Set-Point Theory and personality
development: Reconciliation of a
, Michael VonKorff
, Bertus F. Jeronimus
University Medical Center Groningen, University of Groningen, Groningen,
Group Health Research Institute, Group Health Cooperative,
Seattle, WA, United States
Personality: Developmental perspectives
Personality is defined as enduring differences between individuals in thoughts,
feelings, and behaviors that are not situation-specific (Specht, 2015). Personality
reflects the often unconscious, reflexive ways in which people respond to environ-
mental cues (Allport & Odbert, 1936; Magidson, Roberts, Collado-Rodriguez, &
Lejuez, 2014). Conventionally five high-order personality characteristics are identi-
fied (the “Big Five”): extraversion, neuroticism, agreeableness, conscientiousness,
and openness to experience (Kotov, Gamez, Schmidt, & Watson, 2010). Personality
is typically assessed by self-report questionnaire or interview (John, Robins, &
Pervin, 2008) using items with nonspecific descriptors of frequency, intensity, and
duration. For example, in the NEO-PI-3 (McCrae, Costa, Paul, & Martin, 2005) neu-
roticism is assessed with items like “I often worry about things that might happen”
or “sometimes I feel completely worthless.” Designed to capture the unique ways in
which people think, feel, and interact with others, these questionnaires indicate an
individual’s general level on a particular personality trait.
A popular developmental model is McCrae and Costa’s Five-Factor Theory (FFT) of
personality traits. It posits that personality traits follow a common life course trajec-
tory, viz. traits emerge early in life, reach maturity in young adulthood, followed by
a gradual change in response to age-related brain maturation, and changes in gene
expression (McCrae & Costa, 2003; McCrae, 2010). However, longitudinal evidence
indicates that people can differ substantially in these trajectories of personality
development and change across the lifespan (Luhmann, Orth, Specht, Kandler, &
Lucas, 2014; Roberts & DelVecchio, 2000; Roberts, Walton, & Viechtbauer, 2006).
Personality Development Across the Lifespan. DOI: http://dx.doi.org/10.1016/B978-0-12-804674-6.00009-0
©2017 Elsevier Inc. All rights reserved.
Nowadays theorists convene that personality trait changes are driven by both
genes and experiences (Plomin, DeFries, & Loehlin, 1977; Scarr & McCartney,
1983), but the exact processes underlying adult personality development remain
controversial (Cramer et al., 2012b; Roberts, Wood, & Caspi, 2008; Specht et al.,
2014). Several theories stress the significance of life experiences in personality sta-
bility and change (Jeronimus, Riese, Sanderman, & Ormel, 2014). The best known
is the neosocioanalytic theory or social investment principle, which emphasizes the
impact of social roles on personality, and posits that environmentally driven person-
ality changes may occur throughout life (Roberts & Wood, 2006, Roberts, Wood,
& Smith, 2005).
Another perspective emphasizing environmental influences is the set-point (or
dynamic equilibrium) model of traits, recently proposed by Ormel, Riese, and
Rosmalen (2012; but see also Fleeson & Gallagher, 2009;Fraley & Roberts, 2005;
Luhmann et al., 2014). According to this perspective, personality traits have a person-
specific set-point around which trait levels fluctuate in response to life experiences.
Thus personality levels can temporarily be changed by life experiences, but eventually
people return to their characteristic set-point level. Importantly, major life events or
enduring changes in social circumstances may also change the set-point of personality
traits for long periods of time or even permanently.
Another alternative, proposed by Cramer et al. (2012b), conceives personality as
a system (or network) of affective, cognitive, and behavioral elements. Rather than
a shared underlying factor producing covariance among these elements (as assumed
in the latent factor model of personality traits), the network model suggests that
these elements are causally interdependent (see Fig. 9.1). Personality dimensions
“emerge out of the connectivity structure that exists between the various compo-
nents of personality” (Cramer et al., 2012a, p. 414). The components are jointly
influenced by genetic and environmental forces, and therefore develop synchro-
nously. In factor analysis, the interconnectedness “produces” the latent factors.
