Content uploaded by Phoebe Friesen
Author content
All content in this area was uploaded by Phoebe Friesen on Oct 10, 2019
Content may be subject to copyright.
Expanding Outcome Measures in Schizophrenia Research: Does
the Research Domain Criteria Pose a Threat?
Phoebe Friesen
Philosophy, Psychiatry, & Psychology, Volume 26, Number 3, September
2019, pp. 243-260 (Article)
Published by Johns Hopkins University Press
DOI:
For additional information about this article
Access provided at 17 Sep 2019 16:03 GMT from McGill University Libraries
https://doi.org/10.1353/ppp.2019.0039
https://muse.jhu.edu/article/732771
© 2019 by Johns Hopkins University Press
Expanding Outcome
Measures in
Schizophrenia
Research
Does the Research
Domain Criteria Pose
a Threat?
Phoebe Friesen
AbstrAct: This article examines two significant shifts
that have been taking place within the field of psychia-
try, and asks whether they are moving in compatible
directions or not. The first shift is taking place within
psychiatric research as a result of the National Institute
of Mental Health’s rejection of the Diagnostic and Sta-
tistical Manual of Mental Disorders criteria in favor of
the newly developed Research Domain Criteria (RDoC)
framework. The second shift involves the adoption of
wider outcome measures related to recovery and quality
of life (QOL) within schizophrenia research in place of
narrow measures such as symptom scales. It is argued
that this second shift has been successful in that it has
brought several explanatory models into light that were
previously difficult to see and that are likely to bear
fruit in terms of both understanding schizophrenia and
developing tools and treatments for those living with a
diagnosis of schizophrenia. In light of this, the question
of whether the shift to RDoC will threaten these gains
is considered. In response, it is suggested that although
there are several reasons to think that the first shift may
threaten the knowledge gained by the second shift, there
is also reason to be hopeful.
Keywords: Schizophrenia, RDoC, DSM, Quality of Life,
Participatory Research, Outcome Scales
Explanatory Pessimism and
the Shift to the Research
Domain Criteria
In the introduction to a recent anthology of
contemporary issues in philosophy of psychia-
try, editors Jeffrey Poland and Şerife Tekin de-
clare this to be a moment of crisis within the field.
They suggest that the state of psychiatry today
reflects Thomas Kuhn’s conception of a period of
extraordinary science, which occurs when anoma-
lies begin to build up, confidence in the dominant
paradigm is shook, competing theories arise, and
philosophical questions come to the fore (Kuhn,
1970; Poland & Tekin, 2017). Although perhaps
not all would agree that the field is in crisis, there
is certainly an abundance of pessimism. Within
the realm of research, a mood of explanatory pes-
simism has been growing, characterized by a loss
of hope surrounding the possibility of reaching a
scientific understanding of the mental disorders
that have been under investigation for centuries.
244 ■ PPP / Vol. 26, No. 3 / September 2019
Despite many waves of hype and promise related
to pinpointing biomarkers, genetic bases, or neural
pathways underlying schizophrenia, depression,
anxiety, and other disorders, psychiatric research
has born little fruit in the past several decades
(Kirmayer & Crafa, 2014; Kraemer, 2015). Prog-
ress has been slow, dominant theories have been
overturned, and neurobiological correlates of
disorders have not appeared. Reflecting on these
disappointments, Thomas Insel describes psychiat-
ric research as a realm that has traditionally “ad-
vanced via serendipitous discoveries, stumbling
on treatments that helped people to get better
but not well”, arguing that if the field is going to
make progress, “we will need a more disciplined
scientific approach” (Insel, 2009, p. 132).
In response to this growing state of explanatory
pessimism, a radical change has been taking place
within psychiatric research in the United States, as
the Diagnostic and Statistical Manual of Mental
Disorders (DSM) criteria that have dominated
the field since the 1950s are replaced by the Na-
tional Institute of Mental Health’s newly minted
Research Domain Criteria (RDoC). RDoC has
arrived on the heels of intense and growing criti-
cism of the DSM. Although the earliest editions
were grounded in the psychoanalytic tradition,
DSM III and the editions that followed were de-
veloped with the intention of providing a reliable
and atheoretical nosology of mental disorders.
While these goals have arguably been achieved,
their costs, in terms of validity and scientific
understanding, have been significant (Kawa &
Giordano, 2012; Kendell & Jablensky, 2003).
Pointing to the incredible heterogeneity of DSM
categories like schizophrenia and post-traumatic
stress disorder, the likelihood that experiences in
such categories are brought about through many
causal pathways, and the significant overlap that
is often seen between diagnostic categories, many
have raised doubts that the boundaries drawn by
the DSM have the potential to capture relevant
causal factors underlying mental disorders and
generate predictions regarding treatment responses
(Hoffman & Zachar, 2017; Insel et al., 2010;
Olbert, Gala, & Tupler, 2014; Poland & Tekin,
2017; Tabb, 2015).
Reflecting on the sorry state of research domi-
nated by the DSM paradigm, developers of RDoC
have lamented that “many attempts to understand
the biology of mental illness have been misdirected
at spurious diagnostic entities, such that oppor-
tunities for success have been inherently limited”
(Kozak & Cuthbert, 2016, p. 286). RDoC seeks to
offer a research model that corrects the wrongs of
the DSM and sets psychiatric research on a more
productive path. The framework consists of a
matrix of rows made up of various domains (e.g.,
loss, perception, reward learning) and columns
composed of several units of analysis (e.g., genes,
molecules, cells). This matrix is meant to free re-
searchers from “the rigid boundaries of symptom-
based categories” as well as from drawing a line at
the outset between that which is pathological and
that which is not (Insel, 2014, p. 396). Instead,
researchers are encouraged to examine the variety
of responses that might exist within a particular
domain (e.g., sustained threat) to better under-
stand the mechanisms underlying these responses.
Although the units of analysis offered in the matrix
contain self-report and behavior as well as genes
and circuits, RDoC is explicitly committed to basic
science research, particularly genetic and neurosci-
entific endeavors (Morris & Cuthbert, 2012). The
“complex higher-order psychological constructs”
of the DSM are foregone in favor of “simpler”
or “lower order” phenomena that are thought to
be better “candidates for biological elaboration”
(Kozak & Cuthbert, 2016, p. 287). Currently, the
framework is not intended to guide diagnosis or
any aspect of clinical practice, but is only meant to
provide criteria for psychiatric research. It is likely
to have a major impact on such research though, as
the National Institute of Mental Health, the largest
funder of mental health research in the world, is
now directing a significant amount of its funding
to projects that enlist the RDoC framework in
place of DSM criteria (Insel, ND).
An Account of Causation
To map the significance of the shift to RDoC in
relation to a second shift that will be introduced
below, it is helpful to think of psychiatric research
Friesen / Does RDoC Pose a Threat? ■ 245
as intuitively guided by the insights of James
Woodward regarding causation and explanation.1
According to Woodward, “X causes Y if and only
if, were some intervention [I] that changes the
value of X to occur, Y or the probability distribu-
tion of Y would change in some regular, stable
way, in some range of background circumstances
B” (Woodward, 2008, p. 139).
If I à X à X’
and X’ à Y à Y’
(In B)
Then X causes Y
Note that, on this account, for X to count as a
cause of Y, there needs to be a change in X (which
is transformed into X’) as well as a change in Y
(which is transformed into Y’), such that when an
intervention transforms X to X’, Y reliably trans-
forms into Y’ as well (Woodward, 2008, p. 143).
Take the dopamine hypothesis of schizophrenia
as a simple example. Particularly in its early days,
this hypothesis seemed especially plausible because
an intervention I (antipsychotic medication), had
an impact on levels of X (dopamine, through
blocking dopamine receptors and leading to X’),
and this impacted the presence of Y (schizophre-
nia, through reducing symptoms of psychosis and
leading to Y’). This led researchers to conclude
that levels of dopamine must be causally related
to schizophrenia.2 Ideally, for Woodward, for X to
cause Y, the changes in Y should not be brought
about indirectly (e.g., I à X’ à Q’ à Y’) or
through a common cause (e.g., I à Q à Q’ and
‘X ß Q’ à Y’).
Looking at this model, we can see that those
critical of the DSM were raising different forms of
the question: Are we aiming at the wrong Y? Rec-
ognizing that Y (e.g., schizophrenia) may consist
of many distinct subtypes, or overlap significantly
with another Y (e.g., bipolar disorder), critics of
the DSM worry that our chances of finding an
intervention that will reliably lead to an impact
on Y are quite small. RDoC aims to resolve these
difficulties by breaking down Y (schizophrenia)
into Y1 (agency), Y2 (auditory perception), Y3
(language), and so on, betting that this increase
in granularity will lead to an increase in under-
standing causal mechanisms that underlie each of
these domains.
Meanwhile, in a corner of clinical psychiatry,
another related, but distinct variety of pessimism
has been growing, as a result of the lack of ef-
fective tools and treatments available to support
those living with a diagnosis of schizophrenia.3 In
response, a different kind of shift has been taking
place in psychiatric research, concerned not with
the status of Y, but with that of Y’. Rather than
asking whether the boundaries of schizophrenia
have been adequately captured by the category,
those propelling this shift forward have been
asking: Have we been relying on the wrong Y’?
