Diagnosis and causal explanation in psychiatry

Abstract

In clinical medicine, a diagnosis can offer an explanation of a patient's symptoms by specifying the pathology that is causing them. Diagnoses in psychiatry are also sometimes presented in clinical texts as if they pick out pathological processes that cause sets of symptoms. However, current evidence suggests the possibility that many diagnostic categories in psychiatry are highly causally heterogeneous. For example, major depressive disorder may not be associated with a single type of underlying pathological process, but with a range of different causal pathways, each involving complex interactions of various biological, psychological, and social factors. This paper explores the implications of causal heterogeneity for whether psychiatric diagnoses can be said to serve causal explanatory roles in clinical practice. I argue that while they may fall short of picking out a specific cause of the patient's symptoms, they can nonetheless supply different sorts of clinically relevant causal information. In particular, I suggest that some psychiatric diagnoses provide negative information that rules out certain causes, some provide approximate or disjunctive information about the range of possible causal processes, and some provide causal information about the relations between the symptoms themselves.

Full text

Diagnosis and causal explanation in psychiatry
Hane Htut Maung
Department of Politics, Philosophy, and Religion, Lancaster University, Lancaster, LA1 4YL, United Kingdom
article info
Article history:
Received 22 January 2016
Received in revised form
8 September 2016
Keywords:
Psychiatry
Diagnosis
Causal explanation
Causal heterogeneity
Major depressive disorder
abstract
In clinical medicine, a diagnosis can offer an explanation of a patient’s symptoms by specifying the
pathology that is causing them. Diagnoses in psychiatry are also sometimes presented in clinical texts as
if they pick out pathological processes that cause sets of symptoms. However, current evidence suggests
the possibility that many diagnostic categories in psychiatry are highly causally heterogeneous. For
example, major depressive disorder may not be associated with a single type of underlying pathological
process, but with a range of different causal pathways, each involving complex interactions of various
biological, psychological, and social factors. This paper explores the implications of causal heterogeneity
for whether psychiatric diagnoses can be said to serve causal explanatory roles in clinical practice. I argue
that while they may fall short of picking out a specific cause of the patient’s symptoms, they can
nonetheless supply different sorts of clinically relevant causal information. In particular, I suggest that
some psychiatric diagnoses provide negative information that rules out certain causes, some provide
approximate or disjunctive information about the range of possible causal processes, and some provide
causal information about the relations between the symptoms themselves.
Ó2016 The Author. Published by Elsevier Ltd. This is an open access article under the CC BY license
(http://creativecommons.org/licenses/by/4.0/).
1. Introduction
When a patient presents to the clinic with a set of symptoms,
one of the physician’s tasks is to make a diagnosis that explains
these symptoms. In somatic medicine, the diagnosis usually fulfils
this explanatory role by indicating the cause of the patient’s
symptom presentation (Cournoyea & Kennedy, 2014; Schwartz &
Elstein, 2008). For example, the diagnosis of myocardial infarction
(MI) explains a patient’s chest pain by indicating that the cause is
ischaemic necrosis of the myocardium. This model of causal
explanation suggests essentialism regarding disease kinds,
whereby a diagnosis is taken to pick out a “disease entity”that can
be a treated as a distinctive cause (Hucklenbroich, 2014). Moreover,
this cause is taken to be invariant across cases, such as the diagnosis
of MI referring to a causative pathology, ischaemic necrosis of the
myocardium, which is instantiated by every case of MI.
The essentialistic thinking associated with this model of causal
explanation continues to influence modern conceptions of psy-
chiatric diagnoses (Haslam, 2014; Hyman, 2010). For example, the
following passage from a psychiatric textbook characterises major
depressive disorder (MDD) as a distinctive kind of disease that can
cause the symptom of depression:
Depression is more common in older people than it is in the
general population. Various studies have reported prevalence
rates ranging from 25 to almost 50 percent, although the per-
centage of these cases that are caused by major depressive
disorder is uncertain. (Sadock & Sadock, 2008, p.215)
A popular health information website does so similarly with
generalised anxiety disorder (GAD):
GAD is a long-term condition that causes you to feel anxious
about a wide range of situations and issues, rather than one
specific event. (NHS Choices, 2016)
Similarly again, the following passage from a research paper on
chronic fatigue syndrome (CFS) suggests that MDD refers to a
distinctive disease that can explain fatigue symptoms:
When a well-recognized underlying condition, such as primary
depression, could explain the subject’s symptoms, s/he was
classified as having “CFS-explained”.(Jason et al., 2014, p.43)
These sorts of characterisations are not surprising when we
consider psychiatry’s status as a medical discipline. As noted by
Poland (2014, pp. 31e33), psychiatric practice occurs in a context
shaped by medical roles and traditions. Hence, as in other medical
E-mail address: h.maung@lancaster.ac.uk.
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Studies in History and Philosophy of Biological and Biomedical Sciences 60 (2016) 15e24

disciplines, disorders in psychiatry are treated as distinctive disease
kinds that can be invoked in causal explanations of patients’
symptoms.
However, there are reasons to suspect that such essentialistic
thinking may be misplaced in psychiatry. At present, it is unclear
whether many of our current diagnostic categories actually do pick
out stable and distinctive causes. Studies on the genetics and
neurochemistry of psychiatric disorders have tended to indicate
high degrees of heterogeneity, and while recent advances in
cognitive neuroscience and functional neuroimaging have yielded
compelling insights into the mechanisms involved in psychopa-
thology, it is disputed whether they on their own could supply
individual disease definitions (Hyman, 2010, p. 171). Therefore, we
need to at least consider the possibility that many of the major
psychiatric disorders could turn out to be causally heterogeneous at
every level of analysis (Kendler, 2012; Murphy, 2006; Poland, von
Eckhardt, & Spaulding, 1994).
If it does turn out to be the case that psychiatric diagnoses
cannot be understood essentialistically, then this would cast doubt
on whether such diagnoses genuinely are of any causal explanatory
value in clinical practice. This is not only an epistemological prob-
lem for philosophers, but is relevant to psychiatric researchers and
practitioners. First, it calls into question the validity of our current
diagnostic classification in psychiatry. That is, if it turns out that our
current diagnostic categories do not represent distinctive disease
kinds, then it is questionable whether they can be used to support
inductive inferences and formulate laws (Cooper, 2005). Second, as
argued by Haslam, the essentialisation of psychiatric disorders can
encourage harmful stigma “because it represents sufferers as
categorically abnormal, immutably afflicted, and essentially
different”(Haslam, 2014, p. 25). Hence, if it turns out that diag-
nostic categories in psychiatry do not correspond to distinctive
causal essences, then there is a possibility that such essentialistic
conceptions of psychiatric disorders not only mislead patients, but
also harm them.
