Open Journal of Social Sciences
2013. Vol.1, No.6, 32-39
Published Online November 2013 in SciRes (http://www.scirp.org/journal/jss) http://dx.doi.org/10.4236/jss.2013.16007
Open Access
32
Personality and Heart Rate Variability: Exploring Pathways
from Personality to Cardiac Coherence and Health
Ada H. Zohar1, C. Robert Cloninger2, Rollin McCraty3
1Psychology, Ruppin Academic Center, Emek Hefer, Israel
2Psychiatry, Washington University School of Medicine, St. Louis, USA
3Institute of Heartmath, Boulder Creek, USA
Received October 2013
Background: Personality and heart rate variability (HRV) are each strong predictors of well-being, par-
ticularly cardiac health and longevity. The current project explores the correlates of personality traits on
heart rate variability (HRV) to clarify how autonomic regulation may mediate the development and main-
tenance of health and disease. Hypothesis: Personality traits will be significantly correlated with specific
measures of HRV. In particular, the Character traits of Self-Directedness, Cooperativeness, and Self-
transcendence are known to promote physical, mental, and social aspects of well-being, so they were ex-
pected to be associated with indices of HRV indicating autonomic balance. Methods: Participants were
271 volunteers from the community, adult men and women. They received an extensive self-report ques-
tionnaire, allowing for a comprehensive personality evaluation. Of these participants, 118 underwent am-
bulatory—24 hours recording of HRV. The HRV recordings were sent to the Institute of HeartMath for
interpretation. Data Analysis: Data for personality was retrieved from the Qualtrics site after online ad-
ministration, into which the HRV data were entered. Analyses were conducted in SPSS 20. Results: Sys-
tematic and significant associations between personality traits were found. In particular, the Temperament
and Character Inventory’s character traits were related to autonomic balance as measured by the ratio of
low frequency (sympathetic) to high frequency (parasympathetic) activity. Openness, aggression, avoid-
ant attachment, and forgiveness were found to relate to several HRV variables. Conclusion: The relations
among personality and HRV support the validity of the measures in ways that clarify the strong relations
among personality, HRV, and health. Further work to replicate and extend these preliminary findings in a
larger sample is underway.
Keywords: TCI; HRV; Openness; Forgiveness; Personality; Health
Introduction
Personality Measures and H e alth
There is a strong link between personality and health—phys-
ical health in general and cardiac health in particular. Personal-
ity influences health via several active pathways. There is a
relationship between personality and adopting a healthy life-
style (HLS). For example, personality influences the proba-
bility of smoking (Zohar & Cloninger, 2011), of eating a
healthy diet (van de Bree, Przybeck, & Cloninger, 2006), of
exercising (Raynor & Levine, 2009), and of seeking appropri-
ate and timely medical attention. Personality has considerable
influence on adopting an HLS, and HLS is an obvious pathway
to health. However, HLS does not fully explain the covariance
of personality and health, demonstrating that there are addition-
al pathways (Edmonds, 2011).
Personality influences the perception of stress by an individ-
ual both in everyday social interactions (Uliaszek et al., 2012)
and when faced with major life challenges (van Zuidena et al.,
2011). In particular childhood adversity seems to exercise an
enduring effect on health and vitality that affects individuals
even into old age (Surtees et al., 2011). Stress, and especially
emotional stress, has been shown to pave multiple routes to
ill-health: by affecting the immune system, the hypothalamic-
pituitary-adrenal (HPA) axis, chronically increased levels of
serum cortisol, and by way of chronic hyperactivity of the
sympathetic nervous system (SNS) (Miller, Chen, & Parker,
2011). Childhood adversity, such as neglect or abuse, is also
associated with impaired character development (Josefsson et
al., 2013b), insecure attachment (Kwako et al. 2013), and ag-
gression (Hiramura et al., 2011) as well as epigenetically alter-
ing the function of the immune system (Cole et al., 2010).
The manner in which personality is defined and measured
affects the research results on links between personality and
health. The empirically derived big five factor (BF) personality
traits of low Neuroticism and high Conscientiousness have
been linked to adaptive health behavior (Lodi-Smith et al.,
2011), cardiac health (Chapman & Goldberg, 2011), and lon-
gevity (Chapman, Fiscella, Kawachi, & Duberstein, 2010). The
theoretically derived temperament and character bio-psycho-
social model of personality, measured by the Temperament and
Character Inventory (TCI) has been associated with increased
risk for psychiatric disorders (Cloninger, Zohar, Hirschmann, &
Dahan, 2012), response to a wide range of psychiatric and other
medical interventions, and cardiac risk factors (Hintsanen et al.,
2009) (Rosenstrom et al., 2012). The B F and TCI traits can also
be dichotomized to above and below the median, and combined
to form multidimensional personality profiles associated with
health and well-being (Cloninger & Zohar, 2011; Rosenstrom
et al., 2012).

A. H. ZOHAR ET AL.
Open Access
33
Personality can affect autonomic function and dynamics. In-
creased neuroticism is linked to increased SNS activation, as
measured by increased electro-dermal response, as well as in-
creased anticipatory anxiety (Drabant et al., 2011). Individual
differences in the BF personality traits are linked to individual
differences in electrocardiogram (ECG) amplitude patterns, in
particular high Neuroticism and low positive emotion (Koelsch,
Enge, & Jentschke, 2012).
Heart Rate Variability
Heart rate variability (HRV) is measured by the variability of
beat-to-beat intervals, and is an indicator of health and well-
being in the general population (Antelmi et al., 2004). High
HRV is associated with reduced medical morbidity and in-
creased longevity (Matsuoka et al., 2005), and higher cognitive
functioning. Low HRV is a predictor of risk for myocardial
infarct (MI), and sudden cardiac death, and all-cause mortality
while high HRV is a predictor of recovery from MI (Carney et
al., 2001; Ablonskytė-Dūdonienė et al., 2012). Consequently
differences between people in HRV strongly predict their rates
of morbidity and mortality, including both physical and psy-
chological aspects of health (Araujo et al., 2006).
