Received: 28 September 2022
Accepted: 4 March 2023
The Mental Illness‐Health Matrix and the
Mental State Space Matrix: Complementary
meta‐conceptual frameworks for evaluating
|Tyler J. VanderWeele
Department of Epidemiology, Harvard T. H.
Chan School of Public Health, Human
Flourishing Program, Harvard University,
Cambridge, MA, USA
Departments of Epidemiology and
Biostatistics, Harvard T. H. Chan School of
Public Health, Human Flourishing Program,
Harvard University, Cambridge, MA, USA
Objective: It is increasingly appreciated that mental health
may not just involve a relative absence of mental illness, but
the active presence of positive psychological desiderata.
However, research attention on mental illness and health
has tended to remain siloed and disconnected—proceeding
along parallel tracks—with their potential relationship under-
explored and undertheorized. As such, we sought to develop
theoretical models to help us better understand the interaction
of these two domains of experience.
Methods: Through extensive engagement with relevant
literature, we created two complementary meta‐conceptual
frameworks to represent and evaluate states of mental
illness and health.
Results: The Mental Illness‐Health Matrix allows different
forms of mental illness and health to be situated and
assessed within a common framework. The Mental State
Space Matrix further enables these various forms to be
conceptualized and appraised in terms of numerous
common parameters (e.g., valence and arousal).
Conclusion: It is hoped that these frameworks will stimulate
and support further research on the inter‐relational dynamics
of illness and health. Indeed, the matrices themselves are
provisional works‐in‐progress, with their articulation here
J Clin Psychol. 2023;1–19. wileyonlinelibrary.com/journal/jclp © 2023 Wiley Periodicals LLC.
intended as a foundation for their further development as
understanding of these topics evolves and improves.
flourishing, mental health, mental illness, well‐being
Since the field's inception, psychologists have been concerned with mental illness. Then, in more recent decades,
they have also been increasingly interested in mental health—not merely as an ostensible absence of illness, but the
active presence of certain psychological desiderata. These trends are exemplified in remarks by two of the seminal
figures historically most closely associated with illness and health. The field's traditional emphasis on illness was
captured by Freud, who saw the goal of psychotherapy as mainly limited to turning “hysterical misery into ordinary
unhappiness”(Breuer & Freud, 1955, p. 308). However, other voices such as William James were arguing that
relative freedom from illness was not the same as actively flourishing, and by the 1940s a new generation of
humanistic psychologists were urging psychology to focus on more positive phenomena, captured by notions like
self‐actualization. This vision was eloquently articulated by one of its main architects, Abraham Maslow (1962), who
said “It is as if Freud supplied us the sick half of psychology and we must now fill it out with the healthy half”(p. 5).
Likewise, pioneers such as Jahoda (1958) advocated a focus on “positive mental health,”a call embraced in recent
years by positive psychology especially. Yet despite this twin focus on mental illness and health in psychology, these
have tended to mostly remain separate and parallel tracks. However, there are now efforts to more closely explore
their interaction, as reflected in paradigms like “positive clinical psychology”(Seligman & Peterson, 2003; Wood &
Tarrier, 2010). In this vein, this paper introduces two new frameworks for understanding and assessing the
relationship between mental illness and health: the Mental Illness‐Health Matrix (MIH Matrix) and the Mental State
Space Matrix (MSS Matrix), which we consider in turn.
2|THE MENTAL ILLNESS HEALTH (MIH) MATRIX
This first section introduces the MIH Matrix. First, we provide some theoretical background to the framework in the
form of the “dual continua”model. Next, we outline the matrix itself. We then offer suggestions for how the matrix
might provide an overarching assessment of mental well‐being.
2.1 |The dual continua model
The concepts of mental illness and health are complex and contested, with ongoing debates regarding their
etiology, symptomology, and so on. Simply in descriptive terms though, mental illness tends to be identified by a
person experiencing various undesirable and/or unpleasant psychological phenomena for an extended duration,
usually accompanied by some psychosocial impairment. With mental health, the situation is slightly more complex.
Historically, and even in the present for some people, health has often just denoted a relative absence of illness.
However, over recent decades, various scholars—particularly those aligned with humanistic psychology, like
Maslow—have argued that beyond an absence of illness, mental well‐being also involves positive forms of health,
including the active presence of various desiderata. This case was made influentially by Herzlich (1973) vis‐à‐vis
physical health, where in contrast to the prevailing view of health as simply the absence of illness, she argued it can
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and should be seen in a positive light as “a presence of which one is fully aware because of one's feelings of
freedom and of bodily and functional well‐being”(p. 53). Her work has since been adapted for psychological
functioning, most prominently by Keyes (2002,2005,2014). Initially, efforts to highlight positive mental health
often invoked a continuum metaphor, spanning a negative and positive pole—representing illness and health,
respectively—with a neutral “zero”at mid‐point. This was reflected in Maslow's comment about the need to fill the
“healthy half”of psychology, and was influentially articulated by Keyes' (2002) paper, The Mental Health
Continuum: From Languishing to Flourishing in Life.
However, as generative as this metaphor has been, it is increasingly recognized as flawed. To begin with, it is
unidimensional, implying that a person is either in the negative territory of illness or the positive territory of health. Indeed,
Keyes (2002) himself recognized this limitation, arguing that illness and health are actually somewhat separate—
physiologically, functionally, experientially—and people can experience aspects of both concurrently. To that point, his
paper assessed the prevalence of major depression and positive mental health in 3032 American adults over 12 months.
Of the 511 who had experienced a major depressive episode (14.1% of the entire sample), 143 were deemed languishing
(lack of positive mental health), 259 had moderate mental health, and 27 had positive mental health. While the last
category is numerically small, it is conceptually significant, as it suggests the potential coexistence of mental illness and
health, at least within a given year. To reflect these nuances, Keyes (2005,2014) developed a “dual continua”model, with
separate spectra for illness and health, which visually could be placed orthogonally to create a bivariate state space, with a
horizontal axis of illness, and a vertical axis of health, as shown in Figure 1.