In light of these concerns, it is worth asking whether there are
other ways to think about the explanatory roles of diagnoses that
do not encourage problematic reification. This will be the focus of
this paper. I shall argue that even in the case that psychiatric di-
agnoses turn out to be causally heterogeneous at every level of
analysis, they can still provide information that is explanatorily
valuable in the clinical setting. Moreover, while these other forms
of explanation do not fit the standard model of causal explanation
whereby a diagnosis specifies a distinctive cause, I shall show that
they are nonetheless causal in satisfying ways.
The paper proceeds as follows. I begin in Section 2by dis-
tinguishing two types of explanatory question, which are the
explanation of a syndrome in general and the explanation of the
clinical presentation of a particular patient with appeal to a diag-
nosis. Using MDD as a case study, I explore the potential challenges
that psychiatric disorders pose for these explanatory questions.
While philosophers of psychiatry have offered promising ap-
proaches to the first kind of explanation that handle the challenges
of heterogeneity and multilevel complexity, these problems
continue to affect the second kind of explanation. Nonetheless, I
argue in Section 3that even though psychiatric diagnoses may turn
out not to pick out homogeneous causal essences, there are other
ways in which they might offer causal explanatory information. I
suggest that some can provide negative information that excludes
certain causes, some can provide partial explanations involving
possible causal processes, and some can provide information about
the causal relations between the symptoms themselves.
It should be made clear from the outset that my intention is not
to argue that MDD definitely is a heterogeneous phenomenon.
Rather, it is to explore the philosophical implications for the
explanatory role of the diagnosis if it were to turn out to be causally
heterogeneous. I use MDD as a case study, because it typifies a
scenario where, given our current incomplete understanding of the
causal processes involved, there remains a real possibility that
there is no single causal essence that defines the disorder. However,
even if it were to turn out that MDD is associated with a stable
causal structure, there are other psychiatric diagnoses that are
likely to be causally heterogeneous, and so my analysis of causal
explanation would still be applicable. For example, some re-
searchers suggest schizophrenia (Wheeler & Voineskos, 2014) and
bipolar disorder (Maletic & Raison, 2014) might turn out to be
causally heterogeneous.
2. Challenges for explanation in psychiatry
2.1. Two explanatory questions
Throughout this section, I use the example of MDD to highlight
some of the challenges facing explanation in psychiatry. Before I
turn to the case study, it is important to distinguish two kinds of
explanatory question regarding diagnoses in medicine (Thagard,
1999, p. 20). The first kind, which I henceforth call “disease
explanation”, belongs to medical research. This is the explanation
of a clinical syndrome in general. The goal here is to develop a
general model that brings together the relevant causal factors and
mechanisms responsible for the syndrome. For example, the dis-
order characterised by swollen limbs and bleeding gums known as
scurvy is explained by defective collagen synthesis due to ascorbic
acid deficiency (Thagard, 1999, pp. 120e122). The second kind of
explanation, which I henceforth call “diagnostic explanation”, oc-
curs in the context of clinical practice. This is where a patient
presents with such and such symptoms, and the physician makes a
diagnosis that explains these symptoms. Take the example
mentioned in Section 1of patient’s chest pain being explained by
the diagnosis of MI. Here, the explanandum is not the clinical syn-
drome in general, but the clinical presentation of the particular
patient.
These two explanatory questions are connected. In diagnostic
explanation, where a diagnosis is invoked to explain a patient’s
symptoms, the understanding of the disorder picked out by the
diagnosis comes from the general model that is constructed
through disease explanation. For example, disease explanation in-
forms us that MI in general involves rupture of an atherosclerotic
plaque and thrombus formation leading to occlusion of a coronary
artery and ischaemic necrosis of the myocardium, and it is in virtue
of this knowledge that the diagnosis of MI functions as a causal
explanation of the occurrence of chest pain in a particular patient.
Hence, what the general model of a disorder looks like has impli-
cations for the explanatory function of the diagnosis in the
particular case.
Much of the philosophical literature on explanation in psychi-
atry has focused on disease explanation, rather than diagnostic
explanation. Theorists have expressed concerns that high degrees
of heterogeneity and complexity could present significant chal-
lenges for developing comprehensive models of many major psy-
chiatric disorders (Hyman, 2010; Murphy, 2006; Poland, 2014).
However, as we shall see, this also has implications for diagnostic
explanation. Note that it is not so much the heterogeneity of
symptoms that is the problem, as many medical disorders that have
been successfully modelled can present in several different ways.
For example, syphilis has protean manifestations, which can
include ulceration, gastric dysmotility, cardiac disease, and paresis,
but these many different manifestations are unified by a singular
cause, namely Treponema pallidum infection. Rather, the concerns
H.H. Maung / Studies in History and Philosophy of Biological and Biomedical Sciences 60 (2016) 15e2416

are about the heterogeneity with respect to causes. Let us now turn
to the case of MDD to illustrate these concerns.
2.2. Heterogeneity and complexity in major depressive disorder
Research on the genetics associated with MDD suggests that
while genes increase vulnerability to MDD, environmental factors
remain aetiologically more important.
1
Several environmental
factors have been established as being causally relevant, including
poor parenting, sexual abuse, and stressful life events, but these
vary across individuals (Kendler, Gardner, & Prescott, 2002).
Regarding psychological factors, certain aspects of personality, such
as neuroticism, have been correlated with vulnerability to MDD,
but these are non-specific(Kendler, Gatz, Gardner, & Pedersen,
2006). And so, there is much evidence to suggest that the distal
causes of MDD are highly heterogeneous.
However, it could be argued that heterogeneity with respect to
such distal causes is not by itself problematic for disease explana-
tion, because many medical disorders that have been successfully
modelled have multiple risk factors. For example, distal causes for
MI include genetic vulnerabilities, hypertension, obesity, smoking,
and psychological stress, which vary significantly across cases.
Nonetheless, these all converge onto a singular proximal cause,
ischaemic necrosis of the myocardium, which is a defining feature
of every case of MI. This suggests that we also need to look at
whether the proximal causes of psychiatric disorders are hetero-
geneous. Two prominent neurochemical hypotheses regarding
MDD are the monoamine hypothesis (Schildkraut, 1965) and the
hypothalamic-pituitary-adrenal (HPA) axis hypothesis (Arborelius,
Owens, Plotsky, & Nemeroff, 1999). These posit that depressive
symptoms are caused by underactive serotonin (5-HT) neuro-
transmission and HPA axis dysregulation, respectively. While there
is evidence that such neurochemical abnormalities are involved in
many cases of MDD, research suggests that they are far from being
universal.
2
Therefore, they cannot be considered to be the defining
essences of MDD.
Researchers have also investigated mechanisms at the level of
brain circuitry. Using positron emission tomography (PET) and
functional magnetic resonance imaging (fMRI) techniques, people
with MDD were found to exhibit changes in the activation of the
subgenual anterior cingulate cortex (ACC), which is an area of the
brain that constitutes part of a circuit involved in emotional pro-
cessing (Drevets et al., 1997; Groenewold, Opmeer, de Jonge,
Aleman, & Costafreda, 2013; Mayberg et al., 1999). These results
suggest that altered activity of the brain circuitry involved in
emotional processing is associated with some of the affective
symptoms of MDD. However, while significant, the findings are not
universal. For example, a subsequent review by Drevets, Savitz, and
Trimble (2008) notes that MDD patients who had first-degree
relatives with mania, alcoholism, or sociopathy did not differ from
healthy controls with respect to subgenual ACC metabolism or
volume.
