Confirmatory factor analysis of the Korean version of the short-form McGill pain questionnaire with chronic pain patients: a comparison of alternative models
Sun Ah Choi
Department of Psychology, Chungnam National University
99 Daehak-ro, Yuseong-gu, Daejeon 305-764
Department of Psychology, Chonbuk National University
Deokjin-dong 1ga, Deokjin-gu, Jeonju-si, Jeollabuk-do 561-756
Department of Psychology, Chung-Ang University
84 Heukseok-ro, Dongjak-gu, Seoul 156-756
Background: The Short Form of the McGill Pain Questionnaire (SF-MPQ) is the most widely used assessment of the quality and intensity of pain. In previous validation studies, the factor structure of the SF-MPQ varied widely from various two-factor structures to a five-factor structure, although research on the SF-MPQ quite consistently supports its two-factor structure (i.e., sensory and affective) across different countries and languages. In Korea, the results of exploratory factor analysis of a Korea version of SF-MPQ (KSF-MPQ) showed 2-factor structure consisting of 'sensory' and 'affective' excluding two items such as splitting and heavy. As an attempt to further validate the KSF-MPQ, the purpose of this study was to confirm whether the KSF-MPQ model is an appropriate model for chronic pain patients in Korea by comparing several alternative models of the SF-MPQ. Findings: A total of 150 chronic pain patients seeking treatment in Seoul, Korea, participated and completed the KSF-MPQ. Confirmatory factor analysis was conducted to evaluate the adequacy of the KSF-MPQ model and several alternative models. The results indicated that the adjusted KSF-MPQ model showed the best fit to the data among the models in chronic pain patients in Korea. Conclusions: The results showed the KSF-MPQ is cross-culturally equivalent to the original questionnaire. Thus, the KSF-MPQ is valid measurement for assessing the quality and intensity of pain to chronic pain patients and may be helpful in clinical and research settings in Korea.
Chronic pain is defined as pain that persists for
3 months [1,2] and usually does not respond to
conventional treatment or surgery . As a result of this
long-lasting pain, many chronic pain patients (CPPs)
face restrictions in their daily activities . For
example, the fatigue and mobility limitations
accompanying chronic pain can lead to a deterioration of physical
function, possibly resulting in disability [5,6]. Additionally,
CPPs are likely to have psychological problems (e.g.,
anxiety, depression, sleep disorders), which often lead
to substance abuse and even suicide [7,8]. In such
situations, the proper measurement of the quality and
intensity of painful experiences would be useful for
formulating a plan of treatment and predicting its
The Short Form of the McGill Pain Questionnaire
(SF-MPQ) is the most widely used assessment of the
quality and intensity of pain . The SF-MPQ is an
abbreviated form of the McGill Pain Questionnaire
 and is used in medical settings in place of the
long-form questionnaire for pragmatic reasons. The
SF-MPQ purports to measure sensory and affective
pain (referred herein as the Melzack model) and has
been widely validated in many languages and countries.
The sensory category (e.g., shooting, sharp) focuses on
the nociceptive pain experience, and the affective
category (e.g., tiring-exhausting, fearful) focuses on the
emotional component of nociceptive pain . In
previous validation studies, the factor structure of the
SF-MPQ varied widely from various two-factor
structures to a five-factor structure, although research on
the SF-MPQ quite consistently supports its two-factor
structure (i.e., sensory, affective) across different
countries and languages .
For example, the exploratory factor analysis (EFA) of a
Korean version of the SF-MPQ (KSF-MPQ) has been
performed in CPPs . The results yielded a two-factor
structure consisting of sensory and affective factors,
excluding the two items referring to heavy and
splitting (referred herein as the KSF-MPQ model) .
Wright et al.  performed confirmatory factor
analysis (CFA) for patients with chronic back pain. To
meet the criteria of the model fit indices, they set item
6 (gnawing) as an affective instead of sensory category
and correlated four sets of error terms. They then
obtained a two-factor structure consisting of sensory
and affective factors (referred herein as the Wright
model). Shin et al.  performed EFA for
AsianAmerican cancer patients and obtained a two-factor
structure that differs from the Melzack model (referred
herein as the Shin model). Burckhardt and Bjelle 
performed EFA on a Swedish version of the SF-MPQ
for female patients with either fibromyalgia or
rheumatoid arthritis. The EFA produced three factors: the
sensory category was divided into acute-sensory and
chronic-sensory, and the affective category was retained
(referred herein as the Burckhardt model). Cassisi
et al.  performed EFA for African-Americans and
European-Americans with chronic pain, obtaining a
five-factor solution for African-American patients
(referred herein as the Cassisi A model) and a
fourfactor solution for European-American patients
(referred herein as the Cassisi B model).
To examine the possibility of utilizing the KSF-MPQ
in medical and research settings, further validation of
the KSF-MPQ is necessary. As previous studies have
shown different factor structures of the SF-MPQ across
countries or cultures , it is especially important to
examine its appropriateness for Korea. Thus, this study
aimed to confirm whether the KSF-MPQ model is an
appropriate model for CPPs in Korea by comparing
several alternative models of the SF-MPQ using CFA.
A total of 157 CPPs visiting a pain center in Seoul,
Korea, participated in this study. The inclusion criterion
for the study was pain duration of at least 3 months.
The patients (n = 7) who had experienced pain for <
3 months were excluded, leaving 150 eligible patients.
