Fatigue in Child Chronic Health
Conditions: A Systematic Review of
Assessment Instruments
Alison Crichton, DPsycha,b,c, Sarah Knight, PhDa,b,d, Ed Oakley, PhDb,d,e, Franz E. Babl, MDb,d,e, Vicki Anderson, PhDb,c,e
BACKGROUND AND OBJECTIVE: Fatigue
is common in chronic health conditions in childhood, associated
with decreased quality of life and functioning, yet there are limited data to compare
assessment instruments across conditions and childhood development. Our objective was to
describe fatigue assessment instruments used in children with chronic health conditions and
critically appraise the evidence for the measurement properties of identified instruments.
abstract
Data sources included Medline, Cumulative Index to Nursing and Allied Health
Literature, and PsycINFO (using the EBSCOhost platform). Study selection included
quantitative assessment of fatigue in children with health conditions. Data extraction was as
follows: (1) study design, participant and fatigue instruments, (2) measurement properties of
fatigue instruments, (3) methodological quality of included studies, and (4) synthesis of the
quality of evidence across studies for the measurement properties of fatigue instruments.
METHODS:
Twenty fatigue assessment instruments were identified (12 child reports, 7 parent
reports, 1 staff report), used in 89 studies. Fatigue was assessed in over 14 health conditions,
most commonly in children with cancer and chronic fatigue syndrome. Evidence for the
measurement properties of instruments varied, and overall quality was low. Two fatigue
instruments demonstrated strong measurement properties for use in children with diverse
health conditions and children with cancer.
RESULTS:
CONCLUSIONS: The
review is limited to children younger than 18 years and results are specific to
health conditions described, limiting generalizability of findings to other populations. Evidence
for the measurement properties of fatigue instruments varied according to the population in
which instruments were used and informant. Further evidence is required for assessment of
fatigue in younger children, and children with particular health conditions.
a
Victorian Pediatric Rehabilitation Service, Monash Children’s, Melbourne, Australia; bMurdoch Childrens Research Institute, Melbourne, Australia; cSchool of Psychological Sciences and
Department of Pediatrics, University of Melbourne, Melbourne, Australia; and eRoyal Children’s Hospital, Melbourne, Australia
d
Dr Crichton conceptualized and designed the study, carried out the literature searches, completed the initial analysis, drafted the initial manuscript, and revised the
manuscript; Dr Knight assisted with the data collection instrument, screened articles for inclusion, reviewed analysis, and reviewed the manuscript; Dr Anderson
supervised data collection and critically reviewed the manuscript; Drs Oakley and Babl cosupervised data collection and reviewed the manuscript; and all authors
approved the final manuscript as submitted.
www.pediatrics.org/cgi/doi/10.1542/peds.2014-2440
DOI: 10.1542/peds.2014-2440
Accepted for publication Dec 30, 2014
Address correspondence to Alison Crichton, DPsych, Senior Clinical Neuropsychologist, Critical Care and Neurosciences Theme, Murdoch Childrens Research Institute,
Royal Children’s Hospital, Flemington Rd, Parkville, 3052, Australia. E-mail: [email protected]
PEDIATRICS (ISSN Numbers: Print, 0031-4005; Online, 1098-4275).
Copyright © 2015 by the American Academy of Pediatrics
PEDIATRICS Volume 135, number 4, April 2015
REVIEW ARTICLE
Fatigue refers to a subjectively
overwhelming sense of tiredness, lack
of energy, and feeling of exhaustion.1
It is a common, independent, and
nonspecific symptom identified in
numerous chronic health conditions
in childhood. Consequently, it has
been described as 1 of the most
universal experiences for children
with chronic health conditions,2
although reported rates of fatigue vary
within and between conditions.3–7
Excessive fatigue leads to reduced
quality of life,8 depression,9 and
reduced school participation.10–13
Fatigue is also identified in healthy
children with normal daily functioning.
Given these characteristics, it is
important to identify accurate and
reliable child-friendly measures to
detect excessive fatigue.
