have the primary qualities, while the mind was something else, immaterial and unlocated. Physicalism and dualism are twins, one born straight after the other, combative from the start, each refuting the other, the one supported by the great edifice of modern mechanics, the other known immediately by experience, battling ever since.

It is impossible to overstate the massive influence of modern physics and its accompanying philosophy of nature on the subsequent development of western science through the eighteenth and nineteenth centuries. As sciences developed, studying apparently distinctive domains and processes, the dominant physicalism applied its stringent reductionist test: either the new aspiring science was valid as causal science, in which case it should be reducible to physics, or, it was not reducible to physics, in which case it was pseudo-science, or at best, a ‘science’ studying non-causes. The chemistry that emerged in the nineteenth century passed the test and joined physics. As to biology , psychology and social science , on the other hand, physicalist reductionism aided by dualism caused disunity and more or less havoc—some key points in brief as follows, to be picked up in later chapters:

Biology as we now understand it developed in the nineteenth century, drawing from previous roots in medicine, natural history and botany (see e.g. Ernst Mayr’s seminal work on the history and philosophy of biology, [ 93 ]). This large, complex field, comprising many subfields, with distinctive domains, questions and methods, had an ambiguous relation with physicalism and reductionism . In some areas of biology , especially in medicine, physiology and new subspecialities such as microbiology—there was the possibility of reduction of biological phenomena as chemistry. A key development was Lavoisier’s work on the relation between combustion and respiration, initiating the scientific research programme that became biochemistry. However, for other parts of the broad and diverse field of biology, reducing the phenomena of life to chemistry was not such a clear option. This applied especially to developmental embryology and evolutionary biology , which aimed to understand the formation of individual organisms and whole species, and which used explanatory concepts more akin to older, Aristotelian concepts such as form and function. Such alternative concepts, contrasted with physics and chemistry, will appear in later chapters as we develop biopsychosocial theory. Biology could embrace physicalist reductionism , or ignore it, or argue against it head on. This third option was the doctrine of ‘vitalism ’, which posited a biological life force in addition to mechanical, or more broadly physico-chemical, forces. Vitalism is in this sense a direct response to the mechanisation of the world picture in modern science, a point made by Bechtel and Richardson [ 94 ] (p. 1051):

Vitalism is best understood… in the context of the emergence of modern science during the sixteenth and seventeenth centuries. Mechanistic explanations of natural phenomena were extended to biological systems by Descartes and his successors. Descartes maintained that animals, and the human body, are ‘automata’, mechanical devices differing from artificial devices only in their degree of complexity. Vitalism developed as a contrast to this mechanistic view.

As to psychology , this new science inherited the Cartesian dualist assumptions: immaterial mind evident immediately in consciousness, and the mechanical body. Psychology struggled with the oddness of mind as its subject matter for several decades, then shifted to the other option, compatible with physicalism and reductionism , aligning psychology with physics and chemistry. This was behaviourism, and here is Watson [ 95 ] (p. 158) summarising the new approach:

Psychology , as the behaviorist views it, is a purely objective, experimental branch of natural science which needs introspection as little as do the sciences of chemistry and physics. It is granted that the behaviour of animals can be investigated without appeal to consciousness… This suggested elimination of states of consciousness as proper objects of investigation in themselves will remove the barrier from psychology which exists between it and the other sciences. The findings of psychology become the functional correlates of structure and lend themselves to explanation in physico-chemical terms.

The social sciences , on the other hand, as they emerged through the nineteenth century never were going to lend themselves to comprehension in physico-chemical terms. This would be desperate business. Their subject-matter was, briefly stated, forms and processes of social organisation, which looked a very long way from physics and chemistry, further away than even psychology . As to principles of social causation , perhaps there were universal laws governing change, but equally, social systems and events appeared as specific, even unique. In short, the ontology of the natural sciences was no use to the emerging social sciences , and their methodology was of limited or questionable use. Accordingly alternative approaches developed, drawing from philosophical traditions other than physicalism , emphasising understanding and meaning, ‘hermeneutics’, rather than causal explanation of nature. Here is Anthony Giddens on this point [ 96 ] (pp. viii–ix):

The tradition of the Geisteswissenschaften, or the ‘hermeneutic’ tradition, stretches back well before Dilthey, and from the middle of the eighteenth century onwards was intertwined with, but also partly set off from, the broader stream of Idealistic philosophy. Those associated with the hermeneutic viewpoint insisted upon the differentiation of the sciences of nature from the study of man. While we can ‘explain’ natural occurrences in terms of the application of causal laws, human conduct is intrinsically meaningful, and has to be ‘interpreted’ or ‘understood’ in a way which has no counterpart in nature. Such an emphasis linked closely with a stress upon the centrality of history in the study of human conduct, in economic action as in other areas, because the cultural values that lend meanings to human life, it was held, are created by specific processes of social development.

To sum up, physicalist reductionism had a massive influence on the development of the biological, psychological and social sciences . It prioritised physics, subsequently physics and chemistry, as the benchmark of empirical science and causal explanation. Parts of biology measured up, as biochemistry, evolutionary biology didn’t; psychology struggled; and the social sciences were so far off the mark that new views of science including alternatives to causal explanation were needed.

Against this background, deeply entrenched theory, antithetical to any distinctive forms of biological (as opposed to physico-chemical), psychological and social causation , Engel’s proposal of the biopsychosocial model was audacious. It was, however, prescient, because in the intervening decades the empirical evidence has built up, as outlined in Sect. 1.2 , under the heading “ Emerging Evidence of Psychosocial Causation ”. A main virtue of the empirical, empiricist methodology of Hume and Mill , outlined in Sect. 1.3 , under the heading “ Biopsychosocial Data in Search of Theory ”, is that it can accumulate evidence of causal connections, driving the science forwards, unhindered by theoretical prejudice. The scientific methodology for determining associations and causal connections between one or more factors and a health outcome in indifferent to the nature of the factor variables involved, in particular it has no interest in whether they are called ‘biological’, ‘psychological’ or ‘social’; the methodology has no interest in ontological matters at all—it cares only that the variables are measurable. Equally the empirical and statistical methodology has not much or nothing to say about causal mechanisms . Free of the historical theoretical baggage, it has been able to study relations between biological, psychological and social factors and health outcomes of interest, the upshot of which has been accumulation of evidence that psychological and social factors are at least associated with some health outcomes, physical and mental, and with some evidence of causal impact. Such free creativity is typical of empirical science. On the other hand, the downside is that we have apparently established biopsychosocial ontology and causal interactions, but so far untheorised, and—still feeling the effects of physicalist reductionism in the last few centuries of science—with perplexity and incredulity that such a thing is possible.