This model allows people to be situated in various quadrants. The best option is being without illness and positively
excelling (top right), which Keyes described as “flourishing,”but which we designate instead as “thriving.”This subtle
change is because, in our work, we use “flourishing”in a broader sense to encompass the person and their situational
context (i.e., to describe situations where both are doing well), whereas one could conceivably be in this top right
quadrant (i.e., thriving) despite one's context (Lomas & VanderWeele, 2022), as we consider further below. So, in the
narrower context of the model, thriving is the best option, preferable to being without illness yet not thriving (bottom
right), which we follow Keyes in calling “languishing,”or excelling while also experiencing illness (top left), which Keyes did
not label but we refer to as “struggling.”In turn, the latter are both preferable to the worst permutation of being ill while
also not doing well (bottom left), which we label “faltering.”Moreover, scholarship on the dual continua model has
increasingly recognized that assessments of mental illness/health would ideally not merely place people in one of these
four broad categories, but would allow more nuanced analyses (Iasiello et al., 2020). One option is to account for people's
relative position in these quadrants: with the top right quadrant, for example, the further along the axes one is, the better
one's thriving. While this approach is not harnessed in many studies—most of which simply assign people into the four
categories and compare the groups on various outcomes—one finds it, for example, in longitudinal work on individual
FIGURE 1 The dual continua model.
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change over time (e.g., Trompetter et al., 2017). Another option is to introduce greater taxonomical granularity by
increasing the number of categories. Indeed, Keyes himself differentiated mental health and illness into three levels (low,
moderate, high), creating a matrix of nine permutations. However, as useful as this bivariate (or triviariate) model is, the
picture is even more nuanced, as our next section considers.
First though, let us return to our point about distinguishing thriving from flourishing. This subtle differentiation
is grounded in the linguistic roots of these terms. The verb “to thrive”suggests attainment of well‐being potentially
regardless or even despite inhospitable conditions, as reflected in its etymology, having entered English around
1200 CE from a Scandinavian source akin to Old Norse þrifask, which implied “grasp to oneself.”One can still thrive,
of course, in hospitable conditions, but this is not required. By contrast, flourishing implies being supported by one's
environment, deriving as it does from the Latin florere (“to bloom, blossom, flower”). In this way, flourishing suggests
an adaptive interaction and consonance between the individual and their context, such that the latter helps people
within to prosper, and vice versa. Thus, flourishing makes a stronger claim about how a person is faring: not only are
they doing well (the necessary and sufficient criteria for thriving), but so is their environment. Thriving and
flourishing, therefore, can serve linguistically to subtly differentiate people: (a) doing well potentially without help or
even in the face of obstacles (i.e., thriving), versus (b) being actively supported by their environment (which itself is
also prospering). Significantly, recognition of the dynamics implied in this distinction is often downplayed in
psychology; as Prilleltensky et al. (2001, p. 157) observed, “we typically psychologize [people's] problems and ignore
the social and political context in which their problems occur.”Thus, distinguishing thriving from flourishing allows
an acknowledgment that people living in challenging circumstances cannot truly be said to be flourishing, no matter
their personal qualities. This is, of course, not to disparage people themselves, but rather the society in which they
live that permits such circumstances. Likewise, this view encourages a recognition that if societies wish their
citizens to truly live well, they cannot just leave this to people's own resources or regard this as solely an individual
affair, but instead must look to make the context as “salutogenic”(i.e., conducive to well‐being) as possible (e.g., see
Thompson et al., 2014, on this topic in relation to the community provision of green spaces).
This kind of contextual perspective is arguably often lacking in the field, so is much needed. A pervasive critique of
contemporary approaches to mental illness and health, and psychology generally, is a tendency toward individualism.
Stepping back, one might suggest this bias reflects and stems from the relatively individualistic nature of Western
cultures, which have historically influenced and indeed dominated the ways these disciplines have developed. This
history means that issues such as depression have tended to frequently be essentialized as conditions in people's minds/
brains (e.g., a “chemical imbalance”), rather than the complex product of the interaction between the person and their
environment, as per Prilleltensky et al.'s (2001) remark above. However, in part because of such critiques, there is now
greater awareness that social conditions generate variation and inequities in mental well‐being due to factors such as
identity. The “Minorities' Diminished Returns”theory, for instance, holds that the effects of socioeconomic indicators on
positive outcomes are systemically smaller for racial and ethnic minority groups, a trend attributed to economic and
psychological processes connected to racism and discrimination (Assari, 2018). For example, although education
influences mental health, both directly (e.g., a sense of accomplishment), and indirectly (e.g., via income), its “boosting
effect”in places like the United States is reduced for black people (and other minority groups), who experience higher
depression (Assari, 2017), suicide (Assari, 2015), and mortality (Assari & Lankarani, 2016), relative to equally educated
Moreover,thiskindofcriticalanalysisraisesimportantquestionsofwhatwemean by mental illness and health. Not
only are these outcomes influenced by people's sociocultural context, so are the very constructs through which we
understand illness and health. Such critiques take various forms. At a more extreme end are perspectives articulated by
the likes of Szasz (1962), who argued that mental illness is a “myth,”given that any such diagnoses are based on deviation
from social norms that in themselves may be inherently problematic (Benning, 2016). This view is encapsulated in a
remark attributed to Krishnamurti that “It is no measure of health to be well adjusted to a profoundly sick society.”In a
milder vein, even many scholars who assert the legitimacy of notions of mental illness and health recognize that the way
people experience and understand such states—and moreover the way therapeutic fields diagnose and treat them—is
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informed by the wider sociocultural context, with all these dynamics subject to contestation and change. One sees this,
for example, in relation to sadness, given that prolonged sadness (or “low mood”) is one symptom of depression according
to the Diagnostic and StatisticalManualofMentalDisorders,FifthEdition(DSM‐5). However, the psychiatric literature is
riven with debates on the appropriacy of such judgments. In the case of grief, for example, critics suggest that some
extended sadness is normal, and hence not an illness in any conventional sense (Horwitz, 2019). Similarly, even apart from
grieving, Horwitz and Wakefield (2007) have argued against the medicalization of “regular”sadness, instead advocating
regarding it as an inherent part of the human condition. The broader point here is that how mental illness and health are
experienced by people and understood by fields such as clinical psychology are subject to sociocultural dynamics. As
such, we have constructed our matrices with this critical spirit in mind, imbuing them with an openness and flexibility that
allows for these kinds of considerations.