Variation in HR results mainly from physica l exertion (Grant,
Vilijoen, van Rensburg, & Wood, 2012) but also from res-
ponses to internal and external stimuli, especially novel stimuli
that may be interpreted as threatening (Thayer, Ahs, Fredriksen,
Sollers III, & Wager, 2012). While the heart provides a rela-
tively steady underlying rhythm, this rhythm is affected by the
slowing (inhibitory) influence of the parasympathetic nervous
system (PNS) and the accelerating (excitatory) effect of the
sympathetic nervous system (SNS). The average heart rate of
70 - 80 reflects a relative balance between the action of the two
components of the autonomic nervous system (ANS), the PNS
and the SNS. In ambulatory recordings the ratio of low to high
frequency (LF/HF ratio) is a useful indicator of the relative
balance between the activity in the sympathetic and parasym-
pathetic systems. Several measures of different components of
heart rate variability can be reliably measured to assess the
characteristics and changes of an individuals, autonomic func-
tioning over time (Voss, 2007). For example, HRV is greater in
the young, and in the physically fit, and decreases with age
(Task Force of European Society of Cardiology et al., 1996;
Antelmi et al., 2004).
HRV is also a finely tuned measure of heart-brain communi-
cation, as well as a strong predictor of morbidity and death. We
expect that a better understanding of HRV in relation to indi-
vidual differences in personality and life-style choices will
contribute to improved medical diagnosis and treatment. While
the average heart rate (HR) is relatively easy to measure over a
short time period, its variability can be more challenging to
measure reliably (Jarrin et al., 2012). In order to insure high
reliability of HRV measurement, 24 hour ambulatory record-
ings can be made, as was done in the current study, so that the
HRV variables are calculated over a long sampling window
across the full range of a person’s daily activi ties. The 24-hour
ambulatory recording increases the ecological validity of the
HRV measurement, and hence its relevance to self-regulatory
mechanisms by which personality may mediate and modulate
the relationship between HRV and health.
Personality is a way of describing the way a person has
learned to adapt to their life circumstances. Temperament traits
are moderately stable throughout the life span on average, but
character traits continue to develop in response to the demands
of life roles and social norms throughout the lifespan (Clonin-
ger, 2003; Josefsson et al., 2013a). Specifically, Self-directed-
ness and Cooperativeness increase as needed to facilitate a
person’s responsibility for work and social relatedness to about
age 45 years. Self-transcendence decreases through age 45 and
then later increases again in response to the challenges of ulti-
mate situations like suffering and imminent mortality (Clo-
ninger, 2003; Josefsson et al., 2013a). The maturation of cha-
racter traits appears to be a way to promote and maintain health
by facilitating healthy self-regulation of emotional reactions
and lifestyle choices (Cloninger et al., 2010; Cloninger et al.,
2012). In particular, higher levels of the character traits of Self-
directedness, Cooperativeness, and Self-transcendence are all
associated with positive emotions, satisfying social relations,
and perceived physical health (Cloninger & Zohar, 2011). Out -
looks on life characterized by positive emotions and a sense of
connectedness have been shown to promote psychosocial func-
tioning and psychophysiological coherence including increased
HRV and improved synchronization in ANS dynamics (Bradley
et al., 2010; McCraty et al., 1999).
In prior work we have shown that individual differences in
personality influence the physical, mental, and social aspects of
health and well-being (Cloninger et al., 2010; Cloninger &
Zohar, 2011). Personality affects the individual’s emotional
state, autonomic stability, immune response, capacity to self-
regulate stress, as well as health behavior and response to med-
ical treatments. The current study undertakes an integrative and
comprehensive measurement of personality in order to look for
pathways from personality to HRV. Because of its exploratory
nature, the study was designed to measure many different per-
sonality traits that might contribute to increased HRV and resi-
lience.
Methods
Personality Measures
The Temperament and Character Inventory in Hebrew (TCI),
is based on a neuropsychological and genetic understanding of
brain structure and activity. It measures four temperament
scales and three character traits. The Hebrew version has ex-
cellent psychometric properties and predictive validity for sub-
jective and objective health (Zohar & Cloninger, 2011).
DS14 in Hebrew (Zohar, Denollet, Lev-Ari, & Cloninger,
2011) has 14-items and is made up of two subscales, negative
affect (NA) and social inhibition (SI). Posited by Denollet
(Denollet, 2005) in the context of cardiac health, it awards a
score of Type D to individuals who score 10 and above on both
dimensions, and Non D to those who do not.
The Big Five Factor Brief Inventory in Hebrew (BFI44; Et-
zion & Lasker, 1998), measures the big five factors of perso-
nality: Openness, Agreeableness, Extroversion, as well as Con-
scientiousness and Neuroticism. The latter two have been found
to be highly predictive of HLS, health and longevity. The
BFI44 in Hebrew has excellent psychometric properties and has
been widely used in research.
Toronto Alexithymia Scale (TAS20, Bagby, Parker, & Tay-
lor, 1994) measures difficulty in identifying, describing and
relating to one’s own feelings. This 20-item scale has excellent
psychometric properties in the original English, was translated
with permission into Hebrew, and found to have excellent

A. H. ZOHAR ET AL.
Open Access
34
structural and predictive validity as well as high scale reliability
(Zohar & Cloninger 2011).
Trait Forgivenes s Scale (TFS; Berry, Worthington , O’Connor,
Parrott III L., & Wade, 2005) is a 10-item scale asking about
the degree to which individuals are able to forgive and forget
rather than carry a grudge. The original scale has excellent psy-
chometric properties; it was translated for the proposed study
by a process of translation, independent back-translation, and
revision.
Aggression Questionnaire—is a 29-item inve ntory with ex-
cellent psychometric properties in the original English (Buss &
Perry, 1992) as well as in the Hebrew translation (Al-Krenawi,
Graham, & Kanat-Maymon, 2009). It has four subscales: hos-
tility, anger, physical aggression, and verbal aggression.
Meaning in Life Questionnaire (Steger, Frazier, Oishi, &
Kaler, 2006) includes 10 items about interest in finding mean-
ing and attainment of a sense meaning. It has good psychome-
tric qualities in the original, and has been translated and used in
research in Hebrew with good results.
Center for Epidemiological Studies Depression Scale (CES-
D; Radloff, 1977) is a 20-item depression symptom scale, as-
sessing a one-week time frame, designed as a general-popu-
lation-screener, with an excellent translation into Hebrew.
Authentic Happiness Scale (AHI; Seligman, Steen, Park, &
Peterson, 2005). The AHI is designed to measure changes in
happiness over time. It has 24 multiple choice questions that
encompass four areas of potential happiness: pleasure, engage-
ment, achievement, and meaning. The original scale has excel-
lent psychometric properties; it was translated for the proposed
study by a process of translation, independent back-translation,
and revision. The AHI was designed to be sensitive to changes
in happiness over time. The CES-D and the AHI scores should
be negativel y correlated .