EPIDEMIOLOGY
Excess fatigue is a common presenting
problem in clinical practice, occurring
in children with cancer,14,15
neurologic conditions,16 chronic
fatigue syndrome,17 postural
tachycardia syndrome,18 multiple
sclerosis,6 epilepsy,19 traumatic brain
injury,20 juvenile idiopathic arthritis,21
diabetes,22,23 inflammatory bowel
disease,24 fibromyalgia,25,26 and
obesity.27 Importantly, fatigue in these
conditions is distinguishable from
other related symptoms including
sleepiness, depression, and apathy,28
and is not ameliorated by sleep.1
Precise prevalence estimates are
constrained by issues related to
assessment, terminology, and
measurement, which are heightened
in childhood.
symptoms. Three alternative
frameworks for describing subjective
fatigue are as follows: “central
fatigue” (resulting from central as
opposed to peripheral nervous
system damage and incorporating
mental and physical symptoms)30; as
a “feeling state”;28 and as
a combination of primary (disease
specific) and secondary factors (such
as pain, sleep disturbance, or mood
changes).31 The subjectivity and
breadth of symptoms make
quantification challenging, and
resultantly assessment instruments
focus on the duration or severity of
symptoms (physical, mental,
affective) and other dimensions of the
fatigue experience, including impact
on daily functioning and exacerbating
factors (eg, sleep habits).31–36 In this
review, based on earlier work,37 the
theoretical construct of fatigue will be
categorized as “impact of fatigue on
daily life,” “fatigue severity,” or
“factors influencing fatigue.”
e1016
Although fatigue is a common
symptom in a range of chronic health
conditions, and notable challenges
with its measurement exist, there has
been limited evaluation of assessment
instruments in use with children.
TABLE 1 Data Extraction Items
Data Category
1
2
3
4
MEASUREMENT
Fatigue has been defined as an
overwhelming and sustained sense of
exhaustion that decreases one’s
capacity for physical and mental
work.29 Quantification of fatigue
remains impeded by lack of
consensus framework, terminology,
and the subjective and
multidimensional nature of
It is important for instruments that
assess children’s fatigue to be child
specific. It is a unique experience with
its own symptomatology,
presentation, and natural
history.38–41 Fatigue is inherently
subjective,28 and its assessment in
childhood is challenging because the
accuracy and relevance of parentproxy reports is questionable.42
Further, fatigue in the general
childhood population varies through
development; it is greater in infancy,
early childhood, and late adolescence
than during midchildhood, and is
more common in girls.43–45 Accurate
assessment requires recognition of
the developmental stages and
reference to age and gender norms.
5
6
Description
Data Extracted
Study description
Study aims, design, study duration, and any bias. Participant
numbers, setting, diagnostic criteria, age, gender, country,
comorbidity, and diagnostic criteria used.
Instrument description For each study: name of instrument(s), language version,
theoretical constructs, number of items, description of
domains assessed, theoretical construct,a age, respondents,
response format, and extent of active patient involvement in
instrument development.b
Psychometric properties Criteria ratingc for instrument-level measurement properties
of fatigue measures
(as reported in study): (1) internal consistency, (2)
reliability, (3) measurement error, (4) content validity, (5)
construct validity, (6) structural validity, (7) hypothesis
testing, (8) cross-cultural validity, and (9) responsiveness.
Study quality
Ratingd of study methodological quality for each of the
following measurement properties reported: (1) internal
consistency, (2) reliability, (3) measurement error, (4)
content validity, (5) construct validity, (6) structural validity,
(7) hypothesis testing, (8) cross-cultural validity, (9)
responsiveness (add * if measurement properties were not
checked, and the authors cite published measurement
properties in another article).
Acceptability and
Acceptability (respondent burden, time for completion) and
feasibility
feasibility (time for scoring, ease of scoringe).
Risk of bias
Study and outcome level data: outcome data completeness,
drop-out rate description, any selective outcome reporting.
a
Theoretical construct of fatigue rated as impact of fatigue on daily life, fatigue severity, or factors influencing fatigue.37
INVOLVE definitions of extent of patient involvement in instrument development (“consultation,” “collaboration,” or “userled”).136
c Criteria for good measurement properties on the basis of criteria proposed by Terwee et al.55
d The quality of each included study was evaluated by using the COSMIN checklist54 and rating system.57
e Ease of scoring criteria were “easy,” “moderate,” or “difficult” according to Elbers et al.37
b
CRICHTON et al
TABLE 2 Levels of Evidence for Measurement Properties of Included Fatigue Instruments
Study Design
Level of Evidence
Interventional and observational
studies published in peer-reviewed
journals were eligible for inclusion.
