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The General Factor of Environmental
Sensitivity: Relationships with the
General Factor of Personality
Shuhei Iimura
1
and Kosuke Yano
2
Abstract
Environmental sensitivity is a meta-concept that describes individual differences in susceptibility to both positive and negative
environmental influences and has been repeatedly reported to correlate with other established personality traits, including
the Big Five. The purpose of this study was to examine the correlation between the general factor of environmental sensitivity
(GFS) and the general factor of personality (GFP). A total of 1,046 adult participants (52% female; M
age
=45.15, SD
age
=12.70)
completed a self-report psychological questionnaire on an online form. Confirmatory factor analysis indicated that GFS had a
strong negative correlation with GFP (r=−.41, 95% CI [−.52, −.30], p< .001). Focusing on the relationship with the Big Five,
individuals with higher environmental sensitivity were emotionally unstable and introverted. The trait of environmental sensitivity
may be described not only in relation to the Big Five but also in relation to GFP, which is assumed to be an indicator of social
effectiveness.
Keywords
environmental sensitivity, sensory processing sensitivity, general factor of environmental sensitivity, GFS, Big Five, general factor
of personality, GFP
Date received: March 12, 2024; Revision Submitted: April 28, 2024; Accepted: April 29, 2024
Introduction
Traditionally, several constructs related to psychological indi-
vidual differences are known to be aggregated into a single
higher-order factor, such as the general intelligence factor, g,
which explains the common variance of specific cognitive intel-
ligences, including spatial, verbal, and numerical abilities in
humans (Spearman, 1904). More recently, in addition to the
general factor of psychopathology, the p-factor (Caspi et al.,
2014), the general factor of personality, GFP (Figueredo
et al., 2004; Musek, 2007), on which this study focuses and
the general factor of environmental sensitivity, which we call
GFS (Lionetti et al., 2018; Pluess et al., 2023) have been pro-
posed. Twin studies suggest that the general factors involved
in these individual differences are heritable (Assary et al.,
2021; Haworth et al., 2010; Rushton et al., 2008; Veselka
et al., 2009). Currently, there is a trend to attempt to understand
individual differences in cognitive ability, personality, and psy-
chopathology by examining associations among these general
factors, but to the best of our knowledge, there are no reports
of correlations between GFS and GFP. Therefore, in this
study, we attempted to report for the first time the correlation
between GFS and GFP.
The Genral Factor of Environmental Sensitivity (GFS)
Human neurophysiological or psychosocial development is
influenced by a wide range of environments, including the
quality of parenting and interpersonal relationships, but the
degree of susceptibility can vary depending on individual dif-
ferences in genetic (Assary et al., 2021), neurophysiological
(Weyn et al., 2022a), and temperament/personality (Slagt
1
Faculty of Education, Soka University, Tokyo, Japan
2
National Institution for Youth Education, Tokyo, Japan
Corresponding Author:
Shuhei Iimura, Faculty of Education, Soka University, 1-236 Tangi-machi,
Hachioji-shi, Tokyo 192-8577, Japan.
Email: iimurashuhei@gmail.com
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Original Article
Evolutionary Psychology
April-June 2024: 1–10
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DOI: 10.1177/14747049241254727
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et al., 2018) factors. Environmental sensitivity is a meta-
concept that explains such individual differences in susceptibil-
ity to environmental influences, which is defined as a continu-
ous trait describing individual differences in perception and
processing of environmental stimuli in both adversarial and
supportive environments (Greven et al., 2019). Individuals
with higher degrees of environmental sensitivity are more
likely than those with lower degrees to be negatively affected
by an adversarial environment (e.g., higher depressive symp-
toms and problem behaviors) and positively influenced by a
supportive environment (e.g., lower depressive symptoms and
problem behaviors) (Belsky & Pluess, 2009). According to evo-
lutionary neurodevelopmental psychology theory, this variation
in environmental sensitivity is assumed to have evolved as a
result of a “bet-hedging strategy”(Ellis et al., 2011).
Specifically, because of the unpredictability of the quality of
the environment in which offspring lived during the era of the
ancestors, it is assumed that natural selection favored a repro-
ductive strategy that retained both individuals that responded
stably to their environment and individuals that were suscepti-
ble to change.
Recently, evidence has accumulated that a temperament/per-
sonality trait called sensory processing sensitivity (SPS) is a
concept that corresponds to individual differences in environ-
mental sensitivity (Aron et al., 2012; Hartman et al., 2023).
This construct, based on an evolutionary biological basis,
explains individual differences in a continuum of traits, such
as being alert to novel stimuli by “pause to check,”being
easily overwhelmed by stimuli, and being more aware of
subtle changes in the environment (Greven et al., 2019). The
factor structure of the SPS as measured by the highly sensitive
person (HSP) scale, self-report psychological measure, was
originally envisioned as a one-factor model (Aron & Aron,
1997), but subsequent research proposed a three-factor model
including the ease of excitation, low sensory threshold, and aes-
thetic sensitivity subscales, which has been supported in various
translated versions of the scale, including Dutch (Weyn et al.,
2021), Chinese (Liu et al., 2023), and Japanese (Iimura &
Kibe, 2020). More recently, evidence has accumulated that a
bifactor model that includes these three factors plus a general
factor that explains all items has a good fit with the data
(Lionetti et al., 2018). We refer to this general factor as GFS,
as do existing general factors such as the g-factor, the
p-factor, and GFP. Interestingly, the existence of this GFS has
been confirmed by data from both adults and children from mul-
tiple countries in the West and East (Iimura & Kibe, 2020;
Iimura et al., 2023; Pluess et al., 2018, 2023; Weyn et al.,
2021, 2022b).
