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Psychiatry beyond labels: introducing contextual precision diagnosis across stages of psychopathology

Published online by Cambridge University Press:  17 June 2013

JIM VAN OS ,
PHILIPPE DELESPAUL ,
JOHANNA WIGMAN ,
INEZ MYIN-GERMEYS  and
MARIEKE WICHERS
JIM VAN OS*
Affiliation:
Department of Psychiatry and Psychology, School of Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, The Netherlands King's College London, King's Health Partners, Department of Psychosis Studies, Institute of Psychiatry, UK
PHILIPPE DELESPAUL
Affiliation:
Department of Psychiatry and Psychology, School of Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, The Netherlands
JOHANNA WIGMAN
Affiliation:
Department of Psychiatry and Psychology, School of Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, The Netherlands
INEZ MYIN-GERMEYS
Affiliation:
Department of Psychiatry and Psychology, School of Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, The Netherlands
MARIEKE WICHERS
Affiliation:
Department of Psychiatry and Psychology, School of Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, The Netherlands
*
(Email: j.vanos@maastrichtuniversity.nl) [J. van Os]
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Abstract

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Psychological Medicine , Volume 43 , Issue 7 , July 2013 , pp. 1563 - 1567
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Copyright © Cambridge University Press 2013 

Introduction

George & Klijn (Reference George and Klijn2013) provide cogent arguments for a change in terminology regarding the syndrome that currently goes under the name of schizophrenia. A name change at this stage would introduce significant improvement, but can only be regarded as the first intermediate step towards the much more incisive final goal of a complete redesign of psychiatric diagnosis, guided by two important parameters. First, given that an alternative system of mechanism-based system of diagnosis, based on specific ‘biosignatures’, is still a long time away – if ever (Kapur et al. Reference Kapur, Phillips and Insel2012), a symptom-based approach will remain necessary for the foreseeable future. Second, given that diagnosis in medicine essentially refers to classification with (treatment and prognostic) utility, this should be the guiding principle for any diagnostic system, with a focus on reduction of suffering and incapacity of those who seek our care (Pies, Reference Pies2012). In the following, we will describe, within these parameters, three requirements for a novel system of diagnosis in psychiatry based on (i) the need for a more individualized approach, based on causal influences in symptom circuits (precision diagnosis), (ii) the need to take into account the fact that symptoms reflect responses to context (context diagnosis), and (iii) the need to take into account that syndromes develop over time and have recognizable stages of expression (staging diagnosis) (Fusar-Poli et al. Reference Fusar-Poli, Yung, McGorry and van Os2013).

The principle of contextual precision diagnosis

The main problem with psychiatric diagnosis is that groups identified by a common label, for example schizophrenia, in fact have little in common. The level of heterogeneity in terms of psychopathology, need for care, treatment response, illness course, cognitive vulnerabilities, environmental exposures and biological correlates is so great that it becomes implausible that these labels can provide much clinical utility. In spite of this, disorders continue to be stereotypically depicted as homogeneous. A case in point is the diagnosis of schizophrenia, which in prestigious scientific journals typically is described homogeneously in line with its early twentieth century asylum origins as a ‘devastating brain disease’ or similar stereotype (Sawa & Snyder, Reference Sawa and Snyder2002; Corfas et al. Reference Corfas, Roy and Buxbaum2004; Walsh et al. Reference Walsh, McClellan, McCarthy, Addington, Pierce, Cooper, Nord, Kusenda, Malhotra, Bhandari, Stray, Rippey, Roccanova, Makarov, Lakshmi, Findling, Sikich, Stromberg, Merriman, Gogtay, Butler, Eckstrand, Noory, Gochman, Long, Chen, Davis, Baker, Eichler, Meltzer, Nelson, Singleton, Lee, Rapoport, King and Sebat2008; Esslinger et al. Reference Esslinger, Walter, Kirsch, Erk, Schnell, Arnold, Haddad, Mier, Opitz von Boberfeld, Raab, Witt, Rietschel, Cichon and Meyer-Lindenberg2009; McDannald et al. Reference McDannald, Whitt, Calhoon, Piantadosi, Karlsson, O'Donnell and Schoenbaum2011; Rico, Reference Rico2012). Patients receiving the diagnosis of schizophrenia are thus exposed to pressure to conform to an identity that is compatible with this stereotype, resulting in a strong desire to ‘recover’ from this experience.