Table 1 presents the demographic characteristics of the
participants. All data were collected and analyzed after
obtaining approval by the Institutional Review Board
(Seoul St. Marys Hospital) and informed consent from
Quality and intensity of pain were measured by the
KSFMPQ. The KSF-MPQ consists of 17 items, 15 of which
are adjectives from the 11 sensory and 4 affective
categories that are rated on a 4-point intensity scale from 0
(not at all) to 3 (all the time). The other two items assess
overall pain intensity: the Present Pain Intensity (PPI),
which is rated on an intensity scale from 0 (no pain) to
5 (excruciating), and a Verbal Analogue Scale (VAS),
which consists of a 10-cm line on which pain is rated
between 0 (no pain) and 10 (worst possible pain). The
PPI and VAS were excluded in the present analysis.
Data for the statistical analyses were examined using
SPSS 17.0 and Amos 20.0 for Windows. CFA was
Table 1 Demographic characteristics of the sample
Sample (N = 150)
Marital status (%)
Educational status (%)
Pain duration (months)
Taking pain-related medication (%)
Pain category (%)
conducted to evaluate the adequacy of the models.
Because a factor consisting of a single item cannot be
analyzed in CFA, two factors of the Cassisi A model
were excluded. Thus, three out of five factors were
analyzed in CFA. The indices used to evaluate model
fit in CFA include the root-mean square error of
approximation (RMSEA), comparative fit index (CFI),
normed fit index (NFI), Tucker-Lewis Index (TLI),
Akaike information criterion (AIC), and Bayesian
information criterion (BIC). RMSEA values of < .05
indicate a good fit to the data, values between .05 and
.08 an acceptable fit, values between .08 and .10 a
marginal fit, and values > .10 a poor fit . For the
CFI, NFI, and TLI, values > .90 indicate a good fit to
the data . For the AIC and BIC, smaller values
indicate a better fitting model.
To obtain an adequate model for CPPs in Korea, CFA
with maximum-likelihood estimation was conducted.
All models, except the Wright model, were adjusted
based on a combination of logical and empirical
indicators (i.e., modification indices) guiding path additions.
Tables 2 and 3 presents summary of the models and the
model fit indices for the models of the SF-MPQ,
respectively. The adjusted KSF-MPQ model showed a
good model fit for the CFI, NFI, TLI, and RMSEA, and
had the lowest values for the AIC and BIC among the
models. A single-factor model produced the worst fit
to the data. The Wright, adjusted Burckhardt, and
adjusted Melzack models displayed a marginal model fit
for the RMSEA and a good model fit for the CFI but an
inadequate model fit for the NFI. Also, the adjusted
Burckhardt and adjusted Melzack models showed a
good model fit for the TLI but the Wright model did
not. The adjusted Cassisi B model displayed a good
model fit for the CFI and TLI, a marginal model fit for
the RMSEA, and a poor model fit for the NFI. The
adjusted Cassisi A and adjusted Shin models displayed
a poor model fit for the CFI, NFI, TLI, and RMSEA.
Thus, among the models studied, the adjusted
KSFMPQ provided the best model fit to the data for CPPs
in Korea. The internal consistency for the total, sensory,
and affective scale scores of the KSF-MPQ were Cronbachs
= .93, .90, .91, respectively.
Findings indicated that the (adjusted) KSF-MPQ model
provides the best fit for CPPs in Korea, which is
consistent with the EFA result of the KSF-MPQ in Korea .
Although the KSF-MPQ does not contain two items
(i.e., heavy, splitting), it was fundamentally consistent
with the original Melzack model in terms of its
components (i.e., sensory, affective pain). These two items
were excluded due to low factor loadings in the prior
study . One possible explanation is that they are
likely to best suit patients suffering from pain in a
specific site. For example, splitting tends to be used by
Table 2 Summary of each models description
12. Tiring- exhausting
Number of item
Table 3 Model fit indices for SF-MPQ
Adjusted Melzack2 Wright3
Adjusted Cassisi A5
Adjusted Cassisi B2
patients with severe headaches, and heavy tends to be
used by patients with lower back pain. Moreover, given
that these words are not frequently used in Korea, the
factor structure of the SF-MPQ may be different in
Korea. Future studies should replicate that those two
items should be dropped for a Korean sample.
This study compared several models for CPPs in Korea
to identify the most adequate model and suggests that
the KSF-MPQ is suitable for assessing the quality and
intensity of pain. These results showed that the
KSFMPQ is cross-culturally equivalent to the original
questionnaire. Based on the results of the present study, the
KSF-MPQ may be a useful clinical tool for assessing
patients current state and treatment planning. Using the
KSF-MPQ, both patients and health professionals can
monitor the patients condition more closely and take
appropriate action .
Nevertheless, this study has an important limitation.
The patients who participated in this study were CPPs
who reported pain in different areas and may not be
generalizable to patients with specific pain site(s).
Further study needs to be done with large numbers of
patients with specific pain site(s).
The KSF-MPQ is a valid questionnaire for assessing the
quality and intensity of pain experienced by CPPs in
Korea. Thus, the KSF-MPQ may be a useful tool for
evaluating the pain experience of CPPs and may be
helpful in clinical and research settings in Korea.
CPP: Chronic Pain Patient; SF-MPQ: Short-Form McGill Pain Questionnaire;
KSF-MPQ: Korean version of Short-Form McGill Pain Questionnaire;
EFA: Exploratory Factor Analysis; CFA: Confirmatory Factor Analysis;
RMSEA: Root-Mean Square Error of Approximation; CFI: Comparative fit index;
NFI: Normed fit index; TLI: Tucker-Lewis Index; AIC: Akaike information
criterion; BIC: Bayesian information criterion.
The authors declare that they have no competing interests.
SCN and CS designed the study, CSA collected the entire data and CSA and
CS performed and interpreted the statistical analysis. CSA drafted the manuscript
and revised based on the provided comments by CS and LJH. All authors read
and approved the final manuscript.
This research was supported by the Basic Science Research Program through
the National Research Foundation of Korea (NRF) funded by the Ministry of
Education, Science, and Technology (2012R1A1A2008624).