The Genaral Factor of Personality (GFP)
Similar to the GFS described above, it is known that each factor
in the Big Five model describing individual differences in per-
sonality can be aggregated to one higher-order factor (Musek,
2007). In general, GFP is conceptualized as a higher-order
factor, or Big One, of two meta-traits (i.e., Big Two): Alpha
(or Stability), which describes Agreeableness, Conscientiousness
and Neuroticism, and Beta (or Plasticity), which describes
Openness and Extraversion (DeYoung et al., 2002; Digman,
1997). Evidence obtained by meta-analysis suggests that
models that include the GFP have a better fit than models con-
sisting only of Alpha and Beta (van der Linden et al., 2017).
Based on the Big Five, people with high GFP are described
as extroverted, conscientious, open-minded, compassionate,
and emotionally stable. The existence of GFP has been con-
firmed by data from various countries and different age
groups in the West and East (Dunkel et al., 2021; Kawamoto
et al., 2021; van der Linden et al., 2017; Wu et al., 2021).
However, the interpretation of GFP remains an ongoing
controversy. On one side, critics argue that GFP merely rep-
resents a social desirability or statistical or methodological
artifact (Bäckström et al., 2009; Hawes et al., 2023; Revelle
& Wilt, 2013). In addition, factor analysis of variables that
are positively correlated with each other, whether the
p-factor or GFS, necessarily supports the general factor
model mathematically, but it does not necessarily support
the existence of a substantial underlying factor (van Bork et
al., 2017).
On the other hand, researchers have pointed out that even
when controlling for social desirability bias, GFP is a construct
that holds more psychological meaning than that (Dunkel & van
der Linden, 2014). It is important to note here that both posi-
tions are persuasive in their own right and need not necessarily
be mutually exclusive (Pelt et al., 2020). Focusing on the latter
position, a number of studies have accumulated findings that
GFP correlates with individual differences in aspects of social
effectiveness, such as ability, intelligence, and emotion. For
example, an early study by Musek (2007) reported a strong pos-
itive correlation between GFP and positive emotionality, life
satisfaction, and self-esteem. Subsequent studies, which con-
tinue to date, have reported positive correlations with emotional
intelligence (van der Linden et al., 2017), trait resilience
(Dunkel et al., 2021), leadership as rated by others (Wu et al.,
2021), subjective interpersonal quality (Pelt et al., 2020), and
monthly income (van der Linden et al., 2023a). GFP has also
been shown to be negatively correlated with emotional and
behavioral problems (Kawamoto et al., 2021), the p-factor
(Etkin et al., 2020; van der Linden et al., 2023b), and
Machiavellianism and psychopathy among Dark Triad models
(Kowalski et al., 2016). In addition, GFP may be a continuous
trait influenced by natural selection (Rushton et al., 2008), and
more recently, it has been suggested that high GFP levels are a
more female-typical trait in an evolutionary context (Kanazawa,
2024).
Are GFS Associated with GFP?
The association between GFS and GFP has not yet been exam-
ined. However, evidence is accumulating on correlations
between these subfactors. Although the findings are based
mainly on data obtained from people in Western countries, a
meta-analysis by Lionetti et al. (2019) reported that higher
2Evolutionary Psychology
environmental sensitivity as measured by the HSP scale was
positively correlated with Neuroticism and Openness in adults
and with Neuroticism in children. Not included in this
meta-analysis, a recent study conducted in Japan reported that
environmental sensitivity is positively correlated with
Neuroticism and negatively correlated with Extraversion and
Agreeableness and Conscientiousness in Japanese adults
(Iimura et al., 2023; Yano et al., 2021). Based on the correlation
coefficients obtained, some critics argue that the environmental
sensitivity is an indistinguishable construct from the Big Five
(Hellwig & Roth, 2021), while others argue that the two are dis-
tinguishable (Lionetti et al., 2024). Despite this controversy,
environmental sensitivity has shown relatively robust correla-
tions with several of the Big Five factors. These findings moti-
vate us to examine the question of this study: Is there a
correlation between GFS and GFP?
The Current Study
The purpose of this preregistered study was to investigate the
correlation between GFS and GFP. For this purpose, we con-
ducted an online survey and collected data from 1,046
Japanese adults aged 20–69 years. As reviewed previously,
no findings have examined the association between GFS and
GFP, so we did not hypothesize a priori about the direction or
size of the correlation between the two. We examined the cor-
relation between the two in an exploratory manner using confir-
matory factor analysis. In our analysis, the GFS was composed
of three different models (i.e., a bifactor model, a hierarchical
model, and a one-factor model, respectively), and the correla-
tion coefficients with GFP, composed as higher-order factors
in alpha and beta, respectively, were calculated. The correlation
between GFS and GFP was interpreted based on estimates from
the best-fitting model.
Method
Procedure and Participants
A total of 1,142 Japanese adults (50% female) participated in
the study. Attention checks using the Directed Questions
scale (Maniaci & Rogge, 2014) revealed that 96 (8.4%) of the
participants inappropriately responded to the item “Please
select option of this item strongly disagree,”so these samples
were excluded from the dataset for the analysis. Finally, data
from 1,046 participants (52% female, M
age
=45.15, SD
age
=
12.70, MIN
age
=20, MAX
age
=69) were used in the analysis.