2.2 |The MIH Matrix
Our understanding of mental well‐being has been enhanced by the recognition that illness and health are separate
realms, rather than a continuous spectrum. However, it has further been acknowledged that not only are illness and
health not continuous, but are not singular either, and themselves contain multiple continua. This recognition is
reflected in certain work on the dual‐continua model which, rather than the standard four categories discussed
above, has explored more granular profiles of mental illness and health. Khumalo et al. (2022), for example, used
confirmatory factor analysis and latent class analysis to test the model in relation to the Mental Health Continuum—
Short Form and Patient Health Questionnaire—9, and developed a profile featuring 23 different indicators, 9
pertaining to illness (loss of interest, depressed mood, sleep disturbance, fatigue, appetite change, self‐reproach,
concentration problems, psychomotor problems, and thoughts of suicide), and 14 to health (happiness, interest in
life, satisfaction, social contribution, social integration, social acceptance, social coherence, self‐acceptance,
environmental mastery, positive relations with others, personal growth, autonomy and purpose in life). While in
certain contexts the greater simplicity of the broad four‐category classification may be preferable, a more granular
approach inevitably provides a more detailed assessment of a person's mental illness and health.
As valuable as these more differentiated illness‐health profiles are though, there is scope for even further granularity.
In Khumalo et al.'s analysis, the illness components pertain specifically to depression, while the health aspects center
mainly on two specific forms of positive mental well‐being (hedonic and eudaimonic), together with some social
indicators. Yet with both mental illness and health, numerous other forms have been conceptualized. This differentiation
is already well established with mental illness. The DSM‐5 (APA, 2013), for example, includes 157 mental disorders,
aggregated into 20 categories. The picture for mental health is more opaque and contested, having not had comparable
attention to mental illness. Even so, recent years have seen a burgeoning effort to differentiate forms of positive health.
Most scholarship has focused on a widely accepted taxonomy of two main “types”: hedonic and eudaimonic. The former
is usually construed through the prism of “subjective well‐being”(Diener et al., 1999), which comprises two main
dimensions: cognitive (i.e., life satisfaction) and affective (i.e., positive affect). The latter derives from classical Greek
philosophy, particularly Aristotle (1986), who valorized it—in contrast to hedonic pleasure—as a deeper happiness arising
through self‐cultivation, defined as the “activity of the soul in accordance with virtue”(p. 11). Etymologically it means
having a good daimon (a guiding spirit, or perhaps from a modern perspective, one's conscience), and encompasses the
cultivation of character and commitment to ethical development. This form is sometimes operationalized as
“psychological well‐being,”following the pioneering work of Ryff's (1989), who identified six dimensions: self‐
acceptance; positive relations; autonomy; environmental mastery; purpose in life; and personal growth.
These two forms of health have received the vast majority of attention. Even so, scholars have suggested these
two do not exhaust the potential forms of mental well‐being. Seligman (2002), for instance, proposed “engagement”
as one of three “pathways”to mental well‐being—alongside hedonia and eudaimonia—encapsulating experiences
such absorption and flow (Csikszentmihalyi, 2013). Each is described by Schueller and Seligman (2010)as“neither
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sufficient nor redundant; therefore necessitating cultivation of each to achieve the full life”(p. 253). Moreover, even
these three may not comprehensively cover the relevant terrain. It is argued, for instance, that powerful
transcendent experiences—described using adjectives such as numinous, peak, and spiritual—are not easily
accommodated by the constructs above. As such, Wong (2011) suggests adding chaironic happiness—based on the
Greek chairo, which has meanings like gladness, joy, bliss, grace, and blessing—defined as “feeling blessed and
fortunate because of a sense of awe, gratitude, and oneness with nature or God”(p. 70). Moreover, the picture may
be more complicated still; indeed, we (Lomas & VanderWeele, 2023) have developed a taxonomy featuring 16
forms of mental health identified in the literature. While it is beyond our scope to dwell on its details, the salient
point is that mental health can be differentiated into numerous forms. Indeed, these too can, in turn, be
deconstructed into subforms or internal dimensions, as seen, for instance, in the way Ryff's (1989) analyses of
eudaimonia identified six dimensions of psychological well‐being.
As such, not only may illness and health constitute separate continua, in themselves they encompass numerous
dimensions, with a given person potentially doing poorly on some and better on others at any time. We have,
therefore, adapted the bivariate state‐space of the dual continua model into a multivariate MIH Matrix, shown in
Figure 2. This figure allows the depiction of 11 forms of illness and 11 forms of health, represented visually as 11
horizontal lines (denoted by letters a–k) and 11 vertical lines (numerals i–xi), respectively. Eleven is of course an
arbitrary number, just selected for the purposes of matching a scale from 0 to 10 (which has 11 integers), which can
be used to assess the forms of illness and health (as discussed next). After all, given that the DSM‐5 includes 157
different mental disorders, one could create a grid with 157 horizontal lines. Indeed, diagnoses for many disorders
FIGURE 2 The Mental Illness‐Health Matrix.