Positivity scale (Caprara et al., 2012) is an 8-item inventory
of positive evaluations of the self, answered on a 5-category
Likert-like response scale that adds explained variance to the
BFI model and is independent of the five factors. It was trans-
lated (with permission) for the proposed study by a process of
translation, independent back-translation, and revision.
The Experiences in Close Relationships Short Scale (ECR;
Wei, Russell, Malinckrodt, & Vogel, 2007), is a 12-item ques-
tionnaire designed to assess attachment style in adults. It has
anxiety and avoidance subscales, yielding two continuous
scores, as well as dividing individuals into 4 types, acc or ding to
their score vs the median on the two scales. It has been found to
be reliable and valid, and highly predictive of emotion and
emotion regulation.
HRV Measurement
HRV was recorded using a First beat Body Guard recorder, a
lightweight accurate recorder of HRV with a sample rate of
1000 Hz, which is attached with two snap-on electrodes to the
chest, for 24 hours. Originally designed for use during athletic
training, it weighs only 24 grams and is small in size, so partic-
ipants reported that they were able to forget about it and to go
about their daily activities as usual. The monitors were con-
nected when the batteries were fully charged, allowing for a
margin of time to disconnect and download the recordings. The
recording was then uploaded for analysis to the Institute of
HeartMath (IHM) in CA. The Autonomic Assessment Report
(AAR) issued by IHM after expert manual inspection for ire-
gularities included time domain and frequency domain (i.e.,
power spectral density) variables.
Both the time domain and the frequency domain analyses
have advantages and disadvantages. The time domain measures
are the simplest to calculate but do not provide as good of a
means to quantify the various underlying rhythms in the HRV
or autonomic balance. The heart rate (HR) generated by the
sinoatrial node in the absence of any neural or hormonal influ-
ence is about 100 to 120 beats per minute (Hainsworth, 1995).
The HR of a healthy person reflects the net balance between the
activity of the parasympathetic (vagal) nerves, which slow it
and the sympathetic nerves, which accelerate it. Both the sym-
pathetic and parasympathetic branches of the autonomic nerv-
ous system are tonically active in healthy people, but the para-
sympathetic branch dominates during rest and digestion whe-
reas the sympathetic branch dominates during aggressive or
avoidant (“fight or flight”) responses to stress or challenge and
during physical exercise. The heart responds to parasympathetic
stimulation of the sinus node much more quickly than it does to
sympathetic stimulation. Thus in the absence of arrhythmias,
high frequency (fast) responses indicate parasympathetic acti-
vation whereas lower frequency (slow) responses indicate
sympat hetic activity.
In the time domain the most important measures are heart
rate, SDNN, the SDNN Index, and RMS-SD. SDNN is the
standard deviation of the time interval between successive
normal heart beats (i.e., the RR intervals) in the 24-hour re-
cording, and reflects all influences on HRV including slow
influences across the day, circadian variations, the effect of
hormonal influences such as cortisol and epinephrine. The
SDNN Index is the mean of the standard deviation of all the
normal RR intervals for each 5-minute segment of the 24-hour
recording, and reflects rhythms operating within a 5-minute
segment only. The RMS-SD is the root mean square of the RR
intervals (i.e., square root of the mean of the squared differenc-
es in time between successive normal heart beats), so it reflects
high frequency (fast or parasympathetic) influences on HRV
(i.e., those influencing larger changes from one beat to the
next).
In the frequency domain analysis, measures of different fre-
quencies of HRV are extracted by Fast Fourier Transforms of
the 5-minute segments, thereby excluding the ultra-low fre-
quency (ULF) influences on heart rate related to circadian in-
fluences, such as hormonal release, that are measured in analy-
sis of the 24-hour data. The variance (i.e., power) in HRV is
measured in three bands of the frequency distribution of the
Fourier transforms of the 5-minute segments: Very Low Fre-
quency (VLF, .003 to .04 Hz), Low Frequency (LF, .04 to .15
Hz), and High Frequency (HF, .15 to .40 Hz). The power in HF
bands reflects fast changes in beat-to-beat variability due to
parasympathetic (vagal) activity, whereas that in the VLF band
is thought to reflect an intrinsic rhythm produced by the heart
which is modulated by primarily by sympathetic activity. The
HF band is sometimes called the respiratory band because it
corresponds to HRV changes related to the respiratory cycle
and can be increased by slow, deep breathing (about 6 or 7
breaths per minute) (Kawachi et al., 1995) and decreased by
anticholinergic drugs or vagal blockade (Hainsworth, 1995).
The LF band reflects a mixture of sympathetic and parasympa-
thetic activity, but in long-term recordings like ours, it reflects
sympathetic activity and can be reduced by the beta-adrenergic
antagonist propanolol (McCraty & Atkinson, 1996). In addi-

A. H. ZOHAR ET AL.
Open Access
35
tion to analyzing the 5-minute segments, a spectral analysis is
carried out with the entire 24-hour period as one record to ex-
tract the ULF (below .003) variability due to circadian influ-
ences.
The natural logarithm of the ratio of LF to HF power (Ln
LF/HF) is the main indicator of autonomic balance between the
sympathetic and parasympathetic systems. When a person is in
a state of psychophysiological coherence characterized by a
sine wave pattern in the HRV at a frequency of 0.1 Hertz, the
LF/HF falls greatly because of increased parasympathetic activ-
ity and/or decreased sympathetic activity. Psychophysiological
coherence is a state of calm alertness that occurs naturally with
sustained positive emotions and can be induced by slow, deep
breathing. More subtle reductions in this ratio occur with activ-
ities that increase efferent parasympathetic activity such as
when relaxing, sleeping, or with positive moods states. On the
other hand, when a person is stressed, aggressive, or defensive,
the LF/HF rises due to increased sympathetic activity and/or
decreased par asympathetic activity.
Parti cipant s
271 adult community volunteers, men and women, who had
participated in a previous study of personality and health which
took place between 2006 and 2010 (Zohar & Cloninger, 2011)
completed the online personality self-report. Of these, 118 in-
dividuals were also measured for 24-hour HRV. Inclusion cri-
teria were level of Hebrew good enough to self-report on a
questionnaire, and mobility (coming to the laboratory for the
study). Exclusion criterion was a known heart rate disorder. On
analysis, 14 of the participants (11 of them men) turned out to
have an unusable recording, mostly due to a (unreported) heart
rhythm disorder. Therefore, 104 participants’ data were in-
cluded in the analyses. These participants were 46 to 79 years
old (mean 61.4, SD 8.7) of whom 37.5% were men.