Of the participants, 72.5% were married, 72.7% had at least
one child, and the range of annual household income with the
highest percentage was 4–6 million yen (approximately
26,666–40,000 USD; 18.8%).
This study has been approved by the ethics review commit-
tee of Soka University (Approval No. 2023042). In addition, the
protocol for this study has been preregistered with the Open
Science Framework (OSF; https://doi.org/10.17605/OSF.IO/
THSVM). We recruited Japanese adults from survey panelists
registered with the market research firm Macromill, Inc.
Informed consent was obtained via an online questionnaire
from participants who expressed interest in our study. After
the survey was completed, the market research company gave
participants points that could be exchanged for cash.
Measures
To measure environmental sensitivity as a personality trait, we
utilized the 10-item Japanese version of the HSP scale (Iimura
et al., 2023). This scale consists of three subscales: ease of exci-
tation (5 items, e.g., Do changes in your life shake you up?),
low sensory threshold (3 items, e.g., Are you bothered by
intense stimuli, like loud noises or chaotic scenes?), and aes-
thetic sensitivity (2 items, e.g., Do you notice and enjoy delicate
or fine scents, tastes, sounds, works of art?). Ease of excitation
and low sensory threshold correspond to sensitivity to negative
environments, while aesthetic sensitivity relates to sensitivity to
positive environments. Each item was rated on a 7-point Likert
scale (1 =strongly disagree to 7 =strongly agree). Internal con-
sistency showed Cronbach’sα=.88 (McDonald’sωtotal =.92)
for all 10 items, α=.88 (ωtotal =.88) for ease of excitation, α=
.85 (ωtotal =.85) for low sensory threshold, and α=.71 (ωtotal
=.73) for aesthetic sensitivity. Confirmatory factor analysis
revealed that in the three subfactor model, each goodness-of-fit
index was .969 for comparative fit index (CFI), .957 for
Tucker–Lewis index (TLI), .068 for root mean square error of
approximation (RMSEA), and .038 for standardized root mean
square (SRMR) (See next section for interpretation of the
goodness-of-fit indices). The goodness of fit of the model com-
posed of higher-order factors explaining the three subfactors
also showed the same values as the three-factor model. The
bifactor model (see also next section for details) had a slightly
better fit than the three-factor and higher-order factor models,
with .986 for CFI, .975 for TLI, .052 for RMSEA, and .021
for SRMR.
The Japanese version of the Big Five Inventory-2 (Yoshino
et al., 2022) was used to measure Big Five personality traits.
This scale consists of 60 items, including Extraversion (12
items, e.g., Is outgoing, sociable), Agreeableness (12 items,
e.g., Is compassionate, has a soft heart), Conscientiousness
(12 items, e.g., Is systematic, likes to keep things in order),
Neuroticism (12 items, e.g., Is moody, has up and down
mood swings), and Openness (12 items, e.g., Is curious about
many different things), respectively. Participants rated each
item on a 5-point Likert scale (1 =strongly disagree to 5 =
strongly agree). Internal consistency showed α=.86 (ωtotal
=.86) for Extraversion, α=.78 (ωtotal =.78) for
Agreeableness, α=.83 (ωtotal =.83) for Conscientiousness,
α=.87 (ωtotal =.87) for Neuroticism, and α=.79 (ωtotal =
.79) for Openness.
Data Analysis
First, summary statistics (e.g., mean and standard deviation) for
each variable and correlation coefficients between variables
Iimura and Yano 3
were calculated to describe the characteristics of the data in this
study. Next, we analyzed the following three models (Figure 1),
referring to the method examined in van der Linden et al. (2017)
to examine the association between GFS and GFP. The first is a
bifactor model (Figure 1A; see Rodriguez et al., 2016 for spe-
cific methodology). In this model, GFS is modeled in a bifactor
structure, consisting of a general factor explaining shared vari-
ance among all the items plus a set of group factors explaining
variance in excess of the variance shared by the general factor
(i.e., ease of excitation, low sensory threshold, and aesthetic
sensitivity). The second is a hierarchical model (Figure 1B).
In this model, GFS is modeled as a higher-order factor that
explains three subfactors. The third is a one-factor model
(Figure 1C). In this model, GFS was modeled as a single
factor explaining a single observed scale score. In each
model, GFP was represented as a higher-order factor with an
Alpha factor explaining Agreeableness, Conscientiousness
and Neuroticism, and a Beta factor explaining Openness and
Extraversion, as supported by a meta-analysis by van der
Linden et al. (2017).
The goodness of fit of each model to the data was evaluated
based on CFI,TLI,RMSEA, and SRMR.CFI and TLI are above
.90 and RMSEA and SRMR are below .08, suggesting a good fit
(Hu & Bentler, 1999; Schermelleh-Engel et al., 2003). We inter-
preted the correlations between GFS and GFP based on the
model with a good fit. Although various interpretations of cor-
relation coefficients exist, we regarded r=.10 as small, .20 as
moderate, and .30 as large effect sizes (Gignac & Szodorai,
2016). The dataset used for analysis did not contain missing
values. The significance level (alpha) was set at 5% for this
study. Additionally, the sample size of this study provided suf-
ficient statistical power (=.90) to detect small effect sizes (r=
.10). Data analysis was conducted using R version 4.2.2 and its
interface, R Studio version 2023.06.1. The analysis script has
been uploaded to OSF (https://x.gd/y95yr).
