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Background. Benda and Reichová (2016) recently published the Czech version of the Self-Compassion Scale. Because of the results of the confirmatory factor analyses (CFA), they recommended that six problematic items from this scale were omitted and the 20-item Czech version of the Self-Compassion Scale (SCS-CZ) was to be used instead. Inspired by Neff, Tóth-Király and Colosimo's study (in print) which argues for the use of the Exploratory Structural Equation Modeling (ESEM) in dimensionality studies of the SCS, I decided to test 6 new ESEM models of the Czech version of the Self-Compassion Scale (SCS-26-CZ) in this study. Methods. The sample of 5368 participants from Benda and Reichová's (2016) study was used to test the models. All analyses were performed with Mplus 7. The following fit indices were used to indicate the global fit of the models to the data: the chi-square test, the CFI, the TLI, the RMSEA and the WRMR. Parameter estimates of the models were examined. For bifactor models, the following indices were computed: the PUC, the ECV, the omega, (ω), the omega hierarchical (ωh) and the omega hierarchical subscale (ωhs). Results. The one-factor ESEM model and the two-factor ESEM model showed a poor fit with the data. The six factor ESEM model, the bifactor ESEM model, the two-bifactor ESEM model and the full two-tier ESEM model showed an acceptable fit. The six factor ESEM model, however, was problematic due to the presence of multiple cross-loadings. The bifactor ESEM model and the two-bifactor ESEM model were below the expected benchmark for the ωh and the ECV. Conclusion. The full two-tier ESEM model of the 26-item Czech version of the Self-compassion scale (SCS-26-CZ) showed acceptable fit in a sample of 5368 participants (see Benda, Reichová, 2016) as well as acceptable model-based reliability and dimensionality. The 26-item Czech version of the Self-Compassion Scale (SCS-26-CZ) can thus be used as a measure of compassionate self-responding and reduced uncompassionate self-responding.
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Alternative models of the Czech version of the Self-Compassion Scale (SCS-26-CZ)
Jan Benda1
1Department of Psychology, Charles University in Prague
E-mail: psychoterapeut@gmail.com
Abstract
Background. Benda and Reichová (2016) recently published the Czech version of the Self-Compassion Scale.
Because of the results of the confirmatory factor analyses (CFA), they recommended that six problematic items
from this scale were omitted and the 20-item Czech version of the Self-Compassion Scale (SCS-CZ) was to
be used instead. Inspired by Neff, Tóth-Király and Colosimo's study (in print) which argues for the use of the
Exploratory Structural Equation Modeling (ESEM) in dimensionality studies of the SCS, I decided to test
6 new ESEM models of the Czech version of the Self-Compassion Scale (SCS-26-CZ) in this study. Methods.
The sample of 5368 participants from Benda and Reichová's (2016) study was used to test the models. All
analyses were performed with Mplus 7. The following fit indices were used to indicate the global fit of the
models to the data: the chi-square test, the CFI, the TLI, the RMSEA and the WRMR. Parameter estimates of
the models were examined. For bifactor models, the following indices were computed: the PUC, the ECV, the
omega, (ω), the omega hierarchical h) and the omega hierarchical subscale hs). Results. The one-factor
ESEM model and the two-factor ESEM model showed a poor fit with the data. The six factor ESEM model,
the bifactor ESEM model, the two-bifactor ESEM model and the full two-tier ESEM model showed
an acceptable fit. The six factor ESEM model, however, was problematic due to the presence of multiple cross-
loadings. The bifactor ESEM model and the two-bifactor ESEM model were below the expected benchmark
for the ωh and the ECV. Conclusion. The full two-tier ESEM model of the 26-item Czech version of the Self-
compassion scale (SCS-26-CZ) showed acceptable fit in a sample of 5368 participants (see Benda, Reichová,
2016) as well as acceptable model-based reliability and dimensionality. The 26-item Czech version of the Self-
Compassion Scale (SCS-26-CZ) can thus be used as a measure of compassionate self-responding and reduced
uncompassionate self-responding.