Ethical Review
The research protocol was reviewed and approved by the In-
stitutional Review Board. Participant’s privacy was protected
and data safety ensured. No pressure to participate or to con-
tinue participation was brought to bear. Participants signed an
informed consent form after a discussion of the study with the
experimenter, and the experimenter co-signed the form in the
participant’s presence.
Results
No significant differences in any personality variables meas-
ured at outset (2006-7) (N = 1102) and the current assessment
(N = 104) were found. Thus there was no self-selection for
participation in the current study based on personality variables
that might bias the results.
Our main index of autonomic balance was Ln (LF/HF). We
also examined the correlations between all primary HRV va-
riables and a wide range of personality variables. We expected
that consideration of several of the HRV variables and perso-
nality variables would help to clarify the interpretation of the
complex non-linear relationships between personality and au-
tonomic regulation. We found that HRV was related to perso-
nality in very specific ways, indicating substantial construct and
discriminant validity of both the HRV and the personality va-
riables. We report only on personality variables which had sig-
nificant correlations with at least one HRV variable.
Of the TCI traits, all three character traits correlated nega-
tively with Ln (LF/HF), indicating that a more mature character
development was associated with greater parasympathetic ac-
tivity (vagal tone) and lower overall sympathetic activity. As
the TCI theory predicts that better emotional regulation (and
higher HRV) will be related to an overall rise in all three cha-
racter traits, we also examined Creativity, the product of all
three character traits. Creativity is defined here as the synergis-
tic quality arising from the combination of high Self-directed-
ness (i.e., resourceful, realistic), high Cooperativeness (i.e.,
reasonable, helpful), and high Self-transcendence (i.e., imagin-
ative, intuitive) (Cloninger 2004). Although using the product
also increases measurement error multiplicatively, the correla-
tion between Creativity and Ln (LF/HF) is higher than the cor-
relation of each character trait separately, supporting a non-
linear association of character with HRV. In contrast, being
organized (high Self-directedness and Cooperativeness but low
Self-transcendence) or being fanatical (high Self-directedness
and Self-transcendence but low Cooperativeness) were not
significantly associated with LF/HF. These results are presented
in Table 1.
Table 2 presents relationships of other personality traits with
the HRV variables included in the study. Openness is negatively
correlated with many of the HRV variables, including those
indicative of lower sympathetic activity (negative correlations
with SDNN Index and ULF power) and those indicative of low
parasympathetic activity (negative correlations with RMS-SD
and Ln LF/HF). Low activity for both branches of the auto-
nomic nervous system suggests that heart rate variability is only
weakly regulated in people high in Openness, but parasympa-
thetic regulation is relatively greater than sympathetic influ-
ences (i.e., correlation with Ln LF/HF is negative). In contrast,
Physical Aggression was associated with high sympathetic
activity (indicated by positive correlation with SDNN, SDNN
Index, LF, and VLF power, and no significant correlation with
RMS-SD) whereas Avoidant Attachment was associated with
lower parasympathetic activity (indicated by negative correla-
tions with RMS-SD and Ln LF/HF). Circadian regulation of
HRV is also weak in people high in Openness (indicated by no
significant correlation with ULF in 24 hour analysis), so the
HRV observed in relation to Openness is really unregulated
reactivity to transient stimuli combined with ease of relaxation
when unchallenged. Not shown in Table 2, Agreeableness was
correlated r = .199* (p < .05) Ln (HF5), an indicator of high
parasympathetic activity and Forgiveness was correlated with
SDANN, an indicator of low sympathetic activity, r = −.224 (r
Table 1.
Correlations between TCI traits and HRV measures.
TCI Traits Ln (LF/HF)
Self -Directedness −.199*
Cooperativeness −.199*
Self-Transcendence −.197*
Creative −.277**
Organized Ns
Fanatical Ns
Note: *p < .05; **p < .01; Creative = SD X CO X ST; Organized = SD X CO X
(STmax-STscore); Fanatical = SD X (COmax-COscore) X ST.

A. H. ZOHAR ET AL.
Open Access
36
Table 2.
Correlations between openness, physical aggression, avoidant attach-
ment and HRV measures.
Openness Physical aggression Avoidance
SDNNI −.222* .244* ns
SDNN −.216* .216* ns
SDANN −.233* ns ns
RMS-SD −.209* ns −.234*
Ln TP5 −.202* .277** ns
Ln ULF24 −.247* ns ns
Ln VLF5 −.217* .254** ns
Ln LF5 ns .322** ns
Ln HF5 ns ns −.328**
Ln LF/HF −.217* .229* .318**
Note: *p < .05; *p < .01.
< .05).
Choosing just two of the HRV variables for further scrutiny,
we conducted hierarchical linear regression with one dependent
variable from the power spectrum analysis, specifically the
natural log of the ratio of low frequency (sympathetic) compo-
nent to the high frequency (parasympathetic) component (Ln
(LF/HF)), and also one dependent variable from the time do-
main analysis, specifically the SDNN Index, which is the mean
of standard deviation of the RR intervals for all the 5 minute
intervals of the 24-hour recording. We considered age as first
block predictor and personality traits as second block predictors.
The results are presented in Tables 3 and 4. In the Power Spec-
trum analysis, personality traits explained 23.1% of the va-
riance in Ln (LF/HF), being creative decreased the ratio whe-
reas being forgiving, physically aggressive and being avoi-
dantly attached increased the ratio, so that creativity was asso-
ciated with greater vagal (parasympathetic) activity whereas the
other variables had greater sympathetic activity and/or lower
parasympathetic activity. In the Time domain analysis, perso-
nality traits explained 10.6% of the variance in the SDNN In-
dex: being creative and being physically aggressive had greater
HRV whereas being open had lower HRV on this indicator of
sympat hetic ac tivity. I ncluded in Tables 3 and 4 are the second
models, those with personality traits entered after the first pre-
dictor age at time of measurement.
Discussion
The ratio Ln (LF/HF) is of considerable psychological and
physiological interest. It is considered a measure of balance
between the excitatory action of the SNS and the inhibitory
action of the PNS over the 24-hours. However, the interpreta-
tion of the associations found between personality traits and the
ratio requires consideration of concomitant relations with indi-
cators that can dissociate sympathetic and parasympathetic
inputs. For example, high levels of sympathetic activity are
indicated by high values for the time-domain variables of
SDNN and SDNN Index and by the frequency domain va-
riables of LF, VLF, which we observed to be positively corre-
lated with self-reported Physical Aggression. On the other hand,
high levels of parasympathetic activity are indicated by high
values on the time-domain variable of RMS-SD (which was
Table 3.