In schizophrenia research, the occurrence of Y’,
which represents a change, usually a reduction,
in schizophrenia, is determined by the tools used
to measure efficacy. A closely related question is:
in which cases can we say that schizophrenia has
been treated successfully or that the disorder is
no longer present? The answer to this question
may seem to fall directly out of whatever answer
is given to the question of what Y consists of, in
that once one has drawn boundaries around Y
(schizophrenia), Y’ (a change or lack of schizo-
phrenia) will consist of anything outside of those
boundaries. As will be elucidated below, however,
the question of how to declare the treatment of Y
a success is not always equivalent to the question
of whether Y is no longer present.
Although philosophers of psychiatry have paid
little heed to this shift, I argue here that it has con-
tributed to significant gains in our understanding
of schizophrenia, and that there is a risk of los-
ing what has been gained as the RDoC initiative
makes greater waves within psychiatric research
programs. After elucidating how this shift came
about and mapping out four explanatory models
that have come to light as a result of it, I raise the
question of whether the gains in schizophrenia
research that have resulted from this second shift
are likely to remain available within research
projects that utilize RDoC. I argue that there are
both reasons to see RDoC as a threat to these
gains, but also reasons to think that RDoC is more
compatible with this shift than one might expect.
246 ■ PPP / Vol. 26, No. 3 / September 2019
Clinical Pessimism and
the Shift to QOL Clinical
Pessimism
The second locus of disappointment that has
been looming large within the field of psychiatry
is a clinical one, revolving around the lack of
effective treatments available to support those
diagnosed with schizophrenia. Central to this
clinical pessimism are mounting concerns related
to antipsychotic medications, typically thought
to be the standard of care for schizophrenia in
wealthy nations. These medications often lead to
debilitating physical side effects, including weight
gain, type II diabetes, cardiovascular effects,
sexual dysfunction, and extrapyramidal side ef-
fects (impairments in the motor system), as well as
significant mental side effects, leading those taking
antipsychotic medications “to speak of ‘feeling like
a zombie’ and being ‘unable to think straight’ ”
after just a few doses (Gerlach & Larsen, 1999;
Su Ling, Mark, & Stephen, 2014).
These side effects, along with other factors,
contribute to high rates of ‘noncompliance’
(5%–50%; Sendt, Tracy, & Bhattacharyya, 2015)
as well as significant drop-out rates within clini-
cal trials (37%–62%; Levine, Goldberg, Samara,
Davis, & Leucht, 2015). Although antipsychotics
seem to be fairly effective in reducing positive
symptoms (e.g., hallucinations, delusions) of
schizophrenia, they have little impact on the nega-
tive (e.g., blunted affect) or cognitive symptoms
that also characterize the disorder (Buchanan et
al., 2007). Perhaps most worrisome are findings
that link antipsychotics to deficits in cortical grey
matter (Haijma et al., 2012; Vita, De Peri, Deste,
Barlati, & Sacchetti, 2015) and increased mortal-
ity (Joukamaa et al., 2006), and that suggest that
treatment with antipsychotics may lead to lower
rates of recovery in the long run (Moilanen et al.,
2013; Wunderink, Nieboer, Wiersma, Sytema, &
Nienhuis, 2013). As a result of this, both patients
and professionals alike have been engaging in
discussions of how to reduce the use of these medi-
cations (Hall, Bergman, McNamara, & Sorensen,
2007; Murray et al., 2016).
When second-generation (also called atypi-
cal) antipsychotics were introduced in the early
1990s, they were triumphed as a breakthrough,
and yet the lives of many of those living with a
diagnosis of schizophrenia do not seem to have
improved. Although some evidence suggests that
extrapyramidal side effects are less common with
second-generation antipsychotics, metabolic side
effects occur more frequently (Divac, Prostran, Ja-
kovcevski, & Cerovac, 2014; Hirsch et al., 2017).
Mortality rates of those living with schizophrenia
remain extremely high and may in fact be increas-
ing. On average, individuals with a diagnosis of
schizophrenia live 20 years less than the rest of
the population (Laursen, 2011). While suicide is
a significant contributor (13 times more likely),
natural causes of death are also significantly higher
in those with a diagnosis of schizophrenia (Saha,
Chant, & McGrath, 2007). Rates of recovery
(defined as at least two years of clinical and/or
social improvement) for individuals with a diag-
nosis of schizophrenia have not improved either,
but have instead hovered around 13% for decades
(Jaaskelainen et al., 2013). Especially concerning
to many in wealthy nations is a large body of evi-
dence demonstrating that individuals diagnosed
with schizophrenia in poor countries consistently
fare better and recover faster; the reasons for this
difference are not well-understood (Isaac, Chand,
& Murthy, 2007; Jablensky et al., 1992).
Reflecting on the significant disappointment
that has followed the introduction of second-
generation antipsychotics, some have character-
ized the shortage of treatments for schizophrenia
as stemming from a gap between efficacy and
effectiveness, suggesting that “in recent years,
our field has experienced a growing difficulty in
translating the results of randomized controlled
clinical trials . . . into clinical practice concern-
ing the clinical usefulness of new medications for
the treatment of schizophrenia” (Fleischhacker
& Goodwin, 2009, p. 23; see also Taylor, Cava-
nagh, Hodgson, & Tiihonen, 2012). In response
to this gap, new efforts have been made to bring
research and clinical outcomes closer together, to
decrease the likelihood that interventions deemed
efficacious in a clinical trial will be found to be
ineffective when introduced in clinical practice.
An important piece of these efforts has been the
shift toward using more relevant or meaningful
outcome measures within schizophrenia research.
Friesen / Does RDoC Pose a Threat? ■ 247
Shift to QOL
Popular measures used to track outcomes in
clinical trials of interventions for schizophrenia
include service utilization (e.g., the frequency and
length of hospitalizations), time to discontinuation
(how long until a patient stops taking a medica-
tion), and symptom scales. Service utilization
is primarily measured for the sake of economic
analyses, and time to discontinuation tracks the
length of time until a medication is deemed to
lack efficacy or the side effects have become too
unbearable. Although these measures are com-
monly used within randomized controlled trials
and are praised for their objectivity and simplic-
ity, they have also both been called “crude” as
outcome measures in trials examining treatments
for schizophrenia (Fleischhacker & Goodwin,
2009; Strauss, Carpenter, & Jr, 1974). Changes in
symptom rating scales, however, have been largely
thought to represent the impact of an intervention
on the actual disorder itself. The most popular
symptom rating scales in schizophrenia research
include the Brief Psychiatric Rating Scale (BPRS),
Positive and Negative Syndrome Scale (PANSS),
and the Clinical Global Impression (CGI) scales
(Guy, 1976; Haro et al., 2003; Kay, Fiszbein, &
Opfer, 1987; Mortimer, 2007; Overall & Gorham,
1962).
Criticisms of relying on symptom scales as a
measure of efficacy have been growing steadily,
however, in large part because of their inability
to predict what matters in clinical contexts. It
has been suggested that the symptom scales used
in schizophrenia research are of only “marginal
clinical relevance” (Fleischhacker & Goodwin,
2009, p. 26) and have “yielded little of relevance
to etiology, treatment or prognosis” (Mortimer,
2007, p. s11). Some have pointed out that an
individual diagnosed with schizophrenia can be
declared much improved according to a symptom
scale despite no change in his psychotic symptoms
(Fleischhacker & Kemmler, 2007), whereas others
emphasize that these scales tend to weight positive
psychotic symptoms too heavily to the neglect
of negative and cognitive symptoms (Liberman,
Kopelowicz, Ventura, & Gutkind, 2002). Oth-
ers point out that these scales have no ability
to account for the negative experiences of side
effects that often accompany changes in symp-
toms brought on by treatment, despite the fact
that some patients prefer symptoms over the side
effects of medication (McCabe, Saidi, & Priebe,
2007). The significant distance between the factors
being considered within symptom scales (e.g., the
presence of hallucinations) and the factors said
to matter most to individuals diagnosed with
schizophrenia (e.g., hope, relationships) have been
emphasized by many (Campbell, 1997; Friesen,
2017). This distance only serves to contribute to
the gap between efficacy and effectiveness, and
may “lead clinicians to overlook dimensions of
an individual’s functioning or situation that are
not open to measurement or which are simply not
being measured” (Healy, 2009).
In parallel with, and in large part contributing
to, the increasing awareness of the issues sur-
rounding reliance on symptom scales as primary
measures of efficacy, there have been growing
demands from the recovery movement, c/s/x
(consumer, survivor, ex-patient) groups, and pa-
tient organizations to include more meaningful
outcome measures in research (Priebe, 2007; Rose,
Fleischmann, Wykes, Leese, & Bindman, 2003).
While there is incredible diversity within the beliefs
and actions of these groups, they share the goal of
improving the lives of those diagnosed with mental
disorders and have contributed significantly to a
shift within psychiatry toward thinking of ‘recov-
ery’ as much more than just the amelioration of
symptoms (Anthony, 1993). A much-cited defini-
tion of recovery in this larger sense describes it as
“a deeply personal, unique process of changing
one’s attitudes, values, feelings, goals, skills, and/
or roles… a way of living a satisfying, hopeful,
and contributing life even with limitations caused
by illness” (Anthony, 1993, p. 527). Aspects of
recovery that are often emphasized include hope,
empowerment, connection, self-efficacy, control,
and physical health (Connell, Schweitzer, & King,
2015; Deegan, 1997; Jacobson & Greenley, 2001;
Mead & Copeland, 2000). An important contribu-
tion stemming from this larger understanding of
recovery has been the recognition that “traditional
clinical measures, while providing important in-
formation to clinicians, do not assess constructs
248 ■ PPP / Vol. 26, No. 3 / September 2019
important to consumer-defined psychological
recovery” (Andresen, Caputi, & Oades, 2010,
p. 316).