3
Therefore, there still seems to be variability regarding the
brain mechanisms among patients with the diagnosis of MDD.
4
Another concern that further compounds the problem of het-
erogeneity is that it is contested whether conceptualising MDD
exclusively at the level of brain mechanisms is sufficient for un-
derstanding some of the key features of its psychopathology. It is
sometimes claimed that brain mechanisms are of utmost interest
because they are the proximal causes of behaviour. However, there
is no a priori reason to suppose that diseases must be defined by
their most proximal causes. Furthermore, applying this neuro-
centrism universally can lead to trivial conclusions. For example,
consider a patient presenting with a cough. Strictly speaking, the
proximal cause of the cough qua behaviour is a neurological
mechanism, namely the stimulation of the medulla by afferent fi-
bres in the vagus nerve leading to the subsequent firing of efferent
fibres that innervate the respiratory muscles. While this may be
true, it is too trivial to be of explanatory significance in the clinic.
Rather, we want a diagnosis to capture the causal process, albeit a
less proximal one, that is perpetuating this neurological mecha-
nism, such as a tumour, infection, inflammation, or cardiogenic
pulmonary oedema, partly because this tells us where we can
therapeutically intervene.
Similarly, in the case of a psychiatric disorder like MDD, the
symptoms may indeed be mediated by proximal neurological
mechanisms, but conceptualising the disorder exclusively at the
level of these neurological mechanisms risks explanatory triviality,
because it leaves out crucial information regarding the joint
contribution of the other causal processes on which the mainte-
nance of these neurological mechanisms is contingent and, more-
over, on which it may be possible to intervene therapeutically. As
with the cough example, it could be argued that an explanatory
model of MDD would need to capture these processes to be of
clinical value. Some theorists propose that such causal processes
need not be restricted to internal physiological processes but could
also include external social processes, on the grounds that these
may be processes that are actively perpetuating the patient’s con-
dition (Broome & Bortolotti, 2009; Fuchs, 2012; Zachar & Kendler,
2007).
5
And so, we need to take seriously the idea that psychiat-
ric disorders can only be comprehensively understood as complex
processes involving the interactions of causes across multiple levels
(Kendler, 2012; Mitchell, 2008; Murphy, 2008).
The upshot of this subsection, then, is twofold. First, there is a
possibility that MDD could turn out to be heterogeneous with
respect to its proximal mechanisms and distal causes. Second, there
are reasons to suppose that MDD cannot be aetiologically defined at
1
Data from family, twin, and adoption studies indicates a heritability of
approximately 37% (Sullivan, Neale, & Kendler, 2000). Moreover, association studies
suggest that this heritable component is not attributable to a single gene, but to the
combined effect of many genes, each with a small effect size (Shyn & Hamilton,
2010).
2
For example, it has been estimated that up to 50% of cases of MDD are not
associated with HPA axis dysregulation (Cowen, 2002; Palazidou, 2012) and it has
been suggested that up to two thirds of cases of MDD may not be related to un-
deractive 5-HT neurotransmission (Belmaker & Agam, 2008).
3
Similarly, a review by Roiser et al. (2012) suggests that some patients with MDD
have abnormal ACC activation during emotional processing while other patients
have normal baseline ACC activation, with the former group showing most
improvement with pharmacological treatment and the latter showing most
improvement with psychological therapy. While this has potential prospects for
treatment selection, it rests on the finding that there is variability of brain mech-
anisms among patients with the diagnosis of MDD.
4
The variability of brain mechanisms across cases is further highlighted in a
meta-analysis by Graham et al. (2013),whofind several different brain areas to be
associated with MDD, including the occipital cortex, insula, supplementary motor
cortex, and the cerebellum, as well as finding contradictory data regarding the
activity of the right amygdala. In their conclusion, the authors note that it is not
clear that a single neurological model can be applied to all cases of MDD, but
disaggregation of clinical subtypes may require different models. There are also
other reviews that suggest differences in the neurobiological correlates of different
groups of people with MDD (Baumeister and Parker, 2012; Kaufman, Martin, King,
& Charney, 2001).
5
Fuchs (2012) argues that psychopathology cannot be understood as being de-
tached from the interpersonal context, because the intrapersonal and interpersonal
processes involved are continually intertwined in relations of “horizontal circular
causality”.Broome & Bortolotti, (2009) argue that psychiatric symptoms often have
intentional content whose meaning is supervenient on the social context in which
the patient is situated, and that a description which is exclusively in terms of
neurological mechanisms cannot account for the variance in this intentional
content.
H.H. Maung / Studies in History and Philosophy of Biological and Biomedical Sciences 60 (2016) 15e24 17

any single level, but can only be understood by considering the
causal processes that interact across levels. The following sub-
sections look at the implications for disease explanation and
diagnostic explanation in psychiatry.
2.3. Idealisation and pluralism in disease explanation
If concerns discussed in subsection 2.2 are genuine, then it
would seem that a psychiatric disorder like MDD cannot be
modelled essentialistically. The question, then, is how we can
possibly construct a general model of the disorder given the
problems posed by causal heterogeneity and multilevel complexity.
Theorists have proposed idealisation (Murphy, 2006) and explan-
atory pluralism (Kendler, 2012; Mitchell, 2008) as solutions to these
two problems, respectively.
In response to the problem of heterogeneity, Murphy (2006)
suggests what when we try to explain a syndrome in general,
what we are aiming to explain is an exemplar, which is an idealised
theoretical representation of the syndrome. An exemplar qua ide-
alisation is abstracted away from the idiosyncrasies of individual
patients. Given the high degree of variability between cases of a
given diagnosis, different patients may resemble the exemplar in
different respects and to varying degrees. According to Murphy, to
explain a syndrome is to model the various causal relations and
mechanisms that have been shown to contribute to the develop-
ment of the idealised syndrome described in the exemplar. Again,
such a model represents an idealised scenario, abstracted away
from the actual states of affair in particular cases. There may not be
a single causal factor in the model that is instantiated by every case
of the disorder and there may not be an actual case that instantiates
all of the causal relations described in the model.
In response to the problem of multilevel complexity, Mitchell
(2008) endorses a view called integrative pluralism, according to
which a satisfactory explanation of a complex system like a psy-
chiatric disorder requires the integration of causal components at
multiple levels of organisation. As noted by Murphy (2008), these
variables at different levels do not correspond to the same phe-
nomenon described in different ways, but correspond respectively
to different phenomena. Hence, it is insufficient to look for deter-
ministic regularities exclusively at a single level, because whatever
influence the variables at this level may have is heavily contingent
on the joint contribution of variables at other levels. In the case of
MDD, we might need to include information about genetic sus-
ceptibilities, neurochemical abnormalities, brain circuits, psycho-
logical vulnerabilities, social contextual factors, and the ways in
which these interact.