Summary of hierarchical regression analysis for personality variables
predicting the frequency domain variable Ln (LF/HF).
Model 2
Variable B SE B β
Age −.007 .004 −.161
Creativity .001 .001 −.208*
Forgiveness .123 .055 .219*
Physical aggression .224 .094 .222*
Avoidance .115 .040 .281**
R2 .234
F for change in R2 6.34
Note: *p < .05; **p < .005.
Table 4.
Summary of hierarchical regression analysis for predicting the time
domain indicator of sympathetic influences on HRV, SDNNI total.
Model 2
Variable B SE B β
Age −.127 .174 −.072
Creativity .001 .001 .298**
Openness −6.801 2.357 −.326**
Physical aggression 7.556 3.294 .230**
R2 .108
F for change i n R2 3.78**
Note: *p < .05; **p < .005.
correlated negatively with Openness and with Avoidant At-
tachment) and the frequency-domain variable of HF (which was
correlated positively with Agreeability and negatively with
Avoidant attachment).
The present study found that being creative (the product of
the three TCI character traits) was negatively associated with
the LF/HF ratio. A reasonable interpretation would be that more
mature and developed character (Cl oninger, Svrakic, & Svrakic,
1997) is associated with more PNS inhibitory activity, as a
form of mature emotional regulation that arises from an outlook
of unity and connectedness with other people and one’s sur-
roundings (Cloninger, 2004; Cloninger et al., 2010; Cloninger,
2013). This finding of the relationship between creativity and
high vagal tone indicates that an outlook of unity allows a per-
son for function efficiently in a state of calm awareness without
unhealthy psyc hophysiological ar ousal or de fensiveness (B radley
et al., 2010; McCraty et al., 2009). In other words, people with
a creative character configuration who are highly self-directed,
cooperative, and self-transcendent can function well while re-
maining calm and happy in the face of the challenges of daily
life (Cloninger, 2013). They are healthy beca use of their a bility
to let go rather than to defend themselves with aggression or
avoidance (“fight or flight”). They are able to remain alert and
think clearly by being calm and happy (Fredrickson and Losada
2005). Their physiological coherence promotes resilience and
maintains health (Bradley et al., 2010; Cloninger et al., 2012;
Cohn et al., 2009). Measures of HRV provide an objective set
of indicators of this creative and coherent way of adapting to

A. H. ZOHAR ET AL.
Open Access
37
life challenges.
The finding that Creativity was characterized by a lower Ln
(LF/HF) is noteworthy because other character profiles that
include high Self-directedness were not associated with such
autonomic activity. Creativity was measured as the synergistic
strength that emerges from the combination of being Self-di-
rected (i.e., resourceful and realistic), Cooperative (i.e., rea-
sonable and helpful), and Self-transcendent (i.e., imaginative
and intuitive). The other healthy character profile is being or-
ganized, that is, highly self-directed and cooperative, but not
self-transcendent. Being organized was not significantly asso-
ciated with autonomic balance, suggesting that self-transcen-
dence is crucial for autonomic balance at least under the chal-
lenging conditions of rapid change we face in the world today
(Cloninger, 2013). However, people who are high in Self-di-
rectedness and Self-transcendence but not Cooper ativeness (i.e.,
hostile fanatics) are also not functioning in a state of cardiac
coherence according to our observations. Therefore, it is the
synergy between all three components of character measured by
the TCI that is crucial for functioning with an outlook of unity
and connectedness that includes respect for one’s self, other
people, and the world as a whole.
In contrast, Openness is negatively correlated with many of
the HRV variables, including those indicative of lower sympa-
thetic activity (negative correlations with SDNN Index and
ULF) and those indicative of low parasympathetic activity
(negative correlations with RMS-SD and Ln LF/HF). Low ac-
tivity for both branches of the autonomic nervous system sug-
gests that heart rate variability is only weakly regulated in
people high in Openness, even though parasympathetic regula-
tion is relatively greater than sympathetic influences (i.e., the
correlation with Ln (LF/HF) is negative). Circadian regulation
of HRV is also weak in people high in Openness (indicated by
no significant correlation with ULF in 24 hour analysis), so the
HRV observed in relation to Openness is really unregulated
reactivity to transient stimuli combined with ease of relaxation
when unchallenged.
Physical Aggression was associated with high sympathetic
activity (indicated by positive correlation with SDNN, SDNN
Index, LF, VLF), but was not related to any differences in pa-
rasympathetic activity (indicated by no significant correlation
with RMS-SD). In contrast, Avoidant Attachment was asso-
ciated with low parasympathetic activity (indicated by negative
correlations with RMS-SD and Ln (LF/HF)). On the other hand,
Agreeableness was correlated with an indicator of high para-
sympathetic activity (positive correlation with HF) whereas
Forgiveness was correlated with an indicator of lower sympa-
thetic activity (neg ative correlation with SDANN).
Consequently, in the multiple regression analysis of auto-
nomic balance measured by Ln (LF/HF), being creative de-
creased the ratio whereas being physically aggressive, avoidant,
and/or simply forgiving increased the ratio. In other words,
creative functioning, such as non-violent assertiveness, is cha-
racterized by greater vagal (parasympathetic) regulation to
maintain autonomic balance whereas other personality variables
depend on either greater sympathetic activity and/or lower pa-
rasympathetic activity. Creative problem-solving with a calm,
happy outlook of unity is more integrative and adaptive than
defensive responding (i.e., aggression or avoidance) or submis-
sive responding (i.e., agreement or forgiveness).
In the multiple regression analysis of the SDNN Index,
which is the mean of the standard deviation of the time interval
between successive normal heart beats (i.e., the RR intervals)
throughout the day, being creative or being physically aggres-
sive contributed to greater HRV. In contrast, once creativity
and physical aggression were taken into account, being open
resulted in lower HRV, even though the SDNN Index is consi-
dered to indicate mostly sympathetic activity. This finding fits
with the interpretation that openness is associated with weak
regulation of cardiorespiratory reactivity: once the strong active
influences of creative or aggressive responses are taken into
consideration, openness is not associated with increased HRV.
The results presented here should be considered in the light
of the study limitations. Self-report questionnaires are highly
reliable but imperfect measures of personality. All personality
measures have measurement error due to a variety of known
causes as well as random effects (Schmidt & Hunter, 1996).