Personality development and life experiences
That life experiences can be followed by small but meaningful changes in
personality is well established (Jeronimus et al., 2014; Luhmann et al., 2014;
Figure 9.1 Schematic presentation of two models of traits: the latent factor model (left) and
the dynamic system (or network) model (right).
118 Personality Development Across the Lifespan
Riese et al., 2014; Specht, Egloff, & Schmukle, 2011; Sutin, Costa, Wethington,
& Eaton, 2010). Changes in personality are also observed subsequent to age-
related developmental role transitions (Bleidorn et al., 2013; Lodi-Smith &
Roberts, 2007; Roberts & Mroczek, 2008). For example, Specht et al. (2011)
found that individuals who got married became more introverted while those
who separated from a poor marriage became more agreeable and conscientious.
Men, but not women, became more open after separation. Conscientiousness
declined after having a baby and after retirement, whereas it increased after
starting a first job. After death of a spouse, conscientiousness declined among
women whereas it increased among men. Marriage, remarriage, and experienc-
ing satisfying and engaging employment are all associated with decreases in
neuroticism. In contrast, conflict, poor relationship quality, and chronic or
repeated unemployment have been found to associate with increases in neuroti-
cism (Lucas, Clark, Georgellis, & Diener, 2004; Lu
¨dtke, Trautwein, &
Husemann, 2009; Robins, Caspi, & Moffitt, 2000). Exposure to personal illness
or injury reduced concordance of neuroticism among monozygotic twins
(Middeldorp, Cath, Beem, Willemsen, & Boomsma, 2008). Jeronimus and collea-
gues (2013, 2014) found small but persistent decreases in neuroticism after
positive life events.
Subjective well-being and set-point theory
Subjective Well-Being (SWB) is a well-studied construct that refers to how
people feel and think about their lives (Diener, 1984). Popular measures of SWB
include items like: “How satisfied are you with your life as a whole?” The SWB
construct involves a hybrid of affective judgments (how do I usually feel) and
cognitive assessments of satisfaction with life and its main domains (such as
work and relationships). There is an important distinction between the feelings
people experience and the judgments they make about their lives. In SWB
research, happiness, life satisfaction, and well-being are often conceptualized as
enduring traits (Cummins, 2015; Davern, Cummins, & Stokes, 2007). People
tion (Cummins, 2015), in a process that Kahneman (2011) calls the “affect
heuristic.” It is not surprising, then, that SWB is highly correlated with neuroti-
cism, extraversion, and, although less, conscientiousness (DeNeve & Cooper,
1998; Steel, Schmidt, & Shultz, 2008; Weiss, Bates, & Luciano, 2008).
Like personality traits, SWB shows substantial continuity over time (Lucas &
Donnellan, 2007). Long-term studies of SWB have yielded data that permit evalua-
tion of key hypotheses about the development of SWB and its determinants. While
research on dynamic changes in personality traits is limited, there are relevant theo-
retical constructs and empirical studies pertaining to SWB that can help evaluate the
stable and changing components of personality traits. Stability may be due to
119Set-Point Theory and personality development: Reconciliation of a paradox
genetic factors and other enduring influences, while change may be influenced by
the social environment and by shifts in a person’s physical or psychological health.
Research has not evaluated these dynamic processes for personality per se, but it has
for SWB. An important theoretical model that explains the relationship between the
stability and change of SWB is the set-point theory.
History of set-point theory
Set-point theory has its roots in the concept of physiological homeostasis. In
Canon’s (1932) classic essay, “The Wisdom of the Body,” set-point refers to steady
states of the body that are actively maintained by corrective physiological and
behavioral mechanisms (also referred to as negative feedback loops). This active
defense mechanism or dynamic compensation, generates a degree of stability in the
factor it regulates, such as blood pressure, body temperature, blood glucose level, or
weight (Keesey & Powley, 1986). Before that, psychologists Wundt and James had
transformed the then-dominant humor theory of temperament into a concept of
dimensional psychological traits, a theory that incorporated the principle of a fixed
internal milieu: a set-point with homeostasis (Dumont, 2010; Jeronimus, 2015). The
key feature of a set-point is that it defies change via compensatory mechanisms that
regulate short-term fluctuations caused by internal or external events back to their
typical state (i.e., set-point). Importantly, physiological set-points (e.g., blood pres-
sure) often change with age.