As a result of the growing acceptance of the
importance of recovery and increasing awareness
of the issues related to symptom scales, a signifi-
cant shift away from reliance merely on clinical
outcomes, and toward broader measures able
to capture ‘functional’ outcomes, recovery, and
QOL, has been taking place within schizophrenia
research over the past two decades (Remington
et al., 2016) . As Ann M. Mortimer summarizes:
The value of symptom item or even syndrome
score totals per se is increasingly questioned in
the determination of outcome status. A more
patient-centered definition of outcome, stressing
personal and social function, is often viewed as
more practical than the presence or absence of
esoteric phenomena (symptoms), which may have
little bearing on subjective experience or uptake
of healthcare. (Mortimer, 2007, p. s8)
As Fleischhacker and Goodwin point out, such
“outcomes relative to the patient experience” are
“often subsumed under the clichéd term ‘quality
of life’ ” (Fleischhacker & Goodwin, 2009, 24).
Following them, I refer to this general shift toward
including wider measures in schizophrenia re-
search as the shift toward QOL, and the measures
as QOL measures.4 Although both subjective and
objective measures of QOL are the most frequently
used amongst these wider measures, this shift also
encompasses a diverse range of scales, including
social functioning scales, recovery scales, patient-
reported outcomes, and scales related to social
adjustment, among others (Priebe, 2007). While
all of these measures aim to capture something
broader than mere symptoms and something closer
to the consumer’s perspective of what matters, the
ways in which this something is approached can
look very different according to different scales;
functional measures tend to put weight on the
number of days an individual spends at work or
school, whereas recovery-oriented measures tend
to focus on relationships and subjective experi-
ences (e.g., “How do you feel about the amount
of time you spend with other people?”; Ralph,
Kidder, & Phillips, 2000). Additionally, these
scales “lack a theoretical model, are not based on
universally agreed definitions, focus on a limited
number of aspects”, and there is no consensus in
the field as to which are most appropriate (Priebe,
2007, pp. s18-9). This means that collapsing this
mixed bag of measures into the broad category
of QOL measures makes for a challenge in terms
of drawing conclusions from research involving
them. As will be illustrated below, although the
broadening of these measures has brought sev-
eral new models of treatment for schizophrenia
to light, their diversity also presents a barrier to
drawing any clear conclusions.
Returning briefly to Woodward’s account of
causation, we can see that while the shift to RDoC
has redefined Y (schizophrenia) as Y1 (agency),
Y2 (auditory perception), and so on, the shift
to broader outcome measures in schizophrenia
research has replaced Y’ (symptom scales) with
Y” (QOL scales). The model of causation in this
second shift looks like this:
If I à X à X’
and X’ à Y à Y”
(In B)
Then X causes Y
This broadening of Y’ to Y” is likely to make it
the case that some of B (background conditions)
will be collapsed into Y”, as more is encompassed
in this measure of success or efficacy. It also has
implications for how we might think of Y, which
will be discussed later.
The shift to RDoC and the shift to QOL are
similar, in that they are both pushing away from
the DSM and away from conceptions of mental
disorders based on lists of symptoms. They are dif-
ferent, as well, in that they are moving in opposite
directions in terms of scale. While RDoC aims to
increase the granularity of psychiatric research in
hopes of finding that which is causally relevant,
QOL measures aim to reduce the granularity in
hopes of capturing that which is meaningful to
those living with a diagnosis of schizophrenia.
Whether this difference might mean that the two
shifts are incompatible is discussed in the last sec-
tion. Beforehand, however, I outline four models of
QOL in schizophrenia that have come to light as
a result of the shift toward QOL, further utilizing
Woodward’s model of causation in the process.
Friesen / Does RDoC Pose a Threat? ■ 249
Four Models of QOL in
Schizophrenia
If one looks to the research that has been
conducted on the basis of expanding Y’ to Y”,
away from efficacy based on symptom reduction
and toward efficacy based on the achievement of
QOL, several alternate models for understanding
the what contributes to QOL in schizophrenia
come into light, all of which pose challenges for
traditional conceptions of how efficacy should be
measured in schizophrenia research. Here, I briefly
introduce four of these models. They are by no
means exhaustive, but they serve to illustrate the
extent to which research in the field has taken up
the shift toward QOL and contributed to novel
understanding of how we might better bridge the
gap between efficacy and effectiveness.
Model A: Symptom
Reduction as a Necessary but
Insufficient Step
The first model sees symptom reduction as a
necessary but insufficient step on the journey to-
ward QOL. In line with this, it has been suggested
that “most of the ‘softer’ outcome measures such
as quality of life, social functioning and personal
well-being are only of relevance in situations where
symptom control is relatively well achieved”
(Burns, 2007, p. s5). This model was embraced by
the Remission in Schizophrenia Working Group,
who proposed criteria for remission in schizophre-
nia in 2005, suggesting that:
Remission is a necessary but not sufficient step
toward recovery. The working group chose to
define remission as a state in which patients
have experienced an improvement in core signs
and symptoms to the extent that any remaining
symptoms are of such low intensity that they
no longer interfere significantly with behavior
and are below the threshold typically utilized in
justifying an initial diagnosis of schizophrenia.
(Andreasen et al., 2005, p. 442)
According to the criteria proposed, a reduction in
particular symptoms (psychoticism, disorganiza-
tion, and negative symptoms) must be present for
at least 6 months for an individual with a diagno-
sis of schizophrenia to be deemed ‘in remission’
(Andreasen et al., 2005).
This model is supported by research that sug-
gests that the presence of symptoms prevents those
with a diagnosis of schizophrenia from reaching
their goals, which can reduce one’s experience of
QOL. Clarke, Oades, Crowe, Caputi, and Deane
(2009, p. 395) report that the causal relationship
between symptoms and goal progress seems to
only move in one direction: “Whilst the experience
of severe symptoms impedes goal progress, when
goal progress is made there is not necessarily a
decline in symptom severity.” Relatedly, it has been
found that service users who are most interested
in outcomes related to QOL are those experienc-
ing the least symptoms, particularly depressive
symptoms (Resnick, Rosenheck, & Lehman,
2004; Rosenheck et al., 2005). Similarly, while
investigations of the relationship between QOL
and symptoms in schizophrenia have produced
widely variable results, two recent meta-analyses
concluded that there is a small, but significant,
relationship between the two (Eack & Newhill,
2007; Van Eck, Burger, Vellinga, Schirmbeck, &
de Haan, 2017).
Returning to Woodward’s model, this variation
can be thought of as:
I à X à X’
X’ à Y’
I’ à X’ à X”
X” à Y’ à Y”
Where Y’ (symptom reduction) is a step on the
path toward Y” (QOL), X’ is the change that ac-
companies a reduction in symptoms, and X” is the
change that contributes to the attainment of QOL.
Model B: Mood as a Missing
Mediator
Another model for the treatment of schizophre-
nia derived from research involving broad out-
come measures proposes that there is an important
factor which mediates between clinical symptoms
and QOL that has been previously missing from
discussions of the disorder. This missing factor is
variously characterized as negative affect, depres-
sive symptoms, or mood. This model can be found
in the work of Paul Grant and Aaron Beck,5 who
250 ■ PPP / Vol. 26, No. 3 / September 2019
have put forward the hypothesis “that defeatist
beliefs are a mediating variable between cognitive
impairment, negative symptomatology, and poor
functioning in schizophrenia” (Grant & Beck,
2009, p. 803). Similarly, in an investigation of
the remission criteria discussed above, Oorschot
et al. (2012) found that there was no relationship
between remission and functional recovery, but
did find that negative affect was negatively cor-
related with remission criteria as well as social
functioning. A discussion of these results suggests
that this raises the possibility that “emotion could
be a mediating factor between psychosocial and
neuropsychiatric variables and recovery” (Mor-
rison et al., 2013, p. 204).
Although this model has been called tautologi-
cal by some (Resnick et al., 2004), there is ample
evidence to suggest that the presence of depressive
symptoms is the best predictor of QOL (Corrigan
& Buican, 1995; Holloway & Carson, 1999;
Resnick et al., 2004; Van Eck et al., 2017). One
investigation into the determinants of QOL in
individuals with severe mental illness found that it
is “quite evident that the severity of symptoms of
depression are most consistently and most strongly
related to subjective quality of life” (Hansson,
2006, p. 47).6 In line with this, semi-structured
interviews with consumers with a variety of
psychiatric diagnoses concluded that “our inter-
viewees stated unequivocally that depression had
the most profound impact on quality of life when
compared with their other mental health problems
such as anxiety or psychotic symptoms” (Connell,
O’Cathain, & Brazier, 2014). This suggests that
perhaps the reduction of only depressive symptoms
is required for the attainment of QOL, and that
the traditional focus on symptoms, particularly
positive symptoms, has been misdirected.