Similarly, Kendler (2012) endorses an empirically-based
pluralism. Given the diverse range of causal variables involved, he
argues that there is no single privileged level at which a psychiatric
disorder like MDD can be aetiologically defined. Rather, con-
structing a general model of the disorder requires the incorporation
of research from different disciplines. Kendler (2014) suggests two
philosophical approaches to causation that can guide this project.
The first is Woodward’s (2003) interventionist theory of causation,
which conceptualises causal factors as difference makers, without
placing ontological restrictions on the kinds of variable that can be
such difference makers. This allows the inclusion of different causal
factors regardless of the explanatory levels to which they belong.
The second is the mechanistic approach to causation advocated by
theorists such as Machamer, Darden, and Craver (2000), which
focuses on specifying the mechanisms via which the identified
difference makers interact to produce the clinical features of the
disorder.
And so, with respect to disease explanation in psychiatry, there
is recognition among contemporary theorists in the philosophy of
psychiatry that general explanatory models of disorders are ideal-
isations abstracted away from the heterogeneity of actual cases and
that they involve the integration of diverse kinds of causal variable
from different levels of organisation. However, significantly less has
been written in the philosophical literature about diagnostic
explanation in psychiatry. This is the focus of what is to follow.
2.4. Problems for diagnostic explanation
Idealisation and explanatory pluralism are promising strategies
for disease explanation in psychiatry. When we want to understand
what causes depressive symptoms in general, we can conjure up an
idealised general representation of the syndrome and model the
causal factors that are known to contribute to the phenomena
described in the representation. The resulting model can then
illuminate statistical generalisations and causal regularities at a
population level, in spite of the heterogeneity seen in individual
cases. However, I argue that heterogeneity remains problematic for
diagnostic explanation when we try to apply the model to the in-
dividual cases.
As noted in subsection 2.2, there is a possibility that a psychi-
atric disorder like MDD does not involve a single invariant pa-
thology that is instantiated in every case, but a vast range of diverse
factors, none of which is universally present across all cases. Hence,
as noted by Murphy, the same set of symptoms may be produced by
different sets of causes:
It seems unlikely that the same underlying causes explain an
irritable adolescent who sleeps late, diets frantically, and lies
around the house all day threatening to commit suicide on the
one hand, and a sad middle-aged man who can not settle down
to any of his normal hobbies, hardly sleeps, eats more and more,
can not make love to his wife, and feels worthless.
6
(Murphy,
2006, p.329)
Similarly, Mitchell (2008, p. 30) suggests that there may be
different routes leading to the same symptoms in different in-
dividuals. A general model of MDD, then, would need to represent
the multiple causal pathways that could be responsible for the
development of depressive symptoms.
This has implications for what sort of causal information the
diagnosis of MDD conveys when a patient who presents to the
clinic with mood symptoms is given the diagnosis. It would suggest
that the diagnosis does not unequivocally specifya distinct “disease
entity”that is responsible for the patient’s symptoms in the
particular case. Rather, it subsumes a range of possible causal
structures that could be instantiated by the patient. Another way to
interpret this is to say that MDD is a disjunctive category. Take C
1
,C
2
.C
n
to be the diverse causal variables that have been implicated in
its pathophysiology. These may interact in different combinations
to produce different underlying pathological states, P
1
¼{C
1
.C
x
},
P
2
¼{C
2
.C
y
}, .P
n
¼{C
n
.C
z
}, each of which can produce the
clinical syndrome that satisfies the diagnosis of MDD. Diagnosing a
particular patient with MDD, then, indicates that the underlying
state responsible for the patient’s symptoms could be P
1
or P
2
.P
n
,
but does not provide further causal discrimination beyond this.
6
There is evidence to support this. Neuroimaging studies indicate that late-onset
MDD is associated with cerebrovascular changes, a greater enlargement in the
lateral ventricles, and more white matter hyperintensities, while early-onset MDD
is associated with more hippocampal volume loss. Cognitive tests indicate that late-
onset MDD, in comparison to early-onset MDD, is associated with decreases in
executive function and processing speed (Hermann, Goodwin, & Ebmeier, 2007;
Baumeister and Parker, 2012).
H.H. Maung / Studies in History and Philosophy of Biological and Biomedical Sciences 60 (2016) 15e2418

Furthermore, different cases of MDD may need to be understood
with different theoretical frameworks. As noted in subsection 2.3,
the problem of multilevel complexity suggests that a general model
of the disorder needs to integrate different kinds of causal variable
(Kendler, 2012; Mitchell, 2008). With respect to individual cases, it
is possible that the different combinations of variables instantiated
by different patients with MDD may require different explanatory
perspectives. For example, cognitive, psychodynamic, and social
explanatory perspectives may be of more value for a patient with
psychosocial adversity and a history of childhood trauma, while
more emphasis may be placed on a neurobiological explanatory
perspective for a patient with late-onset depression characterised
by melancholic features.
This further supports the contention made by Poland et al.
(1994) that a psychiatric diagnosis like MDD lacks unity. Not only
can different patients diagnosed with MDD instantiate different
underlying causal structures, but these different causal structures
may need to be understood with appeal to different theoretical
frameworks. Poland (2014) argues that this lack of unifying
invariance makes the diagnostic categories in psychiatry poor tools
for clinical practice. He suggests that a psychiatric diagnosis does
not effectively contribute to serving important clinical functions
because it “leaves most of the important clinical assessment work
undone”(Poland, 2014, p. 35). By subsuming different patients with
diverse pathologies under the same category, a diagnosis masks
information about individual variation that could be important for
treatment selection and prognosis. For example, the undifferenti-
ated diagnosis of MDD does not discriminate between the patient
with a dramatic onset of melancholic symptoms, for whom a tri-
cyclic antidepressant and electroconvulsive therapy may be war-
ranted, and the patient with a history of trauma, for whom
psychotherapy may be more appropriate. Both patients would be
subsumed under the same category of MDD.
The above criticism paints a rather pessimistic picture of psy-
chiatric diagnoses. However, while I agree that the above
mentioned problems significantly impact the clinical roles of di-
agnoses in psychiatry, I do not go as far as to say that the diagnoses
contribute little or nothing of epistemic value to the clinical pro-
cess. In section 3, I argue that while psychiatric diagnoses may not
pick out specific causes, there are still ways in which they supply
causal information that is of explanatory value.
3. Other kinds of diagnostic explanation in psychiatry
3.1. Negative causal explanation
One sort of causal information that can be provided by a psy-
chiatric diagnosis is negative causal information. While a psychi-
atric diagnosis may not specify the precise causal process leading to
the patient’s symptom presentation, it nonetheless excludes
certain causes. To better understand how this works in clinical
practice, we need to look at the process of differential diagnosis,
which is where the physician considers multiple possible diagnoses
that could explain the patient’s symptoms before selecting the
diagnosis that best explains them. For example, after assessing a
patient with chest pain, a physician may consider gastro-
oesophageal reflux disease, pulmonary embolism, and MI as
possible causes, before inferring that MI is the correct diagnosis.
