Abstract
Whole health emphasizes the interconnectedness of various health domains to support individual well-being. This approach is particularly relevant as the world grapples with a range of concurrent health challenges, including the aftermath of the COVID-19 pandemic, the global mental health crisis, and the opioid crisis. These issues illustrate the need for a new (or old?) way of thinking about health—one that views health problems as interrelated rather than isolated, and addresses their complex, systemic origins.
At the heart of whole health is the idea that health is shaped not only by biological factors but also by behavioral, social, and environmental influences. As noted by the National Center for Complementary and Integrative Health’s director Helene Langevin, MD, improving health outcomes requires understanding these factors as they interact. 1 This might involve exploring how environmental conditions like air quality, social determinants like equity, and lifestyle factors like nutrition affect stress levels, immune responses, and chronic conditions.
Whole health also acknowledges the interdependence of mental and physical well-being, advocating for multicomponent—this is, integrative—interventions. By taking a holistic approach, the goal is to not only treat existing health conditions but also foster overall resilience and prevent disease.
Ultimately, whole health encourages a shift from fragmented, disease-specific care toward an integrative model that supports the full spectrum of human health.
Sounds too good to be true? Well, perhaps because it (still) is to a large extent: in 1637 Descartes published his famous Discourse on the Method. Here he not only coined his world-famous “I think, therefore I am” as the core of his philosophy, but also “Divide each difficulty into as many parts as is feasible and necessary to resolve it.” 2 This fundamental idea of reductionism still characterizes the basic understanding of medicine worldwide today as to how diagnostics, therapy and, yes, also research should be conducted.
Reductionism emphasizes solving complex issues by breaking them into smaller, simpler parts, under the belief that understanding each component individually leads to an understanding of the whole. Over the past centuries, reductionism has shaped the framework of scientific inquiry, particularly in disciplines such as biology and medicine, where focusing on specific cells, molecules, or genes has led to groundbreaking discoveries. 3
In medicine, reductionism has been instrumental in isolating specific causes of diseases, developing targeted treatments, and making strides in prevention by addressing distinct biological mechanisms. By concentrating on isolated components, reductionism allows for precision and specificity, providing essential insights into physiological functions and malfunctioning pathways. This methodology has been responsible for many of biomedicine’s triumphs, including the development of antibiotics, vaccines, and various surgical techniques, all of which rely on a detailed understanding of biological functions at the smallest levels.
This has consequences for how we broadly understand medicine today: in a reductionist framework, complex health issues are broken down and managed in isolation, with each symptom or risk factor treated separately. For example, in managing cardiovascular diseases, biomedicine targets risk factors like hyperlipidemia or hypertension by individual drugs. This approach extends to coexisting health conditions, where, say, a patient with coronary artery disease and diabetes will receive separate treatments for each condition, with minimal consideration of how these treatments might interact or influence each other. 3
While this segmented approach makes clinical management straightforward and organized, it oversimplifies the interdependent nature of the body’s systems. By treating each condition and each symptom as if it operates independently, reductionism can overlook the complex interactions between diseases and treatments. This approach assumes that treatment outcomes are linear and additive, whereas, in reality, they often follow more complex, interconnected patterns. Reductionist health, the opposite of whole health.
And of course, it also has consequences for how clinical research ought to be conducted. Our clinical research paradigm is based on a utopian ideal: The typical patient in clinical practice is multimorbid, suffers from numerous, more or less equally burdensome symptoms, is old or young, ethnically diverse, male or female, or of another gender. The patient that clinical research wants is “monomorbid,” has a single “primary” symptom that needs to be addressed, is neither too old nor too young, white, and, except in the case of diseases that only or predominantly affect women, is male. 4
The difficulties of investigating multicomponent integrative health approaches in a design optimized for pharmacological research are legion. Placebo control, blinding, standardization are not only often difficult to impossible, but they are also often not useful. In an integrative health approach (but also in psychotherapy, for example), I want the patient to actively participate; I want to activate their self-healing will. I also aim to consciously use “non-specific” contextual factors (which are often much more specific than one might think). To achieve this, the patient must not stumble “blindly” through the therapy as if it were none of their business.
But reductionist research not only “reduces” the therapy, but also the patient. Taking whole health seriously means that therapy equally addresses objective and subjective, physical, mental and behavioral (and perhaps also social and environmental) outcome parameters. It takes into account the interactions between these parameters and tries to nudge the whole patient along the multifaceted health continuum a little further away from “illness” and a little further towards “health”. The whole patient and not Descartes “as many parts as is feasible and necessary” of this patient. I am a psychologist by training and in fact it is relatively normal in psychology to evaluate associated and interacting parameters together using multivariate analyses. 5 The resulting p-value then does not indicate whether a hypothetical primary outcome parameter has improved, but rather all the parameters of interest as a whole. Try this in medicine. How do I enter this in clinicaltrials.gov alone, with the forced differentiation between primary and secondary outcome parameters?
Don’t get me wrong. The standardization of clinical research has done a lot of good. And even in its reductionist approach, we have been able to show many positive results for integrative health approaches, although strictly speaking the design is not intended for this. But it is not ideal to have to study the effects of integrative health approaches on whole person well-being in a research paradigm optimized for pharmacology and “cardinal symptoms.”
Such whole health research needs, among so many other creative and courageous innovations, a fresh look at the statistics to be used in order not to produce alpha-accumulated artifacts and not to propagate pseudo-effective therapies. I do not have a solution to this problem (although of course I have ideas and fantasies), but I look forward to your suggestions and creative innovations. We will examine each one openly but rigorously and critically.
Holger Cramer, PhD
Editor-in Chief