In Woodward’s model, the missing mediator
might look something like this:
I à X à X’
X’ à Y à Y’
X’ à Y à Y”
Where X’ represents the change that accompa-
nies a reduction in depressive symptoms, which
contributes both to a reduction in symptoms (Y’)
and an improvement in QOL (Y”). This model
holds that an improvement in mood or depres-
sive symptoms is both necessary and sufficient
for individuals diagnosed with schizophrenia to
attain QOL. Unlike model A, a reduction in other
characteristic symptoms (related to psychosis) of
schizophrenia is not necessary within this model.
Model C: Multiple Causal Pathways
Toward QOL
A related model suggests that reaching the goal
of QOL in schizophrenia involves the convergence
of several independent pathways. Following
Strauss and Carpenter, some have characterized
this as an “open-linked system” consisting of sev-
eral semi-independent processes (Brekke & Long,
2000; Resnick et al., 2004). Strauss and Carpenter
(1972) argued that symptoms alone cannot capture
meaningful outcomes for individuals diagnosed
with schizophrenia and that one must use several
measures (e.g., symptoms, employment, social
relations) to appropriately investigate outcomes.
In a contemporary expression of support for this
stance, Stefan Priebe has stated that, “Symptom
improvement and prevention of relapses alone do
not make patients necessarily more likely to com-
plete education, find employment and have social
relationships. These outcomes need therefore to
be assessed separately from symptoms” (2007,
p. s15). Corresponding with this more complex
picture of how QOL might be attained, Liberman
et al. (2002) have proposed operational criteria for
recovery in schizophrenia; these criteria include
measures not just of symptoms, but also related
to an individual’s involvement in school or work,
independent living status, financial circumstances,
and social support.
Evidence for the model of multiple causal path-
ways can be found in research that demonstrates
links between QOL and various factors that are
independent from the presence of symptoms, of
which there are many. In an exploration of other
factors that might impact QOL, Eack, Newhill,
Anderson, and Rotondi (2007) concluded that,
even after controlling for the presence of symp-
toms, unmet need and perceived social support
are both important for shaping the QOL of those
diagnosed with schizophrenia. Other factors that
have been found to correlate with, predict, or con-
Friesen / Does RDoC Pose a Threat? ■ 251
tribute to QOL include locus of control, optimism,
personal agency, taking responsibility, education,
self-advocacy, peer support, self-efficacy, self-
esteem, goal attainment, family psychoeducation,
exercise, and side effects (the latter is negatively
correlated; Morrison et al., 2013; Resnick et al.,
2004; Ritsner et al., 2003). Although much of this
evidence does not conclusively draw a causal line
between these factors and QOL, it implies that
many causal pathways with complex relationships
contribute to QOL. This model suggests that QOL
is determined by many interrelated, but somewhat
independent factors, including but only giving a
small role to symptoms. It also implies that QOL
can be multiply realized (has a different causal
basis in different individuals).
A model for treatment of schizophrenia reflect-
ing multiple causal pathways might look like this:
I à X à X’
I’ à X à X”
I” à X à X'''
X’ + X” + X''' à Y”
Where I is family psychoeducation, I’ is antipsy-
chotic medication, and I” is being involved in a
consumer-run self-help group, and X’, X”, and X”’
represent the changes brought about by each of
these interventions, all of which collectively con-
tribute to an individual reaching Y” and attaining
QOL. This model holds that symptom reduction
is only one of several necessary steps required to
reach QOL, and that the steps that are sufficient
to reach QOL are likely to look different for dif-
ferent individuals.
Model D: QOL Without Symptom
Reduction
Finally, a model that represents a significant de-
parture from reliance on symptom rating scales as
the primary measure of efficacy suggests that QOL
can be achieved without a reduction in symptoms.7
This model has been espoused by many within the
recovery movement. As Patricia Deegan puts it,
One of the biggest things I have had to accept
is that recovery is not the same thing as being
cured. After twenty-three years of living with
this thing it still hasn’t gone away. So I figure
that I’m never going to get ‘cured’ but I can be in
recovery. Recovery is a process, not an end point
or a destination. Recovery is an attitude, a way
of approaching the day and the challenges I face.
(Deegan, 1993)
Many other consumers/survivors/ex-patients share
this view as well, maintaining that there is no con-
flict between the experience of recovery and the
presence of ongoing symptoms (Andresen et al.,
2010; Anthony, 1993; Mead & Copeland, 2000).
The Hearing Voices Network, a large and grow-
ing network of people who hear voices, champion
living with symptoms in a healthy and productive
way, suggesting that QOL and symptoms char-
acteristic of psychosis are not always in conflict
(Ruddle, Mason, & Wykes, 2011). Similarly, a
document on consumer perspectives of recovery
reported that only 14% of surveyed respondents
understood recovery to include freedom from
symptoms (Tooth, Kalyanansundaram, & Glover,
1997; cited in Andresen, Oades, & Caputi, 2003).
Additional support for this model is found in
a longitudinal study of 118 individuals diagnosed
with schizophrenia. The Vermont longitudinal
study reported that 32 years after their initial
contact with the research team, the majority of
participants were doing well, and importantly, a
substantial subset of them were “functioning well
(e.g., working, with good family relationships and
with friends)” despite the continued presence of
hallucinations and delusions (Harding, Brooks,
Ashikaga, Strauss, & Breier, 1987, p. 733). Re-
cent research exploring the link between positive
symptoms and social outcomes indicates that a
sense of subjective recovery can act as a protective
factor, moderating experiences of social function-
ing in relation to psychotic symptoms. The authors
conclude that these results pose a challenge to the
significant body of literature that suggests that
recovery can only be achieved through the remis-
sion of symptoms (Kukla, Lysaker, & Roe, 2014).
Proponents of this model also emphasize research
that has failed to find a link between measures
of symptoms and measures of QOL, or suggests
that other factors better predict QOL, although
as mentioned above, recent meta-analyses suggest
that there is a real, albeit quite small, effect (Albert
et al., 2011; Andresen et al., 2010; Morrison et
al., 2013).
252 ■ PPP / Vol. 26, No. 3 / September 2019
To map this model, we might revise Wood-
ward’s model slightly so that Y’ (symptom reduc-
tion) is excluded, as it is not necessary to reach Y”:
I à X à X’
X’ à Y à Y”
Where X’ represents the changes that take place
leading to QOL that do not include a reduction in
symptoms, but that lead to the attainment of QOL
(Y”). This model holds that symptom reduction is
neither necessary nor sufficient to reach QOL for
those diagnosed with schizophrenia. Of course, if
this model were to be widely adopted in research,
Y (schizophrenia) as defined by the DSM would
need to be significantly re-conceptualized. Quite
radically, this model suggests that an individual
could have every symptom listed under the head-
ing of schizophrenia in the DSM, and yet still be
considered free from the disorder.
Gains from the Shift to QOL
As illustrated by the models described here,
research that seeks to investigate the attainment
of QOL of schizophrenia has grown tremendously
as a result of the shift toward wider outcome
measures. Although some of these models are
compatible with each other (B and C), others can-
not be accepted in conjunction (A and D), and the
evidence is yet to say which will win out, or if some
models will map onto some experiences and not
others. I have no horse in the race, and do not wish
to bet on which model most accurately depicts the
pathways toward QOL in those diagnosed with
schizophrenia, but I do hope to demonstrate how
much has been gained as a result of the embrace of
broader outcome measures within schizophrenia
research.
Beyond a greater, albeit underdetermined,
understanding of what contributes to QOL in
those living with a diagnosis of schizophrenia,
several additional benefits that have resulted
from the shift to QOL in schizophrenia research
are worth noting. First, a greater examination of
diverse outcomes in schizophrenia research has
led to the embrace of a more optimistic picture of
the natural course of the disorder. Examinations
of QOL outcomes “challenge the original view
of schizophrenia as an inevitably deteriorating
condition, and also the more modern view that,
even if the original view is inaccurate, most people
with the disorder cannot improve” (Silverstein &
Bellack, 2008, p. 1111). Findings such as that of
the Vermont longitudinal study, and others since,
demonstrate that it is entirely possible for some to
achieve a high QOL while experiencing symptoms
characteristic of schizophrenia.
Second, the range of treatment programs avail-
able to those with a diagnosis of schizophrenia
have expanded and improved as a result of the
body of research surrounding QOL. A number of
factors that matter greatly to those diagnosed with
schizophrenia, such as hope and self-efficacy, now
play a greater role in clinical settings, where treat-
ments can be shaped to promote their presence.
Novel treatment programs for early psychosis,
often called coordinated care programs, are in-
creasingly being adopted. These programs have
developed with the goal of QOL at the forefront,
seeking to supplement conventional care with
support related to physical health, work or school
engagement, and social relationships (Bello et al.,
2017; Kane et al., 2015; Mueser et al., 2015).
Consumer-run initiatives that are more focused on
improving QOL than reducing symptoms are also
increasingly gaining acceptance (Corstens, Long-
den, McCarthy-Jones, Waddingham, & Thomas,
2014; Rogers & Rogers, 2017). If the outcome
measures being used within these research pro-
grams were narrow ones related only to the pres-
ence of symptoms or the number of days spent
in the hospital, it is less likely that the significant
role played by such factors would be recognized.