1.3.4 Theorising Biopsychosocial Interactions—Not Parallel Worlds

The proposal of biopsychosocial ontology and causal relations—under the weight of philosophical and scientific prejudice according to which psychological and social causation are impossible, even incomprehensible, and there is no distinctive biological causation either, over and above physics and chemistry—is audacious and the task of making theoretical sense of it is non-trivial.

Engel’s biopsychosocial model is a very suitable heading for examining these issues. His papers certainly identified many of them, probably all that were apparent at the time he wrote them. However, Engel’s model is only a heading for the major task of elucidating theory that can comprehend the paradigms and findings of the health sciences of the past few decades that invoke the full range of and interactions between biological, psychological and social factors in health and disease.

We propose to start with biology and especially its relation to physics and chemistry. It is the assumption that biology is no more than physics and chemistry that locks in the physicalist philosophy that the laws of physics and chemistry are the only causal laws. While that philosophical position remains in play, without viable alternative, it is difficult to make out any distinctive psychological or social causation and especially difficult to theorise biopsychosocial interactions. There is simply too much historical conceptual baggage in the way, variations of dualism and the disunity of the sciences.

We will be considering theory changes that have accelerated in the decades since Engel wrote. Up to the 1970s, just about everybody supposed that biology (as least as physiology) was reducible to physics and chemistry, but psychology and social sciences hardly, and so much the worse for them. In the 1970s, however, the reducibility of biology to physics became questionable, with recognition that all the ‘special sciences’, apart from physics/chemistry, had distinctive concepts and apparently causal explanations. However, exactly what the other sciences are sciences of, and what becomes of physicalism , dualism and reductionism , and especially how the various sciences are meant to relate to one another— all remained unclear and contested. Jerry Fodor’s 1974 paper [ 97 ] had the full title ‘Special Sciences (Or: The Disunity of Science as a Working Hypothesis)’. Fodor’s 1997 [ 98 ] update was equally informatively titled, as ‘Special Sciences: Still Autonomous After All These Years’, concluding ‘The world, it seems, runs in parallel, at many levels of description. You may find that perplexing…’

This parallel world view—or perhaps it should be parallel worlds plural—in which it is supposed that as well as the physico-chemical world, there is also a biological world (unless that is the same as the physico-chemical world), and a psychological world, and the social world—is certainly perplexing. It does not get much less perplexing if ‘parallel world(s)’ is replaced by ‘many (parallel) levels of description’. Such a view however is exactly what is intellectually arrived at when forced to acknowledge, when no longer able to deny, that the biological, psychological and social sciences are now established as valid sciences including causal determinations, in some reasonable sense of ‘causal’, such as: can predict; when no longer able to deny this, while at the same time continuing to assume that the physico-chemical world is closed to anything other than physico-chemical causation.

This parallel worlds/levels of description approach can be applied in the health sciences, leading to the idea that psychological and social models of health and disease, as well as the biomedical, can somehow all be valid, but at different levels of description. As indicated previously in Sect. 1.1 , Nassir Ghaemi argued that the biopsychosocial model has been used exactly to resolve turf wars between these various disciplines, by allowing them all to claim validity at the same time, the upshot being irredeemable vagueness and incoherence. We noted however that this thought is not prominent in Engel’s papers, which philosophically relies rather on systems theory in which there is interaction between domains.

Philosophically, the parallel world(s) move, historically inevitable as it probably was, is not really coherent; what is needed rather is a more liberal view of worldly ontology and causation that can encompass not only physics and chemistry but also biological, psychological and social processes and principles of change. In any case, so far as the current sciences are concerned, and especially the health sciences, the idea of parallel causal explanations is unhelpful; rather, what is needed is theory of multifactorial interactive causation. Specifically, data of the sort reviewed in Sect. 1.2 under the heading “ Emerging Evidence of Psychosocial Causation ”, suggesting biopsychosocial involvement in health and disease, need to be theorised in terms of biopsychosocial interactions. The quotes from Chris McManus , Ken Kendler and Dan Blazer considered at the beginning of this section, when setting up the task of the general biopsychosocial model, all refer to the need to integrate biological, psychological and social factors. Another aspect of the same point is that the various kinds of factors are found in the science to account for different proportions of the variance in health outcomes, with relative proportions of the three varying between health conditions and stages of condition. From the point of view of the science, a sentence along such lines as: ‘biological, psychological and social factors (always) each severally account for 100% of the variance – at different levels of description’—is completely incomprehensible.

1.3.5 Finding the Right Metaphor: Evolution and Development

It is not straightforward to find the right metaphor for the relation between the biological, the psychological and the social. The most common is in terms of hierarchical levels, but it suffers from reductionist connotations that lower levels are more basic, more causal, than higher ones. Alternatively, as a transitionary move away from reductionism , appraised in the previous section, it can be interpreted as different levels of ontology and/or description running in parallel, but this makes interactions mysterious. Systemic approaches that envisage interactions are the key, major improvement, but still the metaphors struggle. One, used by Engel in his 1980 paper [ 4 ], is ‘nested squares’ of systemic inter-activity, from the within-body biological, outwards to self-organised activity in the external environment, including interactions with immediate conspecifics, through to complex patterns of social organisation and regulation. This ‘nested’ domains metaphor is not up to much either, however, insofar as it lends itself to the implicit though odd presumption that the inner domain is sorted out first, then the next grows around it, then the next around that; in effect to the idea, absurd once spelt out, that our internal biology comes first, then activity in the outside world, then activity with conspecifics. This sequencing beginning with ‘first’ makes no sense temporally or systemically. Internal biology, functioning in the environment, including with other biological beings, cannot be separated from one another, conceptually or temporally.