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involve numerous symptoms; as such, it would be possible to create an incredibly fine‐grained grid, potentially
involving separate lines for all individual psychiatric symptoms. Similarly, great granularity is possible with mental
health—though not to the same degree as mental illness—such as the 16 forms we identified (which in themselves
can be further deconstructed into subcomponents).
As such, in using this matrix, we would encourage clinicians and researchers to make it as granular as possible for
their particular needs. Indeed, in allowing and even encouraging such flexibility and adaptability, the matrix is sensitive to
the critical insights aired above—namely that the ways illness and health are experienced, conceptualized, and treated are
shaped by one's sociocultural context—while also remaining relevant to more conventional approaches. Clinicians and
scholars will have diverse views on this topic, from the more conservative (e.g., generally endorsing the ethos and details
of the DSM) to the more critical (e.g., embracing Szasz' notion of mental illness as “myth”). Crucially though, our matrix can
accommodate this range of perspectives. From a more conservative stance, one could simply structure the horizontal
illness aspect using the current DSM taxonomy. But from a critical perspective, even if one rejected the DSM taxonomy
entirely and replaced it with another framework, this could still be accommodated. The only exception would be if the
idea of psychological disorders was dismissed completely. However, it seems unlikely anyone would endorse that view;
even Szasz acknowledged people suffered from personal problems, which although not conceptualized as “illnesses”
could nevertheless be developed as a taxonomy and included in the matrix (in which case one might refer to mental
“issues”rather than “illnesses”). Thus, the matrix can accommodate different perspectives and taxonomies in relation to
mental illness and health. Moreover, it enables a scoring system that allows an overarching assessment of mental illness
and health, as we consider next.
2.3 |Mental Illness‐Health assessment
Besides facilitating a fine‐grained understanding of mental illness and health, the MIH Matrix also allows
assessment and quantification in that respect. For every form of illness (i.e., rows a–k) one could assign a number
from −10 to 0, and for every form of health (columns i–xi), a number from 0 to +10. How these numbers are actually
identified is an open question. Many scales and assessments exist for the various forms of mental illness and health.
In principle, in most cases, one could convert the assessment into a score on a 10‐point range, allowing it to be
situated on the matrix. We would ideally want the assessment to reflect the quadrants in how they denote either
the presence or absence of illness and health. With the horizontal illness axis, the left‐hand side of the matrix
(numbers −10 to −5) indicates the presence of illness, while the right‐hand side (−5 to 0) signifies its relative
absence. Conversely, with the vertical health axis, the bottom half of the matrix (0–5) represents the relative
absence of health, while the top half (5–10) denotes its presence. The question is, how do we convert a continuum
into a categorical assessment (i.e., presence or absence of illness or health)?
For certain aspects of mental illness which have been codified into specific disorders, anything lower than −5
could signify the point a person crosses the boundary from technically not being diagnosed as having an illness (the
−5 to 0 range)—even if they experience some symptoms—to being diagnosed with it (the −10 to −5 range). In the
case of major depression, for instance, the DSM states a person must experience five or more out of eight
symptoms during the same 2‐week period to warrant a diagnosis. In terms of the matrix, meeting these diagnostic
criteria could place a person in the left‐hand territory (−10 to −5) of having that illness; conversely, not meeting the
criteria yet still having some symptoms could situate them in the right‐hand territory (−5 to 0) of not technically
having depression, yet experiencing aspects of it. Similarly, with mental health, although the field has not
progressed to the point where one is “diagnosed”as having particular forms, the +5 mark could mark the transition
from having only minimal levels of a given type (0 to +5), hence not attaining mental health per se in that regard, to
being positively deemed to be attaining it (+5 to +10).
In this way, the MIH Matrix could create a detailed summary of a person's mental well‐being. For each form of
illness and health, a person could be assessed on that outcome—as discussed above with depression—thereby
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plotting their location along that line. One could even assign an overall score situating them broadly in one of the
four quadrants of the dual continua model. This would involve creating composite scores for both illness and health,
with their intersection locating the person somewhere in the bivariate state space. Taking first mental illness, say a
hypothetical person receives a score of −2 for depression (line a). As noted above, this would constitute not actually
being diagnosed with this disorder (with such a diagnosis taking the person into −10 to −5 territory), and would
reflect a relatively low presence of symptomology (with a total absence of depression being a 0). This is joined by
assessments for 10 other common disorders (lines b–k), with respective scores of −1, −4, −6, −5, −2, −3, −2, −1, and
−2. An overall composite score for mental illness would, therefore, be their mean value of −2.5, broadly situating the
person in the right hand of Figure 1: a relative absence of mental illness (i.e., averaged across the forms, even
though the person registered −6 with one specific form, so would technically have that one kind). One would
similarly ascertain their scores for 11 forms of mental health, and again calculate the mean to obtain an overall
score. Suppose this produces a health score of 6.8 (e.g., 8, 7, 5, 9, 4, 7, 6, 8, 7, 5, 9). The intersection of −2.6 for
illness and 6.4 for health would locate the person well within the top‐right thriving quadrant.
Moreover, the matrix further allows graphical representations of a person's overall mental illness and health, as
showninFigure3. In terms of health, one could plot the points on the vertical axes (i.e., upward lines spanning i–xi) using
upward‐pointing arrows, and connect these to produce a jagged horizontal line denoting the relative presence or absence
of mental health. One could also create a horizontal rectangle, shaded in light gray, whose upper and lower borders
correspond to the minimum and maximum of the mental health scores across all dimensions, indicating the range of
mental health. Additionally, one could plot a straight thick dashed horizontal line signifying the average mental health
FIGURE 3 An example of the Mental Illness‐Health Matrix assessment.
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score. One could likewise map all points on the horizontal axes (i.e., left‐to‐right lines spanning a–k) using left‐to‐right
arrows, and connect them to produce a jagged vertical line denoting the relative presence or absence of mental illness.