Set-point theory played a prominent role in SWB research over the past 40 years
because this idea of adaptation to changing environments could explain counterintui-
tive properties of SWB. For example, that gains in health, income, and relationships
only had temporary effects on SWB. This kind of adaptive processes also explained
the observation that people with substantial resources are, on average, not much hap-
pier than those with limited resources. Original SWB theories became therefore
founded on the idea that people’s levels of SWB change temporarily in anticipation
and response to life experiences, but do not permanently change (Brickman, Coates,
& Janoffbulman, 1978). This led some to conclude that “trying to be happier [may
Lykken & Tellegen, 1996,p.189).
Cummins (2010, 2015) explicitly argued that a set of psychological processes
actively control and maintain SWB in a manner analogous to the homeostatic main-
tenance of blood pressure or body temperature. These homeostatic processes apply
particularly to the affective component of SWB. The dynamic equilibrium theory of
SWB posits that this continuity in SWB is based on personality, especially neuroti-
cism and extraversion, whereas change is attributed to life experiences (Headey &
Wearing, 1989; Headey, 2006).
Recent revisions of set-point theory for SWB
The results from major longitudinal panel studies led to at least six significant revi-
sions in SWB set-point theory (Diener, Lucas, & Scollon, 2006; Headey, 2006,
120 Personality Development Across the Lifespan
2010; Luhmann, Hofmann, Eid, & Lucas, 2012) that merit discussion when imple-
menting a set-point theory for personality traits:
1. Personal set-point. Person-specific levels of SWB can be accurately predicted from per-
sonality traits. Fig. 9.2 illustrates three trajectories of SWB with personalized individual
2. Persistent negativity. The major components of SWB differ in terms of their set-point and
stability, most saliently that “negative affect” is more stable over increasing time intervals
than “positive affect” or “life satisfaction.”
3. Cultural differences. SWB levels and composition differ substantially between countries,
partly due to economic, social, and political characteristics (Diener & Diener, 1995;
4. Persistent changes in SWB. About 1530% of the population shows long-lasting changes
in SWB following life experiences and typically do not return to their previous baseline
levels within 35 years (Anusic, Yap, & Lucas, 2014; Luhmann et al., 2012). This holds
true in particular for major negative experiences such as disability, widowhood, unem-
ployment, or divorce.
5. Differences in adaptability. Initially SWB theorists assumed that people adapted in similar
ways. For example, Diener et al. (2006, p. 310) observed that, “If adaptation results from
automatic and inevitable homeostatic processes, then all individuals should return to neu-
trality or at least to their own unique baseline.” However, studies observed significant
individual differences in the rate and extent of adaptation after experiencing “objectively”
similar life events (see Fig. 9.2).
6. Differences in susceptibility. Trait stability is partly driven by the tendency of people to
repeatedly experience specific events (cf. corresponsive principle). So, life experiences
may not only cause disequilibrium in SWB, but personalityenvironment correlations
may also maintain stability (Headey & Wearing, 1989; Jeronimus et al., 2014; Ormel &
Schaufeli, 1991). Persistent within-subject changes in SWB may be partially explained by
individual differences in susceptibility to life experiences (see Fig. 9.3). For example, peo-
ple who combine high extraversion with low neuroticism levels may increase in SWB
whereas introverted but highly neurotic people may tend to decrease in SWB.
Personality psychology and set-point theory
Despite the popularity of set-point theory in the psychology of SWB, it has only
occasionally been applied in personality psychology (Costa & McCrae, 1980;
Figure 9.2 Trajectories of SWB of three individuals (A, B, C) with person-specific
set-points and susceptibilities.