Another interesting result of this expansion is
that how we might understand the disorder of
schizophrenia, or perhaps more accurately, the
experience of living with a diagnosis of schizophre-
nia, has started to widen. Rather than consisting
of merely the list of symptoms that constitute
schizophrenia in the DSM, research related to
QOL suggests that the experience of schizophrenia
involves not just symptoms, but oftentimes loneli-
ness, side effects, a deflated sense of self-worth,
financial concerns, and hopelessness. Although
this makes for a much more complicated target in
terms of treatment, as can be seen from these mod-
Friesen / Does RDoC Pose a Threat? ■ 253
els, adopting this more complicated picture of the
disorder also reinforces the importance of relying
on expanded outcome measures that are able to
capture QOL and not merely symptoms, leading
to a sort of feedback loop between expanding the
disorder and expanding the outcome measures.
Perhaps the most important benefit of this
expansion has been the inclusion of the voices of
those who are most impacted by the development
of treatments for schizophrenia in the research
process. Demands for a clinical approach that
leaves individuals feeling well and whole, rather
than without symptoms but not well, have been
heard, and this new goal has been largely taken
up within the field. Rather than seeking treatments
that appeal to clinicians and other health care
professionals, those developing clinical tools for
schizophrenia must keep the perspective of those
who will be engaging in treatment in mind as well
(Simpson & House, 2002).
Additionally, and perhaps unsurprisingly, many
of the factors that have been found to play an
important role in contributing to QOL in those
diagnosed with schizophrenia (e.g., self-esteem,
agency, social relationships) are the very same
factors that matter to everyone seeking a good
QOL. As a result, these findings serve to close
the gap between those living with a diagnosis of
schizophrenia and the rest of the population, who
all care about meaningful work and supportive
relationships as well.
With these benefits in mind, I now turn back
to the topic we started with and consider what
impact the significant shift away from the DSM
criteria and toward National Institute of Mental
Health’s RDoC in psychiatric research is likely to
have on research in schizophrenia.
Returning to RDoC
Returning to the first shift discussed, that of
replacing the DSM categories with RDoC in psy-
chiatric research, it is worth asking whether the
insights that have been gained through expanding
outcome measures in schizophrenia research to
include individual experiences of recovery and
QOL will be lost as more and more research takes
place within the RDoC framework. Here I offer
reasons to think these insights might be lost in the
shift to RDoC, as well as reasons to think we can
remain hopeful that the two shifts will lead us to
similar ends.
Why Think Yes?
Why think that RDoC poses a threat to the
findings that have come out of the shift to QOL
in schizophrenia research? First, RDoC’s explicit
commitment to increasing the granularity of psy-
chiatric disorders and seeking neuroscientific and
genetic explanations for mental disorders moves
the state of research in the opposite direction to
the shift to QOL. Moving away from higher order
psychological constructs, RDoC aims to embrace
“lower order” phenomena that are most likely to
provide the basis for biomarkers, as in other areas
of medicine (Kozak & Cuthbert, 2016, p. 287).
In describing the development of RDoC, Cuthbert
and Insel describe workshops that were held with
experts in the field to determine which behavioral
components would be included in the RDoC ma-
trix. Within these workshops, participants were
instructed that there were “two requirements for
adding a construct to the matrix: first, ‘There
must be strong evidence for the validity of the sug-
gested construct itself [as a behavioral function]’;
second, ‘There must be strong evidence that the
suggested construct maps onto a specific biologi-
cal system, such as a brain circuit’” (Cuthbert &
Insel, 2013, p. 6). This implies that constructs that
lack a known biological system, particularly those
that might be somewhat elusive, such as hope and
self-efficacy, are not candidates for inclusion in
RDoC. As such, rather than widening the picture
of schizophrenia to include a more complicated
picture of what suffering and treatment might
look like for those diagnosed with the disorder,
“distinctly human processes are sidelined” within
the RDoC project (Kirmayer & Crafa, 2014, p.
8). Experiments that can be mapped within the
RDoC matrix, examining a domain (e.g., language
behavior) within a unit of analysis (e.g., genes), are
unlikely to have space for a consideration of the
role of psychological constructs such as responsi-
bility and empowerment.
One might respond that none of the higher
order psychological process highlighted in QOL
models of schizophrenia will matter if researchers
254 ■ PPP / Vol. 26, No. 3 / September 2019
relying on RDoC find a way to cure these disor-
ders through neuroscientific and genetic research.
However, this assumes that the causal story behind
schizophrenia is one that can entirely be explained
through lower level mechanisms, a story which
has not been demonstrated to be true. Given the
impact that these higher level constructs such
as hope and agency seem to have in contribut-
ing to the QOL of individuals diagnosed with
schizophrenia, it seems likely that they are worth
exploring in terms of causation as well. Although
RDoC bets all its horses on lower level processes,
it is possible a causal picture of the disorder will
only become clear through an examination of both
high level and low-level contributors to mental
disorder. Kraemer shares this worry:
There may be no genetic or brain-parameter cause
of any mental health disorder. It may be that a
set of genes determines the susceptibility of an
individual to environmental influences that, in
turn, cause changes in brain structure or function
or gene expression that are then expressed as
the emotional, behavioral, and cognitive prob-
lems identified by a psychiatric diagnosis. In the
absence of identification of the environmental
influence (not in the RDoC matrix8), without
providing some detection of the disorder (ie, a
diagnosis—contrary to the RDoC approach),
and with the interactive effects obscured by the
RDoC matrix, such a path is unlikely to be found
in RDoC studies. (Kraemer, 2015, p. 1164)
This highlights the possibility that higher level
factors that play a significant role in contribut-
ing to the occurrence of mental disorders may go
unrecognized within research programs based on
the RDoC framework.
One might also object, however, that RDoC, at
least at this point, is not intended as a framework
for the evaluation of treatments, but only as one
that can support research that seeks to understand
and explain mental disorders. If a researcher is
seeking to evaluate a novel treatment program
for schizophrenia, an RDoC grant will not be
available to fund such an evaluation, because it is
outside of the current aim of the framework. This
seems to suggest that the large body of research
exploring how to attain QOL in treatments for
schizophrenia will remain unaffected throughout
the shift to RDoC. However, such a suggestion
is based on a false distinction between research
and practice. There is no clear line between these
two realms, especially because the work being
conducted in basic science labs is eventually meant
to inform the development of treatments. Indeed,
the developers of RDoC explicitly say so: “the
RDoC approach presumes that data from genet-
ics research and clinical neuroscience will yield
biosignatures that will augment clinical signs and
symptoms for the purposes of clinical intervention
and management” (Morris & Cuthbert, 2012, p.
33). If psychiatric research focuses exclusively on
lower level, granular processes, the treatments that
will be developed as a result of such research will
reflect that granularity. The role of hope and self-
efficacy are unlikely to enter the picture. As Law-
rence Kirmayer and Daina Crafa have pointed out,
If endophenotypes replace behavior and experi-
ence, we may end up with a situation in which
the biologically defined parameters are assessed
and treated while the patient is asked to stand
to one side. The RDoC model is that of physical
medicine, where a clinician may diagnose and at-
tempt to treat diabetes regardless of the patient’s
recognition and understanding of the disease.
(Kirmayer & Crafa, 2014, p. 6)
Why Think No?
Although the commitment to granularity in
RDoC may pose a threat to the insights found
within the shift to QOL in schizophrenia research,
the lack of diagnostic boundaries provided by
RDoC gives us reason to hold out hope. Stepping
away from symptoms as negative units of analysis,
RDoC seeks to understand the causal mechanisms
underlying a particular domain, but does not nec-
essarily commit to a line being drawn around a
particular pathology at the outset. Looking for a
moment at how the RDoC framework can benefit
research related to auditory hallucinations (AHs),
we can see how these two shifts might align in
interesting ways.
In a discussion of how the RDoC matrix
shapes research related to AHs, Judith Ford and
colleagues describe how “RDoC’s dimensional ap-
proach encourages investigators to think beyond
between-group, patients-vs-controls research
designs and, instead, to design studies that al-
Friesen / Does RDoC Pose a Threat? ■ 255
low analysis of the full range of a dimension of
interest, including clinical as well as nonclinical
groups and remaining agnostic with regard to
diagnosis” (Ford et al., 2014, p. S296). Because
AHs are experienced not only by individuals who
are considered psychotic, but also by many other
patient groups (e.g., those with post-traumatic
stress disorder, depression, traumatic brain injury)
and by nonclinical populations as well (approxi-
mately 9.6% according to a recent meta-analysis
(Maijer, Begemann, Palmen, Leucht, & Sommer,
2017)), Ford and colleagues sought to explore
the qualities of AHs that they found across these
different populations and map the differences
onto the RDoC matrix. During this process, they
noted an important distinction between clinical
and nonclinical cases of hearing voices, in that
those in the clinical population “more often report
negative voices that they cannot control, resulting
in increased distress” (Daalman et al., 2011; Ford
et al., 2014, p. S297). This led the research team
to surmise that further exploring links between
experiences of voice hearing associated with
psychosis and several RDoC domains including
negative valence systems, cognitive control, and
agency would prove fruitful.
