Biopsychosocial Model - Mental and Social Phenomena

George Engel’s perspective is contrasted with a so-called monistic or reductionistic view, in which all phenomena could be reduced to smaller parts and understood as molecular interactions. Nor did he endorse a holistic-energetic view, many of whose adherents espouse a biopsychosocial philosophy; these views hold that all physical phenomena are ephemeral and controllable by the manipulation of healing energies.

Rather, in embracing Systems Theory, Engel recognized that mental and social phenomena depended upon but could not necessarily be reduced to (ie, explained in terms of) more basic physical phenomena given our current state of knowledge. He endorsed what would now be considered a complexity view, in which different levels of the biopsychosocial hierarchy could interact, but the rules of interaction might not be directly derived from the rules of the higher and lower rungs of the biopsychosocial ladder. Rather, they would be considered emergent properties that would be highly dependent on the persons involved and the initial conditions with which they were presented, much as large weather patterns can depend on initial conditions and small influences. This perspective has guided decades of research seeking to elucidate the nature of these interactions.

Engel objected to a linear cause-effect model to describe clinical phenomena. Clinical reality is far more complex. For example, although genetics may have a role in causing schizophrenia, no clinician would ignore the sociologic factors that might unleash or contain the manifestations of the illness.

Few morbid conditions could be interpreted as being of the nature “one microbe, one illness”; rather, there are usually multiple interacting causes and contributing factors. Thus, obesity leads to both diabetes and arthritis; both obesity and arthritis limit exercise capacity, adversely affecting blood pressure and cholesterol levels; and all of the above, except perhaps arthritis, contribute to both stroke and coronary artery disease. Some of the effects (depression after a heart attack or stroke) can then become causal (greater likelihood of a second similar event). Similar observations can be made about predictors of relapse in schizophrenia.

These observations set the stage for models of circular causality, which describes how a series of feedback loops sustain a specific pattern of behavior over time. Complexity science is an attempt to understand these complex recursive and emergent properties of systems and to find interrelated proximal causes that might be changed with the right set of interventions (family support and medications for schizophrenia; depression screening and cholesterol level reduction after a heart attack).

This post, The Biopsychosocial Model 25 Years Later: Principles, Practice, and Scientific Inquiry, was first featured in www.ncbi.nlm.nih.gov/.

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