121Set-Point Theory and personality development: Reconciliation of a paradox
Jeronimus et al., 2013; Lykken & Tellegen, 1996; Lykken, 2007; Ormel et al.,
2013; Vachon & Krueger, 2015). For example, Williams (1993) proposed a set-
point hypothesis to explain the stability of personality traits: “In this set-point
hypothesis, psychological function is treated as having a substantial basis in physi-
ology with a specified level and a surrounding ‘bandwidth’ of typical behavior for a
given individual [...] it is necessary to determine whether a prevailing personality
pattern, stable or otherwise, is actively defended by appropriate behavioral or psy-
chological adjustments” (p. 52).
Also the network perspective on personality traits describes people as functioning
within a relatively fixed region of a potentially large behavioral space, resulting in
stable states. The causally interconnected affective, cognitive, and behavioral ele-
ments are “in relative equilibrium with themselves and their environments” (Cramer
et al., 2012a, p. 416), suggesting sort of trait set-point. In the network perspective,
life experiences may support trait stability (as they influence the total complex of
elements) but can also induce personality change as the system finds an alternative
stable state (see “Alternative Explanations for Homeostatic Stable States” section).
Provided that SWB may be a manifestation of underlying personality traits, as
assumed in set-point theory, it seems timely to consider whether set-point theory
can help explain stability and change in personality traits over the lifespan.
Immutable, experience-dependent, and mixed
In considering the application of set-point theory to research on stability and change
of personality traits, it is useful to differentiate three set-point models (Ormel &
Rijsdijk, 2000; Ormel et al., 2012): (1) the immutable set-point model; (2) the
experience-dependent set-point model; and (3) the mixed set-point model.Fig. 9.4
depicts these three models. The time scale describing stability and change in these
models is measured in years, rather than days or weeks.
Figure 9.3 Four different within-subject trajectories of personality trait scores. Note: Capital
letters A, B, C, and D refer to each of the individuals; StoC 5sensitivity to context;
122 Personality Development Across the Lifespan
Immutable set-point model
The immutable set-point model posits that individual set-points of personality traits
are “set like plaster” (James, 1890). This notion of an immutable person-characteristic
set-point of personality traits is compatible with the “basic tendencies” in Costa and
McCrae’s classical (FFT) trait model (1990; McCrae, 2010), being both internally
determined and largely independent of environmental influences. In this model,
homeostatic forces keep an individual’s trait set-point constant over time. Deviations
Figure 9.4 (A) Immutable set-point model. Note:T5latent trait factor; O
scores at 5 waves. (B) Experience-dependent set-point model. Note:O
scores at 5 waves; S
5latent changing component; z
5influence of unobserved
determinants of change; b (if intervals are equal, these will typically be equal as well);
e5time-specific and measurement error variance. (C) Mixed set-point model. Note:
T5latent trait factor; O
5observed trait scores at 5 waves; S
5latent changing component;
e5measurement error variance; z
5influence of unobserved determinants of change in
changing component; b 5autoregression coefficient (if intervals are equal, these will
typically be equal as well).
123Set-Point Theory and personality development: Reconciliation of a paradox
from the set-point, which may be due to life experiences, are assumed to be temporal,
and levels eventually return to the set-point. Thus the immutable set-point model fits
both the FFT and genotypeenvironment theory of personality development.
The “environment perspectives” of personality development (e.g., neo-
socioanalytic model) are incompatible with an immutable set-point model, which
permits only temporary experience-driven changes. Also the “network perspective”
is definitely inconsistent with the immutable set-point model.