Results
Preliminary Analysis
Histograms and frequency distributions for each variable are
available in Supplemental Figures 1–10 uploaded to OSF
(https://x.gd/y95yr). Summary statistics for each variable are
presented in Table 1. As depicted in Supplemental Table 1,
females exhibited higher means than males for environmental
sensitivity, ease of excitation, low sensory threshold, aesthetic
sensitivity, Agreeableness, and Neuroticism (t(1044) =3.27 to
6.11, Cohen’sd=0.20 to 0.38, p≤.001). Males reported a
higher mean for Extraversion than females (t(1044) =3.27, d
=0.20, p=.001).
Table 2 displays the bivariate correlation coefficients.
Environmental Sensitivity exhibited a weak negative correla-
tion with Conscientiousness (r=−.14, 95% CI [−.20, −.08],
p< .001), a strong positive correlation with Neuroticism (r=
.50, 95% CI [.45, .55], p< .001), and a strong negative
correlation with Extraversion (r=−.31, 95% CI [−.36, −.25],
p< .001).
Associations Between GFS and GFP
Confirmatory factor analysis revealed that among the three
models, Model 1 (bifactor model) had the best fit to the data,
while Model 2 (hierarchical model) and Model 3 (one-factor
model) had significantly lower fit.
As depicted in Figure 2, Model 1 exhibited a strong negative
correlation between GFS and GFP (r=−.41, 95% CI [−.52,
−.30], p< .001). The goodness of fit for the model was .940
for CFI, .915 for TLI, and .087 for both RMSEA and SRMR.
Although RMSEA and SRMR were slightly higher, overall,
the fit between the data and model was good.
Model 2 (see Supplemental Figure 1 for details) yielded a
very strong negative correlation coefficient between GFS and
GFP (r=−.73, 95% CI [−.80, −.66], p< .001). However, the
goodness of fit for the model was .843 for CFI, .804 for TLI,
.112 for RMSEA, and .107 for SRMR, suggesting that Model
2 did not fit the data.
For Model 3, no correlation coefficient between the general
factors was obtained due to the lack of convergence of the solu-
tions. More details on other estimates of these models can be
found in OSF (https://x.gd/y95yr).
Discussion
The aim of this study was to examine the correlation between
the GFS and the GFP. We analyzed data from 1,046 Japanese
adults ranging in age from 20 to 69 years and found a strong
negative correlation between GFS and GFP. This means that,
overall, adults with higher environmental sensitivity tended to
report lower GFP scores, characterized by more introversion,
emotional instability, less industriousness, less openness, and
less agreeableness. Consequently, we have provided new
opportunities to describe environmental sensitivity in relation
to GFP.
Focusing on the correlation with the Big Five, similar to the
findings of a meta-analysis based on Western adult samples
(Lionetti et al., 2019), higher environmental sensitivity in
Japanese adults was strongly and positively correlated with
Neuroticism. Meanwhile, in contrast to the existing
meta-analysis, which reported no correlation between environ-
mental sensitivity and extraversion, Japanese adults with high
environmental sensitivity were more introverted. Our findings
are consistent with several previous studies analyzing
Japanese adult data (Iimura et al., 2023; Yano et al., 2021)
and seem to indicate relatively robust evidence that environ-
mental sensitivity in Japanese adults is characterized by low
levels of both Emotional Stability and Extraversion. Such dis-
crepancies across regions and/or cultures are not surprising,
as previous research has noted variations in the associations
among personality traits across different cultural contexts
(Schmitt et al., 2007). Data collected from 56 regions and/or
countries indicated that East Asians, including Japanese,
4Evolutionary Psychology
Figure 1. Three models for examining the relationship between the GFS and the GFP. Note. GFP =the general factor of personality, GFS =the
general factor of environmental sensitivity, EOE =ease of excitation, LST =low sensor y threshold, AES =aesthetic sensitivity.
Iimura and Yano 5
exhibited relatively higher levels of introversion and emotional
instability (Schmitt et al., 2007). Consequently, the association
between susceptibility, which correlates strongly with emo-
tional instability, and introversion may appear more pro-
nounced among East Asians. These cultural and regional
differences may ultimately influence the relationship between
GFS and GFP, as well as the relationship between their respec-
tive subfactors. However, there are currently no studies directly
examining these potential effects, and the mechanisms underly-
ing the co-evolution of culture, GFS, and GFP remain largely
unexplored. Addressing this gap is an important task for
future research in this field.
Given both the existing evidence that GFP is negatively cor-
related with the p-factor (Etkin et al., 2020; van der Linden
et al., 2023) and that environmental sensitivity is positively cor-
related with psychopathology (Greven et al., 2019), it is reason-
able to expect a negative correlation between GFS and GFP.
Additionally, if GFP represents social effectiveness, including
high emotional intelligence and trait resilience (Dunkel et al.,
2021; van der Linden et al., 2017), GFS may be negatively asso-
ciated with variables reflecting social effectiveness at the bivari-
ate correlation level. However, in light of the various theories of
evolutionary developmental psychology (Belsky & Pluess,
2009; Ellis et al., 2011), it is important to consider the goodness
of fit with the environment in order to properly understand the
relationship between environmental sensitivity and adjustment.
Furthermore, if a high level of GFP indicates a slow life history
strategy (Kanazawa, 2024; Rushton et al., 2008), GFS nega-
tively correlated with GFP may be an indicator of fast life
history strategy. However, it would be undesirable to oversim-
plify this speculation: In addition to the view that GFP is asso-
ciated with both ends of the life history strategy continuum (Del
Giudice, 2018), some individuals with high environmental sen-
sitivity are more susceptible to supportive environments (Pluess
& Belsky, 2013), which may reflect slow life history strategies.