Interestingly, bringing together these systems to
better understand phenomenological experiences
of voice hearing points toward novel approaches
to the treatment of AHs that resembles, in interest-
ing ways, the models for the treatment of schizo-
phrenia presented above. Ford et al.’s research
on AHs suggests that for some individuals, like
model A, symptom remission may be required as
a first step of treatment, especially if the voices
are particularly distressing, although like model
C, it may be that only some symptoms need to be
reduced, particularly those related to agency and
negative valence. Or, as with model B, it could be
that agency and valence are mediating between
AHs and QOL, leading some voice hearers to
require clinical support and others to feel healthy
despite the presence of AHs. In contrast, the re-
search findings also support model D, in that it is
clear from looking across these populations that
the elimination of the symptom of AHs is not
required for one to be well.9
Although all AHs are seen as negative within
the DSM framework, the RDoC approach encour-
aged Ford and colleagues to examine the entire
domain of voice hearing across populations to
better understand what might contribute to patho-
logical and healthy experiences of voice hearing.
This novel way of understanding how AHs might
be understood in relation to wellness stems from
RDoC’s commitment to not drawing any diag-
nostic lines at the outset. Within this framework,
researchers cannot take as a given which signs
and symptoms are average responses to stress,
healthy but abnormal adaptations, or problematic
symptoms. Of course, lines of pathology must be
drawn at some point in order to determine where
to provide support, and the categories of clinical
and nonclinical did come into play within Ford
et al.’s analysis. However, RDoC’s distance from
diagnostic categories makes space for many novel
versions of this line to be drawn as a result of the
data, rather than in advance.
Conclusion
As increasing alarm has been raised in response
to the heterogeneity, overlap, and lack of validity
seen in the DSM taxonomy of mental disorder,
a great deal of excitement has been generated in
response to RDoC, which offers an alternative
framework for psychiatric research, founded on
a commitment to dimensionality and granularity.
Although philosophers and psychiatrists have
provided a rich analysis of both the shortcomings
of the DSM and the promise and concerns that
RDoC brings with it, they have largely neglected
what may be an equally exciting shift taking place
within schizophrenia research. This shift also in-
volves a rejection of the influence of DSM criteria
in psychiatric research, but rather than moving
to a smaller scale, it embraces wider outcome
measures as determinants of efficacy in treatment.
This second shift reflects a growing dissatisfaction
with the distance between declarations of efficacy
in clinical trials and the likelihood of effectiveness
in clinical practice. Moving away from simply
relying on symptom checklists as the primary
outcome measures in schizophrenia research and
adopting measures that reflect recovery and QOL
256 ■ PPP / Vol. 26, No. 3 / September 2019
instead, this second shift has led to significant gains
related to a clinical understanding of the experi-
ence of schizophrenia, and has produced several
novel models of how treatments for schizophrenia
might be improved. Reflecting on whether the
shift away from the DSM and toward RDoC will
threaten the gains made within this second shift
in schizophrenia research, I have suggested that
while the increase in granularity embraced by
RDoC may pose a threat to the research programs
exploring QOL in schizophrenia research, the
lack of diagnostic boundaries within the RDoC
framework may help to produce clinical findings
that resemble the advances seen in QOL research
in schizophrenia. Fortunately, RDoC is not set in
stone, as the framework has been developed with
the intention of changing shape in response to new
findings and research developments, and hopefully,
in response to critiques from philosophers as well.
Notes
1. Although none of the arguments within this article
hang on Woodward’s account, it serves nicely as a frame
in which to discuss two shifts that have been taking place
in psychiatry as of late, and I will use it throughout this
paper for that purpose.
2. Although useful as a toy model here, the dopamine
hypothesis of schizophrenia has been quite unsuccess-
ful in providing a causal model of schizophrenia (see
Kendler & Schaffner, 2011 for a thorough discussion).
3. I use schizophrenia as a shorthand here to refer
broadly to disorders primarily characterized by the
presence of psychosis or psychotic symptoms.
4. It is also common to refer to this shift as one
moving away from clinical recovery toward functional
recovery, although this usage tends to lean toward objec-
tive measures (e.g., job status) and away from subjective
measures (McCabe et al., 2007; Mortimer, 2007). The
term ‘social outcomes’ has also been used to describe
these wider measures (Priebe, 2007).
5. Note that Aaron Beck is the founder of cognitive
behavioral therapy (CBT) and this hypothesis aligns
quite closely with the model underlying CBT.
6. Others have pointed to anxiety as a significant
predictor of QOL (Hansson, 2006; Huppert & Smith,
2001).
7. Some researchers who favor this model even sug-
gest that treatments that focus on reducing symptoms
and instilling insight (recognition of oneself as disor-
dered) may in fact be doing harm, because they “can
convey pessimistic messages of hopelessness and lack
of personal agency” (Morrison et al., 2013, p. 208).
8. There is actually a ‘fourth dimension’ not seen on
the RDoC matrix, that is meant to account for envi-
ronmental aspects, as well as a third for developmental
processes, but these have not been as clearly articulated
by the creators of RDoC as the first two dimensions
(domains and units of analysis).
9. Interestingly, these possible treatment approaches
align very well with the picture of voice hearing es-
poused by the Hearing Voices Network, which promotes
a model of listening to and learning to create positive
relationships with one’s voices rather than merely seek-
ing to make them disappear (Corstens et al., 2014).
References
Albert, N., Bertelsen, M., Thorup, A., Petersen, L.,
Jeppesen, P., Le Quack, P., . . . Nordentoft, M.
(2011). Predictors of recovery from psychosis
Analyses of clinical and social factors associated
with recovery among patients with first-episode
psychosis after 5 years. Schizophrenia Research, 125
(2–3), 257–266.
Andreasen, N. C., Carpenter, W. T., Jr., Kane, J. M.,
Lasser, R. A., Marder, S. R., & Weinberger, D. R.
(2005). Remission in schizophrenia: Proposed crite-
ria and rationale for consensus. American Journal
of Psychiatry, 162 (3), 441–449.
Andresen, R., Caputi, P., & Oades, L. G. (2010). Do
clinical outcome measures assess consumer-defined
recovery? Psychiatry Research, 177 (3), 309–317.
Andresen, R., Oades, L., & Caputi, P. (2003). The ex-
perience of recovery from schizophrenia: Towards
an empirically validated stage model. Australian and
New Zealand Journal of Psychiatry, 37 (5), 586–594.
Anthony, W. A. (1993). Recovery from mental illness:
The guiding vision of the mental health service
system in the 1990s. Psychosocial Rehabilitation
Journal, 16 (4), 11–23.
Bello, I., Lee, R., Malinovsky, I., Watkins, L., Nossel,
I., Smith, T., . . . Sederer, L. I. (2017). OnTrackNY:
The development of a coordinated specialty care
program for individuals experiencing early psychosis.
Psychiatric Services, 68 (4), 318–320.
Brekke, J. S., & Long, J. D. (2000). Community-based
psychosocial rehabilitation and prospective change
in functional, clinical, and subjective experience
variables in schizophrenia. Schizophrenia Bulletin,
26 (3), 667–680.
Buchanan, R. W., Javitt, D. C., Marder, S. R., Schooler,
N. R., Gold, J. M., McMahon, R. P., . . . Carpenter,
W. T. (2007). The Cognitive and Negative Symptoms
in Schizophrenia Trial (CONSIST): The efficacy of
glutamatergic agents for negative symptoms and cog-
nitive impairments. American Journal of Psychiatry,
164 (10), 1593–1602.
Friesen / Does RDoC Pose a Threat? ■ 257
Burns, T. (2007). Evolution of outcome measures in
schizophrenia. British Journal of Psychiatry, 191
(50), s1-s6.
Campbell, J. (1997). How consumers/survivors are
evaluating the quality of psychiatric care. Evalu-
ationReview, 21 (3), 357–363.
Clarke, S. P., Oades, L. G., Crowe, T. P., Caputi, P., &
Deane, F. P. (2009). The role of symptom distress
and goal attainment in promoting aspects of psycho-
logical recovery for consumers with enduring mental
illness. Journal of Mental Health, 18 (5), 389–397.
Connell, J., O’Cathain, A., & Brazier, J. (2014). Mea-
suring quality of life in mental health: Are we asking
the right questions? Social Science and Medicine,
120, 12–20.
Connell, M., Schweitzer, R., & King, R. (2015). Re-
covery from first-episode psychosis: A dialogical
perspective. Bulletin of the Menninger Clinic, 79
(1), 70–90.
Corrigan, P. W., & Buican, B. (1995). The construct
validity of subjective quality of life for the severely
mentally ill. Journal of Nervous and Mental Disease,
183 (5), 281–285.
Corstens, D., Longden, E., McCarthy-Jones, S., Wad-
dingham, R., & Thomas, N. (2014). Emerging
perspectives from the hearing voices movement:
Implications for research and practice. Schizophrenia
Bulletin, 40 (Suppl. 4), S285-S294.
Cuthbert, B. N., & Insel, T. R. (2013). Toward the future
of psychiatric diagnosis: The seven pillars of RDoC.
BMC Medicine, 11 (1), 126.
Daalman, K., Boks, M. P., Diederen, K. M., de Weijer,
A. D., Blom, J. D., Kahn, R. S., & Sommer, I. E.
(2011). The same or different? A phenomenologi-
cal comparison of auditory verbal hallucinations in
healthy and psychotic individuals. Journal of Clinical
Psychiatry, 72 (3), 320–325.