Strong
Rating
Criteria
+++ or 2 2 2
Consistent findings in multiple studies of good methodological
quality or in 1 study of excellent methodological quality
Consistent findings in multiple studies of fair methodological
quality or in 1 study of good methodological quality
One study of fair methodological quality
Conflicting findings
Only studies of poor methodological quality
Moderate
++ or 2 2
Limited
Conflicting
Unknown
+ or 2
+/2
?
+, positive rating; ?, indeterminate rating; 2, negative rating.55
Exceptions are reviews of measures
in children with cancer46,47 and
chronic fatigue syndrome.48 It is
important to identify the instruments
available and to evaluate their
measurement properties. The
objectives of this review of fatigue in
children and adolescents with chronic
health conditions were to (1)
describe participant and study
characteristics of included studies,
(2) describe and systematically
review available instruments used to
assess fatigue, detailing those
available for child (self) and parent
(proxy) report, (3) interpret
instruments by using
a multidimensional framework of
fatigue, (4) review identified
instruments within a developmental
framework, and (5) summarize and
synthesize the psychometric
properties of the these instruments
and the quality of the evidence.
literature) and publications,50 and
secondary references were also
checked.
Search
The searches were limited to Englishlanguage publications. Subject
headings and key words used were
the following: (1) fatigue, weary,
weariness, exhaustion, exhausted,
lacklustre or astheni*, letharg*, tired;
or (2) (lack* or loss or lost) and
(energy or vigor or vigor); (3) feeling
and (drained or sleepy or sluggish or
weak*); (4) central nervous system
diseases, neoplasms, multiple
sclerosis, congenital heart defects,
anemia, chronic pain, chronic disease,
cerebral palsy, cardiovascular
diseases, diabetes mellitus (type 1);
chronic fatigue syndrome; and (5)
questionnaires or psychological tests.
Eligibility Criteria
Population
METHODS
Information Sources
The search strategy was designed to
retrieve literature relating to
measures of subjective fatigue in
children with chronic health
conditions. The systematic review
was conducted according to the
Preferred Reporting Items for
Systematic Reviews and MetaAnalyses (PRISMA).49 The EBSCOhost
platform was used to search the
electronic databases Medline,
Cumulative Index to Nursing and
Allied Health Literature, and
PsycINFO from 1990 to August 24,
2013 (updated June 12, 2014).
Nonconventional documents (gray
PEDIATRICS Volume 135, number 4, April 2015
Children and/or adolescents (#18
years of age) with a health condition.
Assessment Tool
Any questionnaire designed to
measure fatigue by using more than
1 item. Fatigue subscales included in
quality-of-life or other measures
were eligible for inclusion, provided
that fatigue scores could be
extracted separately (ie, total
subscale scores provided). Fatigue
assessment must be subjective,
quantified, and based on child report
or parent/other report, to be eligible
for inclusion.
Outcome
Any clinical outcome.
Exclusion Criteria
Review articles, opinion pieces, and
single case studies were excluded as
follows: studies that only reported
qualitative information as a measure
of fatigue (ie, professional opinion or
interview data); fatigue measures
that used a single item, either stand
alone (single item visual analog scales
[VASs]) or as part of another
questionnaire (ie, quality of life/
depression/symptom checklists); and
objective measures of performance
decrement (ie, attention vigilance,
muscle fatigue).
Study Selection
Titles and abstracts of all articles
were assessed for inclusion by 2
independent reviewers (Drs Crichton
and Knight) and agreement checked.
Data Collection Process
A standardized data extraction form
was developed and informed by
standard processes for systematic
reviews,51,52 earlier reviews in the
field,37,46–48 and incorporating
recommendations for patientreported outcome measure
evaluation and standards for
appraisal of methodological
quality.53–55 The form was
independently piloted in 2 randomly
selected studies by Drs Crichton and
Knight. Data were extracted by Dr
Crichton, independently checked by
Dr Knight, and disagreements were
resolved by consensus with
consultation of a third reviewer
(Dr Anderson; Table 1).
The data extraction and assessment
included information from 6 domains
(Table 1). The measurement
properties evaluated in data
categories 3 and 4 in Table 1
incorporate a consensus-based
taxonomy of measurement properties
considered important in patientreported outcome measures, defined
e1017
or “no information available.”55 If
measurement properties were not
checked, but the authors cited
published measurement properties in
another article, this was recorded and
the above ratings were maintained.