The statistical model that corresponds with the immutable set-point model is the
common factor model, which asserts that items on a trait scale and their summary
scores correlate over time because of underlying latent traits, which are essentially
immutable. The immutable set-point model predicts that testretest correlations are
virtually independent of the length of time between assessments. While the notion
of an immutable set-point fits the evidence of high stability of personality traits, it
is inconsistent with a large body of evidence showing a gradual but persistent
decline in the differential stability of personality traits over time and experience-
Experience-dependent set-point model
The experience-dependent set-point model posits that set-points can change over
the lifespan when impelled by life experiences with long-term behavioral conse-
quences. The experience-dependent model assumes that these consequences can
result in set-point change (see person C in Fig. 9.3) through three mechanisms,
viz. cognitive, biological, and environmental embedding. Cognitive embedding
occurs when such consequences lead to persistent alterations in beliefs about the
self and others and changes in the approach to appraising and coping with stress-
ful events (Laceulle, Jeronimus, Van Aken, & Ormel, 2015; Ormel & Rijsdijk,
2000). An example of biological embedding is when environmental factors trigger
chemic changes that activate or silence genes via epigenetic processes such as
DNA methylation and chromatin remodeling (Van der Knaap et al., 2015;
Weaver et al., 2004; Zhang & Meaney, 2010). Such epigenetic changes occur
most frequently early in life but continue to occur throughout the lifespan (Fraga
et al., 2005; Kanherkar, Bhatia-Dey, & Csoka, 2014). Biological embedding may
follow cognitive embedding if cognitive alterations bring about persistent changes
in the regulatory neurophysiological systems, e.g., via epigenetic processes
(McEwen, 2012; Zhang & Meaney, 2010). Environmental embedding occurs
when changes in behavioral repertoires become maintained by correspondingly
The statistical model that corresponds with environmentally dependent set-points
is the autoregressive (or simplex) model, which asserts ongoing cumulative differ-
ential change. That is, traits change continuously at a very slow rate. The autore-
gressive model predicts that testretest correlations decrease gradually over time,
theoretically declining toward a correlation of zero (Ormel & Rijsdijk, 2000;
Roberts & Jackson, 2008; Roberts & Mroczek, 2008).
124 Personality Development Across the Lifespan
Mixed set-point model
The mixed set-point model combines the previous two models and basically extends
on the experience-dependent set-point model by incorporating features of an
immutable set-point. The mixed model seeks to differentiate variation in personality
traits into a stable trait component (T, in Fig. 9.4C) and an in time varying compo-
nent (Si). In contrast to the experience-dependent model, the mixed model allows
for two possibilities. The first is that some people have (virtually) immutable set-
points but that other people’s set-points change. The second possibility is that the
trait set-point is complex, and has partly an immutable component and partly a
changing component. Thus changes in the set-point itself are possible in the mixed
model, for example, in response to long-term difficulties and marked altered life
circumstances. In contrast to the immutable set-point model, the mixed set-point
model assumes that differential stability correlations will fall with time but, due to
the enduring influence of stable personality components, will never reach zero,
something which is possible with the experience-dependent model.
Between-subject and within-subject models
These set-point models have been used primarily to analyze between-subject differ-
ences and cannot be directly generalized to understand within-subject changes
(Barlow & Nock, 2009; Molenaar, 2008; Van der Krieke et al., 2015). The mixed
model may provide a better fit to longitudinal data compared to either the
immutable or experience-dependent set-point models, because at the population
level, it is more flexible for modeling within-subject change. New statistical
approaches have been developed to formally test the differences in person-specific
developmental trajectories (Borsboom et al., 2016).
It remains complex to account for within-subject changes in analyses of stability
and change in personality traits. Fig. 9.3 displays the hypothetical development of a
personality trait during adulthood in four individuals who differ in terms of both their
trait set-point and sensitivity to context. The trait set-point is highest for D (blue), fol-
lowed by C (purple), B (red), and then A (green). Low sensitivity to context is char-
acteristic of A and D. High sensitivity to context is characteristic of B and C, evident
as relatively low and high amplitudes of deviation from the set-point, respectively. If
individuals differ in sensitivity to context the most sensitive may experience enduring
changes in personality in response to major life experiences and long-term difficulties
(Boyce & Ellis, 2005). Individuals with low sensitivity to context may resist the
effects of environmental events on personality traits; person A and D respond more
or less the same way to the same events. In addition, individual C is exposed to far-
reaching positive and negative experiences which change C’s set-point twice.
Theories to explain set-point change
Two theories may help explain the association between personality trait change and
life experiences or (age-graded) role transitions: the social investment principle and
125Set-Point Theory and personality development: Reconciliation of a paradox
the social production function (SPF) theory, which are outlined later. Roberts et al.