Because this is an exploratory study we used a wide range of
personality instruments, and many of them did not associate
systematically with HRV variables. The personality variables
we reported on were those that had at least one two-tailed sig-
nificant correlation at p ≤ .05 with at least one of the HRV va-
riables included in the analyses. Casting a wide net as we did,
all results should be viewed as hypothesis-generating, rather
than as conclusive.
In addition, the measurement of HRV is restricted in the
study to 104 complete records. The measurement of HRV is
highly reliable and ecologically valid because it is conducted
over 24 hours and the analyses of the data were conducted by
expert technicians and physiological psychologists. The inter-
pretation of our results should be viewed with these reserva-
tions in mind.
The results of this study require replication. However, they
sketch intriguing pathways through personality traits, emotional
response, CNS action, and heart activity. The regulation of
cardiorespiratory functioning through the autonomic nervous
system may be an important way by which personality jointly
influences the physical, mental, and social aspects of health and
well-being.
REFERENCES
Ablonskytė-Dūdonienė, R., Bakšytė, G., Ceponienė, I., Kriščiukaitis,
A., Drėgūnas, K., & Ereminienė, E. (2012). Impedance cardiography
and HRV for long-term cardiovascular outcome prediction after MI.
Medicina, 48, 350-358.
Al-Krenawi, A., Graha m, J. R., & Kanat-Maymon, Y. (2009). Analysis
of trauma exposure, symptomatology and functioning in Jewish Is-
raeli and Palestinian adolescents. The British Journal of Psychiatry,
195, 427-432. http://dx.doi.org/10.1192/bjp.bp.108.050393
Antelmi, I., de Paula, R. S., Shinzato, A. R., Peres, C. A., Mansur, A. J.,
& Grupi, C. J. (2004). Influence of age, gender, body mass index,
and functional capacity on heart rate variability in a cohort of sub-
jects without heart disease. American Journal of Cardioliogy, 93,
381-385. http://dx.doi.org/10.1016/j.amjcard.2003.09.065
Araújo, F., Antelmi, I., Pereira, A. C., Latorre, M. R., Grupi, C. J.,
Krieger, J. E., & Mansur, A. J. (200 6), Lower heart rate variability is
associated with higher serum high-sensitivity C-reactive protein con-
centration in healthy individuals aged 46 years or more. Internsl
Journal of Cardiology, 107, 333-337.
http://dx.doi.org/10.1016/j.ijcard.2005.03.044
Bagby, R. M., Parker, J. D. A., & Taylor, G. J. (1994). The 20-item
Toronto alexithymia scale-I. Item selection and cross-validation of
the factor structure. Journal of Psychosomatic R esearch, 38, 23-32.
http://dx.doi.org/10.1016/0022-3999(94)90005-1
Berry, J. W., Worthington, E. L., O’Connor, L. E., Parrott III, L., &
Wade, N. G. (2005). Forgivingness, vengeful rumination, and affec-

A. H. ZOHAR ET AL.
Open Access
38
tive traits. Journal of Personality, 73, 183-226.
http://dx.doi.org/10.1111/j.1467-6494.2004.00308.x
Bradley, R. T., McCraty, R., Atkinson, M., Tomasino, D., Daugherty,
A., & Arguelles, L. (2010). Emotion, self-regulation, psychophysio-
logical coherence, and test anx iety: Results from an experiment using
lectrophysiological measures. Applied sychophysiological Biofeed-
back, 35, 261-283. http://dx.doi.org/10.1007/s10484-010-9134-x
Buss, A. H., & Perry, M. (1992). The aggression questionnaire. Journal
of Personality and Social Psychology, 63, 452-459.
http://dx.doi.org/10.1037/0022-3514.63.3.452
Caprara, G. V., Alessandri, G., Eisenberg, N., Kupfer, A., Steca, P.,
Caprara, M. G., Yamaguchi, S., Fukuzawa, A., & Abela, J. (2012).
The positivity scale. Psychological Assessment, 24, 701-712.
http://dx.doi.org/10.1037/a0026681
Carney, R. M., Blumenthal, J. A., Stein, P. K., Watkins, L., Catellier,
D., Berkman, L. F., Czajkowski, S. M., O’Connor, C., Stone, P. H.,
& Freedland, K. E. (2001). Depression, heart rate variability, and
acute myocardial infarction, Circulation, 104, 2024-2028.
http://dx.doi.org/10.1161/hc4201.097834
Chapman, B. P., & Goldberg, J. R. (2011). Replicability and 40-year
predictive power of childhood ARC types. Journal of Personality
and Social Psychology, 101, 593-606.
http://dx.doi.org/10.1037/a0024289
Chapma n, B. P., Fiscella, K., Kawachi, I., & Duberstein, P. R. (2010).
Personality, socioeconomic status, and all-cause mortality in the
United States. American Journal of Epidemiology, 171, 83-92.
http://dx.doi.org/10.1093/aje/kwp323
Cloninger, C. R. (2003). Completing the psychobiological architecture
of human personality development: Temperament, character, and
coherence. In U. M. Staudinger, & U. E. R. Lindenberger (Eds.),
Understanding human development: Dialogues with lifespan psy-
chology (pp. 159-182). London: Kluwer Academic Publishers.
http://dx.doi.org/10.1007/978-1-4615-0357-6_8
Cloninger, C. R. (2004). Feeling good: The science of well-being (p.
374). New York: Oxford University Press.
Cloninger, C. R. (2013). What makes people healthy, happy, and ful-
filled in the face of current world challenges? Mens Sana Mono-
graphs, 11, 16-24. http://dx.doi.org/10.4103/0973-1229.109288
Cloninger, C. R., & Zohar, A. H. (2011). Personality and the p erception
of health and happiness. Journal of Affective Disorders, 128, 24-32.
http://dx.doi.org/10.1016/j.jad.2010.06.012
Cloning er, C . R., Sallou m, I. M., & Mezzi ch, J. E. (201 2). The dynamic
origins of positive health and wellbeing. International Journal of
Person-Centered Medicine, 2, 1-9.
Cloninger, C. R., Svrakic, N. M., & Svrakic, D. M. (1997). Role of
personality self-organization in development of mental order and
disorder. Development and Psychopathology, 9, 881-906.
http://dx.doi.org/10.1017/S095457949700148X
Cloning er, C. R., Zohar, A. H ., & Cloning er, K. M. (2010). Promotion
of well-being in person-centered mental health care. Focus, 8, 165-
179.
Cloninger, C. R., Zohar, A. H., Hirschmann, S., & Dahan, D. (2012).