Keywords: self-compassion, self-coldness, Self-Compassion Scale, bifactor analysis, two-tier model
Introduction
The Self-Compassion Scale (SCS; Neff, 2003) is so far the most often used measure of self-
compassion (Neff, Tóth-Király, Colosimo, in print). Benda and Reichová (2016) recently translated
the SCS into Czech (with a back-translation procedure) and tested four different models of the factor
structure of the Czech version of the SCS in a sample of 5368 participants: one-factor model (all
2
items load onto one factor); six-factor model (items load onto six factors); hierarchical model (six
factors load onto one factor) and three-factor model (items load onto three factors based on three
theoretically proposed components of self-compassion). Because the confirmatory factor analysis
with maximum likelihood estimation in their survey 1 (N = 5368) confirmed none of the models,
Benda and Reichová (2016) decided to remove six problematic items (items 3, 9, 15, 21, 22 and 23)
from the Czech version of the SCS. Subsequent CFA (with ML estimation) confirmed both the six-
factor model and the hierarchical model of the 20-item Czech version of the Self-Compassion Scale
(SCS-CZ). The correlation between the total scores of the 20-item and 26-item Czech versions of the
SCS was r = .99 (p < .01).
Since the publication of Benda and Reichová's (2016) article, there was, however, an ongoing debate
about the factor structure of the SCS. Some authors (e.g. Brenner et al., 2017; Brenner et al., 2018;
Coroiu et al., 2018; Costa et al., 2016; López et al., 2015; Muris, Petrocchi, 2017; Muris, Otgaar,
Petrocchi, 2016; Pfattheicher et al., 2017) suggested a two-factor solution of the SCS. Neff argued
for the use of a global self-compassion factor and recommended the use of a bifactor ESEM models
in dimensionality studies of the SCS (e.g. Neff, 2016a,b; Neff, Tóth-Király, Colosimo, in print; Neff,
Whittaker, Karl, 2017; Tóth-Király, Bőthe, Orosz, 2017). According to Neff, Tóth-Király and
Colosimo (in print) the Exploratory Structural Equation Modeling provides a more realistic
representation of the self-compassion construct compared to CFA. Therefore, in this short article I
decided to test some additional ESEM models of the Czech version of the SCS using the sample 1
from Benda and Reichová's (2016) study.
Method
Participants
In their original article, Benda and Reichová (2016) included 5368 participants, of whom 1585 were
males (29.5%) and 3783 females (70.5%). The mean age was 33.79 years (SD = 11.58) and ranged
from 14 to 81 years. The participants were recruited through Facebook.
Measure
Self-compassion was measured with the 26-item Czech version of the Self-Compassion Scale (SCS-
26-CZ, Neff, 2003; Czech translation Benda, Reichová, 2016), which assesses six different
components of self-compassion: self-kindness (SK), self-judgment (SJ), common humanity (CH),
isolation (IS), mindfulness (MI) and over-identification (OI). Respondents rated each self-statement on
3
a five-point Likert-type scale (from 1 = almost never to 5 = almost always). Total self-compassion score is
calculated as a grand mean of all six subscales.
Statistical analyses
All analyses were performed with Mplus 7 (Muthén & Muthén, 1998-2012). Models were estimated
with the weighted least squares mean- and variance-adjusted (WLSMV) estimator. Inspired by the
studies of Neff, Tóth-Király and Colosimo (in print) and Coroiu et al. (2018) I decided to test six
ESEM models: 1) a one-factor model with a single self-compassion dimension; 2) a two-factor
correlated model with one factor representing compassionate self-responding (SK, CH & MI items)
and reduced uncompassionate self-responding (SJ, IS & OI items); 3) a six-factor correlated model
representing the six components of self-compassion self-kindness, self-judgment, common
humanity, isolation, mindfulness and over-identification; 4) a bifactor model with a general self-
compassion factor and six specific factors that were orthogonal to each other; 5) a two-bifactor model
including two correlated general compassionate self-responding (CS) and reduced uncompassionate
self-responding (RUS) factors, each with three CS or RUS group factors which were orthogonal to
one another and the general factors as well; and 6) a full two-tier model with two uncorrelated general
compassionate self-responding (CS) and reduced uncompassionate self-responding (RUS) factors,
and six group factors, three corresponding to the CS factor (SK, CH, MI), and three corresponding to
the RUS factor (SJ, IS, OI). Cross-loadings were allowed (see Figure 1).
Figure 1
Full two-tier ESEM model (model 6)
Note. ESEM = exploratory structural equation modeling; Circles represent latent variables, squares
represent scale items. One-headed full arrows represent factor loadings, one-headed dashed arrows
represent cross-loadings.