Deegan, P. E. (1993). Recovering our sense of value
after being labeled. Journal of Psychosocial Nurs-
ing, 31 (4), 7–11.
Deegan, P. E. (1997). Recovery and empowerment for
people with psychiatric disabilities. Social Work in
Health Care, 25 (3), 11–24.
Divac, N., Prostran, M., Jakovcevski, I., & Cerovac,
N. (2014). Second-generation antipsychotics and
extrapyramidal adverse effects. BioMed Research
International, 2014, 656370.
Eack, S. M., & Newhill, C. E. (2007). Psychiatric symp-
toms and quality of life in schizophrenia: A meta-
analysis. Schizophrenia Bulletin, 33 (5), 1225–1237.
Eack, S. M., Newhill, C. E., Anderson, C. M., & Ro-
tondi, A. J. (2007). Quality of life for persons liv-
ing with schizophrenia: More than just symptoms.
Psychiatric Rehabilitation Journal, 30 (3), 219–222.
Fleischhacker, W. W., & Goodwin, G. M. (2009). Ef-
fectiveness as an outcome measure for treatment
trials in psychiatry. World Psychiatry, 8 (1), 23–27.
Fleischhacker, W. W., & Kemmler, G. (2007). The
clinical relevance of percentage improvements on
the PANSS score. Neuropsychopharmacology, 32
(11), 2435–2436.
Ford, J. M., Morris, S. E., Hoffman, R. E., Sommer,
I., Waters, F., McCarthy-Jones, S., . . . Cuthbert,
B. N. (2014). Studying hallucinations within the
NIMH RDoC framework. Schizophrenia Bulletin,
40 (Suppl. 4), S295–304.
Friesen, P. (2017). A place for subjectivity in psychiatry.
AJOB Neuroscience, 8 (2), 116–117.
Gerlach, J., & Larsen, E. B. (1999). Subjective experi-
ence and mental side-effects of antipsychotic treat-
ment. Acta Psychiatrica Scandinavica. Supplemen-
tum, 395, 113–117.
Grant, P. M., & Beck, A. T. (2009). Defeatist beliefs
as a mediator of cognitive impairment, negative
symptoms, and functioning in schizophrenia. Schizo-
phrenia Bulletin, 35 (4), 798–806.
Guy, W. (1976). ECDEU assessment manual for psy-
chopharmacology (Vol. 76). Washington, DC: US
Department of Health, Education, and Welfare,
Public Health Service, Alcohol, Drug Abuse, and
Mental Health Administration, National Institute
of Mental Health, Psychopharmacology Research
Branch, Division of Extramural Research Programs.
Haijma, S. V., Van Haren, N., Cahn, W., Koolschijn, P.
C. M. P., Hulshoff Pol, H. E., & Kahn, R. S. (2012).
Brain volumes in schizophrenia: A meta-analysis in
over 18 000 subjects. Schizophrenia Bulletin, 39
(5), 1129–1138.
Hall, W., Bergman, C., McNamara, A., & Sorensen, J.
(2007). Harm reduction guide to coming off psychi-
atric drugs: NY, NY: The Icarus Project.
Hansson, L. (2006). Determinants of quality of life in
people with severe mental illness. Acta Psychiatrica
Scandinavica, 113, 46–50.
Harding, C. M., Brooks, G. W., Ashikaga, T., Strauss,
J. S., & Breier, A. (1987). The Vermont longitudi-
nal study of persons with severe mental illness, II:
Long-term outcome of subjects who retrospectively
met DSM-III criteria for schizophrenia. American
Journal of Psychiatry, 144 (6), 727–735.
Haro, J., Kamath, S., Ochoa, S., Novick, D., Rele, K.,
Fargas, A., . . . Kharbeng, A. (2003). The Clinical
Global Impression–Schizophrenia scale: A simple
instrument to measure the diversity of symptoms
present in schizophrenia. Acta Psychiatrica Scandi-
navica, 107 (s416), 16–23.
Healy, D. (2009). Trussed in evidence? Ambiguities at
the interface between clinical evidence and clinical
practice. Transcultural Psychiatry, 46 (1), 16–37.
258 ■ PPP / Vol. 26, No. 3 / September 2019
Hirsch, L., Yang, J., Bresee, L., Jette, N., Patten, S., &
Pringsheim, T. (2017). Second-generation antipsy-
chotics and metabolic side effects: A systematic re-
view of population-based studies. Drug Safety, 1–11.
Hoffman, G. A., & Zachar, P. (2017). RDoC’s meta-
physical assumptions: Problems and promises.
Extraordinary Science: Responding to the Crisis in
Psychiatric Research, 59–86.
Holloway, F., & Carson, J. (1999). Subjective quality
of life, psychopathology, satisfaction with care and
insight: An exploratory study. International Journal
of Social Psychiatry, 45 (4), 259–267.
Huppert, J. D., & Smith, T. E. (2001). Longitudinal
analysis of subjective quality of life in schizophrenia:
Anxiety as the best symptom predictor. Journal of
Nervous and Mental Disease, 189 (10), 669–675.
Insel, T., Cuthbert, B., Garvey, M., Heinssen, R., Ko-
zak, M., Pine, D. S., . . . Wang, P. (2010). Research
Domain Criteria (RDoC): Toward a new classifica-
tion framework for research on mental disorders.
American Journal of Psychiatry, 167.
Insel, T. R. (ND). The anatomy of NIMH funding.
Available: www.nimh.nih.gov/funding/funding-
strategy-for-research-grants/white-paper_149362.
pdf. Accessed 1 June 2019.
Insel, T. R. (2009). Translating scientific opportunity
into public health impact: A strategic plan for re-
search on mental illness. Archives of General Psy-
chiatry, 66 (2), 128–133.
Insel, T. R. (2014). The NIMH Research Domain
Criteria (RDoC) Project: Precision medicine for
psychiatry. American Journal of Psychiatry, 171
(4), 395–397.
Isaac, M., Chand, P., & Murthy, P. (2007). Schizophre-
nia outcome measures in the wider international
community. British Journal of Psychiatry, 191 (50),
s71-s77.
Jaaskelainen, E., Juola, P., Hirvonen, N., McGrath, J.
J., Saha, S., Isohanni, M., . . . Miettunen, J. (2013).
A systematic review and meta-analysis of recovery
in schizophrenia. Schizophrenia Bulletin, 39 (6),
1296–1306.
Jablensky, A., Sartorius, N., Ernberg, G., Anker, M.,
Korten, A., Cooper, J. E., . . . Bertelsen, A. (1992).
Schizophrenia: Manifestations, incidence and course
in different cultures A World Health Organization
Ten-Country Study. Psychological Medicine Mono-
graph Supplement, 20, 1–97.
Jacobson, N., & Greenley, D. (2001). What is recovery?
A conceptual model and explication. Psychiatric
Services, 52 (4), 482–485.
Joukamaa, M., Heliövaara, M., Knekt, P., Aromaa, A.,
Raitasalo, R., & Lehtinen, V. (2006). Schizophrenia,
neuroleptic medication and mortality. British Journal
of Psychiatry, 188 (2), 122–127.
Kane, J. M., Robinson, D. G., Schooler, N. R., Mueser,
K. T., Penn, D. L., Rosenheck, R. A., . . . Heins-
sen, R. K. (2015). Comprehensive versus usual
community care for first-episode psychosis: 2-year
outcomes from the NIMH RAISE Early Treatment
Program. American Journal of Psychiatry, ap-
piajp201515050632.
Kawa, S., & Giordano, J. (2012). A brief historicity
of the Diagnostic and Statistical Manual of Mental
Disorders: Issues and implications for the future of
psychiatric canon and practice. Philosophy, Ethics,
and Humanities in Medicine, 7, 2–2.
Kay, S. R., Fiszbein, A., & Opfer, L. A. (1987). The
positive and negative syndrome scale (PANSS) for
schizophrenia. Schizophrenia Bulletin, 13 (2), 261.
Kendell, R., & Jablensky, A. (2003). Distinguishing
between the validity and utility of psychiatric diag-
noses. American Journal of Psychiatry, 160.
Kendler, K. S., & Schaffner, K. F. (2011). The dopa-
mine hypothesis of schizophrenia: An historical and
philosophical analysis. Philosophy, Psychiatry, and
Psychology, 18 (1), 41–63.
Kirmayer, L. J., & Crafa, D. (2014). What kind of sci-
ence for psychiatry? Frontiers in Human Neurosci-
ence, 8, 435.
Kozak, M. J., & Cuthbert, B. N. (2016). The NIMH
Research Domain Criteria initiative: Background,
issues, and pragmatics. Psychophysiology, 53 (3),
286–297.
Kraemer, H. C. (2015). Research Domain Criteria
(RDoC) and the DSM--Two methodological ap-
proaches to mental health diagnosis. JAMA Psychia-
try, 72 (12), 1163–1164.
Kuhn, T. S. (1970). The structure of scientific revolu-
tions, 2nd ed. Chicago: University of Chicago Press.
Kukla, M., Lysaker, P. H., & Roe, D. (2014). Strong
subjective recovery as a protective factor against the
effects of positive symptoms on quality of life out-
comes in schizophrenia. Comprehensive Psychiatry,
55 (6), 1363–1368.
