Karon F. Cook, Winnie Dunn, James W. Griffith, et al.
Pain assessment using the NIH Toolbox
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located on the World Wide Web at:
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Neurology. All rights reserved. Print ISSN: 0028-3878. Online ISSN: 1526-632X.
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® is the official journal of the American Academy of Neurology. Published continuously
Karon F. Cook, PhD
Winnie Dunn, PhD,
James W. Griffith, PhD
M. Tracy Morrison, OTD
Dory Sabata, OTD,
David Victorson, PhD
Leeanne M. Carey, PhD
Joy C. MacDermid,
BScPT, MSc, PhD
Brian J. Dudgeon, PhD,
Richard C. Gershon, PhD
Pain assessment using the NIH Toolbox
Objective: Pain is an important component of health and function, and chronic pain can be a prob-
lem in its own right. The purpose of this report is to review the considerations surrounding pain
measurement in the NIH Toolbox, as well as to describe the measurement tools that were adopted
for inclusion in the NIH Toolbox assessment battery.
Methods: Instruments to measure pain in the NIH Toolbox were selected on the basis of scholarly
input from a diverse group of experts, as well as review of existing instruments, which include
verbal rating scales, numerical rating scales, and graphical scales.
Results: Brief self-report measures of pain intensity and pain interference were selected for inclusion
in the core NIH Toolbox for use with adults. A 0 to 10 numerical rating scale was recommended for
measuring pain intensity, and a 6-item Patient Reported Outcome Measurement Information System
measure was recommended as a supplemental measure. No specific measure was recommended for
measuring pain intensity in children.
Conclusions: Core and supplemental measures were recommended for the NIH Toolbox.
Additional measures were reviewed for investigators who seek tools for measuring pain intensity
in pediatric samples. Neurology?2013;80 (Suppl 3):S49–S53
DIF 5 differential item function; IRT 5 item response theory; NRS 5 numerical rating scale; PROMIS 5 Patient Reported
Outcome Measurement Information System; VAS 5 visual analog scale; VRS 5 verbal rating scale; WBFPRS 5 Wong-Baker
Faces Pain Rating Scale.
took responsibility for considering the best methods for evaluating pain in the general population.
In the International Classification of Functioning, Disability and Health, sensory functions and
pain are grouped together as body functions; however, sensationof pain is distinguished from sen-
sory functions such as proprioception or touch, as well as functions related to temperature and
other stimuli.1The definition of somatosensory function includes the “detection, discrimination,
and recognition” of pain (Dunn et al., this issue). However, pain is more than a biological process
and can be integral to function, role participation, and overall quality of life. As such, its assess-
ment often becomes a primary end point in clinical trials and treatment effectiveness studies. This
led the Toolbox team to consider pain and its assessment in parallel with somatosensory function
and to dedicate separate manuscripts to discussions of pain and somatosensation.
The science of pain measurement has benefited from recent advances in measurement
approaches and applications.2–4The field of outcomes research has well-developed, self-reported
pain measures that havebeen validated in a range of acute and chronic medical conditions. Forthis
reason, the team chose not to develop new pain measures but to adopt existing instruments that
would add to the battery of tests included in the NIH Toolbox. In this article, we describe the
importance of pain to the assessment of health and discuss its multidimensional nature. We
From the Northwestern University (K.F.C., J.W.G., D.V., R.C.G.), Chicago, IL; University of Kansas Medical Center (W.D., M.T.M., J.T., D.S.),
Kansas City; National Stroke Research Institute (L.M.C.), Heidelberg; LaTrobe University (L.M.C., J.C.M.), Melbourne, Australia; and McMaster
University (B.J.D.), Hamilton, Canada.
Go to Neurology.org forfull disclosures. Funding informationand disclosuresdeemed relevant by the authors, if any, are provided atthe end ofthearticle.
© 2013 American Academy of NeurologyS49
identify pain subdomains of particular interest
to users of the NIH Toolbox and review cur-
rent strategies for measuring those subdomains
in adults and in children. This review is in-
tended to provide users with a context for
understanding the measurement of pain sub-
domains. Our recommendations for the
NIH Toolbox core and supplemental meas-
ures of pain are summarized.
PAIN AND HEALTH ASSESSMENT Pain has been
defined as an “unpleasant sensory and emotional expe-
or described in terms of such damage.”5,6The Interna-
tionalAssociationforthe StudyofPainhascalled unre-
lieved pain “a major global healthcare problem.”7
Experiences and assessments of pain are often char-
acterized as acute, chronic, or persistent.8Acute pain
comes on abruptly and lasts a relatively short time.