Although a name change likely would provide some relief in the short term, it does not address the underlying problem of low utility associated with extensive heterogeneity within the label. In other areas of medicine, unexplained heterogeneity is being addressed by the introduction of precision (or personalized) diagnosis. For example, blood pressure, plasma glucose, cardiac rhythm, EEG, muscle tone and other somatic outcomes can now be monitored in daily life, allowing for a diagnosis that yields individualized information about the pattern of variation of the parameter in question in response to daily life circumstances. This diagnostic information is precise, as it reflects highly personal patterns of variation, and it is contextual, as it traces variation to daily life circumstances of, for example, stress, sleep, medication and life style. This not only enables precise indexing of treatment needs (diagnosis), but also precise monitoring of treatment response (prognosis). A similar system of contextual precision diagnosis may be useful in psychiatry.

Precision: diagnosing mental causation in symptom circuits

How can diagnosis based on psychopathology be individualized? To date, the most commonly used attempt at individualization is based on assigning individuals to diagnostic categories, in combination with personalised ratings of psychopathology across different dimensions. In theory, this system of ‘dimensionalized categories’ ought to yield acceptable precision, given that two individuals within the same diagnostic category will nearly always have different psychopathological profiles. While attractive, recent research nevertheless indicates that it is based on the false premise that symptoms always vary together as a function of a latent underling dimension or category – which does not appear to be the case (Kendler et al. Reference Kendler, Zachar and Craver2010; Borsboom et al. Reference Borsboom, Cramer, Schmittmann, Epskamp and Waldorp2011). Instead, it has been argued that mental ‘disorders’ in fact may represent sets of symptoms that are connected through a system of causal relations that may explain individualized co-occurrence of different symptoms (Cramer et al. Reference Cramer, Waldorp, van der Maas and Borsboom2010; Kendler et al. Reference Kendler, Zachar and Craver2010). For example, the negative and positive symptoms of schizophrenia have largely independent courses (Eaton et al. Reference Eaton, Thara, Federman, Melton and Liang1995) and aetiological factors appear to operate at the symptom level rather than the diagnostic disorder level (Bentall et al. Reference Bentall, Wickham, Shevlin and Varese2012; Cramer et al. Reference Cramer, Borsboom, Aggen and Kendler2012; Linscott & van Os, Reference Linscott and van Os2012). Therefore, there is increasing interest in how multiple symptoms in individuals arise not as a function of a latent construct, but as a function of symptoms impacting on each other, for example insomnia impacting on depressive symptoms (Sivertsen et al. Reference Sivertsen, Salo, Mykletun, Hysing, Pallesen, Krokstad, Nordhus and Overland2012) or on paranoia (Freeman et al. Reference Freeman, Pugh, Vorontsova and Southgate2009), depressive symptoms clustering with anxiety symptoms (Kendler & Gardner, Reference Kendler and Gardner2011), affective disturbance impacting on psychosis (Garety et al. Reference Garety, Kuipers, Fowler, Freeman and Bebbington2001; Myin-Germeys & van Os, Reference Myin-Germeys and van Os2007), and hallucinations impacting on delusions (Maher, Reference Maher2006; Smeets et al. Reference Smeets, Lataster, Dominguez, Hommes, Lieb, Wittchen and van Os2012). Not only between-symptom dynamic relationships have been described, intra-symptom temporal dynamics resulting in persistence are also important. For example, intra-symptom dynamics over time, in the form of intra-symptom feedback loops, have been described in the area of psychosis, in the form of psychotic experiences impacting on persistence of such experience over time, both at the momentary ‘micro-level’ over the course of a single day in daily life (Wigman et al. Reference Wigman, Collip, Wichers, Delespaul, Derom, Thiery, Vollebergh, Lataster, Jacobs, Myin-Germeys and van Os2013a), or over the course of months or years (Dominguez et al. Reference Dominguez, Wichers, Lieb, Wittchen and van Os2011; Wigman et al. Reference Wigman, van Winkel, Raaijmakers, Ormel, Verhulst, Reijneveld, van Os and Vollebergh2011), under the influence of genetic and non-genetic risk factors (Mackie et al. Reference Mackie, Castellanos-Ryan and Conrod2011; Kuepper et al. Reference Kuepper, van Os, Lieb, Wittchen, Hofler and Henquet2011; Wigman et al. Reference Wigman, Collip, Wichers, Delespaul, Derom, Thiery, Vollebergh, Lataster, Jacobs, Myin-Germeys and van Os2013a).