One could similarly also create a vertical rectangle, shaded darker gray, whose left‐hand and right‐hand borders
correspond to the maximum and minimum scores across all dimensions to show the range of mental illness. Finally, one
could plot a straight thick dashed vertical line corresponding to the average mental illness score. The two straight thick
dashed lines would intersect at the point of the matrix (−2.5, 6.8) in the upper right quadrant corresponding to the
average scores in each of the composite health‐illness dimensions.
We acknowledge that while this exercise might be helpful in seeing and understanding both the multidimensional
nature, and also possible coexistence, of mental illness and health, it is of course, a crude approximation. Most if not all
forms of mental illness (e.g., depression) and health (e.g., eudaimonia) are multidimensional and may be experienced in
different ways with varying symptoms. As such, any given MIH Matrix configuration is necessarily selective—greater
granularity and additional dimensions will always be possible. Even so, with that limitation in mind, the matrix provides a
helpful framework to visualize the complex multidimensional nature of mental illness and health. However, while it allows
the representation and assessment of mental illness and health, it still leaves open the question of what it means to
experience one state versus another, and how—in fine‐grained detail—we might view differences between states. The
second matrix is designed to address these issues.
3|THE MENTAL STATE SPACE (MSS) MATRIX
Our second framework for understanding mental states is the MSS Matrix. As per the MIH Matrix, it conceptualizes
mental states along numerous dimensions. However, instead of these constituting different forms of illness and
health, the MSS Matrix allows us to hypothesize the construction of illness and health out of various other
parameters. We begin by providing some context regarding the theoretical background to the MSS Matrix, namely
Fell's (2004)“state space”approach. Next, we introduce the MSS Matrix itself, followed by a metaphor for how one
might construe its operation.
3.1 |The state space approach
The inspiration for the MSS Matrix is Fell's state space model. This model is situated in the “neural correlates of
consciousness”paradigm, which examines associations between “mind”(e.g., subjective mental states of qualia) and
“body”(e.g., objective neurophysiological brain states). Their relationship remains poorly understood, and is still, at
some level, considered by most to be mysterious. This paradigm cannot yet establish causality, for instance. Mental
states certainly seem to depend—“supervene”in philosophical terminology—on brain states for their existence.
However, the brain is perhaps better seen as the physiological architecture or mechanism by which mind is
instantiated, rather than its cause, as for instance elucidated by Lomas et al. (2022) vis‐à‐vis happiness. Positive
affect, for example, has been associated with neurotransmitters like dopamine and serotonin. But its cause may be a
smile from a loved one. Indeed, from one perspective, mind and body could be regarded as two sides of the same
coin: mind is the body/brain experienced from the “inside,”and the body/brain is the mind observed from “outside”
(Nagel, 2012). In any case, while not yet able to ascertain causality, the neural correlates of consciousness paradigm
is based on the notion that any given subjective state of mind is accompanied by an associated objective brain state.
In Fell's model, both subjective mind and objective brain constitute state spaces of ndimensions (i.e., any
number of dimensions). The n‐dimensional state‐space of the mind is intended to map or approximate every
possible quale: all thoughts, feelings, emotions, sensations, perceptions, and other phenomena a human is capable
of experiencing. A given experiential state will, therefore, occupy a specific “location”somewhere in this n‐
dimensional phenomenological state‐space. This location will then correlate with a comparable location in the n‐
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dimensional physiological state‐space of the brain. Consider, for example, a state of joy. According to the model,
this experience is constituted by the configuration of a person's mental state‐space along many dimensions (e.g.,
valence, arousal), which then correlates with an analogous neurophysiological state‐space configuration pertaining
to neural processes (such as activation of specific brain regions and release of certain neurotransmitters). Should the
configurations change in any way—a lessening of subjective intensity say, accompanied by concomitant reduction in
the analogous brain‐state dimension—the feeling of joy would likewise change, shifting perhaps into a less aroused
state recognized as “contentment.”
However, Fell's theory does not adumbrate which dimensions might configure the mental or neurophysiological
state spaces, so ascertaining these is an open empirical question and a topic for future research. In that respect, our
MSS Matrix offers an initial foundation for such work by suggesting some likely candidates, though any
enumeration will always at best be an approximation. Thus, drawing on diverse psychological literature pertaining to
the mind, we focus on the possible parameters of the mental state space. Then, per the neural correlates of
consciousness paradigm, future work would ideally explore the equivalent neurophysiological parameters of the
brain state space, as considered in the conclusion.
3.2 |The MSS Matrix
There are many possible parameters for configuring the mental state spaces, but we can start with two of the most well‐
studied and conceptualized, valence and arousal. These are central to Russell's (1980) influential circumplex model of
affective states, which holds that such states are generated through the interaction of two independent
neurophysiological systems: valence (i.e., pleasant vs. unpleasant) and arousal (i.e., high vs. low, or active vs. passive)
(J. Posner et al., 2005). With valence, Cacioppo and Berntson's (1994) model suggests that rather than a bipolar
continuum, affect involves a bivariate space, with positive and negative valence being independent. Nevertheless,
regardless of the underlying mechanisms, valence is one dimension of the circumplex model, with affective states
evaluated as if on a spectrum (most negative to most positive). The second dimension is arousal, sometimes interpreted as
the “activation”in the central nervous system (from sleep/sleepiness to intense energy/excitement). Juxtaposing these
dimensions creates a two‐dimensional state space with four affective quadrants: low arousal and negative valence (e.g.,
depression); high arousal and negative valence (e.g., anxiety); low arousal and positive valence (e.g., calmness); and high
arousal and positive valence (e.g., elation). However, arousal and valence are not the only possible parameters on which
one can differentiate affective experiences, and certainly not forqualiamorebroadly(i.e.,allexperientialstates).Assuch,
here we identify other potential candidates, drawing on ideas across psychology.