One conceivable scenario, in terms of a “bet-hedging strat-
egy”(Ellis et al., 2011), is as follows: The quality of the envi-
ronment experienced during childhood emerges as one of the
most promising mediating variables for explaining the associa-
tion between GFS and GFP. In a supportive environment, indi-
viduals with high GFS may exhibit higher GFP due to their
adoption of slow life history strategies. Conversely, those
with high GFS exposed to harsh environments are likely to
develop lower GFP, opting for faster life history strategies.
Moreover, individuals with low GFS are less susceptible to
the influences of both positive and negative environments. In
the light of such a scenario, the observed negative correlation
between GFS and GFP in this study could be interpreted as a
consequence of the fact that a relative majority of Japanese par-
ticipants were particularly vulnerable to adverse childhood con-
texts. If the dataset included an equal number of participants
who experienced positive and adverse childhood environments,
it is plausible that the association between GFS and GFP would
be uncorrelated. To gain a deeper understanding of the associ-
ation between GFS and GFP, future studies would benefit
from including measures of childhood environment quality.
Finally, we note some important limitations and additional
future challenges in this study. First, and importantly, this
study did not find a biological basis underlying the association
between GFS and GFP. Therefore, we cannot rule out the pos-
sibility that it is merely an association between statistical arti-
facts (van Bork et al., 2017). Given the existing controversy,
Table 1. Descriptive Statistics (N =1,046)
M SD MIN MAX Skewness Kurtosis
Environmental
sensitivity
4.18 1.04 1.00 6.90 −0.35 0.25
Ease of excitation 4.15 1.24 1.00 7.00 −0.33 −0.01
Low sensory
threshold
4.22 1.36 1.00 7.00 −0.32 −0.33
Aesthetic
sensitivity
4.19 1.25 1.00 7.00 −0.26 0.12
Agreeableness 3.32 0.49 1.17 5.00 −0.04 1.01
Conscientiousness 3.15 0.57 1.00 5.00 −0.06 0.82
Neuroticism 3.01 0.64 1.17 4.92 0.29 0.24
Openness 3.04 0.54 1.08 4.92 0.13 0.46
Extraversion 2.78 0.64 1.00 4.75 −0.07 −0.03
Table 2. Correlation Coefficients (N =1,046)
12345 678910
1. Gender (male =1, female =2) —
2. Age −.04 —
3. Environmental sensitivity .17** −.14** —
4. Ease of excitation .19** −.20** .91** —
5. Low sensory threshold .12** −.04 .84** .63** —
6. Aesthetic sensitivity .04 −.02 .54** .30** .30** —
7. Agreeableness .10** .10** −.03 −.08** −.07* .19** —
8. Conscientiousness −.02 .19** −.14** −.27** −.05 .14** .41** —
9. Neuroticism .10** −.24** .50** .53** .40** .11** −.37** −.35** —
10. Openness −.04 .07* .06 −.09** −.05 .53** .32** .35** −.15** —
11. Extraversion −.10** .06 −.31** −.37** −29** .10** .22** .27** −.35** .37**
Note. *p< .05. **p< .01.
6Evolutionary Psychology
as this study relied on self-reported data, it would be beneficial
for future research to explore the relationship between GFS and
GFP while considering measures of social desirability bias.
Second, because this is the first study to examine the relation-
ship between GFS and GFP, it is currently unable to provide
specific discussion. In order to discuss GFS in relation to
social effectiveness and life history strategies, future studies
need to directly examine the correlation between GFS and
these factors. Third, although existing studies suggest that
both GFS and GFP have relatively stable factor structures
regardless of ethnicity, there may be cultural and/or regional
differences in their association. Future examination of the cor-
relation between GFS and GFP based on a large, culturally
diverse sample would be beneficial for understanding the asso-
ciation between the two. Additionally, it would also be useful to
examine using samples from childhood to adolescence.
Author Contributions
Shuhei Iimura contributed to conceptualization, investigation, data
analysis, and writing—original draft preparation; Kosuke Yano con-
tributed to investigation, data analysis, and writing—original draft
preparation.
Data Availability
Supplementary materials were uploaded to the Open Science
Framework (https://x.gd/y95yr). Those who wish to make secondary
use of the data should contact the corresponding author.
Declaration of Conflicting Interests
The authors declared no potential conflicts of interest with respect to
the research, authorship, and/or publication of this article.
Ethics Approval
This study was approved by the Ethics Review Committee of Soka
University (approval number: 2023042).
Funding
The authors disclosed receipt of the following financial support for the
research, authorship, and/or publication of this article: This study was
funded by JSPS KAKENHI to the first author (Grant Number
22K03049) and the second author (Grant Number 22K20329).
Informed Consent
Informed consent was obtained from all individual participants
included in the study.
ORCID iD
Shuhei Iimura https://orcid.org/0000-0002-4410-187X
Supplemental Material
Supplemental material for this article is available online.
References
Aron, E. N., & Aron, A. (1997). Sensory-processing sensitivity and its
relation to introversion and emotionality. Journal of Personality
Figure 2. Correlations between the GFS and the GFP (Bifactor Model). Note. GFP =the general factor of personality, GFS =the general factor
of environmental sensitivity, EOE =ease of excitation, LST =low sensor y threshold, AES =aesthetic sensitivity. We confirmed that the same
analysis with reversal code for Neuroticism yielded the same goodness-of-fit index.