For MDD, other conditions to be considered in the differential
diagnosis include thyroid disorders, adrenal disorders, dementia,
cerebral tumours, nutritional deficiencies, drug or alcohol intoxi-
cation, and other psychiatric disorders. When assessing a patient
with depressive symptoms, it is recommended that he or she is
appropriately investigated for these conditions:
The workup should include tests for thyroid and adrenal func-
tions because disorders of both of these endocrine systems can
appear as depressive disorders. In substance-induced mood
disorder, a reasonable rule of thumb is that any drug a depressed
patient is taking should be considered a potential factor in the
mood disorder.
7
(Sadock & Sadock, 2008, p. 217).
In the fifth edition of the Diagnostic and Statistical Manual of
Mental Disorders, it is recommended that MDD should only be
diagnosed once these other medical diagnoses have been excluded:
Such symptoms count towards a major depressive diagnosis
except when they are clearly and fully attributable to a general
medical condition. (American Psychiatric Association, 2013,
p.164)
What this highlights is a the diagnosis of MDD is not made solely
on the basis of the relevant symptoms being present, but also re-
quires certain medical causes for the symptoms to be ruled out. A
patient who presents with depressive symptoms that turn out tobe
caused by a cerebral tumour would not be diagnosed with MDD,
because the diagnosis is excluded by the fact that the symptomsare
clearly and fully attributable to a general medical condition. In
virtue of this exclusion criterion, then, a psychiatric diagnosis
provides information about what is not in the causal history of the
patient’s clinical presentation. A diagnosis of MDD may not pick out
a specific cause of the patient’s mood symptoms, but it does suggest
that they are not being caused by hypothyroidism, drug intoxica-
tion, a tumour, and so on.
Lewis (1986) argues that this exclusion of causes still qualifies as
a legitimate sort of causal explanation. According to his account of
causal explanation, “to explain an event is to provide some infor-
mation about its causal history”(Lewis, 1986, p. 217). This does not
necessarily entail specifying a cause of the event, as there are other
kinds of information one can give about an event’s causal history,
including information about what is not in its causal history. For
Lewis (1986, p. 222), negative causal information can still be
explanatorily relevant information, and so a psychiatric diagnosis
can be explanatorily relevant by excluding certain causes, even if it
does not itself cite a specific cause.
Beebee (2004) offers a modal analysis of how negative causal
information can be explanatorily relevant. She argues that infor-
mation about the absence of an event provides information about
the causal processes in counterfactual worlds where that event
occurs. For example, consider that Flora normally waters the or-
chids regularly, but forgets on one occasion. According to Beebee,
Flora’s failure to water the orchids cannot be a cause, because it
does not denote an event, but rather the absence of an event.
Nonetheless, we still accept Flora’s failure to water the orchids as an
explanation of the orchids dying. This is because it provides infor-
mation about the causal histories of the nearby possible worlds
where Flora had not failed to water the orchids and how these
causal histories differ from the causal history of the actual world. In
these counterfactual worlds, the causal processes would have
ensued in such a way that the orchids would have survived.
7
This is not to say that extensive investigations are always performed whenever
a patient presents with mood symptoms. Some conditions may be implicitly
excluded due to their unlikelihood in the patient’s demographic group, such as a
cerebral tumour in a young and otherwise healthy patient with mild depressive
symptoms. However, it is normally the case that a patient presenting to secondary
care with new affective or psychotic symptoms would at least have blood and urine
tests to exclude certain common conditions before a psychiatric diagnosis is
established.
H.H. Maung / Studies in History and Philosophy of Biological and Biomedical Sciences 60 (2016) 15e24 19

It is worth acknowledging that Beebee’s analysis focuses spe-
cifically on the roles of absences in causal explanations, and so is
not wholly analogous with my example of diagnostic explanation in
psychiatry. Nonetheless, it highlights the general point that a causal
explanation does not have to cite a specific cause, but can provide
modal information about the possible causal histories of the
explanandum. I suggest that a similar modal analysis can be applied
to other cases of negative causal information, including diagnoses
in psychiatry. By indicating that the patient’s mood symptoms are
not attributable a general medical disorder, the diagnosis of MDD is
providing information about what would have been expected in the
counterfactual worlds where the patient’s mood symptoms are
attributable to a general medical disorder. For example, in the
actual world, the physician might only diagnose a patient with
MDD after a thyroid function test yields a normal result, which
suggests that the result from the thyroid function test would have
been abnormal in the possible world where the patient is not
diagnosed with MDD due to his or her mood symptoms being
attributable to a thyroid disorder.
This negative causal explanation can be valuable in the clinical
setting. First, it has utility in predicting outcomes and guiding
therapeutic interventions. Indicating that a patient’s mood symp-
toms are not due to hypothyroidism suggests that levothyroxine
supplementation would not be a therapeutically effective inter-
vention and indicating that they are not due to a cerebral tumour
suggests that neurosurgical referral is not required. Hence, by
excluding these causes, a diagnosis of MDD can inform clinical
decisions. Second, even if it does not specify precisely what is
causing his or her symptoms, a psychiatric diagnosis can offer relief
and reassurance by ruling out certain medical diagnoses. For
example, when the family of a patient with a new onset of anhe-
donia, poor concentration, and psychomotor retardation want to
know why the patient has these symptoms, they may find it
extremely valuable to know that the symptoms are not caused by a
cerebral tumour or a neurodegenerative disease.
8
This account of negative causal explanation, then, suggests that
a psychiatric diagnosis does not need to identify a specific disease
kind to be of causal explanatory value, but can be explanatorily
valuable in virtue of the exclusion criterion that states that the
symptoms must not be attributable to a general medical disorder.
As noted by Beebee (2004),“Ebecause C”is not equivalent to “C
causes E”. Hence, the causal claim “the patient’s mood symptoms
are caused by MDD”may indeed be misguided, we can still legiti-
mately make the explanatory claim “the patient has mood symp-
toms because of MDD”.
However, in spite of the usefulness of negative information in
the clinical setting, the account of diagnostic explanation presented
here has limits. One problem is that it sets the standard for an
acceptable causal explanation too low. If all that is needed for a
causal explanation is information about what is not the cause of the
explanandum, then all sorts of claims that we would not normally
consider to be explanations would qualify as causal explanations.
For instance, “not tuberculosis”would count as a causal explana-
tion of a patient’s chronic cough according to the negative causal
explanation account. In response, one could propose that the
strength of a negative causal explanation depends on how many
causal possibilities are excluded by the explanans. Hence, MDD is a
better explanation than “not tuberculosis”, because the former
excludes several medical disorders while the latter only excludes
tuberculosis. Nonetheless, this would still relegate psychiatric di-
agnoses to the same controversial status as the so-called medically
unexplained syndromes, which also exclude several medical dis-
orders as causes of patients’symptoms yet are widely considered to
be explanatorily unsatisfactory (Cournoyea & Kennedy, 2014).