The notion that traditional diagnostic categories and dimensions need to be transformed to represent the dynamics of symptoms impacting on each other over time in a model of ‘mental causation’ is tantalizing. It implies that special methodology is required to collect repeated measures of symptoms over time in the flow of daily life, both at the momentary level and over more extended periods (Myin-Germeys et al. Reference Myin-Germeys, Oorschot, Collip, Lataster, Delespaul and van Os2009). This type of information allows for a detailed analysis and systematic presentation (Epskamp et al. Reference Epskamp, Cramer, Waldorp, Schmittmann and Borsboom2012) of how symptoms impact each other (Cramer et al. Reference Cramer, Waldorp, van der Maas and Borsboom2010; Kendler et al. Reference Kendler, Zachar and Craver2010; Wigman et al. Reference Wigman, van Os, Thiery, Derom, Collip, Jacobs and Wichers2013b).

Context: diagnosing environmental reactivity

Although it is widely believed that mental disorders have their origin in altered cerebral function, disease categories as defined in DSM and ICD do not map on to what the brain actually does: mediating the continuous flow of meaningful perceptions of the social environment that guide adaptive behaviour. The use of ex-cathedra static diagnostic categories appears distal from the neural circuits that mediate dynamic adaptation to social context.

Therefore, reformulation of the basic psychopathological unit towards capturing dynamic reactivity, modelled on the role of neural circuits in mediating adaptive functioning to social context, may be productive in the context of diagnosis. Momentary assessment technology phenotypes capturing dimensional variation in mental states [typically assessed as continuous variables, using Likert scales, in the Experience Sampling Method (ESM)] in response to other mental states in the symptom circuit on the one hand, and environmental variation on the other, are well placed to fill these requirements (Fig. 1), resulting in a diagnosis that is both contextual and precise. It is proposed that momentary assessments of contextual symptom circuits, using the ESM, will provide a fertile phenotype for investigation of psychopathology, encompassing phenotypes at multiple levels of neurofunctional organization (Yordanova et al. Reference Yordanova, Kolev, Kirov and Rothenberger2010). For example, momentary assessment technology studies of exposure to early trauma in humans have yielded replicated evidence that early environmental exposures predict altered momentary response to stress in adulthood that increase the risk of mental disorder (Glaser et al. Reference Glaser, van Os, Portegijs and Myin-Germeys2006; Wichers et al. Reference Wichers, Schrijvers, Geschwind, Jacobs, Myin-Germeys, Thiery, Derom, Sabbe, Peeters, Delespaul and van Os2009; Lardinois et al. Reference Lardinois, Lataster, Mengelers, van Os and Myin-Germeys2011). There is a suggestion that these ESM phenotypes of behavioural sensitization (Myin-Germeys et al. Reference Myin-Germeys, Delespaul and van Os2005a) can be linked to biological models of sensitization (Myin-Germeys et al. Reference Myin-Germeys, Marcelis, Krabbendam, Delespaul and van Os2005b; Collip et al. Reference Collip, Myin-Germeys and van Os2008), thus suggesting that the momentary environmental reactivity may represent a key variable in linking mental and neurobiological phenotypes (van Os et al. Reference van Os, Kenis and Rutten2010). Also, several ESM mental state measures have shown that connections between momentary mental states and environments are sensitive to genetic effects, not just in terms of heritability and familial resemblance (Jacobs et al. Reference Jacobs, Rijsdijk, Derom, Vlietinck, Delespaul, van Os and Myin-Germeys2006; Menne-Lothmann et al. Reference Menne-Lothmann, Jacobs, Derom, Thiery, van Os and Wichers2012), but particularly in terms of the genetics underlying environmental sensitivity (Myin-Germeys et al. Reference Myin-Germeys, van Os, Schwartz, Stone and Delespaul2001; van Winkel et al. Reference van Winkel, Henquet, Rosa, Papiol, Fananas, De Hert, Peuskens, van Os and Myin-Germeys2008; Wichers et al. Reference Wichers, Aguilera, Kenis, Krabbendam, Myin-Germeys, Jacobs, Peeters, Derom, Vlietinck, Mengelers, Delespaul and van Os2008a,Reference Wichers, Kenis, Jacobs, Myin-Germeys, Schruers, Mengelers, Delespaul, Derom, Vlietinck and van Osb; Lataster et al. Reference Lataster, Wichers, Jacobs, Mengelers, Derom, Thiery, van Os and Myin-Germeys2009; Simons et al. Reference Simons, Wichers, Derom, Thiery, Myin-Germeys, Krabbendam and van Os2009; Collip et al. Reference Collip, van Winkel, Peerbooms, Lataster, Thewissen, Lardinois, Drukker, Rutten, van Os and Myin-Germeys2011; Peerbooms et al. Reference Peerbooms, Rutten, Collip, Lardinois, Lataster, Thewissen, Rad, Drukker, Kenis, van Os, Myin-Germeys and van Winkel2012), a mechanism referred to as gene–environment interaction.