Iimura and Yano 7
and Social Psychology,73(2), 345–368. https://doi.org/10.1037/
0022-3514.73.2.345
Aron, E. N., Aron, A., & Jagiellowicz, J. (2012). Sensory processing
sensitivity: A review in the light of the evolution of biological
responsivity. Personality and Social Psychology Review,16(3),
262–282. https://doi.org/10.1177/1088868311434213
Assary, E., Zavos, H. M. S., Krapohl, E., Keers, R., & Pluess, M.
(2021). Genetic architecture of environmental sensitivity reflects
multiple heritable components: A twin study with adolescents.
Molecular Psychiatry,26, 4896–4904. https://doi.org/10.1038/
s41380-020-0783-8
Bäckström, M., Björklund, F., & Larsson, M. R. (2009). Five-factor
inventories have a major general factor related to social desirability
which can be reduced by framing items neutrally. Journal of
Research in Personality,43(3), 335–344. https://doi.org/10.1016/
j.jrp.2008.12.013
Belsky, J., & Pluess, M. (2009). Beyond diathesis stress: Differential
susceptibility to environmental influences. Psychological Bulletin,
135(6), 885–908. https://doi.org/10.1037/a0017376
Caspi, A., Houts, R. M., Belsky, D. W., Goldman-Mellor, S. J.,
Harrington, H., Israel, S., Meier, M. H., Ramrakha, S., Shalev, I.,
Poulton, R., & Moffitt, T. E. (2014). The p factor: One general psy-
chopathology factor in the structure of psychiatric disorders?
Clinical Psychological Science,2(2), 119–137. https://doi.org/10.
1177/2167702613497473
Del Giudice, M. (2018). Evolutionary psychopathology: A unified
approach. Oxford University Press.
DeYoung, C., Peterson, J. B., & Higgins, D. M. (2002). Higher-order
factors of the Big Five predict conformity: Are there neuroses of
health? Personality and Individual Differences,33(4), 533–552.
https://doi.org/10.1016/S0191-8869(01)00171-4
Digman, J. M. (1997). Higher-order factors of the Big Five. Journal of
Personality and Social Psychology,73(6), 1246–1256. https://doi.
org/10.1037/0022-3514.73.6.1246
Dunkel, C. S., & van der Linden, D. (2014). Evidence for the general
factor of personality as social-effectiveness. Personality and
Individual Differences,64, 147–151. https://doi.org/10.1016/j.
paid.2014.02.030
Dunkel, C. S., van der Linden, D., Kawamoto, T., & Oshio, A. (2021).
The general factor of personality as ego-resiliency. Frontiers in
Psychology,12, 741462. https://doi.org/10.3389/fpsyg.2021.
741462
Ellis, B. J., Boyce, W. T., Belsky, J., Bakermans-Kranenburg, M. J., &
van Ijzendoorn, M. H. (2011). Differential susceptibility to the
environment: An evolutionary-neurodevelopmental theory.
Development and Psychopathology,23(1), 7–28. https://doi.org/
10.1017/S0954579410000611
Etkin, P., Mezquita, L., López-Fernández, F. J., Ortet, G., & Ibáñez, M.
I. (2020). Five factor model of personality and structure of psycho-
pathological symptoms in adolescents. Personality and Individual
Differences,163(1), 110063. https://doi.org/10.1016/j.paid.2020.
110063
Figueredo, A. J., Vásquez, G., Brumbach, B. H., & Schneider, S. M. R.
(2004). The heritability of life history strategy: The K-factor, covi-
tality, and personality. Biodemography and Social Biology,51(3-
4), 121–143. https://doi.org/10.1080/19485565.2004.9989090
Gignac, G. E., & Szodorai, E. T. (2016). Effect size guidelines for indi-
vidual differences researchers. Personality and Individual
Differences,102,74–78. https://doi.org/10.1016/j.paid.2016.06.
069
Greven, C. U., Lionetti, F., Booth, C., Aron, E. N., Fox, E., Schendan,
H. E., Pluess, M., Bruining, H., Acevedo, B., Bijttebier, P., &
Homberg, J. (2019). Sensory processing sensitivity in the context
of environmental sensitivity: A critical review and development
of research agenda. Neuroscience and Biobehavioral Reviews,98,
287–305. https://doi.org/10.1016/j.neubiorev.2019.01.009
Hartman, S., Belsky, J., & Pluess, M. (2023). Prenatal programming of
environmental sensitivity. Translational Psychiatry,13, 161.
https://doi.org/10.1038/s41398-023-02461-y
Hawes, M. T., Klein, D. N., Olino, T. M., & Kotov, R. (2023).
Multi-method longitudinal investigation of the general factor of
child temperament (GFT): Substantive phenomenon or methodo-
logical artifact? Journal of Research in Personality,104, 104375.
https://doi.org/10.1016/j.jrp.2023.104375
Haworth, C. M. A., Wright, M. J., Luciano, M., Martin, N. G., de Geus,
E. J. C., van Beijsterveldt, C. E. M., Bartels, M., Posthuma, D.,
Boomsma, D. I., Davis, O. S. P., Kovas, Y., Corley, R. P.,
DeFries, J. C., Hewitt, J. K., Olson, R. K., Rhea, S.-A.,
Wadsworth, S. J., Iacono, W. G., & McGue, M., …R. Plomin
(2010). The heritability of general cognitive ability increases line-
arly from childhood to young adulthood. Molecular Psychiatry,
15, 1112–1120. https://doi.org/10.1038/mp.2009.55
Hellwig, S., & Roth, M. (2021). Conceptual ambiguities and measure-
ment issues in sensory processing sensitivity. Journal of Research
in Personality,93, 104130. https://doi.org/10.1016/j.jrp.2021.