Another problem is that in practice there are many instances
where psychiatric diagnoses are made without other medical dis-
orders being excluded. In the above discussion, I have been
considering an idealised case of differential diagnosis where a pa-
tient presents with a new onset of mood symptoms and different
diagnoses are presented as possible explanations of the mood
symptoms. Here, the diagnoses of MDD, hypothyroidism, and drug
intoxication are presented as competing hypotheses, and the
diagnosis of MDD is only established when the other diagnoses
have been adequately excluded. However, there are also cases
where a psychiatric disorder is not considered as a competing
diagnosis, but as a comorbid diagnosis. For example, MDD is often
treated as an additional comorbid diagnosis in patients with mul-
tiple sclerosis (MS), even though it is recognised that in these cases
the depressive symptoms may be caused by the pathology associ-
ated with the MS (Marrie et al., 2009). Hence, in this sort of sce-
nario, the diagnoses of MDD fails to exclude MS from the causal
history of the patient’s mood symptoms.
And so, while psychiatric diagnoses do sometimes provide
valuable negative causal explanations, it is implausible that their
entire explanatory worth lies only in their providing negative in-
formation. In the following subsections, I argue that they can also
provide positive causal information. While these sorts of positive
causal information fall short of picking out the specific causative
pathologies in individual cases, they may nonetheless be explana-
torily valuable in the clinical context.
3.2. Disjunctive causal explanation
The claim that psychiatric diagnoses do provide some positive
causal information about patients’symptoms is corroborated by
the fact that we have at least some scientific knowledge of the
causal factors associated with certain disorders. As noted in
subsection 2.3, even though there is high heterogeneity among
cases MDD, we can seek to understand MDD in general by con-
structing an idealised model that is abstracted away from the idi-
osyncrasies of individual cases. Murphy (2014) argues that
although patients may differ from the idealisation in different re-
spects and to different degrees, the model can nonetheless provide
at least an approximation of the causal processes in the individual
case:
The bet is that real patients will be similar to the exemplar in
enough respects so that the explanation of the exemplar carries
over to the patient. We assume that within the individual there
are phenomena and causal relations that are relevantly similar
to those worked out for the exemplar, but we cannot expectvery
precise predictions. (Murphy, 2014,p.106)
The suggestion here is that while a psychiatric diagnosis qua
idealised generalisation may not specify the precise causal struc-
ture underlying the patient’s symptoms in a particular case, it does
tell us about processes that are approximately similar to the actual
causal processes in the patient’s case. Hence, Murphy argues that a
psychiatric diagnosis is explanatorily significant, because it gives us
at least a vague idea of the sort of process that is producing the
patient’s symptoms.
8
In this sense, the diagnosis of MDD might be compared to the diagnosis of non-
cardiac chest pain, which is a diagnosis that is made when a patient presents with
central chest pain but investigations reveal no evidence of cardiac disease. The
category does not pick out a specific disease kind, as it encompasses oesophageal,
pleuritic, and musculoskeletal pathologies, but it is explanatorily valuable because
it excludes cardiac causes of the chest pain.
H.H. Maung / Studies in History and Philosophy of Biological and Biomedical Sciences 60 (2016) 15e2420

However, I argue that things are more complicated than this.
While the above picture acknowledges the high degree of variation
between individuals, it rests on the assumption that cases of the
disorder nonetheless share a similar sort of causal process (Murphy,
2014, p. 106). As noted in subsection 2.2, though, it is possible that
there are different sets of causes leading to the same symptoms in
different individuals, and so a general model of the disorder would
need represent the different routes via which the syndrome can be
produced. For example, it is possible that depressive symptoms are
not caused by a single invariant pathology, but may be associated
with a disjunction of several underlying states, P
1
or P
2
.P
n
, each
produced by a different combination of interacting causal variables.
This might be viewed as problematic, because it is a matter of
contention whether or not such disjunctive information can
constitute an explanation. According to Kim (1998), it cannot. He
argues that information about a disjunction of possible causes does
not yield a single explanation with a disjunctive cause, but a
disjunction of different possible explanations of which the correct
explanation remains unknown. His example is the symptom of
joint pain, which can be caused by a number of different disorders,
including rheumatoid arthritis (RA) and systemic lupus erythe-
matosus (SLE). Consider that a patient with joint pain undergoes a
clinical test, the result of which suggests that he or she either has
RA or SLE, but does not indicate which. Kim argues that we do not
yet have an explanation of the patient’s joint pain:
I think there is a perfectly clear and intelligible sense in which
we don’t as yet have an explanation: what we have is a
disjunction of two explanations, not a single disjunctive expla-
nation. What I mean is this: we have two possible explanations,
and we know that one or the other is the correct one but not
which it is. What we have, I claim, is not an explanation with a
“disjunctive cause”, having rheumatoid arthritis or lupus. There
are no such “disjunctive diseases”.(Kim, 1998, p.108)
Kim further qualifies this by arguing that “RA or SLE”qua
disjunction does not specify a kind of event, and so is not eligible as
a cause. Because it is not eligible as a cause, it cannot then be
“citable as a cause in a causal explanation”(Kim, 1998, p. 109).
If Kim is right, then there is reason to suppose that MDD does
not offer a positive causal explanation of a patient’s mood symp-
toms, because it is associated with a range of many possible un-
derlying causal structures but does not specify which one is actually
the case in the patient. However, Kim’s criteria for explanation are
too restrictive. Even if a disjunctive category does not meet the
explanatory ideal of picking out a specific cause, I argue that it can
nonetheless provide some causal explanatory information. As
noted in subsection 3.1, it is not necessary to cite a specific cause of
an explanandum in order to provide explanatorily relevant infor-
mation about the explanandum’s causal history. For example, one
could give information about the possible causal histories within
which the explanandum’s actual causal history lies. I suggest that
this is the sort of information a disjunctive category provides.
We can highlight the explanatory relevance of a disjunctive
diagnosis by reframing the language in Kim’s example. Suppose we
say that the test result indicates that the patient has a multisystem
autoimmune disease. This is a heterogeneous category that in-
cludes RA and SLE. Hence, stating that the patient has a multi-
system autoimmune disease is equivalent to stating that that he or
she has the disjunction “RA or SLE .”without specifying which of
these disorders he or she actually has. Nonetheless, it is generally
agreed that indicating that the patient has a multisystem autoim-
mune disease is still explanatorily relevant with respect to his or
her joint pain (Rose & Mackay, 1985). Not only does it greatly nar-
row down the range of conditions in which the patient’s actual
condition could lie, but it also provides positive causal information
about the conditions that do fall within this range. The diagnosis of
multisystem autoimmune disease tells us that the patient’s joint
pain could be caused by the erosion of the joint surfaces in the case
of RA, or by systemic inflammation of the connective tissues in the
case of SLE, and so on.