We can first bring conceptual order to the kaleidoscope of possibilities by drawing on a theoretical framework of
psychological dynamics proposed by Lomas et al. (2015). The salient point about their framework is it differentiates
mental functioning and behavior into five broad heuristic levels (which overlap and are interconnected): consciousness,
emotions, cognitions, physicality, and behavior. Each, moreover, can be subjected internally to varying levels of
differentiation. For instance, one way of looking at consciousness is through the construct of attention. Thus, attention
could be one parameter of the mental state space which, construed simply, could specify how attentive one is at a given
proposes three functionally distinct neural networks: sustained attention (ongoing readiness for processing stimuli),
selective attention (allocation of resources to specific stimuli), and executive attention (monitoring/selecting from
competing stimuli). One could conceivably have a state space dimension for each component. Moreover, attention—
whether conceived unitarily or modularly—does not exhaust the granularity of consciousness. Other relevant concepts
include: awareness—from unconscious to maximally alert/awake (Morin, 2006); self‐presence—how self‐conscious versus
selfless (Millière, 2020); mindfulness—how mindfully “present”(Kabat‐Zinn, 2003); interoceptive awareness—how aware
of the internal state of one's body (Tsakiris & Critchley, 2016); vividness—how sharp and detailed the contents of
attention (Todd et al., 2012); esthetics—how beautiful the contents (Tylka & Iannantuono, 2016); and directionality—
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whetherfocusedoninnerqualiaorouterstimuli(Shaw,1996). Even these possibilities do not exhaust the potential
contours of consciousness, but are enough for now (and more than suffice to make the point).
It is beyond our scope to fully delve into the potential dimensions of the MSS Matrix in all their depth and
complexity. After all, each proposed dimension could itself warrant an entire paper devoted to it, as indeed the citations
provided for each dimension have done. Moreover, we cannot even exhaustively elucidate all possible dimensions:
ascertaining these, and moreover studying each in depth—particularly in terms of identifying potential correlates in the
neurophysiological state space of the brain—will be a key goal of future research. Nevertheless, we can briefly suggest
some likely dimensions to show the scope and potential of the MSS Matrix. After consciousness, the next “tier”is
emotions, within which we could include valence and arousal, as well as qualities like embodiment—the extent to which
mental states are felt throughout the body, as opposed to being more “in the head”(Coello & Fischer, 2016). Under
cognitions we could include: discursivity—how relatively full or empty the mind is of thought, and the extent to which this
thought is articulated in words (Bar et al., 2007); valence—how positive or negative the thoughts (Hogendoorn
et al., 2010); self‐referentiality—the extent to which thoughts concern the self (Northoff et al., 2006); abstractness—how
concrete or abstract the thoughts (Lehmann et al., 2010); significance—how important or consequential their content
(Lyhne & Kørnøv, 2013); meaningfulness—how personally meaningful (Steger et al., 2008); and memoriality—the extent to
which thoughts invoke/involve memories (Mildner & Tamir, 2019).
Next, under physicality, we could put attributes like: action—how much physical activity is involved in the state
(Schutz et al., 2001); labor—how arduous the action (Trudeau et al., 2015); and skilfulness—level of skill involved
(Hildenbrand & Sanchez, 2022). Then, under behavior, we can put appraisals like: aspiration—the extent to which
the state reflects progress toward some goal (Harkin et al., 2016); achievement—how indicative of achieving a goal
(Gollwitzer & Sheeran, 2006); value alignment—how much it resonates with one's values (Veage et al., 2014); and
moral worth (Nash et al., 2013). Finally, we could have parameters for the dynamics of the state itself, such
as: duration—how long‐lasting (Klostermann & Moeinirad, 2020); frequency—how often one has this experience
(Clare et al., 2012); complexity—how complex and multifaceted (Martinon et al., 2019); agency—how in control of
their experience people feel (Tapal et al., 2017); and numinosity—the degree to which the state feels qualitatively
special and different from “ordinary”experiences (Underwood & Teresi, 2002).
3.3 |The MSS Matrix Mixing Desk
We suggest that any particular form of mental illness or health—and any experiential state more generally—could be
defined by a specific position on all the myriad dimensions above (all of which are hypothesized to correlate with an
associated neurophysiological dimension). A good way to appreciate these dynamics is through a musical metaphor,
specifically a mixing desk. This is a piece of hardware or software that allows sound engineers to manipulate the sound of
a given musical set up (e.g., a band), either in a live performance or recording session. The signal for each instrument or
voice feeds into the desk (e.g., via a microphone), with each having its own “channel.”Thus, with each instrument or voice,
the engineer can adjust its volume—and other acoustical properties, like tone—as required to obtain a good overall sound.
So, we might construe the various MSS Matrix dimensions as different channels on a mixing desk, as per Figure 4,with
the specific state of that dimension represented by its volume level. Just as we imagined the dimensions of the MIH
Matrix on a standardized 0–10 scale, so might we picture any given channel as having a volume from 0 to 10. In some
instances, 0–10 will represent the minimal and maximal level of a given quality (i.e., 0 its absence/inactivation, and 10 its
maximal possible expression). In other cases, 0–10 represent poles of a particular spectrum (e.g., valence). In both cases, a
given state could be situated somewhere along that particular dimension, with the state as a whole constituting a unique
configuration of the mixing desk. This is currently only a hypothesis though, and will require substantiating by future
research, as we consider further in our concluding section.
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FIGURE 4 The Mental State Space Matrix Mixing desk.