(2005) introduced the social investment principle explicitly to explain why role tran-
sitions and associated life events can change personality. The social production the-
ory, in contrast, has been developed to explain individual differences in SWB,
especially the impact of life experiences on SWB (Ormel, Lindenberg, Steverink, &
Vonkorff, 1997). Note that neither of these theories preclude genetic effects on per-
sonality change; rather, they address in particular the transactional and random fac-
tors that contribute to personality development.
Social investment principle
According to the social investment principle, people build identities through commit-
ments to age-graded social roles, such as work, marriage, family, and community.
Each role comes with a set of expectations and contingencies that create a reward
structure that promotes becoming more socially dominant, agreeable, and conscien-
tious, and less neurotic. These expectations and contingencies induce and maintain
altered behavior patterns and these, in turn, may change personality traits in a
bottom-up fashion. A growing body of evidence supports the social investment prin-
ciple (Bleidorn et al., 2013; Hudson & Roberts, 2016). However, the evidence is
largely limited to crude, epidemiological measures of role experiences as presented
above, rather than psychological experiences. Thus it is still necessary to demonstrate
that role expectations drive personality development and not vice versa.
Social production function theory
Whereas the social investment principle seems particularly suited to understand how
role transitions may change personality traits, SPF theory might help explain why
particular experiences have long-term behavioral consequences that might, in turn,
alter self-perception and hence personality. In addition, SPF theory seems better
suited to clarify non-normative personality change compared to the social invest-
ment principle. However, the evidence supporting the utility of SPF theory in under-
standing personality development is lacking and SPF remained limited to SWB.
SPF theory holds that people seek physical and social well-being (Lindenberg,
1996; Ormel et al., 1999;Steverink, Lindenberg, & Ormel, 1998), which they
achieve through behaviors that enhance status, affection, and behavioral confirma-
tion. Physical well-being is achieved by behaviors that are stimulating or activating,
and that enhance physical comfort. Over an adult’s lifespan, having work, being
happily married, and having good friends and family gives a person status, behav-
ioral confirmation, affection, and comfort.
The SPF perspective suggests that the initial magnitude and persistence of per-
sonality change is likely to depend on how the consequences of altered life circum-
stances affect one’s ability to achieve physical and social well-being. For example,
a harmonious intimate relationship provides opportunities for activities that produce
comfort, affection, and behavioral confirmation. Moreover, SPF theory holds that
enduring impairments of the resources and ability to produce physical or social
126 Personality Development Across the Lifespan
well-being should have unfavorable effects on personality development. Empirical
evidence regarding how social production influences personality comes entirely
from research linking changes in SWB to major life events. Therefore, it is unclear
what effects social circumstances have on traits other than those that are associated
with SWB (neuroticism, extraversion, and, to a lesser extent, conscientiousness).
Life events and depression
Research into the effects of life events and major role transitions on personality
development is still limited, especially regarding SPF theory. This is in contrast to
the enormous amount of research into the relationship between life events and
psychological states, especially depression. Core symptoms of major depressive
disorder are depressed mood and loss of interest that last for at least 2 weeks.
Depression is strongly associated with low levels of SWB and high neuroticism.
Importantly, the onset and remission of major depressive illnesses are often
accompanied by alterations in neuroticism, extraversion, and conscientiousness.
Often these alterations are temporary, in that they wax and wane in parallel with
depression status (Ormel, Oldehinkel, Nolen, & Vollebergh, 2004). Although lim-
ited in quantity, some recent research indicates that psychotherapeutic interventions
are associated with more persistent personality change (Clark, Vittengl, Kraft, &
Jarrett, 2003; De Fruyt, Van Leeuwen, Bagby, Rolland, & Rouillon, 2006; Tang
et al., 2009). For instance, Tang and colleagues found that the combination of cog-
nitive therapy and antidepressant medication not only associated with remission of
depression but reduced neuroticism as well. Importantly, the improvements in
depression seemed driven by decreases in neuroticism. De Fruyt et al. (2006),
investigating a similar combined treatment, reported more extraversion, openness to
experience, agreeableness, conscientiousness, and substantially less neuroticism
after treatment. Therefore, life events involved in the onset and remission of major
depressive episodes may yield important insights into what kind of experiences
might change personality traits.