104130
Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes
in covariance structure analysis: Conventional criteria versus
new alternatives. Structural Equation Modeling: A
Multidisciplinary Journal,6,1–55. https://doi.org/10.1080/
10705519909540118
Iimura, S., & Kibe, C. (2020). Highly sensitive adolescent benefits in
positive school transitions: Evidence for vantage sensitivity in
Japanese high-schoolers. Developmental Psychology,56(8),
1565–1581. https://doi.org/10.1037/dev0000991
Iimura, S., Yano, K., & Ishii, Y. (2023). Environmental sensitivity in
adults: Psychometric properties of the Japanese version of the
Highly Sensitive Person Scale 10-item version. Journal of
Personality Assessment,105(1), 87–99. https://doi.org/10.1080/
00223891.2022.2047988
Kanazawa, S. (2024). The general factor of personality as a female-
typical trait. Personality and Individual Differences,218, 112470.
https://doi.org/10.1016/j.paid.2023.112470
Kawamoto, T., Kubota, A. K., Sakakibara, R., Muto, S., Tonegawa,
A., Komatsu, S., & Endo, T. (2021). The general factor of person-
ality (GFP), trait emotional intelligence, and problem behaviors in
Japanese teens. Personality and Individual Differences,171,
110480. https://doi.org/10.1016/j.paid.2020.110480
Kowalski, C. M., Vernon, P. A., & Schermer, J. A. (2016). The general
factor of personality: The relationship between the Big One and the
Dark Triad. Personality and Individual Differences,88, 256–260.
https://doi.org/10.1016/j.paid.2015.09.028
8Evolutionary Psychology
Lionetti, F., Aron, A., Aron, E. N., Burns, G. L., Jagiellowicz, J., &
Pluess, M. (2018). Dandelions, tulips and orchids: Evidence for
the existence of low-sensitive, medium-sensitive and high-sensitive
individuals. Translational Psychiatry,8, 24. https://doi.org/10.
1038/s41398-017-0090-6
Lionetti, F., Dumpfrey, R. S. C., Richetin, J., Fasolo, M., Nocentini,
A., Penolazzi, B., Pluess, M., Santona, A., Spinelli, M., & Preti,
E. (2024). Is environmental sensitivity a unique trait? A multi-
sample study on the association between sensitivity, personality,
and psychological adjustment. Personality and Individual
Differences,217, 112463. https://doi.org/10.1016/j.paid.2023.
112463
Lionetti, F., Pastore, M., Moscardino, U., Nocentini, A., Pluess, K., &
Pluess, M. (2019). Sensory processing sensitivity and its associa-
tion with personality traits and affect: A meta-analysis. Journal of
Research in Personality,81, 138–152. https://doi.org/10.1016/j.
jrp.2019.05.013
Liu, D., Van Dijk, A., Lin, S., Wang, Z., Dekovic, M., & Dubas, J. S.
(2023). Psychometric properties of the Chinese version of the
Highly Sensitive Child Scale across age groups, gender, and infor-
mants. Child Indicators Research,16(4), 1755–1780. https://doi.
org/10.1007/s12187-023-10032-2
Maniaci, M. R., & Rogge, R. D. (2014). Caring about carelessness:
Participant inattention and its effects on research. Journal of
Research in Personality,48,61–83. https://doi.org/10.1016/j.jrp.
2013.09.008
Musek, J. (2007). A general factor of personality: Evidence for the Big
One in the five-factor model. Journal of Research in Personality,
41, 1213–1233. https://doi.org/10.1016/j.jrp.2007.02.003
Pelt, D. H. M., van der Linden, D., Dunkel, C. S., & Born, M. P.
(2020). The general factor of personality and daily social experi-
ences: Evidence for the social effectiveness hypothesis.
Personality and Individual Differences,155, 109738. https://doi.
org/10.1016/j.paid.2019.109738
Pluess, M., Assary, E., Lionetti, F., Lester, K. J., Krapohl, E., & Aron,
E. N. (2018). Environmental sensitivity in children: Development
of the Highly Sensitive Child Scale and identification of sensitivity
groups. Developmental Psychology,54(1), 51–70. https://doi.org/
10.1037/dev0000406
Pluess, M., & Belsky, J. (2013). Vantage sensitivity: Individual differ-
ences in response to positive experiences. Psychological Bulletin,
139(4), 901–916. https://doi.org/10.1037/a0030196
Pluess, M., Lionetti, F., Aron, E. N., & Aron, A. (2023). People differ
in their sensitivity to the environment: An integrated theory, mea-
surement and empirical evidence. Journal of Research in
Personality,104, 104377. https://doi.org/10.1016/j.jrp.2023.
104377
Revelle, W., & Wilt, J. (2013). The general factor of personality: A
general critique. Journal of Research in Personality,47, 493–
504. https://doi.org/10.1016/j.jrp.2013.04.012
Rodriguez, A., Reise, S. P., & Haviland, M. G. (2016). Evaluating
bifactor models: Calculating and interpreting statistical indices.
