Looking for the Self in Psychiatry: Perils and Promises of Phenomenology–Neuroscience Partnership in Schizophrenia Research

Psychiatric research on schizophrenia is currently undergoing a period of extraordinary science, with many alternative research programs investigating the illness using different assumptions and methodologies. As the struggles the DSM-led research faces are now “more generally recognized as such by the profession,” trust in the dominant DSM-led research paradigm is shaken, and “numerous partial solutions to the problem” are made available (Kuhn 1962, 82-83). I use philosophical tools in this chapter to evaluate one of these alternative research approaches that I call “phenomenology-neuroscience partnership” (PNP). In part II, I lay out the phenomenological approach to schizophrenia that is critical of the DSM-led research. In part III, I focus on the phenomenology-neuroscience partnership (PNP) that takes this phenomenological approach as a starting point to investigate schizophrenia, and address its shortcomings. In part IV, I conclude by pointing out the strengths of the PNP and offer prescriptions for its improvement.

Classification, Rating Scales, and Promoting User-Led Research

Psychiatric research currently faces multiple crises; one is that trust in reported research findings has been eroded. Concerns that much research serves the interests of industry rather than the interests of patients have become mainstream. Such worries are not unique to psychiatry, but extend to many areas of science. One way in which such concerns can be ameliorated is via the development of more amateur/ citizen/ user-led research. I argue that promoting research conducted outside of traditional academic settings promises a range of benefits – both to the non-traditional researchers themselves and to others who want truths to be discovered. Having argued that it would be a good idea to have more user-produced research, I discuss how research by users might be facilitated or hindered by changes to the informational infrastructure of science. In particular, I discuss how different styles of classification, and rating scale, can facilitate the work of some research communities and set-back the work of others.

Kinds or Tails?

Are psychiatric syndromes the tails of traits distributed over the general population or do they form distinct kinds or taxa? For instance, do individuals suffering from depression form a distinct kind or rather are they the tail of the distribution of neuroticism in the general population? Do people suffering from delusions form a distinct kind or rather are they individuals with an extreme openness to experience? Before being able to answer such questions, we must address a preliminary question: How would we know whether psychiatric syndromes should be treated as taxa or as the tails of distributions defined over the general population? To address this preliminary epistemological question, I first contrast informal methods (e.g., clinical judgment) and formal methods (e.g., cluster analysis), arguing for the superiority of the latter. I then examine some of the formal methods developed in taxometrics, including cluster analysis and Paul Meehl’s taxometric procedures (e.g., MAXCOV or MAMBAC), in order to understand what assumptions about kinds or taxa are built into them.

Introduction: Psychiatric Research and Extraordinary Science

This chapter introduces the core thematic ideas of the present volume: that psychiatric research is in crisis, that it has entered a period of extraordinary science, and that a fully adequate response to the crisis should be responsive to the perspectives and interests of persons. We identify various sources of the crisis, drawing special attention to controversies concerning the role of the DSM in psychiatric research. And, we identify different strategies of response to the current crisis, including approaches that emphasize the importance of personal perspectives and the needs of the clinic and those that emphasize the important role of various scientific research programs. Further, we survey various developments (e.g., debates over fundamentals and a role for philosophical analysis, probing of the problems of the DSM framework, relaxation of standard forms of research practice, the introduction of the Research Domain Criteria initiative and other novel research programs) that are jointly suggestive of Thomas Kuhn’s characterization of periods of crisis that can arise in scientific research and of the “extraordinary science” that ensues. We suggest that this Kuhnian framework is useful for understanding the state of psychiatric research and it provides a framework for thinking about responses to the current crisis. We conclude with brief overviews of the contributions to the volume, each of which provides such a response.

Evidence-Based Medicine, Biological Psychiatry, and the Role of Science in Medicine

Both evidence-based medicine (EBM) and biological psychiatry aim to improve clinical practice by basing it more firmly on the results of scientific research. In this chapter, however, I show that the two approaches have very different views on what kinds of research will improve practice. This is because EBM is a form of medical empiricism – it focuses solely on whether treatments work, while biological psychiatry is a form of medical rationalism – it seeks to understand the causes that give rise to observed clinical outcomes. I argue that EBM’s empiricism is ultimately shortsighted and that it should integrate some of the rationalist concerns with pathophysiology. I then use this analysis to draw some lessons for research based on the NIMH’s new Research Domain Criteria.