Brown and Harris and their colleagues have contributed much to our insights into
the life events that can induce depressive illness and significant decreases in SWB.
These events include loss events, humiliating events, and entrapment events (Brown,
Harris, & Hepworth, 1995). They also explored the specific experiences that are likely
to reduce depression and enhance SWB, including anchoring, a fresh start, and events
that neutralize a long-term environmental difficulty (Brown, Lemyre, & Bifulco,
1992). Loss includes not only loss of a person but also loss of a social role (becoming
unemployed). Most loss events involve core roles and relationships, with a substantial
proportion linked to events likely to produce a sense of defeat. Entrapment events
occur in the context of a prolonged and marked difficulty, emphasizing that the diffi-
culty may last much longer than initially thought. Anchoring events involved
increased security, increased hope, or amelioration of a difficulty. It would be interest-
ing to determine whether loss, humiliation, or entrapment events produce enduring
negative changes in personality, and whether anchoring, fresh start, and difficulty-
neutralizing events yield enduring positive changes in personality.
127Set-Point Theory and personality development: Reconciliation of a paradox
Alternative explanations for homeostatic stable states
Cramer et al. (2012aand 2012b) have proposed that dynamic systems have alterna-
tive homeostatic stable states, also called “dynamic regimes” (Scheffer et al., 2009)
or “mechanistic property clusters” (Kendler, Zachar, & Craver, 2011). Marked tran-
sitions from one dynamic regime to another have been observed for diverse com-
plex dynamic systems such as lake ecosystems, climate, financial markets, and also
mood (Van de Leemput et al., 2014). Positive-feedback loops among related ele-
ments within a major trait domain might yield alternative stable states. This has
consequences for how complex dynamic systems respond to deviations from
homeostasis. Fig. 9.5 illustrates that when a system approaches a tipping point (due
to a major shock or cumulative incremental changes), the system becomes vulnera-
ble. It loses resilience and becomes unstable. Small perturbations may then cause a
shift to an alternative stable state.
How can this perspective help the modeling of stability and change in personal-
ity? If there are specific stable trait positions on a distribution one expects a
multimodal distribution of population scores, with relatively high frequencies at
stable state positions and low frequencies at regions in between. In existing data-
bases, multimodal trait score distributions are not observed (Van der Krieke et al.,
2015). At the individual level, the question becomes whether someone can have
two or more person-characteristic stable trait levels? Currently we lack the data to
test this question. Nonetheless, we do know that personality trait change scores tend
to be normally distributed, with frequent small changes and fewer marked changes.
However, this does neither falsify nor confirm the idea of multiple person-
characteristic stable trait levels if these levels differ between individuals (Fig. 9.3).
Databases with sufficient participants, assessments, and time coverage to formally
test expected differences in set-point models have not been available. Optimal
Figure 9.5 Ball-in-a-cup diagram (A vs B). Note: This example assumes two stable states
normal and depressed. The stability of a healthy person may become more fragile close to a
transition toward depression, which can intuitively be understood from these two ball-in-a-
Source: With permission from Van de Leemput, I. A., Wichers, M., Cramer, A. O. J.,
Borsboom, D., Tuerlinckx, F.,Kuppens, P., . . . Scheffer, M. (2014). Critical slowing down as
early warning for theonset and termination of depression. PNAS, doi:10.1073/
pnas.1312114110, p. 88.
128 Personality Development Across the Lifespan
research designs are needed to: (1) compare between-subject set-point models;
(2) determine the impact of major life events and altered social circumstances on
personality, both in terms of the magnitude of change and rate of adaptation; and
(3) identify typical within-subject trajectories before and after major life events or
changes in social circumstances. But first it is important to consider how long a
change in personality trait score must persist to indicate set-point change.
Identifying set-point change
Trait set-points are theoretical constructs that cannot be measured directly.
Identifying a set-point involves inference from repeated measurements. In order to
distinguish measurement error, temporary deviation from the set-point, and enduring
change in trait set-point, personality needs to be measured multiple times. The key
question remains what true set-point change is and what that interpretation implies
for the time scale of assessments.