The psychological costs an d benefits of being highly persistent: Per-
sonality profiles distinguish mood disorders from anxiety disorders.
Journal of Affective Disorders, 136, 758-766.
http://dx.doi.org/10.1016/j.jad.2011.09.046
Cohn, M. A., Fredrickson, B. L., Brown, S. L., Mikels, J. A., & Con-
way, A. M. (2009). Happiness unpacked: Positive emotions increase
life satisfaction by building resilience. Emotion, 9, 361-368.
http://dx.doi.org/10.1037/a0015952
Cole, S. W., Arevalo, J. M., Takahash i, R., Sloan, E. K., Lutgend orf, S.
K., Sood, A. K., & Seeman, T. E. (2010). Computational identifica-
tion of gene-social environment interaction at the human IL6 locus.
Proceedings of the National Academy of Sciences, 107, 5681-5686.
http://dx.doi.org/10.1073/pnas.0911515107
Denollet, J. (2005). DS14 : Standard assessment of n egative affectivity,
social inhibition, and type D personality. Psychosomatic Medicine,
67, 89-97. http://dx.doi.org/10.1097/01.psy.0000149256.81953.49
Drabant, E. M., Kuo, J. R., Ramel, W., Blechert, J., Edge, M. D.,
Cooper, J. R., Goldin , P. R., Hariri, A. R., & Gro ss, J. J. (2011). Ex-
periential, autonomic, and n eural re sponses during threat anticip ation
vary as a function of threat intensity and neuroticism, Neuroimage,
55, 401-410. http://dx.doi.org/10.1016/j.neuroimage.2010.11.040
Edmonds, G. W. (2011). Personality and the healthy li festyle (HLS) as
predictor of physical hea lth: Can the HLS b e explained by per sona li-
ty? Doctoral Dissertation, Champaign: University of Illinois at Ur-
bana.
Etzion, D., & La ski, S. (1998). The big five inventory (version 5a). Tel-
Aviv: Tel-Aviv University.
Fredrickson, B. L. & Losada, M. F. (2005). Positive affect and the
complex dynamics of human flourishing. American Psychologist, 60,
678-686. http://dx.doi.org/10.1037/0003-066X.60.7.678
Grant, C. C., Vilijoen, M., van Rensburg, D. C., & Wo od, P. S. (2012).
HRV assessment of the effect of training on autonomic cardiac con-
trol. Annals of Noninvasive Electrocardiology, 17, 219-229.
http://dx.doi.org/10.1111/j.1542-474X.2012.00511.x
Hainsworth, R. (1995). The control and physiological importanceof
heart rate. In M. Malik, & A. J. Camm (Eds.), Heart rate va riability
(pp. 147-163). Armonk, NY: Futura Publishing Company, Inc.
Hintsanen, M., Pulkki-Råback, L., Juonala, M., Viikari, J. S., Raitakari,
O. T., & Keltikangas-Järvinen, L. (2009). Cloninger’s temperament
traits and preclinical atherosclerosis: The cardiovascular risk in
young Finns study . Journal of Psychosomatic Research, 67, 77-84.
http://dx.doi.org/10.1016/j.jpsychores.2009.01.002
Hiramura, H., Uji, M., Sh ikai, N., Ch en, Z. , Matsuo k a, N., Kitamura, T.
et al. (2010). Understanding externalizing behavior from children’s
personality and parenting characteristics. Psychiatry Research, 175,
142-147. http://dx.doi.org/10.1016/j.psychres.2005.07.041
Jarrin, D. C., McGrath, J. J., Giovanniello, S., Porier, P., & Lambert, M.
(2012). Measurement f idelity of HRV signal proces sing: The devil is
in the details. International Journal of Psychophysiology, 86, 88-97.
http://dx.doi.org/10.1016/j.ijpsycho.2012.07.004
Josefsson, K., Jokela, M., Cloninger, C. R., Hintsanen, M., Salo, J.,
Hinsta, T., Pulkki-Rabak, L., & Keltikangas-Järvinen, L. (2013a).
Maturity and change in personality: Developmental trends of tempe-
rament and character in adulthood. Development and Psychopathol-
ogy, 25, 713-727. http://dx.doi.org/10.1017/S0954579413000126
Josefsson, K., Jokela, M., Hintsanen, M., Cloninger, C. R., Pulkki-
Rabak, L., Merjonen, P ., Hutri-Kahonen, N., & Keltikan gas-Järvinen,
L. (2013b). Parental care-giving and home environment predicting
offspring’s temperament and character traits after 18 years. Psychia-
try Research.
Uhttp://dx.doi.org/10.1016/j.psychres.2013.01.007iU
Kawachi, I., Sparrow, D., Vokonas, P. S., & Weiss, S. T. (1995). De-
creased heart rate variability in men with phobic anxiety (data from
the normative aging study). American Journal of Cardiology, 75,
882-885. Uhttp://dx.doi.org/10.1016/S0002-9149(99)80680-8U
Koelsch, S., Enge, J., & Jentschke, S. (2012). Cardiac signatures of
personality. PLOS ONE, 7, 1-9.
Uhttp://dx.doi.org/10.1371/journal.pone.0031441U
Kwako, L. E., Noll, J. G., Putnam, F. W., & Trickett, P. K. (2010).
Childhood sexual abuse and attachment: An intergenerational pers-
pective. Clinical Child Psychology and Psychiatry, 15, 407-422.
Uhttp://dx.doi.org/10.1177/1359104510367590U
Lodi-Smith, J., Jacks on, J., B ogg, T., Walton , K., Wo od, D., Harms, P .,
& Roberts, B. W. (2010). Mechanisms of health: Education and
health-related behaviours partially mediate the relationship between
Conscientiousness and self-reported physical health. Psychology and
Health, 25, 305-319. Uhttp://dx.doi.org/10.1080/08870440902736964U
Matsuoka, O., Otsuka, K., Murakami, S., Hotta, N., Yamanaka, G.,
Kubo, T., Y amanaka, M., Shinagawa, M., Nunoda, S., Nishimura, Y.,
Shibita, K., Saitoh, H., Nishinaga, M., Ishine, M., Wada, T., Oku-
miya, K., Matsubayashi, K., Yano, S., Ishihara, K., Cornelissen G.,
Halberg, F., & Ozawa, T. (2005). Arterial stiffness independently
predicts CVE in an elderly community—Longitudinal investigation
for the LILAC study. Biomedical Pharmacotherapy, 59, S40-S44.