Truth and Sanity: Positive Illusions, Spiritual Delusions, and Metaphysical Hallucinations

We criticize a worrisome trend in contemporary psychiatry that pathologizes normalcy on dubious epistemic grounds, on the naïve premise that mental health has some sort of clear, precise, and firm link to true belief and conversely that mental disease or disorder has some clear, precise and firm link to false or misbegotten belief. We deny this premise and show how it should make us worry that we understand what makes illusions, delusions, and hallucinations unhealthy or abnormal. In fact, we deny that illusions, delusions, and hallucinations are categorically or even typically unhealthy or abnormal.

DSM Applications to Young Children: Are There Really Bipolar and Depressed Two-Year-Olds?

Scientific commonsense would suggest that very young children cannot have psychiatric disorders such as bipolar disorder or major depression since they do not have the level of development to express the complex characteristics of these disorders. This chapter provides a detailed survey of current evidence supporting this common sense claim. The chapter first gives a general perspective on DSM that will be applied in looking at childhood psychiatric diagnoses and should be of some interest in its own right. I argue that there are some DSM based categorizations--those of major depressive disorder and bipolar disorder--that have substantial empirical support. I look at these two classifications as the best case for pediatric psychiatric disorders. I argue that this best case fails given our current state of knowledge, raising doubts in general about psychiatric diagnoses in small children. This conclusion has practical importance, since small children are increasingly being given powerful psychoactive drugs.

Six Myths about Schizophrenia: A Paradigm Well Beyond Its Use-By Date?

The target of this chapter is a set of six commonly held assumptions in the biomedical approach to schizophrenia, a highly regarded view in mainstream American psychiatry. A careful examination of the available research literature reveals that these widely accepted assumptions are, at best, questionable and, in many cases, refuted by empirical data. In this chapter I argue that the endurance of the biomedical schizophrenia concept in the face of mounting evidence of its inadequacy is a testament to the power that scientific paradigms hold over the minds of researchers, and of the failure of the normal process of empirical refutation that ensues.

The Shift to Mechanistic Explanation and Classification

Despite widespread recognition that psychiatry would be better served by a classificatory system based on etiology rather than mere description, it goes without saying that much of the necessary work is yet to be done. Most of it will be empirical, but there are also conceptual issues that need to be addressed. In this chapter I take up the increasingly important question of how mechanistic explanation fits into the larger effort to build a scientifically sound etiological and nosological framework for psychiatry. I sketch a rough picture of what mechanistic explanation should look like in the context of psychiatric research, with a focus on several potential challenges posed by the special features of many psychiatric conditions. These include the role of social and environmental factors, the relatively transient nature of symptoms, the presumably complex organization of underlying systems, and the likelihood that many disorders are the product of a nonstandard developmental course. I suggest that these explanatory challenges can be met with a sufficiently broad notion of mechanism, one that allows for something less than the flawless execution of internal operations, attends to organizational relations both within the mechanism itself and across the wider cognitive system, and appeals to the influence of contextual factors.

Personalized Psychiatry and Scientific Causal Explanations: Two Accounts

Contemporary personalized psychiatry faces head-on the tension to be individualized and patient-centered, while also striving to be scientific. We explore this tension by applying two accounts of scientific causal explanation, Woodward’s interventionist account and Silva, Landreth, and Bickle’s metascientific account, to recent research in social neuroscience and environmental epigenetics that bear directly on psychopathology. We’re less concerned in this chapter with which account of causal-mechanistic explanation is right, although we will have some comments about the relative advantages of each. Instead we stress two lessons for personalized psychiatry. First, properly understood, basic scientific research is not necessarily inconsistent with the aims of personalized psychiatry. There are even ways the former can advance the latter. Second, non-epistemic considerations such as clinical utility and therapeutic applicability partly determine which account of scientific causal explanation best fits with reasonable interpretations of personalized psychiatry, including questions about the most appropriate level at which to explain psychiatric disorders.