What is missing from and obscured by these two-dimensional picture metaphors of levels and nested domains is the temporal, evolutionary and developmental, parameter . Everything is present in the original, primitive, prototypic forms . A cell is an individual unit, separate from but essentially interacting with the environment, extracting and expending energy, including interaction with other biological entities such as viruses. Parent sea birds catch fish and put it in the mouths of developmentally immature offspring, promoting the biologically necessary energetic reactions by bringing the chemicals into close enough proximity, acting like a catalyst—unless the fish is taken away first by a bigger bird of the same or different species. All these biological-environmental-individual-within-and-between-species-interactive processes are involved from the start in the simple forms , which become ever more complex. In short, no static metaphor, whether in terms of levels or nested systems, capable of being drawn on a page, does justice to the new systems sciences, which essentially invoke dynamical interaction in present time, on the basis of co-evolution through deep time.

1.3.6 Developing the General Model

Evolution and development involve increasing complexity of forms , and our argument will be that these forms bring with them new causal properties. Another way of expressing this is to say that what comes into being are increasingly complex systems, and that these systems have new and distinctive causal properties. There is in particular a quantum leap at the boundary between inanimate and biological material in which new forms or systems appear that manage the physics and chemistry of the matter, specifically energy exchanges governed by physico-chemical equations. This is the argument of Chapter 2 , Sect. 2.1 . The biological/biomedical sciences in the last half-century have done all the work to undo the restrictive assumption that biology is only physics and chemistry and to construct instead new deep theory involving another kind of ontology , turning on dynamical forms , and causation as regulation and control. The way out of physicalist reductionism starts here—exactly at the place where physics and chemistry become biology. This is the argument of Chapter 2 , Sect. 2.2 .

The evolution of life forms ends up with human psychological and social phenomena. This ‘ends up with’, as currently understood in the science, is not a matter of logic or scientific law, but is entirely contingent—accidental. In this sense, biopsychosocial systems theory is unlike some traditional philosophical systems, which start with axioms and deduce the rest, or which elucidate natural law that covers everything. So when we move from defining key features of biology , in Chapter 2 , to defining key features of psychological and hence social phenomena in Chapter 3 , there is a gap, evident at the start in Sect. 3.1 , one which cannot be filled in by logic or natural law, but only by contingent facts of evolution , development and change.

Human psychological and social phenomena have lives of their own—multiple distinctive modes of operation, turning on systemic concepts and principles already evident in biology, such as form , organisation , ends , communication , rules and regulations . In the evolution and development of new forms or systems, it can be said that they all share—from the start, and remaining in—the same ‘ontological space/time’. This is a good way of capturing the fact that they can bump into one another and affect one another, that they causally interact, as opposed to being in parallel universes. This is to say, the ontological point is at the same time essentially a point about causal interaction. We propose defining key features of psychosocial phenomena and causation in the first sections of Chapter 3 , Sects. 3.1 – 3.4 , consistent with the key features of biology proposed in Chapter 2 . With the whole biopsychosocial system in view, we return in Sect. 3.4 , to the general theory of biopsychological systems, interwoven ontology and causal theory. We address the vexed issues of top-down causes, vexed from the point of view of physicalist reductionism : psychological effects on biological processes, and social effects on our biology and psychology . However, by this stage in the argument—and in the current science we intend to be tracking—the prejudicial concepts and assumptions of physicalist reductionism are nowhere to be seen. Rather, in the new approach, there are coherent core concepts and principles of causation by regulatory control , which are found already in biology , and which can elucidate in a relatively straightforward way the logic of what is traditionally regarded as top-down processing in biological, psychological and social domains. In brief, control mechanisms employ agents at the lower level, compliant with any laws that may apply at that level, but also acting as messengers from higher levels, defined by networks of relations at those higher levels.

The detailed arguments elucidating the general theory of biopsychosocial interactions are developed through the next two chapters. The fourth chapter expands on relevance to health and disease. In fact, however, the whole theory is at its core, from the start, a theory of health and disease. This is because the theory is fundamentally normative, in terms of concepts such as functioning well or badly, being well or unwell. The contrast here with physicalist reductionism is striking: the old theory makes a point of excluding any hint of normativity, with no interest in any difference between life and death or anything else related.

Engel, G. L. (1977). The need for a new medical model: A challenge for biomedicine. Science, 196 (4286), 129–136.

Article PubMed Google Scholar

Ghaemi, S. N. (2010). The rise and fall of the biopsychosocial model: Reconciling art and science in psychiatry . Baltimore, MD: Johns Hopkins University Press.

Google Scholar

Kendler, K. S. (2010). [Book Review] The rise and fall of the biopsychosocial model: Reconciling art and science in psychiatry. American Journal of Psychiatry, 167 (8), 999–1000. https://doi.org/10.1176/appi.ajp.2010.10020268 .

Article Google Scholar

Engel, G. L. (1980). The clinical application of the biopsychosocial model. American Journal of Psychiatry, 137 (5), 535–544.

Marmot, M. (2010). Fair society, healthy lives: Strategic review of health inequalities in England post-2010 . London, UK: Department of Health.

Frankel, R. M., Quill, T. E., & McDaniel, S. H. (Eds.). (2003). The biopsychosocial approach: Past, present, and future . Rochester, NY: University of Rochester Press.

Sadler, J. Z., & Hulgus, Y. F. (1990). Knowing, valuing, acting: Clues to revising the biopsychosocial model. Comprehensive Psychiatry, 31 (3), 185–195.

Lindau, S. T., Laumann, E. O., Levinson, W., & Waite, L. J. (2003). Synthesis of scientific disciplines in pursuit of health: The interactive biopsychosocial model. Perspectives in Biology and Medicine, 46 (Suppl. 3), S74–S86.

Article PubMed PubMed Central Google Scholar

Smith, R. C., Fortin, A. H., Dwamena, F., & Frankel, R. M. (2013). An evidence-based patient-centered method makes the biopsychosocial model scientific. Patient Education and Counseling, 91 (3), 265–270. https://doi.org/10.1016/j.pec.2012.12.010 .