4
In addition to the chi-square test, which is highly sensitive to sample size (Marsh, Hau, & Grayson,
2005), the following fit indices were used to indicate the global fit of the models to the data: the
Comparative Fit Index (CFI), the Tucker-Lewis Index (TLI), the Root Mean Square Error of
Approximation (RMSEA) with its 90% confidence interval and the weighted root-mean-square
residual (WRMR). An acceptable model fit was indicated by TLI and CFI ≥ .95, RMSEA ≤ .06 and
WRMR ≤ 1.0 (DiStefano et al., 2018; Hu, Bentler, 1999). For bifactor models, the following indices
were further computed: percentage of uncontaminated correlations (PUC), explained common
variance (ECV), omega (ω), omega hierarchical h) and omega hierarchical subscale hs). If PUC
was > .80, the recommended cut offs of ECV > .80 and ωh and ωhs > .80 were used to identify strong
general factors (Reise, 2012; Rodriguez, Reise, Haviland, 2016). However, if PUC was below .80,
cut offs of ECV. > 60 and ωh and ωhs > .70 were used (e.g., Reise, Scheines, Widaman, & Haviland,
2013).
Results
Table 1 Goodness-of-Fit Statistics for the Estimated Models for the SCS-26-CZ (N = 5368)
Model χ2 df CFI TLI RMSEA 90% CI WRMR
1. One-factor ESEM: One G-factor (SC)
29950*
299
.76
.74
.14
.14-.14
2. Two-factor ESEM: Two G-factors (CS,
RUS)
19819*
274
.84
.81
.12
.11-.12
3. Six-factor ESEM: Six S-factors (SK, SJ,
CH, IS, MI, OI)
2201*
184
.98
.97
.05
.05-.05
4. Bifactor ESEM: One G-factor (SC) Six S-
factors (SK, SJ, CH, IS, MI, OI)
1560*
164
.99
.98
.04
.04-.04
5. Two-bifactor ESEM: Two G-factors (CS,
RUS) Six S-factors (SK, SJ, CH, IS, MI, OI)
1115*
157
.99
.98
.03
.03-.04
6. Full two-tier ESEM: Two G-factors (CS,
RUS), Six S-factors, three for CS factor (SK,
CH, MI), and three for RUS factor (SJ, IS,
OI), with cross-loadings allowed.
1080*
325
.99
.98
.04
.03-.04
Note. χ2 = Chi-square test of exact fit; df = Degrees of freedom; CFI = Comparative fit index; TLI = Tucker-
Lewis index; RMSEA = Root mean square error of approximation; 90% CI = 90% confidence interval of the
RMSEA; WRMR = Weighted root-mean-square residual; PCFI = Parsimony-corrected CFI; SC = Self-
Compassion; CS = Compassionate Self-responding; RUS = Reduced Uncompassionate Self-responding; SK =
Self-Kindness; SJ = Self-Judgment (reduced); CH = Common Humanity; IS = Isolation (reduced); MI =
Mindfulness; OI = Over-Identification (reduced); G-factor = Global factor; S-factor = Specific factor; *p < .01.
Goodness-of-fit statistics for the SCS-26-CZ are reported in Table 1. As is shown, models 1 and 2
provided a poor fit to the data. Models 3, 4, 5 and 6 showed an acceptable fit. Closer inspection of
the parameter estimates, however, revealed multiple statistically significant cross-loadings in models
5
3, 4, 5 and 6 (see e.g. items 6, 21, 23, in Tables 3, 4, 5 and 6). The presence of such cross-loadings
suggest that these items might better reflect a global construct. In model 3 (Six-factor ESEM) the
factor loadings ranged from .12 to .89 and means were between .35 and .57 (see Table 3). Yet, model
3 can be considered as problematic due to the cross-loadings. In model 5 (two-bifactor ESEM) the
two general factors were weakly defined (CS: |λ| = .01 to .35, M = .16; RUS: |λ| = .17 to .45, M = .32,
see Table 5; ECV for the CS factor was .06 and for the RUS factor .32, see Table 2). In models 4 and
6, the general factor loadings were acceptable.
In model 4 (Bifactor ESEM) the factor loadings of the global self-compassion factor ranged from .24
to .76, M = .55 (see Table 4). The omega coefficient (ω) was .96 and omega-hierarchical h) for the
global self-compassion factor was .73. The model 4 PUC was .87. The explained common variance
for the global factor (ECV) was .58, meaning that the global self-compassion factor explains 58% of
the common variance extracted with 42% of the common variance spread across specifics factors
(SK, SJ, CH, IS, MI and OI). Omega-h subscale hs) was .04 for the self-kindness factor, .03 for the
self-judgment factor, .04 for the common humanity factor, .05 for the isolation factor, .05 for the
mindfulness factor and .03 for the over-identification factor (see Table 2).