Such pain serves as a warning of an injury or sudden
illness and may be mild or severe.9Chronic pain
extends beyond the expected period of healing, often
designated as persisting 6 months or more. A national
survey estimated the point prevalence of chronic pain
at .30%, with half of these reporting daily pain and
32% reporting 3-month average pain $7 on a scale
of 0 to 10.10Not only is pain highly prevalent, its
impact on quality of life is far-reaching. Pain interferes
with sleep, makes activities of daily living more diffi-
cult, limits social engagement, and is financially bur-
densome to individuals and their families (see, for
example, references 11–15). Furthermore, pain causes
changes in neural function that outlast the precipitat-
ing disease or injury. Although typically triggered by
injury or disease, chronic pain “becomes independent;
it takes on a life of its own.”16Thus, pain has been
described as “a disease in its own right.”16The preva-
lence, impact, and psychological and physiologic con-
sequences of unrelieved chronic pain make it a critical
domain in the assessment of health.
Because pain has a variety of origins and expressions,
it is best described as multidimensional.17Subdomains
and localization, and interference with quality of life,
affect, and behavior. A full assessment of pain might
include measures of each of these subdomains. For the
purposes of the NIH Toolbox, investigators focused on
the 2 most frequently assessed subdomains: pain inten-
sity and pain interference.18Below we summarize com-
mon strategies for the measurement of pain intensity
and interference within adult and pediatric populations.
PAIN INTENSITY Measuring pain intensity of adults.
pain,”19is a narrow construct often measured using a
1-item scale. To measure pain intensity of adults, the
most common strategies are verbal rating scales (VRSs),
numerical rating scales (NRSs), visual analog scales
(VASs), and graphical scales. With VRSs, participants
select from among pain descriptors (e.g., mild, moder-
ate, severe). VASs present a line on which respondents
mark the point they believe most descriptive of their
pain. The line has verbal descriptors, “anchors,” at the
ends (e.g., “no pain” or “extreme pain”). Sometimes
descriptors between anchors are included. NRSs ask
respondents to pick a number that represents their pain
level (e.g., 0–10). Graphical scales represent graduated
levels of pain as drawings (e.g., faces) that express
increasing levels of distress. Participants select the
picture that best represents their level of pain. Graphical
scales have verbal or numerical descriptors as anchors
andmayhave oneormore descriptorsbetweenanchors.
An extensive review on behalf of the European Palli-
ative Care Research Collaborative examined 54 pub-
lished studies that compared at least 2 of 3 different
categories of scales (i.e., VRSs, VASs, NRSs) in acute
or chronic pain.20Across the 54 studies, 131 unique
measures were cataloged: 59 VASs, 39 VRSs, and 33
NRSs. Most of the reviewed studies recommended no
particular category of pain-intensity scaling. Of those
that did, 3 suggested a scale from a category other than
NRSs, VRSs, or VASs; 11 recommended using NRSs;
7, VRSs; and 4, VASs. Correlations are typically high
between scores from different kinds of pain-intensity
measures,20but substantial nonequivalence between
individual scores has been documented,21–24and this
nonequivalence in scores varied in direction.22,23
Measuring pain intensity of children. Even more chal-
lenging than measuring the pain of adults is measuring
pain intensity experienced and reported by children.
Strategies include self-report, physiologic indicators,
and behavioral measures (including proxy report).25–27
These different approaches produce nonequivalent
results that only weakly correlate with each other.26
The weak associations suggestthat they may be assess-
ing distinct constructs.26
As with adults, self-report is accepted as the “gold
standard” for measuring the pain intensity of chil-
dren.25,28Graphical scales are arguably less abstract
than NRS and VAS measures and often are used for
measuring children’s pain intensity. There are a num-
ber of “faces pain scales” that include drawings of
faces to suggest graduated levels of distress (e.g., smil-
ing face at one end; face with tears at the other).
Tomlinson et al.28conducted a review of self-reported
pain-intensity measures for children and found that
children prefer faces scales to other single-item meas-
ures. In their review, the Wong-Baker Faces Pain
Rating Scale (WBFPRS)29was preferred by children
in studies that compared more than one faces scale.