The methodological quality of
included studies were evaluated by
using the consensus-based standards
for the selection of health
measurement instruments (COSMIN)
checklist and 4-point rating scale.57
The COSMIN checklist contains 114
data points (12 boxes, 9 assessing
measurement properties), relating to
design requirements and preferred
statistical methods and consensus on
statistical values considered
adequate. Of these, 91 data points
(8 boxes) were relevant to the current
review: internal consistency (11),
reliability (14), measurement error
(11), content validity (5), structural
validity (7), hypothesis testing (10),
cross-cultural validity (15), and
responsiveness (18). Each item was
scored on a 4-point rating scale (ie,
“poor,” “fair,” “good,” or “excellent,”
and “not applicable” if omitted). For
each measurement property, the final
rating was determined by the lowest
rating of any of the items within the
box. If more than 1 instrument was
included in a study (eg, parent and
child versions), the same
measurement property was assessed
for each instrument.
Data Synthesis
FIGURE 1
PRISMA flow diagram of study identification and selection. a The sum of the included instruments is
higher than n = 89 because some studies evaluate more than 1 measure.
by Mokkink et al56 (Table 2, p. 743).
Relevant properties include the
following: (1) internal consistency,
(2) reliability, (3) measurement error,
(4) content validity, (5) construct
validity, (6) structural validity, (7)
hypothesis testing, (8) cross-cultural
validity, and (9) responsiveness.
Criterion validity is not relevant for
fatigue assessment, so it was
excluded. The 9 listed measurement
e1018
properties provided the domains for
data extraction for 2 key data sets at
an individual study level: (1) rating
the measurement property of the
instrument; (2) rating the quality of
the study (data categories 3 and 4,
Table 1; floor/ceiling effects and
interpretability not rated). According
to predefined criteria, each
measurement property was rated as
“positive,” “indeterminate,” “negative,”
Study level data were synthesized to
provide summary information for
each fatigue instrument. Information
across studies was summarized to
describe identified instruments and
the populations to whom instruments
were administered. Second, as
guidelines for pooling of
measurement properties are still
under development, best evidence
synthesis was performed integrating:
(1) the rating for the instrument’s
measurement property across
studies55 and (2) the COSMIN rating
for the methodological quality of the
studies.57 For each fatigue
CRICHTON et al
instrument, the consistency across
studies was reviewed for each
measurement property. The level of
evidence for the measurement
properties of instruments across
studies was rated by using predefined
criteria of positive, indeterminate, or
negative, accompanied by levels of
evidence, as proposed by the
Cochrane Back Review Group
(Table 1),52 detailed in Table 2.
RESULTS
Figure 1 illustrates the flow of article
selection. A total of 89 studies
measuring fatigue by using 20
instruments were included in data
extraction and synthesis.4,6,7,11,12,17,
20,23–25,27,33,36,38,58–132 One study
was not included in data synthesis for
measurement properties because
insufficient information was available
for data extraction.97
FIGURE 2
Child health conditions of patient group in included studies, n (%).
respectively.38,61,67,68,75,76,78–83,
85,95,107–109,113,128,132
Patient and Study Characteristics
Most reviewed studies were crosssectional (55; 62%), with a median
sample size of 69 subjects
(6–3890). Instruments were used to
assess fatigue in children with
a number of health conditions
(grouped into 14 diagnostic
categories). The most frequently
studied patient groups were
hematology/oncology diagnoses
(37; 42%) and chronic fatigue
syndrome (17; 19%; Fig 2).
Most (69; 77%) studies assessed
fatigue by using 1 or more of 12
identified child report instruments,
whereas 48 (54%) of included
studies assessed fatigue by using 1 or
more of 7 identified parent report
instruments. Five studies (6%)
included staff (“other”) report, using
1 instrument. Insufficient information
was available for 1 parent report
questionnaire.97 Descriptive
information on the child and
parent (and other) report
instruments to assess fatigue are
found in Tables 3 and 4,
respectively. See Table 5 for
respondent types within studies.