Table 2 Statistical indices of models 4, 5 and 6 (N = 5368)
Model ω ωh ωhs PUC ECV
4. Bifactor ESEM .96 .73 .04 SK; .03 SJ; .04 CH; .05 IS; .05 MI; .03 OI .87 .58
5. Two-bifactor ESEM
CS
.91
.06
.55 SK; .18 CH; .13 MI
.72
.06
RUS
.84
.32
.20 SJ; .26 IS; .06 OI
.72
.32
6. Full two-tier ESEM
CS
.86
.73
.05 SK; .06 CH; .02 MI
.72
.59
RUS
.87
.79
.04 SJ; .02 IS; .01 OI
.72
.71
Note. ω = omega; ωh = omega hierarchical; ωhs = omega hierarchical subscale; PUC = percent of
uncontaminated correlations; ECV = explained common variance; CS = Compassionate Self-responding
factor; RUS = Reduced Uncompassionate Self-responding factor.
In model 6 (Full two-tier ESEM) the factor loadings of the compassionate self-responding (CS) factor
ranged from .29 to .71, M = .55 and the factor loadings of the reduced uncompassionate self-
responding (RUS) factor ranged from .17 to .69, M = .52 (see Table 6). The model 6 PUC was .72.
For the CS factor ω = .86, ωh = .73 and ECV = .59; ωhs = .05 for self-kindness, ωhs = .06 for common
humanity and ωhs = .02 for mindfulness CS group factors. For the RUS factor ω = .87, ωh = .79 and
ECV = .71; ωhs = .04 for self-judgment, ωhs = .02 for isolation, and ωhs = .01 for over-identification
RUS group factors. Concerning model-based reliability and dimensionality, model 6 showed superior
properties compared to model 4. The low omega hierarchical subscale hs) in model 6 indicates that
6
reliability diminishes upon partialing out common variance shared with the general factors. The use
of six subscale scores of the SCS-26-CZ is thus not recommended.
Conclusion
In this study, the Full two-tier ESEM model of the 26-item Czech version of the Self-compassion
scale (SCS-26-CZ) showed an acceptable fit in a sample of 5368 participants (see Benda, Reichová,
2016) as well as an acceptable model-based reliability and dimensionality. The 26-item Czech version
of the Self-Compassion Scale (SCS-26-CZ) thus can be used as a measure of compassionate self-
responding and reduced uncompassionate self-responding.
A closing note
I hope this study will contribute to the debate about the factor structure of the Self-Compassion Scale.
I will appreciate any comments, criticism or discussion. Please add your comments to this article.
7
Table 3 Standardized Parameter Estimates for the Model
3: Six-factor ESEM solution of the SCS-26-CZ (N = 5368)
SK (λ) SJ (λ) CH (λ) IS (λ) MI (λ) OI (λ)
Self-kindness
sk5
.71
-.01
.12
-.03
.02
-.03
sk12
.73
.02
.05
-.08
.08
-.02
sk19
.89
-.01
.03
-.03
.03
-.06
sk23
.17
-.60
.14
.07
.25
.05
sk26
.34
-.34
.11
.06
.36
.06
Self-judgment
sj1
-.03
.65
-.05
.06
.10
.08
sj8
-.24
.51
.04
-.09
.23
.04
sj11
-.08
.56
-.02
.07
-.08
.12
sj16
-.06
.40
.01
.34
-.09
.11
sj21
-.49
.16
.00
.13
.19
-.06
Common humanity
ch3
-.01
.07
.34
-.17
.23
.02
ch7
-.05
.09
.89
.06
-.15
.01
ch10
-.02
.07
.88
.11
-.11
-.01
ch15
.16
-.13
.36
-.09
.39
.09
Isolation
is4
-.03
.16
-.12
.52
.05
.14
is13
-.07
-.03
-.00
.63
-.11
.14
is18
-.03
.09
.07
.61
-.16
.06
is25
-.07
.09
-.16
.50
.07
.20
Mindfulness
mi9
.07
.13
.02
.21
.42
-.50
mi14
.13
.13
.11
-.07
.54
-.18
mi17
.09
.05
.17
-.18
.53
-.03
mi22
.46
.03
.09
-.12
.31
.14
Over-identification
oi2
-.06
.15
-.10
.42
-.09
.26
oi6
-.03
.36
-.06
.39
-.05
.12
oi20
-.07
.06
.04
-.07
-.17
.64
oi24
.07
.06
-.02
.25
-.16
.38
mean .57 .46 .62 .57 .45 .35
Note. ESEM = exploratory structural equation modeling; SK = self-
kindness; SJ = self-judgment (reduced); CH = common humanity; IS
= isolation (reduced); MI = mindfulness; OI = over-identification
(reduced); Note that negative SCS items are reverse-coded; λ =
standardized factor loadings; Target factor loadings are in bold. Non-
significant parameters (p ≥ .05) are italicized.