Ghaemi, S. N. (2009). The rise and fall of the biopsychosocial model. The British Journal of Psychiatry, 195 (1), 3–4.

Engel, G. L. (1978). The biopsychosocial model and the education of health professionals. General Hospital Psychiatry, 1 (2), 156–165.

Davey Smith, G. (2005). The biopsychosocial approach: A note of caution. In P. D. White (Ed.), Biopsychosocial medicine: An integrated approach to understanding illness (pp. 77–102). New York, NY: Oxford University Press.

McManus, C. (2005). Engel, Engels, and the side of the angels. The Lancet, 365 (9478), 2169–2170. https://doi.org/10.1016/S0140-6736(05)66761-X .

Marmot, M. (2005). Remediable or preventable social factors in the aetiology and prognosis of medical disorders. In P. D. White (Ed.), Biopsychosocial medicine: An integrated approach to understanding illness (pp. 39–58). New York, NY: Oxford University Press.

Marmot, M. (2006). Status syndrome: A challenge to medicine. Journal of the American Medical Association, 295 (11), 1304–1307.

Marmot, M. G., Rose, G., Shipley, M., & Hamilton, P. J. (1978). Employment grade and coronary heart disease in British civil servants. Journal of Epidemiology and Community Health, 32 (4), 244–249.

Link, B. G., & Phelan, J. (1995). Social conditions as fundamental causes of disease. Journal of Health and Social behavior , Special Issue, 80–94.

Cockerham, W. C. (2007). Social causes of health and disease . Cambridge: Polity Press.

Felitti, V. J., Anda, R. F., Nordenberg, D., Williamson, D. F., Spitz, A. M., Edwards, V., et al. (1998). Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults. The Adverse Childhood Experiences (ACE) Study. American Journal of Preventative Medicine, 14 (4), 245–258.

Adler, N. E., Epel, E. S., Castellazzo, G., & Ickovics, J. R. (2000). Relationship of subjective and objective social status with psychological and physiological functioning: Preliminary data in healthy, white women. Health Psychology, 19 (6), 586–592.

Singh-Manoux, A., Adler, N. E., & Marmot, M. G. (2003). Subjective social status: Its determinants and its association with measures of ill-health in the WhiteHall II study. Social Science and Medicine, 56 (6), 1321–1333.

Beck, A. T., Rush, A. J., Shaw, B. F., & Emery, G. (1979). Cognitive therapy of depression . New York, NY: Guilford Press.

Hunsley, J., Elliott, K., & Therrien, Z. (2013). The efficacy and effectiveness of psychological treatments. Report to the Canadian Psychologial Association. https://cpa.ca/docs/File/Practice/TheEfficacyAndEffectivenessOfPsychologicalTreatments_web.pdf . Accessed 21 December 2018.

Falagas, M. E., Zarkadoulia, E. A., Ioannidou, E. N., Peppas, G., Christodoulou, C., & Rafailidis, P. I. (2007). The effect of psychosocial factors on breast cancer outcome: A systematic review. Breast Cancer Research, 9 (4), R44. https://doi.org/10.1186/bcr1744 .

Chida, Y., Hamer, M., & Steptoe, A. (2008). A bidirectional relationship between psychosocial factors and atopic disorders: A systematic review and meta-analysis. Psychosomatic Medicine, 70 (1), 102–116.

Ritz, T., Meuret, A. E., Trueba, A. F., Fritzsche, A., & von Leupoldt, A. (2013). Psychosocial factors and behavioral medicine interventions in asthma. Journal of Consulting and Clinical Psychology, 81 (2), 231–250.

Chida, Y., & Vedhara, K. (2009). Adverse psychosocial factors predict poorer prognosis in HIV disease: A meta-analytic review of prospective investigations. Brain, Behavior, and Immunity, 23 (4), 434–445.

Ironson, G. H., & Hayward, H. (2008). Do positive psychosocial factors predict disease progression in HIV-1? A review of the evidence. Psychosomatic Medicine, 70 (5), 546–554.

Langford, S. E., Ananworanich, J., & Cooper, D. A. (2007). Predictors of disease progression in HIV infection: A review. AIDS Research and Therapy, 4 (1), 1–11.

Laisné, F., Lecomte, C., & Corbière, M. (2012). Biopsychosocial predictors of prognosis in musculoskeletal disorders: A systematic review of the literature (corrected and republished). Disability and Rehabilitation, 34 (22), 1912–1941.

Berk, H. O. S. (2010). The biopsychosocial factors that serve as predictors of the outcome of surgical modalities for chronic pain. Agri, 22 (3), 93–97.

Block, A. R., Ben-Porath, Y. S., & Marek, R. J. (2013). Psychological risk factors for poor outcome of spine surgery and spinal cord stimulator implant: A review of the literature and their assessment with the MMPI-2-RF. The Clinical Neuropsychologist, 27 (1), 81–107.

Celestin, J., Edwards, R. R., & Jamison, R. N. (2009). Pretreatment psychosocial variables as predictors of outcomes following lumbar surgery and spinal cord stimulation: A systematic review and literature synthesis. Pain Medicine, 10 (4), 639–653.

den Boer, J. J., Oostendorp, R. A. B., Beems, T., Munneke, M., Oerlemans, M., & Evers, A. W. M. (2006). A systematic review of bio-psychosocial risk factors for an unfavourable outcome after lumbar disc surgery. European Spine Journal, 15 (5), 527–536.

Epker, J., & Block, A. R. (2001). Presurgical psychological screening in back pain patients: A review. The Clinical Journal of Pain, 17 (3), 200–205.

Gaudin, D., Krafcik, B. M., Mansour, T. R., & Alnemari, A. (2017). Considerations in spinal fusion surgery for chronic lumbar pain: Psychosocial factors, rating scales, and perioperative patient education. World Neurosurgery, 98, 21–27.

Lall, M. P., & Restrepo, E. (2017). The biopsychosocial model of low back pain and patient-centered outcomes following lumbarfusion. Orthopaedic Nursing, 36 (3), 213–221.