Psychological Methods,21(2), 137–150. https://doi.org/10.1037/
met0000045
Rushton, J. P., Bons, T. A., & Hur, Y.-M. (2008). The genetics and
evolution of the general factor of personality. Journal of
Research in Personality,42(5), 1173–1185. https://doi.org/10.
1016/j.jrp.2008.03.002
Schermelleh-Engel, K., Moosbrugger, H., & Müller, H. (2003).
Evaluating the fit of structural equation models: Tests of signifi-
cance and descriptive goodness-of-fit measures. Methods of
Psychological Research,8(2), 23–74. https://doi.org/10.23668/
psycharchives.12784
Schmitt, D. P., Allik, J., McCrae, R. R., & Benet-Martínez, V. (2007).
The geographic distribution of Big Five personality traits: Patterns
and profiles of human self-description across 56 nations. Journal of
Cross-Cultural Psychology,38(2), 173–212. https://doi.org/10.
1177/0022022106297299
Slagt, M., Dubas, J. S., van Aken, M. A. G., Ellis, B. J., & Dekovic,M.
(2018). Sensory processing sensitivity as a marker of differential
susceptibility to parenting. Developmental Psychology,54(3),
543–558. https://doi.org/10.1037/dev0000431
Spearman, C. (1904). “General intelligence,”objectively determined
and measured. The American Journal of Psychology,15(2), 201–
292. https://doi.org/10.2307/1412107
van Bork, R., Epskamp, S., Rhemtulla, M., Borsboom, D., & Van Der
Maas, H. L. J. (2017). What is the p-factor of psychopathology?
Some risks of general factor modeling. Theory and Psychology,
27(6), 759–773. https://doi.org/10.1177/0959354317737185
van der Linden, D., Dunkel, C. S., & Dutton, E. (2023a). The general
factor of personality (GFP) is associated with higher salary, having
a leadership position, and working in a social job. Acta
Psychologica,234, 103847. https://doi.org/10.1016/j.actpsy.2023.
103847
van der Linden, D., Dunkel, C. S., Prinzie, P., Yamanaka-Altenstein,
M., von Wyl, A., & Hengartner, M. P. (2023b). Overlap between
general factors of psychopathology and personality: They share
associations with daily life functioning and communication style.
Current Psychology,42(13), 10964–10976. https://doi.org/10.
1007/s12144-021-02354-7
van der Linden, D., Pekaar, K. A., Bakker, A. B., Schermer, J. A.,
Vernon, P. A., Dunkel, C. S., & Petrides, K. V. (2017). Overlap
between the general factor of personality and emotional intelli-
gence: A meta-analysis. Psychological Bulletin,143(1), 36–52.
https://doi.org/10.1037/bul0000078
Veselka, L., Schermer, J. A., Petrides, K. V., & Vernon, P. A. (2009).
Evidence for a heritable general factor of personality in two studies.
Twin Research and Human Genetics,12(3), 254–260. https://doi.
org/10.1375/twin.12.3.254
Weyn, S., Van Leeuwen, K., Pluess, M., Goossens, L., Claes, S.,
Bosmans, G., van den Noortgate, W., Lutin, E., Bröhl, A. S.,
Chubar, V., Geukens, F., & Bijttebier, P. (2022a). Individual differ-
ences in environmental sensitivity at physiological and phenotypic
level: Two sides of the same coin? International Journal of
Psychophysiology,176,36–53. https://doi.org/10.1016/j.ijpsycho.
2022.02.010
Weyn, S., Van Leeuwen, K., Pluess, M., Lionetti, F., Goossens, L.,
Bosmans, G., van den Noortgate, W., Debeer, D., Bröhl, A. S., &
Bijttebier, P. (2022b). Improving the measurement of environmen-
tal sensitivity in children and adolescents: The Highly Sensitive
Child Scale-21 Item Version. Assessment,29, 607–629. https://
doi.org/10.1177/1073191120983894
Iimura and Yano 9
Weyn, S., Van Leeuwen, K., Pluess, M., Lionetti, F., Greven, C. U.,
Goossens, L., Colpin, H., van den Noortgate, W., Verschueren,
K., Bastin, M., van Hoof, E., De Fruyt, F., & Bijttebier, P.
(2021). Psychometric properties of the Highly Sensitive Child
scale across developmental stage, gender, and country. Current
Psychology,40(7), 3309–3325. https://doi.org/10.1007/s12144-
019-00254-5
Wu, P., van der Linden, D., Dunkel, C. S., Ding, R., Li, J., Li, X.,
Harmon, A., & Born, M. P. (2021). A meta-analysis on the
general factor of personality and its relation with leadership out-
comes: Evidence from mainland China. Personality and
Individual Differences,179, 110953. https://doi.org/10.1016/j.
paid.2021.110953
Yano, K., Kase, T., & Oishi, K. (2021). The associations between
sensory processing sensitivity and the Big Five personality traits
in a Japanese sample. Journal of Individual Differences,42(2),
84–90. https://doi.org/10.1027/1614-0001/a000332
Yoshino, S., Shimotsukasa, T., Oshio, A., Hashimoto, Y., Ueno, Y.,
Mieda, T., Migiwa, I., Sato, T., Kawamoto, S., Soto, C. J., &
John, O. P. (2022). A validation of the Japanese adaptation of the
Big Five Inventory-2. Frontiers in Psychology,13, 924351.
https://doi.org/10.3389/fpsyg.2022.924351
10 Evolutionary Psychology