Fig. 1. Momentary assessment with the Experience Sampling Method (ESM). Experience sampling methodology showing the details of a single day in the ESM paradigm. At 10 random moments during the day, mental states (e.g. anxiety, low mood, paranoia, being happy) and contexts (stress, company, activity, drug use) are assessed. The arrows represent examples of prospectively analysing the impact of mental states and contexts on each other over time.

The nomenclature of contextual precision diagnosis in psychiatry

An example of contextual precision diagnosis is depicted in Fig. 2. ‘Diagnosis’ here refers to the visual display of causal relationships between symptoms and environment (in the example: stress) in the circuit. The circuit not only focuses on environment and symptoms, but also includes positive affective states, thus increasing therapeutic relevance. Previous work has shown that contextual precision diagnosis is highly sensitive to longitudinal development of phenotypes across definable stages, in that connection strength and connection variability between mental states differ in a predictable fashion across different stages of psychopathology (Wigman et al. Reference Wigman, van Os, Thiery, Derom, Collip, Jacobs and Wichers2013b).

Fig. 2. Contextual precision diagnosis. Thicker lines indicate stronger associations. The (simulated) patient in this example did 6 days of experience sampling in order to determine circuit patterns of stress and mutually impacting mental states. The resulting causal circuit is depicted above. A strong positive feedback loop exists between positive states (relaxed and cheerful) and a negative feedback loop exists between the opposite mental states of being cheerful and being paranoid. Stress occasions paranoia and impacts negatively on cheerfulness. Being relaxed helps reducing low mood and anxiety. Both cheerfulness and paranoia have a strong tendency to persist over time, increasing the probability of stable symptoms (Wigman et al. Reference Wigman, Collip, Wichers, Delespaul, Derom, Thiery, Vollebergh, Lataster, Jacobs, Myin-Germeys and van Os2013a,b).

Contextual precision diagnosis is idiographic and sensitive to stages of psychopathology, replacing the need for nomothetic approaches that lack validity and practical utility (McGorry & van Os, Reference McGorry and van Os2013). Perhaps it may be useful to retain some of the higher order syndromal groupings, such as common mental disorder and severe mental disorder. The focus of contextual precision diagnosis, however, is on the individual, neutralizing the forces of stereotyping that George & Klijn wish to attenuate.

Declaration of Interest

None.

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Figure 0

Fig. 1. Momentary assessment with the Experience Sampling Method (ESM). Experience sampling methodology showing the details of a single day in the ESM paradigm. At 10 random moments during the day, mental states (e.g. anxiety, low mood, paranoia, being happy) and contexts (stress, company, activity, drug use) are assessed. The arrows represent examples of prospectively analysing the impact of mental states and contexts on each other over time.

Figure 1

Fig. 2. Contextual precision diagnosis. Thicker lines indicate stronger associations. The (simulated) patient in this example did 6 days of experience sampling in order to determine circuit patterns of stress and mutually impacting mental states. The resulting causal circuit is depicted above. A strong positive feedback loop exists between positive states (relaxed and cheerful) and a negative feedback loop exists between the opposite mental states of being cheerful and being paranoid. Stress occasions paranoia and impacts negatively on cheerfulness. Being relaxed helps reducing low mood and anxiety. Both cheerfulness and paranoia have a strong tendency to persist over time, increasing the probability of stable symptoms (Wigman et al.2013a,b).