A disjunctive diagnosis, then, does not specify the actual cause
of the patient’s symptoms, but it nonetheless subsumes the actual
cause within a tighter range of possible causal histories than
otherwise would have been available and, moreover, provides some
indication of the mechanisms involved in these possible causal
histories. This information indicates differences between the causal
histories of patients with the diagnosis and those of patients
without the diagnosis that can inform further investigations and
therapeutic interventions. For instance, stating that a patient has a
multisystem autoimmune disease suggests that his or her condition
is likely to respond to treatments that act on the immune system
and provides a rational basis for further investigations, such as
blood tests for specific autoantibodies, which can help specify
whether he or she actually has RA or SLE.
9
The above analysis accommodates the notion that a psychiatric
diagnosis qua disjunctive category could still provide explanatorily
valuable information about a patient’s symptoms, even if it does
not specify the precise cause of these symptoms. The diagnosis of
MDD, for instance, might be taken to suggest that the patient’s
symptoms could be due to a state involving underactive 5-HT
neurotransmission plus variables C
1
.C
n
, or by a state involving
HPA dysregulation plus variables C
2
.C
nþ1
, and so on. The
explanatory value of this disjunctive information is that it tells us
some of the ways in which the possible causal structures that could
be underlying the patient’s symptoms might differ from the causal
structure of the non-depressed state. In this sense, the explanatory
role of a psychiatric diagnosis like MDD may be more akin to that of
a superordinate category like multisystem autoimmune disorder
than to that of a specific medical diagnosis like RA.
However, while this analysis shows that disjunctiveness does
not necessarily preclude a diagnosis from being explanatory, it
could be argued that this explanatory value is also contingent on
other conditions. First, it is contingent on whether an exhaustive
list of disjuncts can be specified. The superordinate category of
cancer is explanatorily valuable, because we are able to specify the
different kinds of malignancy that fall under the category and have
impressive knowledge of their respective causal structures. By
contrast, we are far from being able to specify all the possible causal
structures that fall under the category of MDD, or indeed say how
many there are. As noted in subsection 2.2, we know a number of
the causal variables that can be associated with MDD, but we still
know very little about how different combinations of these vari-
ables interact to produce symptoms in individual cases.
Second, even if some of the disjuncts included in the category
could be specified, one might argue that the explanatory value of
the category is still contingent on whether we are capable of finding
out precisely which disjunct is involved in any given case. This
might be made possible with the discovery of biomarkers which
indicate specific causal factors that may be potential targets for
intervention. Recent neuroscientific data has suggested some po-
tential avenues for biomarker research, such as the review of fMRI
and PET studies by Roiser, Elliott, and Sahakian (2012), which found
9
Another example of such a category is cancer. This is highly disjunctive, as it
encompasses many different kinds of malignancy. Nonetheless, it is hard to deny
that it is of causal explanatory value, as it narrows down possible causal histories,
provides some indication of the mechanisms involved in these causal histories, and
informs investigations to further specify the diagnosis.
H.H. Maung / Studies in History and Philosophy of Biological and Biomedical Sciences 60 (2016) 15e24 21

differential responses to pharmacological treatment and psycho-
logical therapy for patients with and without abnormal ACC ac-
tivity. However, with respect to biomarker tests that could be
readily used in clinical practice, rather than just in the research
laboratory, psychiatry has fallen short of other medical specialties.
Hence, we may currently be in a situation where research can
discover various causal factors associated with a psychiatric disor-
der, but we cannot match them to individual patients in the clinic.
As a modest response to the above two concerns, a disjunctive
category could still provide causal explanatory information of a
statistical nature regarding the patient’s condition. Even if we
cannot specify all of the possible disjuncts that fall under the
category or find out which disjunct is involved in any given case,
the diagnosis still indicates an increased probability of the patient
having a given causal mechanism. For example, on the basis of the
knowledge that a proportion of people with MDD have underactive
5-HT neurotransmission, we can say that a given patient with a
diagnosis of MDD has an increased probability of having underac-
tive 5-HT neurotransmission. This might provide some justification
for a trial of antidepressant medication, which is presumed to exert
its action via 5-HT. However, it also needs to be acknowledged that
many similar probabilistic causal explanations in psychiatry may be
of little clinical value, because the diagnosis might turn out to be
too causally heterogeneous to have explanatory significance. The
number of disjuncts in the category may be so vast that there is only
a minute statistical association between each causal variable and
the disorder. Therefore, knowledge of such causal variables may, on
average, be statistically unhelpful in the guiding of treatment.
In summary, a disjunctive analysis accommodates the possibil-
ity of a heterogeneous diagnostic category being of causal explan-
atory value. However, this explanatory value is also dependent on
other considerations, including the extent of heterogeneity,
whether the disjuncts can be exhaustively specified, and whether
we are able to find out which causal variables are involved in any
given case. Given the ongoing challenges for research into causal
pathways and biomarkers in psychiatry, it must be conceded that at
present the positive causal explanatory value of a psychiatric
diagnosis qua disjunctive category is modest at best.
3.3. Causal networks of symptoms
The third sort of causal information a psychiatric diagnosis can
provide is information about the causal relations that occur be-
tween the symptoms and sustain them as a stable cluster. This
draws on a recent development in the study of psychopathology,
namely the symptom network approach to psychiatric disorders
advocated by Borsboom (2008) and Cramer, Waldorp, van der
Maas, and Borsboom (2010). According to this approach, a psychi-
atric disorder is conceptualised as a network of symptoms that
reinforce each other via causal relations. For example, in the case of
MDD, “fatigue may lead to a lack of concentration, which may lead
to thoughts of inferiority and worry, which may in turn lead to
sleepless nights, thereby reinforcing fatigue”(Cramer et al., 2010,
pp. 140e141).
By emphasising the causal relations between the symptoms
themselves, the symptom network approach accounts for why the
symptoms associated with a given psychiatric diagnosis tend to
cluster together in a statistically significant way, without the need
to invoke an underlying latent pathology as the cause of these
symptoms. Fatigue, poor concentration, worry, and sleepless nights
cluster together because they causally reinforce each other, not
because they are caused by a common underlying pathology.
Hence, by defining a psychiatric disorder at the level of its symp-
toms rather than at the level of underlying biological causal factors,
Borsboom and his colleagues can sidestep the problems of
heterogeneity and complexity that affect these underlying causal
factors.