Laursen, T. M. (2011). Life expectancy among persons
with schizophrenia or bipolar affective disorder.
Schizophrenia Research, 131 (1), 101–104.
Levine, S. Z., Goldberg, Y., Samara, M., Davis, J. M.,
& Leucht, S. (2015). Joint modeling of dropout and
outcome in three pivotal clinical trials of schizo-
phrenia. Schizophrenia Research, 164 (1), 122–126.
Liberman, R. P., Kopelowicz, A., Ventura, J., & Gut-
kind, D. (2002). Operational criteria and factors
related to recovery from schizophrenia. International
Review of Psychiatry, 14 (4), 256–272.
Maijer, K., Begemann, M., Palmen, S., Leucht, S., &
Sommer, I. (2017). Auditory hallucinations across
the lifespan: A systematic review and meta-analysis.
Psychological Medicine, 1–10.
Friesen / Does RDoC Pose a Threat? ■ 259
McCabe, R., Saidi, M., & Priebe, S. (2007). Patient-
reported outcomes in schizophrenia. British Journal
of Psychiatry, 191 (50), s21-s28.
Mead, S., & Copeland, M. E. (2000). What recovery
means to us: Consumers’ perspectives. Community
Mental Health Journal, 36 (3), 315–328.
Moilanen, J., Haapea, M., Miettunen, J., Jaaskelainen,
E., Veijola, J., Isohanni, M., & Koponen, H. (2013).
Characteristics of subjects with schizophrenia
spectrum disorder with and without antipsychotic
medication—A 10-year follow-up of the Northern
Finland 1966 Birth Cohort study. European Psychia-
try, 28 (1), 53–58.
Morris, S. E., & Cuthbert, B. N. (2012). Research
Domain Criteria: Cognitive systems, neural circuits,
and dimensions of behavior. Dialogues in Clinical
Neuroscience, 14 (1), 29–37.
Morrison, A. P., Shryane, N., Beck, R., Heffernan, S.,
Law, H., McCusker, M., & Bentall, R. P. (2013).
Psychosocial and neuropsychiatric predictors of sub-
jective recovery from psychosis. Psychiatry Research,
208 (3), 203–209.
Mortimer, A. M. (2007). Symptom rating scales and
outcome in schizophrenia. British Journal of Psy-
chiatry, 191 (50), s7-s14.
Mueser, K. T., Penn, D. L., Addington, J., Brunette,
M. F., Gingerich, S., Glynn, S. M., . . . Kane, J.
M. (2015). The NAVIGATE Program for FIRST-
EPISODE PSYCHOSIS: Rationale, overview, and
description of psychosocial components. Psychiatric
Services, 66 (7), 680–690.
Murray, R. M., Quattrone, D., Natesan, S., van Os, J.,
Nordentoft, M., Howes, O., . . . Taylor, D. (2016).
Should psychiatrists be more cautious about the
long-term prophylactic use of antipsychotics? British
Journal of Psychiatry, 209 (5), 361–365.
Olbert, C. M., Gala, G. J., & Tupler, L. A. (2014).
Quantifying heterogeneity attributable to polythetic
diagnostic criteria: Theoretical framework and em-
pirical application. Journal of Abnormal Psychology,
123 (2), 452–462.
Oorschot, M., Lataster, T., Thewissen, V., Lardinois,
M., van Os, J., Delespaul, P. A., & Myin-Germeys,
I. (2012). Symptomatic remission in psychosis and
real-life functioning. British Journal of Psychiatry,
201 (3), 215–220.
Overall, J. E., & Gorham, D. R. (1962). The brief
psychiatric rating scale. Psychological Reports, 10
(3), 799–812.
Poland, J., & Tekin, S. (2017). Introduction. In J. Po-
land & S. Tekin (Eds.), Extraordinary science and
psychiatry: Responses to the crisis in mental health
research. Cambridge, MA: MIT Press.
Priebe, S. (2007). Social outcomes in schizophrenia.
British Journal of Psychiatry, 191 (50), s15-s20.
Ralph, R. O., Kidder, K., & Phillips, D. (2000). Can
we measure recovery? A compendium of recovery
and recovery-related instruments. Washington, DC:
Evaluation Center@ HRSI.
Remington, G., Foussias, G., Fervaha, G., Agid, O.,
Takeuchi, H., Lee, J., & Hahn, M. (2016). Treat-
ing negative symptoms in schizophrenia: An up-
date. Current Treatment Options in Psychiatry, 3,
133–150.
Resnick, S. G., Rosenheck, R. A., & Lehman, A. F.
(2004). An exploratory analysis of correlates of
recovery. Psychiatric Services, 55 (5), 540–547.
Ritsner, M., Kurs, R., Gibel, A., Hirschmann, S.,
Shinkarenko, E., & Ratner, Y. (2003). Predictors
of quality of life in major psychoses: A naturalistic
follow-up study. Journal of Clinical Psychiatry, 64
(3), 308–315.
Rogers, E. S., & Rogers, E. S. (2017). Peer support
services: State of the workforce-state of the field in
the USA. Mental Health and Social Inclusion, 21
(3), 168–175.
Rose, D., Fleischmann, P., Wykes, T., Leese, M., &
Bindman, J. (2003). Patients perspectives on elec-
troconvulsive therapy: Systematic review. BMJ, 326
(7403), 1363.
Rosenheck, R., Stroup, S., Keefe, R. S., McEvoy, J.,
Swartz, M., Perkins, D., . . . Lieberman, J. (2005).
Measuring outcome priorities and preferences in
people with schizophrenia. The British Journal of
Psychiatry, 187 (6), 529–536.
Ruddle, A., Mason, O., & Wykes, T. (2011). A review
of hearing voices groups: Evidence and mechanisms
of change. Clinical Psychology Review, 31 (5),
757–766.
Saha, S., Chant, D., & McGrath, J. (2007). A systematic
review of mortality in schizophrenia: Is the differen-
tial mortality gap worsening over time? Archives of
General Psychiatry, 64 (10), 1123–1131.
Sendt, K.-V., Tracy, D. K., & Bhattacharyya, S. (2015).
A systematic review of factors influencing adherence
to antipsychotic medication in schizophrenia-spec-
trum disorders. Psychiatry Research, 225 (1), 14–30.
Silverstein, S. M., & Bellack, A. S. (2008). A scientific
agenda for the concept of recovery as it applies to
schizophrenia. Clinical Psychology Review, 28 (7),
1108–1124.
Simpson, E. L., & House, A. O. (2002). Involving us-
ers in the delivery and evaluation of mental health
services: systematic review. Bmj, 325(7375), 1265.
Strauss, J. S., Carpenter, W. T., & Jr. (1974). The pre-
diction of outcome in schizophrenia: II. relation-
ships between predictor and outcome variables: A
report from the WHO International Pilot Study of
Schizophrenia. Archives of General Psychiatry, 31
(1), 37–42.
260 ■ PPP / Vol. 26, No. 3 / September 2019
Strauss, J. S., & Carpenter, W. T., Jr. (1972). The predic-
tion of outcome in schizophrenia. I. Characteristics
of outcome. Archives of General Psychiatry, 27 (6),
739–746.
Su Ling, Y., Mark, T., & Stephen, M. L. (2014). “First
do no harm.” A systematic review of the prevalence
and management of antipsychotic adverse effects.
Journal of Psychopharmacology, 29 (4), 353–362.
Tabb, K. (2015). Psychiatric progress and the assump-
tion of diagnostic discrimination. Philosophy of
Science, 82 (5), 1047–1058.
Taylor, M., Cavanagh, J., Hodgson, R., & Tiihonen, J.
(2012). Examining the effectiveness of antipsychotic
medication in first-episode psychosis. J Psychophar-
macol, 26 (5 Suppl.), 27–32.
Tooth, B. A., Kalyanansundaram, V., & Glover, H.
(1997). Recovery from schizophrenia: A consumer
perspective. Final Report to Health and Human
Services Research and Development Grants Program
(RADGAC). Bethesda: NIH.
Van Eck, R. M., Burger, T. J., Vellinga, A., Schirm-
beck, F., & de Haan, L. (2017). The relationship
between clinical and personal recovery in patients
with schizophrenia spectrum disorders: A systematic
review and meta-analysis. Schizophrenia Bulletin,
sbx088-sbx088.
Vita, A., De Peri, L., Deste, G., Barlati, S., & Sacchetti,
E. (2015). The effect of antipsychotic treatment
on cortical gray matter changes in schizophrenia:
Does the class matter? A meta-analysis and meta-
regression of longitudinal magnetic resonance imag-
ing studies. Biological Psychiatry, 78 (6), 403–412.
Woodward, J. (2008). Cause and explanation in psy-
chiatry: An interventionist perspective. In K. S.
Kendler & J. Parnas (Eds.), Philosophical issues in
psychiatry: Explanation, phenomenology, and nosol-
ogy. Baltimore, MD: Johns Hopkins University Press.
Wunderink, L., Nieboer, R. M., Wiersma, D., Sytema,
S., & Nienhuis, F. J. (2013). Recovery in remitted
first-episode psychosis at 7 years of follow-up of an
early dose reduction/discontinuation or maintenance
treatment strategy: Long-term follow-up of a 2-year
randomized clinical trial. JAMA Psychiatry, 70 (9),
913–920.