8
Table 4 Standardized Parameter Estimates for the Model 4: Bifactor
ESEM solution of the SCS-26-CZ (N = 5368)
SC (λ) SK (λ) SJ (λ) CH (λ) IS (λ) MI (λ) OI (λ)
Self-kindness
sk5
.62
.50
-.02
.12
-.05
-.02
-.02
sk12
.64
.50
-.04
.06
-.02
.02
-.04
sk19
.70
.65
.02
.06
-.04
.02
-.04
sk23
.74
-.01
.26
.01
-.21
-.02
-.11
sk26
.76
.09
.01
.03
-.25
.02
-.07
Self-judgment
sj1
.49
-.00
.56
-.06
.03
-.09
-.04
sj8
.30
.11
.29
-.09
-.11
-.30
.02
sj11
.64
-.11
.21
-.09
-.07
-.15
.07
sj16
.69
-.11
.14
-.12
.15
-.08
.04
sj21
.44
.28
-.06
-.02
-.02
-.39
.00
Common humanity
ch3
.40
-.00
-.06
.27
.10
.20
-.06
ch7
.24
.07
-.05
.76
-.02
-.01
-.00
ch10
.27
.08
-.05
.76
-.06
-.00
.01
ch15
.72
.05
-.01
.26
-.06
.20
-.13
Isolation
is4
.60
-.04
.08
.02
.36
-.06
.06
is13
.62
-.05
-.09
-.07
.41
.04
.09
is18
.64
-.10
-.02
-.14
.36
.02
.01
is25
.60
-.02
.02
.07
.35
-.06
.14
Mindfulness
mi9
.27
.01
-.10
.05
-.06
.48
.38
mi14
.54
.03
-.16
.08
.00
.43
.11
mi17
.63
-.02
-.12
.11
.04
.36
-.03
mi22
.64
.21
-.26
.06
-.12
.00
-.10
Over-identification
oi2
.63
.01
.15
.01
.34
.15
.13
oi6
.67
-.06
.22
-.05
.24
-.02
.02
oi20
.38
-.06
-.05
-.05
-.01
.21
.66
oi24
.43
-.10
.04
-.03
.24
.22
.27
mean .55 .35 .25 .51 .37 .32 .27
Note. ESEM = exploratory structural equation modeling; SC = global self-compassion
factor; SK = self-kindness; SJ = self-judgment (reduced); CH = common humanity;
IS = isolation (reduced); MI = mindfulness; OI = over-identification (reduced); Note
that negative SCS items are reverse-coded; λ = standardized factor loadings; Target
factor loadings are in bold. Non-significant parameters (p ≥ .05) are italicized.