Defining the disorder at the level of its symptoms has significant
implications for diagnostic explanation. In their commentary on
Cramer et al.’s (2010) paper, Hood and Lovett (2010) argue that a
logical consequence of excluding underlying causes from the con-
ceptualisation of a psychiatric disorder is that the disorder cannot
then function as a causal explanation of a patient’s symptoms. If
MDD, for example, is nothing over and above the symptoms of low
mood, anhedonia, fatigue, and so forth, then to invoke the diagnosis
of MDD as an explanation of why these symptoms occur in a
particular patient would be tautological. However, even if Hood and
Lovett are right in claiming that a disorder cannot be the cause of its
symptoms if it is nothing over and above these symptoms, I argue
that the symptom network approach enables a psychiatric diag-
nosis to provide causal information of a different sort. In particular,
it provides information about the above mentioned causal relations
between the symptoms themselves. It is in virtue of this causal
information that the symptom network approach distinguishes
between an arbitrary grouping of symptoms and a grouping of
symptoms that reflect the causal structure of the world. As argued
by Borsboom and Cramer:
In addition, network modeling has the philosophical advantage
of dropping the unrealistic idea that symptoms of a single dis-
order share a single causal background, while it simultaneously
avoids the relativistic consequence that disorders are merely
labels for an arbitrary set of symptoms .(Borsboom & Cramer,
2013, p.93)
This suggests that although the symptom network model de-
fines a psychiatric diagnosis at the level of its symptoms, the
diagnosis does not merely serve as a descriptive label for these
symptoms, but also provides additional information about the
causal relations that sustain these symptoms as a stable cluster.
Consider the patient who presents to the clinic with low mood,
poor concentration, fatigue, and insomnia. According to the
symptom network approach, the diagnosis of MDD indicates that
these symptoms constitute a dynamically stable system held
together by causal relations. Again, this does not meet the standard
model of explanation where a diagnosis picks out an underlying
pathology that is causing the patient’s symptoms, but there is
nonetheless good reason to think of it as being a sort of causal
explanation. In particular, it explains why the patient’s symptoms
of occur concomitantly. By positing causal relations between the
symptoms, the diagnosis of MDD explains why they have aggre-
gated and persisted as they have, regardless of what pathological
processes may be underlying them in the particular case.
Hence, if the symptom network approach is assumed, a psy-
chiatric diagnosis can provide some causal explanatory information
about a patient’s symptoms, even if the underlying causes of the
symptoms vary across cases. However, it is causal explanatory in-
formation of a different sort from that provided by a medical
diagnosis like MI, which picks out an underlying cause of the pa-
tient’s chest pain. Again, a claim such as “the patient’s mood
symptoms are caused by MDD”is misguided, this time because the
symptom network model suggests that MDD does not refer to a
latent underlying pathology responsible for the symptoms, but we
can still claim that the diagnosis of MDD causally explains the pa-
tient’s symptoms on the grounds that it refers to the causal struc-
ture by which the symptoms induce and reinforce each other.
The claim that a psychiatric diagnoses provide information
about the causal structures by which sets of symptoms are main-
tained sits well with the fact that specific therapies for some psy-
chiatric disorders often achieve reductions in some symptoms by
H.H. Maung / Studies in History and Philosophy of Biological and Biomedical Sciences 60 (2016) 15e2422

optimally intervening on others (Borsboom & Cramer, 2013, p. 98).
For example, cognitive-behavioural therapy for MDD employs the
notion that thoughts, actions, emotions, and bodily symptoms can
all influence one another. The idea is that intervening on the pa-
tient’s negative thoughts and level of activity through cognitive
restructuring and behavioural activation might then lead to im-
provements in his or her mood and interest level. Therefore, under
the symptom network approach, the causal information conveyed
by a psychiatric diagnosis can provide a rational basis for thera-
peutic intervention.
The symptom network approach, then, makes it possible for a
psychiatric diagnosis to convey causal explanatory information
about a patient’s symptoms without specifying an underlying
causative pathology. However, a limitation of the approach is that it
may turn out not to be applicable to all major psychiatric diagnoses.
For instance, it is not obvious why, in the case of schizophrenia,
hallucinations and delusions should be causally connected to
blunted affect and catatonic behaviour. Similarly, in the case of
bipolar disorder, it is not obvious how mania and depression are
supposed to causally induce each other. It appears that in these
cases we need to appeal to additional causal variables, such as
underlying neurobiological processes, in order to make the link
between hallucinations and affective blunting, and the link be-
tween mania and depression intelligible. Therefore, while there are
plausibly some psychiatric diagnoses that provide causal explana-
tory information about symptoms without needing to invoke in-
formation about the underlying processes, it is unlikely that this is
the case for all psychiatric diagnoses.
4. Concluding remarks
We should take seriously the possibility that many major psy-
chiatric disorders may turn out to exhibit high degrees of causal
heterogeneity and complexity. This paper has examined some of
the implications of this for the diagnostic explanation in psychiatry.
If it turns out that a given diagnostic category subsumes a variety of
different underlying causal structures, then this would suggests
that diagnostic explanation in psychiatry falls short of the essen-
tialistic ideal where a diagnosis specifies the causative pathology
responsible for the patient’s symptoms. Nonetheless, I have argued
that some psychiatric diagnoses can still provide other sorts of
causal information that can be explanatorily relevant. First, in vir-
tue of the exclusion criteria, a psychiatric diagnosis can sometimes
provide negative causal information by ruling out other medical
causes. Second, in virtue of our scientific knowledge of some of the
various causal factors implicated in psychiatric disorders, a diag-
nosis can provide some probabilistic or disjunctive information
about the possible causal processes that might be relevant to the
patient, although this information is likely to be vague and partial
given our limited scientific understanding of how these various
factors come together. Third, in virtue of the causal relations be-
tween the symptoms themselves, a psychiatric diagnosis can pro-
vide information about why the patient’s symptoms occur together
and persist as they do.
The high degrees of causal heterogeneity associated with psy-
chiatric diagnoses suggest a need to review the ways in which
diagnostic terms are sometimes communicated in clinical psychi-
atry. For example, because the category MDD is not associated with
a specific causative pathology, there are problems with citing MDD
as the “cause”of a patient’s low mood in the same way as citing MI
as the cause of a patient’s chest pain. Such a causal claim risks
falsely essentialising MDD. As noted in section 1, this essentialisa-
tion is not only misleading to patients, but can encourage harmful
stigma (Haslam, 2014). Hence, caution is warranted in the way
psychiatric diagnoses are represented in the professional discourse
of psychiatry. Nonetheless, I have shown how the causal explana-
tory roles of psychiatric diagnoses might still be useful in clinical
practice, even if they do not pick out specific causal essences. The
negative causal information can exclude certain avenues for inter-
vention and offer reassurance to patients. The probabilistic infor-
mation about possible causal processes can occasionally support
therapeutic decisions, although it must be conceded that we are far
from being able to specify pathways and biomarkers that could
allow for powerful interventions. Finally, the information about the
causal relations between symptoms can support therapeutic in-
terventions that target particular symptoms to optimally reduce
others.
Acknowledgments
This paper was written during my doctoral studies at Lancaster
University, for which I acknowledge financial support from the
Wellcome Trust Humanities Studentship (ref. 104897/Z/14/Z). I
would like to thank Rachel Cooper, Brian Garvey, and Dane Ray-
ment for their generous comments. I would also like to thank the
two anonymous reviewers and the expert adjudicator for taking the
care to offer helpful comments on the manuscript.
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