S50Neurology 80 (Suppl 3)March 12, 2013
NIH Toolbox pain-intensity measures. For measuring
the pain intensity of adults, the NIH Toolbox adopted
a single-item measure for inclusion within its core bat-
tery of assessments. The item, “In the past 7 days, how
would you rate your pain on average?” is scored on a 0
to 10 NRS in which 0 5 no pain and 10 5 worst
imaginable pain. The 0 to 10 NRS is frequently used
in clinical studies, and its validity has been demon-
strated empirically.19Adding to its usefulness are esti-
mations made within different clinical populations,
based on the 0 to 10 scale, of cut-scores for different
levels of pain (e.g., mild, moderate, severe).30–32How-
ever, thisrecommendationisqualified bythe empirical
scores.21–24No measure of pain intensity can fully cap-
ture individuals’ experiences of pain.
Although the NIH Toolbox only addressed assess-
ment of average pain intensity, it is important to note
that “worst pain” also has been suggested as a clinical
trial end point.33,34Worst pain may be measured by
substituting the phrase “on average” with a phrase such
as “at its worst.”
For the measurement of children’s pain intensity,
no specific supplemental measure was identified for
the NIH Toolbox. Although research indicates that
children prefer a faces scale,28the WBFPRS has weak-
nesses. The anchor faces of the WBFPRS (a smiley
face and a face with tears) may confound affect with
pain intensity, especially in younger children.28
PAIN INTERFERENCE MEASUREMENT Pain inter-
ference may be thought of as a functional consequence
of pain intensity. There is substantial empirical and
clinical evidence that the 2 are distinct constructs
and that each provides valuable information.18Pain
intensity is a relatively narrow domain, but pain inter-
ference is broader, multifaceted, and associated with
pain disability. The subdomains typically tracked by
on physical function, work, recreation, social activities,
family roles, activities of daily living, and sleep.
Measuring pain interference in adults. There are many
published measures of pain interference for use in adult
ever, with few exceptions,3,35,39pain interference meas-
ures have been developed using classic test theory
approaches. Compared with classic psychometric
approaches, newer strategies such as item response the-
ory (IRT) allow for finer-grade evaluations of measures.
Psychometric assessments are made at the individual
item level, not at the scale level as with classic test the-
ory. Furthermore, the precision of scores at different
levels of pain interference can be assessed with IRT
methods by calculating scale information.40The
Patient Reported Outcome Measurement Information
System (PROMIS) initiative applied IRT methods in
developing the PROMIS Pain Interference item bank.3
As described on the PROMIS Web site (http://www.
nihpromis.org), “The pain interference item bank meas-
ures the self-reported consequences of pain on relevant
aspects of one’s life. This includes the extent to which
pain hinders engagement with social, cognitive, emo-
tional, physical, and recreational activities ...”
Measuring pain interference in children. Although sub-
stantial psychometric attention has been given to the
measurement of children’s pain intensity, the same is
not true of the measurement of children’s pain interfer-
Interview41and the PROMIS Pediatric Pain Interfer-
ence Scale.42An advantage of the PROMIS scale over
the Child Activity Limitations Interview is the fact that
it was developed using modern psychometric methods
(IRT), and the items of the bank were tested for differ-
ential item function (DIF) between boys and girls of
interference constant, the probabilities of different
responses to an item vary by subgroup. DIF is a threat
to measurement validity because the trait being mea-
sured should drive how respondents answer a question,
not their membership in a particular demographic
or clinical subgroup. An 8-item subscale assesses pain
impact on children’s sleep, attention, mobility (e.g.,
walking,running, standing), ability to have fun, school-
work, and affect (e.g., anger when in pain). A recently
published study with 8- to 17-year-old children with
cancer found evidence for the feasibility and validity of
the PROMIS pediatric measures, including the
PROMIS Pain Interference measure.
NIH Toolbox pain interference measures. For the mea-
surement of pain interference in adults, the NIH Tool-
box adapted the PROMIS Pain Interference v1.0–Pain
Interference 6a (https://www.assessmentcenter.net).
The 6 items of this short form ask, “How much did
around the home, c) your ability to participate in social
activities, d) your household chores, e) the things you
usually do for fun, and f) your enjoyment of social
activities?” Each item is scored from 1 to 5, where
1 5 not at all, 2 5 a little bit, 3 5 somewhat, 4 5
quite a bit, and 5 5 very much. The item set in short
form 6a includes 6 of the 10 most “discriminating”
items in the item bank; that is, the items that
best distinguish among different levels of pain inter-
ference. Items with greater discrimination yield more
precision in estimating individuals’ pain interfer-
The NIH Toolbox adopted the PROMIS Pediatric
Pain Interference measure for use in measuring self-
reported pain interference in children. To date, clinical
validity of this measure has been evidenced in children
Neurology 80 (Suppl 3) March 12, 2013 S51
aged 8 to 17 years. Future studies need to evaluate
whether the measure retains its validity and feasibility
in younger clinical populations.