9
Table 5 Standardized Parameter Estimates for the Model 5: Two-bifactor ESEM
solution of the SCS-26-CZ (N = 5368)
CS (λ) RUS (λ) SK (λ) SJ (λ) CH (λ) IS (λ) MI (λ) OI (λ)
Self-kindness
sk5
-.20
.73
.04
.20
.11
.11
.12
sk12
-.23
.73
.04
.16
.18
.15
.08
sk19
-.35
.84
.07
.17
.14
.15
.11
sk23
.12
.56
.55
.12
.19
.11
.01
sk26
.12
.66
.31
.14
.18
.21
-.10
Self-judgment
sj1
.17
.30
.60
.02
.08
-.08
.32
sj8
.20
.35
.32
-.06
-.16
-.18
.11
sj11
.25
.39
.50
.03
.18
.12
-.09
sj16
.31
.36
.41
.02
.40
.15
-.05
sj21
.32
.61
-.02
.01
-.06
-.19
-.03
Common humanity
ch3
.13
.24
.02
.32
.25
.20
.13
ch7
.04
.17
-.04
.77
-.01
.03
-.01
ch10
.05
.21
-.02
.80
-.03
.07
-.03
ch15
.25
.57
.17
.34
.25
.23
.15
Isolation
is4
.40
.31
.20
.13
.40
.10
.15
is13
.40
.31
.07
.05
.50
.22
.13
is18
.35
.30
.18
-.01
.54
.18
.07
is25
.45
.33
.12
.17
.34
.15
.16
Mindfulness
mi9
.01
.09
.00
.08
.02
.67
.07
mi14
.21
.36
-.02
.13
.22
.52
.19
mi17
.21
.41
.07
.19
.35
.41
.13
mi22
.12
.67
-.03
.12
.21
.15
.06
Over-identification
oi2
.33
.32
.22
.12
.37
.28
.32
oi6
.31
.35
.38
.07
.39
.13
.16
oi20
.39
.14
.10
.00
-.08
.65
.02
oi24
.29
.11
.15
.05
.25
.41
.17
mean .16 .32 .70 .37 .56 .45 .44 .17
Note. ESEM = exploratory structural equation modeling; CS = Compassionate Self-responding
factor; RUS = Reduced Uncompassionate Self-responding factor; SK = self-kindness; SJ = self-
judgment (reduced); CH = common humanity; IS = isolation (reduced); MI = mindfulness; OI =
over-identification (reduced); Note that negative SCS items are reverse-coded; λ = standardized
factor loadings; Target factor loadings are in bold. Non-significant parameters (p .05) are
italicized.
10
Table 6 Standardized Parameter Estimates for the Model 6: Full two-tier ESEM
solution of the SCS-26-CZ (N = 5368)
CS (λ) RUS (λ) SK (λ) SJ (λ) CH (λ) IS (λ) MI (λ) OI (λ)
Self-kindness
sk5
.62
.44
.15
.07
.08
-.03
.01
sk12
.63
.44
.08
.01
.06
-.03
-.00
sk19
.69
.61
.11
-.00
-.00
-.03
-.01
sk23
.58
-.04
.28
-.02
-.20
-.05
-.08
sk26
.71
.01
.15
-.05
-.09
-.08
.03
Self-judgment
sj1
.52
.06
.45
.01
-.19
.08
-.18
sj8
.20
.10
.54
-.05
-.02
-.11
-.00
sj11
.54
-.05
.23
-.05
-.13
-.14
.07
sj16
.69
.02
.01
-.06
-.06
-.15
.01
sj21
.17
.24
.36
-.02
.27
-.30
.08
Common humanity
ch3
.38
-.03
-.07
.23
.12
.16
-.05
ch7
.36
.03
-.03
.71
.01
-.03
.01
ch10
.41
.03
-.03
.71
-.02
-.03
.03
ch15
.70
-.04
.10
.18
.09
.15
-.08
Isolation
is4
.63
.09
.02
.10
.19
-.00
-.02
is13
.62
.06
-.09
-.01
.32
.06
.04
is18
.66
.03
-.09
-.08
.21
-.00
-.03
is25
.59
.09
.05
.14
.27
.03
.07
Mindfulness
mi9
.29
.00
-.23
.01
-.10
.39
.39
mi14
.54
-.05
-.10
.00
.14
.38
.15
mi17
.58
-.06
-.12
.04
.11
.26
.01
mi22
.68
.11
.04
-.04
.19
-.09
.03
Over-identification
oi2
.64
.11
.05
.07
.16
.24
.03
oi6
.67
.05
.12
.01
.04
.03
-.06
oi20
.36
.01
-.03
-.01
-.00
.25
.62
oi24
.48
-.02
-.07
.02
.10
.26
.20
mean .55 .52 .31 .32 .46 .25 .28 .23
Note. ESEM = exploratory structural equation modeling; CS = Compassionate Self-responding
factor; RUS = Reduced Uncompassionate Self-responding factor; SK = self-kindness; SJ = self-
judgment (reduced); CH = common humanity; IS = isolation (reduced); MI = mindfulness; OI =
over-identification (reduced); Note that negative SCS items are reverse-coded; λ = standardized
factor loadings; Target factor loadings are in bold. Non-significant parameters (p .05) are
italicized.
11
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