One operational definition might depart from the assumption that personality
trait set-points are immutable and determined entirely by an individual’s genetic
make-up. In this view, all change is temporary. According to this view, the best
operational definition of set-point would be the average observed trait score across
multiple assessments over an extended period of time, at least decade.
An alternative is to identify the time scale over which an observed change in trait
score may indicate a true change in set-point. One approach could be based on the
adaptation period plus a few months. In this approach, it is crucial to establish when
the adaption process has entirely leveled off. If the trait level has not returned to its
pre-event level, say a few months after leveling off, we could define the difference
as a change in set-point. Some evidence suggests that the leveling off period may
last as long as 1 year (e.g., retirement, marriage) to more than 5 years (e.g., disabil-
ity, widowhood), depending on the specifics of the event and contextual factors,
such as age (Diener et al., 2006; Luhmann et al., 2012). For personality traits, these
dynamics require further study (Jeronimus, 2015; Ormel et al. 2013).
Optimal research designs
Compare the between-subject set-point models
In this chapter, we distinguished three fundamental set-point models that have dif-
ferent implications which can be empirically tested. First, the immutable set-point
model predicts a constant differential stability, independent of the time interval.
Conversely, the experience-dependent model predicts an ongoing drop, even after
intervals of 1020 years. The mixed set-point model predicts that the drop in differ-
ential stability levels off over time. Second, because the mixed model assumes that
part of the trait score variance is not influenced by life events, the prospective asso-
ciation between major life events and trait scores at successive follow-ups is pre-
dicted to drop faster in the mixed model than in the experience-dependent model.
Third, if the trait is entirely plastic, which implies there is no trait component, the
129Set-Point Theory and personality development: Reconciliation of a paradox
experience-dependent model should fit longitudinal data better than a mixed model
with a large immutable variance component.
However, sufficient statistical power is needed to distinguish the experience-
dependent and mixed set-point models. Assuming a steady drop of testretest trait
correlations with time and a 25-year testretest correlation of between 0.40 and
0.50, a sample of at least 1200 individuals would be necessary to differentiate the
models (Ormel & Rijsdijk, 2000). Moreover, multiple assessments (at least four)
over a long time period (preferably .10 years) are needed (see also Kenny &
Zautra, 1995;Ormel & Rijsdijk, 2000).
Determine the impact of major life events and altered social
circumstances on personality, both in terms of the magnitude of
change and rate of adaptation
Since the average occurrence rate of major life events and importantly altered social
circumstances is low in most segments of the population-at-large, evaluation of
their effects on personality traits may require novel research designs. For example,
studies of the impact of the planned closure of a large employer could assess
changes in personality traits before and after closure relative to a similar population
that did not experience job displacement. To obtain reliable and valid data for
modeling nonlinear change, the interval between the postevent assessments should
gradually increase from 12to36 months and continue for at least 5 years. The
timing of measurement intervals is important and, ideally, should match theory-
based predictions on trajectories of personality development, the impact of events,
and the rate of adaptation (Luhmann et al., 2014). With a sufficient frequency of
measurements, it is possible to estimate measurement error variance, and short-term
and long-term mean-level and rank-order stability and change adjusted for measure-
Identification of typical within-subject trajectories
The designs proposed above, with 1025 assessments during at least 5 years would
not only allow for diverse between-subject analyses but within-subject panel regres-
sion analyses as well. The latter could address a variety of questions. For instance,
whether typical trajectories exist, in terms of set-point bandwidth and adaptation
rate, and the associated individual characteristics. This would address important
sensitivity-to-context issues (Boyce & Ellis, 2005) and help to identify the kinds of
environmental changes and personal events that have the potential to change per-
sonality trait set-points. Another possibility would be to examine whether changes
in personality traits relate to simultaneous changes in level of life event exposure
(Heady, 2006). Another advantage of so many assessments across an extended
period is the potential to examine hypotheses about both event and individual char-
acteristics that determine the effects of major life events on personality.
130 Personality Development Across the Lifespan
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set-point models provide a promising framework for future research to better under-
stand stability and change in adult personality development because they fit avail-
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