Wilhelm, M., Reiman, M., Goode, A., Richardson, W., Brown, C., Vaughn, D., et al. (2015). Psychological predictors of outcomes with lumbar spinal fusion: A systematic literature review. Physiotherapy Research International, 22 (2), e1648.

Fineberg, S. K., West, A., Na, P. J., Oldham, M., Schilsky, M., Hawkins, K. A., et al. (2016). Utility of pretransplant psychological measures to predict posttransplant outcomes in liver transplant patients: A systematic review. General Hospital Psychiatry, 40, 4–11.

Pignay-Demaria, V., Lespérance, F., Demaria, R. G., Frasure-Smith, N., & Perrault, L. P. (2003). Depression and anxiety and outcomes of coronary artery bypass surgery. The Annals of Thoracic Surgery, 75 (1), 314–321.

Rosenberger, P. H., Jokl, P., & Ickovics, J. (2006). Psychosocial factors and surgical outcomes: An evidence-based literature review. Journal of the American Academy of Orthopaedic Surgeons, 14 (7), 397–405.

Tully, P. J., & Baker, R. A. (2012). Depression, anxiety, and cardiac morbidity outcomes after coronary artery bypass surgery: A contemporary and practical review. Journal of Geriatric Cardiology, 9 (2), 197–208.

Alexander, S. J. (2013). Time to get serious about assessing—and managing—psychosocial issues associated with chronic wounds. Current Opinion in Supportive and Palliative Care, 7 (1), 95–100.

Soon, K., & Acton, C. (2006). Pain-induced stress: A barrier to wound healing. Wounds UK, 2 (4), 92–101.

Mollayeva, T., Kendzerska, T., Mollayeva, S., Shapiro, C. M., Colantonio, A., & Cassidy, J. D. (2014). A systematic review of fatigue in patients with traumatic brain injury: The course, predictors and consequences. Neuroscience and Biobehavioral Reviews, 47, 684–716.

Chang, E. Y., Chang, E., Cragg, S., & Cramer, S. C. (2013). Predictors of gains during inpatient rehabilitation in patients with stroke: A review. Critical Reviews in Physical and Rehabilitation Medicine, 25 (3–4), 203–221.

Admi, H., Shadmi, E., Baruch, H., & Zisberg, A. (2015). From research to reality: Minimizing the effects of hospitalization on older adults. Rambam Maimonides Medical Journal, 6 (2), e0017. https://doi.org/10.5041/RMMJ.10201 .

Felix-Aaron, K., Moy, E., Kang, M., Patel, M., Chesley, F. D., & Clancy, C. (2005). Variation in quality of men’s health care by race/ethnicity and social class. Medical Care, 43 (3), I-72–I-81.

Grintsova, O., Maier, W., & Mielck, A. (2014). Inequalities in health care among patients with type 2 diabetes by individual socio-economic status (SES) and regional deprivation: A systematic literature review. International Journal for Equity in Health, 13 (1), 43. http://www.equityhealthj.com/content/13/1/43 .

Davidson, E., Liu, J. J., & Sheikh, A. (2010). The impact of ethnicity on asthma care. Primary Care Respiratory Journal, 19 (3), 202–208.

Crawshaw, J., Auyeung, V., Norton, S., & Weinman, J. (2016). Identifying psychosocial predictors of medication non-adherence following acute coronary syndrome: A systematic review and meta-analysis. Journal of Psychosomatic Research, 90, 10–32.

Ghimire, S., Castelino, R. L., Lioufas, N. M., Peterson, G. M., & Zaidi, S. T. R. (2015). Nonadherence to medication therapy in haemodialysis patients: A systematic review. PLoS One, 10 (12), e0144119.

Loiselle, K., Rausch, J. R., & Modi, A. C. (2015). Behavioral predictors of medication adherence trajectories among youth with newly diagnosed epilepsy. Epilepsy & Behavior, 50, 103–107.

Zwikker, H. E., van den Bemt, B. J. F., Vriezekolk, J. E., van den Ende, C. H. M., & Dulmen, S. (2014). Psychosocial predictors of non-adherence to chronic medication: Systematic review of longitudinal studies. Patient Preference and Adherence, 8, 519–563.

Edwards, R. R., Dworkin, R. H., Sullivan, M. D., Turk, D. C., & Wasan, A. D. (2016). The role of psychosocial processes in the development and maintenance of chronic pain. The Journal of Pain, 17 (9), T70–T92.

Ong, K. S., & Keng, S. B. (2003). The biological, social, and psychological relationship between depression and chronic pain. The Journal of Craniomandibular & Sleep Practice, 21 (4), 286–294.

Harrison, A. M., McCracken, L. M., Bogosian, A., & Moss-Morris, R. (2015). Towards a better understanding of MS pain: A systematic review of potentially modifiable psychosocial factors. Journal of Psychosomatic Research, 78 (1), 12–24.

Mallen, C. D., Peat, G., Thomas, E., Dunn, K. M., & Croft, P. R. (2007). Prognostic factors for musculoskeletal pain in primary care: A systematic review. British Journal of General Practice, 57 (541), 655–661.

PubMed Google Scholar

Whibley, D., Martin, K. R., Lovell, K., & Jones, G. T. (2015). A systematic review of prognostic factors for distal upper limb pain. British Journal of Pain, 9 (4), 241–255.

Pincus, T., Burton, A. K., Vogel, S., & Field, A. P. (2002). A systematic review of psychological factors as predictors of chronicity/disability in prospective cohorts of low back pain. Spine, 27 (5), E109–E120.

Ramond-Roquin, A., Bouton, C., Bègue, C., Petit, A., Roquelaure, Y., & Huez, J. F. (2015). Psychosocial risk factors, interventions, and comorbidity in patients with non-specific low back pain in primary care: Need for comprehensive and patient-centered care. Frontiers in Medicine, 2 (73), 1–6.

Campbell, P., Wynne‐Jones, G., & Dunn, K. M. (2011). The influence of informal social support on risk and prognosis in spinal pain: A systematic review. European Journal of Pain, 15 (5), 444. e1–14. https://doi.org/10.1016/j.ejpain.2010.09.011 .