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4|CONCLUSION, LIMITATIONS, AND FUTURE DIRECTIONS
This paper has proposed two related frameworks for understanding and assessing mental illness and health. First,
the MIH Matrix allows an appreciation that both mental illness and health are in themselves multidimensional, and a
person could experience various forms of both to varying degrees at a given time. Thus, the matrix positions types
of illness and health as horizontal versus vertical dimensions, respectively, enabling an overarching summary of
one's overall well‐being upon these dimensions collectively. The MIH Matrix is augmented by the MSS Matrix,
which is also multidimensional, but instead of the dimensions constituting different forms of illness and health
allows us to hypothesize the construction of illness and health out of various other parameters. To that end, we
proposed 30 possible parameters, though we acknowledge that our selections are purely conceptual, and any actual
mapping requires exploration in future research. In that respect, we conclude by offering suggestions for such
research (as well as work on the MIH Matrix), doing so through the prism of also considering the potential clinical
“pay off”for harnessing the matrices. We submit that the benefits could be manifold, including improving scientific
validity, understanding, and clinical care. Let us briefly consider these in turn.
First, the MIH Matrix, in particular, offers the possibility for enhanced scientific validity regarding the
constructs and measures through which mental illness and health are understood. An especially promising line of
research could involve, (a) construct validation in clinical settings (e.g., factor analytic research involving
psychometric measures of illness and health), (b) person‐centered research (e.g., latent profile analyses to develop
individualized profiles of mental well‐being), and even ideally (c) a combination of (a) and (b). Considerable progress
has already been made using these approaches. With (a), for example, Iasiello et al. (2022) conducted a meta‐
analysis of 46 studies that used the Mental Health Continuum—Short Form, and found the scale provides a robust
measure of general mental well‐being, tapping into emotional, social, and psychological aspects of well‐being in
both general and clinical populations. We are also seeing inroads using a person‐centered approach, some of which
also combine construct validation, as per Khumalo et al.'s (2022) analysis above. However, the matrices have the
potential to further enhance this line of research. Recall that Khumalo et al.'s work featured 23 indicators, 14
regarding mental health (mainly focusing on hedonic and eudaimonic well‐being), and 9 pertaining to illness
(focusing on depression). While such granularity is a good start, there are many other relevant indicators, as
discussed above, which would also be worth including in the MIH Matrix. As such, future research on this matrix
could ideally assemble a detailed and exhaustive taxonomy of all proposed forms of mental illness (e.g., spanning
the gamut of the DSM) and health (e.g., taking into account the wealth of emergent constructs in the relevant
literature)—a list of indicators which may well run into the hundreds—and conduct the kind of analysis exemplified
by Khumalo et al.
The matrices also have the power to enhance our understanding of mental illness and health. This is particularly
so with the MSS Matrix. While the MIH Matrix has great potential in developing our overall taxonomy of illness and
health, it may not necessarily constitute a radical advance in this area, but rather a complexification and refinement
of existing efforts (such as the dual continua model). By contrast, we suggest the MSS Matrix offers a truly new and
innovative perspective on mental illness and health that could greatly enhance our understanding of these topics.
Fruitful lines of enquiry in that regard might involve, (a) qualitative research, (b) neurophysiological analysis, and
even (c) a combination (as per the neurophenomenology paradigm). With (a), for example, people could be recruited
based on having a given type of mental illness or health. In‐depth interviews could be conducted about these states,
in which each MSS Matrix dimension is systematically asked about (e.g., open questions like “Tell us about the
quality of your attention, such as your level of distraction or focus”). The results could be analyzed using
Interpretative Phenomenological Analysis (Smith, 2011), which facilitates in‐depth exploration of subjectivity. Such
work could be augmented by other qualitative methods, like Online Photovoice, a participatory action technique
where participants take and narrate photographs to share their experiences and perspectives (e.g., Tanhan &
Strack, 2020). Similarly, with (b), people currently experiencing a given type of illness or health could be assessed
using neurophysiological techniques (e.g., EEG) to assess the biological contours of these states (see e.g., Lomas,
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Ivtzan, et al., 2015, for a review of such work in relation to mindfulness). The neurophenomenology paradigm then
brings (a) and (b) together to provide further insights, where neurophysiological analysis of a mental state can be
matched to detailed subjective descriptions of that state, allowing more fine‐grained and nuanced analysis of its
mental dynamics. In this way, one could identify the MSS Matrix contours of different states of mental illness and
Finally, the matrices have the potential to improve clinical care in various ways. For a start, they can help
practitioners appreciate different trajectories of client change and tailor clinical treatments accordingly. Recent
years have seen increased acknowledgment of the value of moving away from the variable‐centered approach (i.e.,
explaining relationships between specific variables in a population) that has dominated mental illness/health work
over recent decades, and toward approaches that are person‐centered (i.e., analyzing subgroups of similar subjects
within a population) and person‐specific (i.e., explaining relationships between variables in a subject) (Howard &
Hoffman, 2018). Central to the latter paradigms is an appreciation of the idiosyncratic complexity of experiences
and trajectories of mental illness and health, and that clinical treatment and interaction need to be personalized
accordingly. To that end, research is progressing toward creating more individualized profiles of people's mental
states, as discussed above. In that respect, the matrices offer a step‐change in these kinds of personalized profile:
with its focus on different types of mental illness/health, the MIH Matrix allows mental well‐being to be assessed
with unprecedented granularity, creating a unique profile for a given person; similarly, in focusing on different
elements of experience, the MSS Matrix enables mental states to be understood and analyzed with nuance and
precision. Of course, as noted, much more work is needed to identify and substantiate the details of the matrices,
including the different forms of illness/health for the MIH Matrix, and the various mental parameters for MSS
Matrix. So, as work on the matrices progresses, they will be increasingly useful in person‐centered and person‐
Moreover, even in their current nascent state, these matrices could inform current clinical practice. As it stands,
the MIH matrix already has potential in terms of encouraging clinicians to harness techniques to promote positive
mental health. Indeed, it is now 20 years since Seligman and Peterson (2003) mooted the idea of “positive clinical
psychology.”Since then, this approach has proved relatively effective,characterized broadly by taking concepts and
interventions that initially had success in promoting mental health among nonclinical populations (see e.g., Sin &
Lyubomirsky, 2009; White et al., 2019, Koydemir et al., 2021, and van Dierendonck & Lam, 2022, for meta‐
analyses), and applying these in a clinical context (see e.g., Carr et al., 2021, Geerling et al., 2020, Pina et al., 2021,
and Pan et al., 2022, for meta‐analyses). Such activities range from exercises involving specific qualities such as
gratitude, to more involved courses featuring numerous elements, such as “well‐being therapy”(Fava et al., 1998;
Guidi & Fava, 2021). However, despite this emergent literature, it remains a relatively niche concern; for instance,
while a search on Google Scholar in February 2023 shows that since the start of 2022 there have been 35,300
articles published with the phrase “clinical psychology,”there are only 387 featuring “positive clinical psychology,”
suggesting only around one in a hundred papers is considering the topic. This is understandable, given that a focus
on mental illness is a prerogative and defining feature of clinical psychology; as such, one can hardly expect the field
to have anywhere near an equal focus on mental illness and health (i.e., on the vertical and horizontal aspects of the
MIH Matrix). Nevertheless, we would encourage all clinicians to include at least some consideration of mental
health dimensions in their assessment and treatment of clients. Admittedly, understanding of the terrain of mental
health lags many decades behind that of mental illness, given that the latter has well‐established taxonomies (e.g.,
the DSM‐5) and treatment protocols, and the former is still in its early phases of being conceptualized and
categorized. Even so, certain aspects of mental health have received extensive study and validation, and have been
shown to be very relevant in clinical settings.