Uhttp://dx.doi.org/10.1016/S0753-3322(05)80008-3U
McCraty, R. , & A tkinson, M. (1996). Autonomic assessment report: A
comprehensive heart rate variability analysis. In R. McCraty (ed.),
Heart ma th research center reports. Boulder Creek, CA: In stitute of

A. H. ZOHAR ET AL.
Open Access
39
Heart Math.
McCraty, R., Atkinson, M., Lipsenthal, L., & Arguelles, L. (2009).
New hope for correctional officers: An innovative program for re-
ducing stress and health risks. Applied Psychophysiological Bio-
feedback, 34, 251-272. http://dx.doi.org/10.1007/s10484-009-9087-0
McCraty, R., Atkinson, M., Tomasino, D., Goelitz, J., & Mayrovitz, H.
N. (1999). The i mpact of an e motional self-management skills course
on psychosocial functioning and autonomic recovery to stress in
middle school children. Integrative Physiological and Behavioral
Sciences, 34, 246-268. http://dx.doi.org/10.1007/BF02688693
Miller, G. E., Chen, E., & Parker, K. J. (2011). Psychological stress in
childhood and susceptib ility to the c h ron ic d iseases of ag in g: Mo vin g
toward a model of behavioral and biological mechanisms. Psycho-
logical Bulletin, 137, 939-997. http://dx.doi.org/10.1037/a0024768
Radloff, L. S. (1977). The CES -D scale: A self-report depressio n scale
for research in the general population. Applied Psychological Mea-
surement, 1, 385-401.
http://dx.doi.org/10.1177/014662167700100306
Raynor, D. A., & Levine, H. (2009). Associations between the five-
factor model of perso nality and health behaviors among college stu-
dents. Journal of American College Health, 58, 73-81.
http://dx.doi.org/10.3200/JACH.58.1.73-82
Rosenström, T., Jokela, M., Cloninger, C. R., Hintsanen, M., Juonala,
M., Raitakari, O., Viikari, J., & Keltikan gas-Järvinen, L. (20 12). As-
sociations between di mensional personality measures and preclinical
atherosclerosis: The cardiovascu lar risk in Young Finns study. Jour-
nal of Psychosomatic Research, 72, 336-343.
http://dx.doi.org/10.1016/j.jpsychores.2012.02.003
Schmidt, F. L., & Hunter, J. E. (1996). Measurement error in psycho-
logical research: Lessons from 26 research scenarios. Psychological
Methods, 1, 199-223. http://dx.doi.org/10.1037/1082-989X.1.2.199
Seligman, M. E. P., Steen, T. A., Par k, N., & Peterso n, C . (2005 ). Posi-
tive psychology prog ress: Empirical validation of intervention s. Am-
erican Psychologist, 60, 410-421.
http://dx.doi.org/10.1037/0003-066X.60.5.410
Steger, M. F., Frazier, P., Oishi, S., & Kaler, M. (2006). The meaning
in life questionnaire: Assessin g the presence of an d search for mean-
ing in life. Journal of Counseling Psychology, 53, 80-93.
http://dx.doi.org/10.1037/0022-0167.53.1.80
Surtees, P. G., Wainwright, N. W. J., Pooley, K., A., Luben, R. N.,
Khaw, K.-T, Easton, D. F., & Dunning, A. M. (2011). Life stress,
emotional health, and mean telomere length in the EPIC—Norfolk
population. Journal of Gerontology, 66A, 1152-1162.
http://dx.doi.org/10.1093/gerona/glr112
Task force of the European So ciety of Cardiology, & The North A mer-
ican Society of Pacin g Electrophysiology (1996). HRV, s tandards of
measurement, physiological interpretation, and clinical use. Euro-
pean Heart Journa l, 17, 354-381.
http://dx.doi.org/10.1093/oxfordjournals.eurheartj.a014868
Thayer, J. F., A hs, F., Fredrik son, M., Sollers III, J. J., & Wager, T. D.
(2012). A meta-analysis of HRV and neu roimaging studies: Implica-
tions for HRV as a marker of stress and health. Neuroscience and
Biobehavioral Reviews, 36, 747-756.
http://dx.doi.org/10.1016/j.neubiorev.2011.11.009
Uliaszek, A. A., Zinbarg, R. E., Min eka, S., Craske, M . C., Griffith, J.
W., Sutton, J. M., Epstein, A., & Hammen , C. (2012 ). A longitudinal
examination of stress gen eration in depressive and anxiety disorders.
Journal of Abnormal Psychology, 121, 4-15.
http://dx.doi.org/10.1037/a0025835
van de Bree, M. B. M., Przybeck, T. R., & Cloninger, C. R. (2006).
Diet and personality: Associations in a population-based sample.
Appetite, 46, 177-188. http://dx.doi.org/10.1016/j.appet.2005.12.004
van Zuiden, M., K avelaars, A., Rademaker, A . R., Vermetten, E., Heij-
nen, C. J., & Geuze, E. (2011). A prospective study on personality
and the cortisol awakening response to predict posttraumatic stress
symptoms in response to military deplo yment. Journal of Psychiatr ic
Research, 45, 713-719.
http://dx.doi.org/10.1016/j.jpsychires.2010.11.013
Voss, A. (2007). Lon gitudinal analysis of HRV. Journal of Electroca r-
diology, 40, 826-829.
http://dx.doi.org/10.1016/j.jelectrocard.2006.10.024
Watson, D., Clark, L. A., & Tellegen, A. (1988). Development and
validation of brief measures of positive and negative affect: The
PANAS scales. Journal of Personality and Social Psychology, 54,
1063-1070. http://dx.doi.org/10.1037/0022-3514.54.6.1063
Wei, M., Russell, D. W., Malinckrod t, B., & Vogel, D. L. (2007). The
experience in close relationship ECR-short form: Reliability, valid-
ity, and factor structure. Journ al of Personality Assessmen t, 88, 187-
204. http://dx.doi.org/10.1080/00223890701268041
Zohar, A. H., & Cloninger C. R. (2011). The psychometric properties
of the TCI-140 in Hebrew. European Journal of Psychological As-
sessment, 27, 73-80. http://dx.doi.org/10.1027/1015-5759/a000046
Zohar, A. H., Denollet, J. K., Lev-Ari, L., & Cloninger, C. R. (2011).
The psychometric properties of the DS14 in Hebrew and the preva-
lence of type D in Israeli adults. European Journal of Psychological
Assessment, 27, 274-281.
http://dx.doi.org/10.1027/1015-5759/a000074