Riegel, B., Bruenahl, C. A., Ahyai, S., Bingel, U., Fisch, M., & Löwe, B. (2014). Assessing psychological factors, social aspects and psychiatric co-morbidity associated with Chronic Prostatitis/Chronic Pelvic Pain Syndrome (CP/CPPS) in men: A systematic review. Journal of Psychosomatic Research, 77 (5), 333–350.

Somers, T. J., Keefe, F. J., Godiwala, N., & Hoyler, G. H. (2009). Psychosocial factors and the pain experience of osteoarthritis patients: New findings and new directions. Current Opinion in Rheumatology, 21 (5), 501–506.

Novy, D. M., & Aigner, C. J. (2014). The biopsychosocial model in cancer pain. Current Opinion in Supportive and Palliative Care, 8 (2), 117–123.

Schreiber, K. L., Kehlet, H., Belfer, I., & Edwards, R. R. (2014). Predicting, preventing and managing persistent pain after breast cancer surgery: The importance of psychosocial factors. Pain, 4 (6), 445–459.

Von Korff, M. (2005). Fear and depression as remediable causes of disability in common medical conditions in primary care. In P. D. White (Ed.), Biopsychosocial medicine: An integrated approach to understanding illness (pp. 117–131). New York, NY: Oxford University Press.

Naylor, C., Parsonage, M., McDaid, D., Knapp, M., Fossey, M., & Galea, A. (2012). Long-term conditions and and mental health: The cost of co-morbidities. The King’s Fund and Centre for Mental Health. Available at https://www.kingsfund.org.uk/sites/default/files/field/field_publication_file/long-term-conditions-mental-health-cost-comorbidities-naylor-feb12.pdf . Accessed 21 December 2018.

Parle, M., Jones, B., & Maguire, P. (1996). Maladaptive coping and affective disorders among cancer patients. Psychological Medicine, 26 (4), 735–744.

Cordella, M., & Poiani, A. (2004). Behavioural Oncology: Psychological, communicative, and social dimensions . New York, NY: Springer-Verlag.

NHS England & NHS Improvement. (2018). The Improving Access to Psychological Therapies (IAPT) pathway for people with long-term physical health conditions and medically unexplained symptoms . London, UK: NHS.

Allart, P., Soubeyran, P., & Cousson-Gélie, F. (2013). Are psychosocial factors associated with quality of life in patients with haematological cancer? A critical review of the literature. Psycho-Oncology, 22 (2), 241–249.

Bakaniene, I., Prasauskiene, A., & Vaiciene‐Magistris, N. (2016). Health‐related quality of life in children with myelomeningocele: A systematic review of the literature. Child: Care, Health and Development, 42 (5), 625–643.

Sales, P. M. G., Carvalho, A. F., McIntyre, R. S., Pavlidis, N., & Hyphantis, T. N. (2014). Psychosocial predictors of health outcomes in colorectal cancer: A comprehensive review. Cancer Treatment Reviews, 40 (6), 800–809.

Bours, M. J. L., van der Linden, B. W. A., Winkels, R. M., van Duijnhoven, F. J., Mols, F., van Roekel, E. H., et al. (2016). Candidate predictors of health-related quality of life of colorectal cancer survivors: A systematic review. Oncologist, 21 (4), 433–452.

Kang, K., Gholizadeh, L., Inglis, S. C., & Han, H. R. (2017). Correlates of health-related quality of life in patients with myocardial infarction: A literature review. International Journal of Nursing Studies, 73, 1–16.

Peeters, C. M. M., Visser, E., Van de Ree, C. L. P., Gosens, T., Den Oudsten, B. L., & De Vries, J. (2016). Quality of life after hip fracture in the elderly: A systematic literature review. Injury, 47 (7), 1369–1382.

Pragodpol, P., & Ryan, C. (2013). Critical review of factors predicting health-related quality of life in newly diagnosed coronary artery disease patients. Journal of Cardiovascular Nursing, 28 (3), 277–284.

Taylor, R. S., Sander, J. W., Taylor, R. J., & Baker, G. A. (2011). Predictors of health-related quality of life and costs in adults with epilepsy: A systematic review. Epilepsia, 52 (12), 2168–2180.

Seiam, A. H. R., Dhaliwal, H., & Wiebe, S. (2011). Determinants of quality of life after epilepsy surgery: Systematic review and evidence summary. Epilepsy & Behavior, 21 (4), 441–445.

Walders-Abramson, N. (2014). Depression and quality of life in youth-onset type 2 diabetes mellitus. Current Diabetes Reports, 14 (1), 449. https://doi.org/10.1007/s11892-013-0449-x .

Blazer, D. (2010). [Book Review] The rise and fall of the biopsychosocial model: Reconciling art and science in psychiatry. The International Journal of Psychiatry in Medicine, 40 (3), 361–362. https://doi.org/10.2190/PM.40.3.j .

Mill, J. S. (1843). A system of logic . London: John W. Parker.

Hume, D. (1902). An enquiry concerning human understanding (L. A. Selby-Bigge, Ed.). Oxford: Oxford University Press (Original work published 1777).

Koch, R. (1890). Uber bacteriologische forschung. Deutsche Medizinische Wochenschrift, 16, 756–757.

Evans, A. (1976). Causation and disease: The Henle-Koch postulates revisited. The Yale Journal of Biology and Medicine, 49, 175–195.

PubMed PubMed Central Google Scholar

Bolton, D. (2008). The epistemology of randomized, controlled trials and application in psychiatry. Philosophy, Psychiatry & Psychology, 15 (2), 159–165.

Rutter, M. (2000). Psychosocial influences: Critiques, findings, and research needs. Development and Psychopathology, 12 (3), 375–405. https://doi.org/10.1017/S0954579400003072 .

Stoljar, D. (2015)., “Physicalism”, The Stanford Encyclopedia of Philosophy (Winter 2017 Edition), Edward N. Zalta (ed.), URL = < https://plato.stanford.edu/archives/win2017/entries/physicalism/ >. Accessed 12/21/2018.

Burtt, E. A. (1932). The metaphysical foundations of modern physical sciences . London: Routledge and Kegan Paul.