Perhaps the prime example is Ryff's (1989) framework of psychological well‐being (PWB) (see Joseph &
Wood, 2010; for a review). Not only is PWB strongly correlated with depression, it appears to be a risk factor in its
etiology: in a 10‐year cohort study looking at the onset of clinical depression in over 5500 people in middle age,
Wood and Joseph (2010) found people low in PWB were over seven times more likely to meet clinical cut‐offs for
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depression 10 years later, and even with very conservative control variables (including initial depression,
personality, demographic, economic, and physical health variables) were still more than twice as likely to be
depressed 10 years later. Thus, they argue that even if middle‐aged people with low PWB do not currently meet
diagnostic criteria for depression, low PWB is a “time bomb”likely to lead to this in older age. At the very least then,
clinicians could assess clients in relation to PWB using the scales developed in Ryff's original work. But beyond that,
practices have been developed to help clients in clinical settings cultivate PWB, most prominently well‐being
therapy (Fava et al., 1998; Guidi & Fava, 2021). This includes, for instance, techniques to help people develop
greater meaning and purpose in life (a key dimension of PWB). As such, even while we wait for the terrain of
positive mental health—the vertical dimensions of the MIH Matrix—to be studied and charted in greater detail,
certain elements such as PWB are already well‐established. So, even as it stands, we encourage clinicians to engage
at least with the notion of PWB, at a minimum assessing this in clients, and more ambitiously harnessing tools like
well‐being therapy to promote it.
With the MSS Matrix, its current clinical potentials are less well‐defined or self‐evident. The MIH Matrix builds
on decades of scholarship emphasizing the importance of augmenting a clinical focus on mental illness with
attention to positive mental health. By contrast, the MSS Matrix is far newer and less well‐grounded in existing
clinical literature. Nevertheless, even without yet having been fully formalized or substantiated, it could still be
useful in clinical settings. For instance, its dimensions could serve as helpful prompts or discussion points in clinical
sessions, augmenting the standard protocol of enquiring about particular symptoms, and empowering clinicians to
explore people's experiences in terms of the MSS Matrix dimensions. The current iteration of the matrix includes 30
parameters, each of which could function as a generative question about a person's recent experience (either
specific events or a general state of affairs over a given period). There are seven dimensions pertaining to
consciousness, for example, which collectively would give an insight into a person's state of attention and
awareness. In the case of vividness, say, one could ask, “how vivid was this experience, from very blurry to very
sharp?”This kind of questioning would then augment the standard clinical questioning focused around conventional
This would have various benefits, including, for instance, allowing more culturally contextualized interactions
and practices. As discussed above, from a critical perspective, the diagnostic categories in established clinical
taxonomies like the DSM can be regarded as cultural constructions that not all people or cultures may share (e.g.,
what is regarded as an illness in one cultural context may not be in another). In that respect, discussing such clients'
experiences through the prism of these taxonomies can potentially be problematic. Indeed, clinical psychology and
comparable fields are increasingly attuned to the need to develop more culturally sensitive practices (Benuto
et al., 2021). With that in mind, the MSS Matrix offers a framework that could be helpful in discussing clients'
experiences, since it is more normatively neutral and less valued‐loaded than the DSM. Rather than being
constructed in terms of symptoms—which already presupposes and imposes a frame of illness around a state—it
asks in more generic terms about the elements of a given experience. This would still allow clinicians to appraise and
understand clients' experiences in depth, yet in ways that can be more accommodating to cultural nuances and
other such contextual dynamics. As such, even while these matrices are just an early work‐in‐progress, we hope
they may already serve a purpose in helping the field better understand and treat experiences of mental illness, and
moreover make progress in appreciating and facilitating states of positive mental health.
DATA AVAILABILITY STATEMENT
Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.
The peer review history for this article is available at https://www.webofscience.com/api/gateway/wos/peer-
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How to cite this article: Lomas, T., & VanderWeele, T. J. (2023). The Mental Illness‐Health Matrix and the
Mental State Space Matrix: Complementary meta‐conceptual frameworks for evaluating psychological
states. Journal of Clinical Psychology,1–19. https://doi.org/10.1002/jclp.23512
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