CONCLUSION Inthisarticle,wepresenta contextfor
understanding the importance of pain and review
strategies for its measurement. Two measures were
adopted intotheNIHToolbox core batteryforadults:
a 0 to 10 NRS for measuring pain intensity and a 6-
item PROMIS Pain Interference short form. The
PROMIS Pediatric Pain Interference is included as a
supplemental measure for measuring children’s pain
interference. No particular scale for measuring pain
intensity in pediatric populations was recommended.
Dr. Cook: manuscript concept and design. Dr. Dunn, Dr. Griffith, Dr.
Morrison, Dr. Tanquary, Dr. Sabata, Dr. Victorson: domain conceptualiza-
tion and critical review of the manuscript for important intellectual content.
Dr. Carey: study supervision, domain conceptualization and critical review
of the manuscript for important intellectual content, domain conceptualiza-
tion, and critical review of the manuscript for important intellectual content.
Dr. MacDermid, Dr. Dudgeon, Dr. Gershon: study supervision, domain
conceptualization and critical review of the manuscript for important intel-
This study is funded in whole or in part with Federal funds from the
Blueprint for Neuroscience Research, NIH, under contract no.
K. Cook has received financial support from Center for Psychiatric Reha-
bilitation Boston University, InvivoData, Xenoport, BrightOucome, the
NIH, Veteran’s Affairs Research and Development, National Institute
on Disability and Rehabilitation Research (NIDDR), and Agency for
Healthcare Research and Quality (AHRQ). In addition to Toolbox, Dr.
Cook receives other funding from NIH (5RC1NR011804-02 and
1U5AR057943-01). She also is currently supported by grants from
NIDDR (H133B090024) and AHRQ (1R03HS020700-01). W. Dunn
is the author of the Sensory Profile measures, which are published by
Pearson Inc. Pearson Inc. owns the copyright on these tests, and Dr.
Dunn receives a royalty when they are sold. J. Griffith has received finan-
cial support from NorthShore University HealthSystem, the Cleveland
Clinic Foundation/Teva Neurosciences, Inc., Ironwood Pharmaceuticals,
Inc. and Forest Laboratories, Inc., the NIH, the Department of Defense
(DOD)–United States Army, and the FWO, Belgium. In addition to
NIH Toolbox funding, he receives funding from the NIH for other
research (grant U01 DK082342). He has also been a paid consultant to
Dr. Kathryn Grant of DePaul University, and maintains a clinical
psychology practice for which he bills for his services. T. Morrison, J.
Tanquary, and D. Sabata report no disclosures. D. Victorson holds stock
options in Eli Lilly and Company, received an honoraria for serving on the
Steering Committee of the Reeve Neuro-Recovery Network, was funded
by NIH contracts HHSN265200423601C and HHS-N-260-2006-
00007-C and grants R01HD054569-02NIDRR, 1U01NS056975-01,
R01 CA104883, received support from the American Cancer Society
(national and Illinois Division) for research in prostate cancer, received
institutional support from NorthShore University HealthCare System for
research in prostate cancer, received institutional support from the Medical
University of South Carolina for sarcoidosis research, and received insti-
tutional support from the Northwestern Medical Faculty Foundation for
urology research. L. Carey is supported by an Australian Research Council
Future Fellowship (FT0992299) and was previously supported by
a National Health and Medical Research Council of Australia Career
Development Award (307905). Dr. Carey is an expert consultant for
the NIH Toolbox Project. J. MacDermid and B. Dudgeon report no
disclosures. R. Gershon has received personal compensation for activities
as a speaker and consultant with Sylvan Learning, Rockman, and the
American Board of Podiatric Surgery. He has several grants awarded by
NIH: N01-AG-6-0007, 1U5AR057943-01,
1U01DK082342-01, AG-260-06-01, HD05469; NINDS: U01 NS 056
975 02; NHLBI K23: K23HL085766; NIA: 1RC2AG036498-01;
NIDRR: H133B090024; OppNet: N01-AG-6-0007.
Received June 6, 2012. Accepted in final form September 27, 2012.
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Neurology 80 (Suppl 3)March 12, 2013S53
DOI 10.1212/WNL.0b013e3182872e80 Download full-text
Karon F. Cook, Winnie Dunn, James W. Griffith, et al.
Pain assessment using the NIH Toolbox
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