Dijksterhuis, E. J. (1961). The mechanization of the world picture (C. Dikshoorn, Trans.). Oxford: Oxford University Press.

Koyré, A. (1968). Metaphysics and measurement: Essays in the scientific revolution . London: Chapman and Hall.

Mayr, E. (1982). The growth of biological thought: Diversity, evolution, and inheritance . Cambridge, MA: Harvard University Press.

Bechtel, W., & Richardson, R. C. (2005). Vitalism. In E. Craig (Ed.), The shorter Routledge encyclopedia of philosophy (p. 1051). Oxford: Routledge.

Watson, J. B. (1913). Psychology as the behaviorist views it. Psychological Review, 20 (2), 158–177.

Giddens, A. (2005). Introduction to the protestant ethic and the spirit of capitalism, by Max Weber (T. Parsons, Trans.). London: Routledge.

Fodor, J. (1974). Special sciences (Or: The disunity of science as a working hypothesis). Synthese, 28 (2), 97–115.

Fodor, J. (1997). Special sciences: Still autonomous after all these years. Philosophical Perspectives, 11, 149–163.

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Bolton, D., Gillett, G. (2019). The Biopsychosocial Model 40 Years On. In: The Biopsychosocial Model of Health and Disease. Palgrave Pivot, Cham. https://doi.org/10.1007/978-3-030-11899-0_1

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Biopsychosocial Model: Examples, Overview, Criticisms

biopsychosocial model example, definition and components, explained below

George Engel first articulated the b iopsychosocial model in 1977, proposing that understanding a person’s medical condition requires assessing not only their biology but also psychological and social influences.

The biopsychosocial model encompasses three primary elements: physiological, psychological, and sociocultural aspects.

For example, biological factors can include a person’s age, genetic makeup, health history, and gender. Psychological influences can include the individual’s emotions, thoughts, and behavior.

Finally, social aspects like economic status, family relationships, and access to healthcare services can drastically alter one’s choices.

This method emphasizes that people possess unique well-being needs, recognizing the interrelationship of these three components for optimal care.

By taking a comprehensive approach to patient healthcare, medical practitioners can understand the root causes of illness, thus enabling them to craft individualized care plans.

Overview of the Biopsychosocial Model

A biopsychosocial model is a holistic approach to understanding health and illness considering multiple influences. It recognizes the interplay between biological, psychological, and social factors on health throughout a person’s lifespan (Bolton & Gillett, 2019).

Through this model, practitioners can gain insight into how physical, psychological, and social stressors can interact to affect an individual’s overall health.

According to Erb and Schmidt (2021), a biopsychosocial model:

“…is a general model of care, positing that biological, psychological (i.e., thoughts, emotions, and behaviors), and social factors all play a significant role in human functioning in the context of disease or illness (p. 29).

While traditional medical models focus purely upon problems’ pathological origins, this alternative considers multiple aspects beyond mere biological cause.

This method focuses on comprehending how combined biological, psychological, and social aspects can affect our well-being.

Kusnanto and colleagues (2018) state that:

“…the biopsychosocial model is an ideal representation of science and humanism in medical practice, although many argue that the model is hard to implement” (p. 497).

Integrating mental, physical, and social factors into patient care can be arduous. Its primary goal is to give a complete view of patient care by concentrating on nurturing the individual as an entirety rather than solely focusing on their medical symptoms.

For example, a person suffering from persistent pain could find relief through integrated physical and psychological therapies, along with the assistance of their psychologist. The treatment plan must always be carefully tailored to an individual’s needs accordingly.

Simply, the biopsychosocial model allows practitioners to understand the root causes of ailments or discomfort, enabling them to create more tailored treatment strategies.

Three Components of the Biopsychosocial Model

The biopsychosocial healthcare model comprises three interrelated components: biological, psychological, and social (Landow, 2006).

Let’s look at each of these components:

1. Biological Component

This component refers to the physiological and genetic characteristics of the individual that affect his health. It includes predisposition to certain diseases, immune system, age, gender, and other biological factors.

For instance, hereditary factors may make a patient with a family history of type 2 diabetes more prone to developing the disorder.

2. Psychological Component

The psychological aspect covers the patient’s emotional and psychological state, including stress, anxiety, mood, and consciousness.

Psychological factors can influence health through behavioral and cognitive processes.

As in the first case, in a patient with a chronic condition such as arthritis, increased stress levels can increase pain and cause depression.

3. Social Component

This component affects the social environment and cultural factors that affect human health.

For example, it may include health care availability and quality, family support, economic status, and educational attainment.

A patient with low socioeconomic status may have limited access to quality health care or a healthy diet, leading to chronic diseases.

Biopsychosocial Model Examples

Eating Disorders : The biopsychosocial model offers invaluable insights into the development of eating disorders, such as anorexia nervosa, bulimia nervosa, and binge eating, by exploring their biological, psychological, and social nuances. Evidence affirms that these conditions cannot be attributed to any cause but rather a combination of factors from several domains. So, treatment plans must look at all aspects of an individual’s condition rather than solely focusing on physical symptoms.
Anxiety Disorders : Anxiety can be attributed to biological, psychological, and social factors. Thus, by blending biological elements such as neurotransmitter imbalances with psychological approaches like cognitive behavioral therapy (CBT) and social paradigms , including supportive networks – it is achievable to mitigate the symptoms of anxiety conditions, for example, panic disorder or OCD.
Depression : This psychological condition can be caused by various components, such as genetics, hormone imbalances, detrimental thought patterns and environmental pressures. An effective treatment should take into consideration each of these contributing aspects to successfully tackle depression symptoms.
Addiction : Addictive behaviors may have a biological base due to chemical imbalances in the brain or genetic predispositions. Still, they can also be triggered by personal struggles or difficult situations in a person’s life. So, before developing a treatment strategy, it’s important to consider all the contributing factors to an individual’s addiction.
Chronic Pain : If you experience persistent pain, there is likely to be a physiological cause. Additionally, psychological and environmental elements can contribute to distress. To successfully handle chronic soreness requires physical treatments that address the root of your condition and cognitive-behavioral strategies designed to lessen its emotional impact while receiving support from family members or friends.
Heart Disease : Biological risk factors like smoking or high cholesterol levels and psychological elements like stress and lack of physical activity can contribute to this chronic condition. Understanding these different components helps healthcare professionals create comprehensive prevention plans for individuals at risk of developing heart disease.
Autism Spectrum Disorders : Like many other conditions, ASD can be the result of biological factors such as neural development or genetic makeup. Psychological issues, including anxiety, or social problems, such as communication or social interaction difficulties, can also influence it. Integrating all of these components into treatment plans can help to improve the lives of those struggling.
ADHD/ADD : Biological causes, like an increase in certain neurotransmitters levels alongside environment elements e.g. absence/or not enough parental monitoring and inadequate nutrition are known causes culminating to Attention Deficit /Hyperactive disorder (ADHA/ADD). So, treatment plans should take all of these factors into consideration to help those affected by this condition.
Schizophrenia : This mental disorder is associated with multiple biological changes in the brain and possible genetic influences. However, social factors, including trauma or relationship issues, may trigger its onset or exacerbate existing symptoms. Thus, creating an effective treatment plan should include assessing these contributing components.
Insomnia : Studies suggest that there are both physical and emotional drivers behind insomnia. Thus, if you have insomnia, a comprehensive treatment plan should include not just lifestyle interventions such as reducing caffeine and alcohol intake. In addition, consider taking some form of mental health guidance such as CBT (cognitive behavioral therapy) aimed at detecting and addressing underlying emotions capable of disrupting adequate slumber.

Origins of the Biopsychosocial Model

In the 1970s, George L. Engel – an American psychiatrist – proposed a biopsychosocial model as an alternative to the biomedical model that was then prevailing (Smith, 2002).

The biomedical model focused exclusively on the physical and biological aspects of the disease. It marked the beginning of a revolutionary new era in psychiatry and medicine.

Still, this model took a reductionist approach and only looked at the disease from an anatomical, physiologic, and chemical perspective of the body. Thus, psychological and social influences were disregarded.

According to Smith (2002), based on various studies and clinical experience, Engel proposed the biopsychosocial model to combine diseases’ biological, psychological, and social aspects.

This model emphasizes the significance of taking into account all three elements in combination in order to gain a comprehensive insight into diseases and their causes.

Over time, the biopsychosocial model has earned immense global recognition from researchers.

It found considerable traction in many current approaches to diagnosing, curing, and averting ailments ranging from psychological conditions to chronic illnesses.

Criticisms of the Biopsychosocial Model

While the biopsychosocial model may look a promising unified approach to patient treatment, its ambiguity in terms of outcomes, lack of unity amongst practitioners, and its complexity have been heavily criticized.

Here are some key criticisms of this model:

Lack of c larity and s tructure : One major criticism of the biopsychosocial model is its relative uncertainty and absence of structure. The lack of clear boundaries and criteria for each component (biological, psychological, and social) can make developing and evaluating standard treatment techniques challenging (Carey et al., 2014).
Lack of unity : The biopsychosocial model is often seen as an alternative to the biomedical model but is not always integrated with it. This separation can lead to interaction problems between specialists in different fields and a lack of a unified treatment strategy.
Complex ity : Measuring and evaluating psychological and social factors can be complex and subjective. Determining the relationship between these components and diseases can take time, creating difficulties in developing and evaluating treatment effectiveness (Carey et al., 2014).
Resource limitations : The biopsychosocial model requires a broader and deeper approach to treatment, which can require significant resources and time. Implementing such an approach can be challenging, especially with limited budgets and overburdened healthcare facilities.

To gain insight into every aspect of one’s well-being requires a comprehensive perspective such as what’s provided by the biopsychosocial model.

This evidence-based approach helps us gain greater insight into how physical and mental issues come about – giving us an invaluable tool for improving our overall health.

Developed by George Engel in the late 1970s, healthcare practitioners have widely adopted this model due to its comprehensive and integrative approach.

Despite its advantages, the biopsychosocial model has been criticized for its lack of certainty, structure, unity, complex process, and resource limitations.

Still, it serves as a significant means of comprehending and dissecting physical and mental healthcare challenges, whilst devising potent treatments for multiple conditions.

Bolton, D., & Gillett, P. G. (2019). The biopsychosocial model 40 years on. In www.ncbi.nlm.nih.gov . Palgrave Pivot. https://www.ncbi.nlm.nih.gov/books/NBK552030/

Carey, T. A., Mansell, W., & Tai, S. J. (2014). A biopsychosocial model based on negative feedback and control. Frontiers in Human Neuroscience , 8 . https://doi.org/10.3389/fnhum.2014.00094

Erb, M., & Schmid, A. A. (2021). Integrative rehabilitation practice: The foundations of whole-person care for health professionals . Jessica Kingsley Publishers.

Kusnanto, H., Agustian, D., & Hilmanto, D. (2018). Biopsychosocial model of illnesses in primary care: A hermeneutic literature review. Journal of Family Medicine and Primary Care , 7 (3), 497–500. https://doi.org/10.4103/jfmpc.jfmpc_145_17

Landow, M. V. (2006). Stress and mental health of college students . New York: Nova Science Publishers.

Smith, R. C. (2002). The biopsychosocial revolution. Journal of General Internal Medicine , 17 (4), 309–310. https://doi.org/10.1046/j.1525-1497.2002.20210.x

Viktoriya Sus (MA)

Viktoriya Sus is an academic writer specializing mainly in economics and business from Ukraine. She holds a Master’s degree in International Business from Lviv National University and has more than 6 years of experience writing for different clients. Viktoriya is passionate about researching the latest trends in economics and business. However, she also loves to explore different topics such as psychology, philosophy, and more.

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Chris Drew (PhD)

This article was peer-reviewed and edited by Chris Drew (PhD). The review process on Helpful Professor involves having a PhD level expert fact check, edit, and contribute to articles. Reviewers ensure all content reflects expert academic consensus and is backed up with reference to academic studies. Dr. Drew has published over 20 academic articles in scholarly journals. He is the former editor of the Journal of Learning Development in Higher Education and holds a PhD in Education from ACU.

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