Respondent type varied across the
diagnostic groups of participants; in
studies of children with chronic
fatigue syndrome, child report
instruments were exclusively used,
whereas studies of children with
hematology/oncology diagnoses were
Identified Instruments
Twenty fatigue instruments were
identified (Fig 3). The Pediatric
Quality of Life Inventory (PedsQL)
Multidimensional Fatigue Scale (MFS)
parent and child report was the most
commonly used, cited in 26 (29%)
and 20 (22%) studies,
respectively.20,23–25,27,36,64,65,70,72,
74,84,86,93,94,98,100,103,111,115,
116,118,125,126,129,131
The fatigue
scales (Fatigue Scale-Child [FS-C];
Fatigue Scale-Adolescent [FS-A], and
the Fatigue Scale-Parent [FS-P]) were
the second most common
instruments to be cited in 18 (20%),
16 (18%), and 12 (13%) studies,
PEDIATRICS Volume 135, number 4, April 2015
FIGURE 3
Fatigue instruments used across identified studies, n (%).
e1019
e1020
CRICHTON et al
Severity of
fatigue;
impact of
fatigue
Severity of
fatigue;
impact of
fatigue
Severity of
fatigue;
impact of
fatigue
Severity of
fatigue;
impact of
fatigue
Severity of
fatigue
PedsQL MFS
(child)
FS-C
FS-A
CIS-20
Chalder
Fatigue
Scale
FSS
10–19 (3)
8–18 (2)
5–18 (1)
8–18b
5–18
10–17 (5)
10–18
5–19
13–18 (1)
13–18
7–12 (2)
7–12
Cognitive and physical
weariness; added
effort and assistance
needed to do usual
activities; needing
rest and feeling
angry; avoiding
social activities
Sleep/tiredness; mood;
cognitive function;
physical activity;
school performance;
withdrawal
Subjective experience
of fatigue;
concentration;
motivation;
physical activity
Physical; mental fatigue
5–18 (9)
5–7; 8–18
Sleep/tiredness;
cognitive function
1 mo
1 wk
2 wk
24 h or 1 wk
or 4 wk
24 h or 1 wk
or 4 wk
1 mo
Healthy
Recall Period
Controls
Age Range
(n = studies)
Participant
Age Range
Other Constructs
Severity of
Not specified
fatigue;
impact of
fatigue
PedsQL 3.0 CP Not specified Not specified
Module
(child)
Construct
Assesseda
Measure
TABLE 3 Characteristics of Included Child Report Fatigue Instruments
Response
Options
Health Conditions
Assessed
Administration
Burden
5-point or 4-point
Likert
Total fatigue (4; 0–100)
as subdomain total
of scale with 7
domains
Neurologic/CFS
Hematology/
oncology
Hematology/
oncology
CFS
Hematology/
oncology;
neurologic
disease
5-point Likert (ages Neuromotor
8–18); 4-point
Likert (ages 5–7)
Subjective fatigue (8);
7-point Likert
concentration (5);
motivation (4);
physical activity (3);
total (20; 20–140)
Physical (7); mental (4); 3- or 4-item Likert
total fatigue (11
or 14)
Total fatigue (9; 1–7
7-point Likert
average)
Intensity (14; 0–56 or
14–70)
Administrator
required to
read and
complete
child report
5–7 y
Not specified
Not specified
Not specified
Not specified
Administrator
General fatigue (6);
5-point Likert (ages Hematology/
required to
oncology;
8–18); 4-point
sleep/rest fatigue
read and
Likert (ages 5–7)
neurologic
(6); cognitive fatigue
complete
(6); total fatigue (18,
disease;
child report
rheumatological
0–100)
5–7 y
disease; obesity;
chronic pain;
brain injury;
heart diseases
(congenital);
diabetes, type 1;
gastroenterology
Intensity (14; 0–70);
5-point Likert yes/ Hematology/
Able to be
frequency (14; 0–14);
no, then 4-point
oncology
completed
by 6-y-olds
total fatigue (10 or
Likert
14, 0–70)
Dimension (n = items,
range)
Easy
Difficult
30 min
including
consent
Easy
Moderate
Easy
Easy
Difficult
Ease of
Scoring
Not specified
Not specified
Not specified
2–4 min; 4–5
min
3–10 min
5 min
Time to
Complete
PEDIATRICS Volume 135, number 4, April 2015
e1021
Severity of
fatigue
Severity of
fatigue;
impact of
fatigue
Severity of
fatigue;
impact of
fatigue
Severity of
fatigue;
impact of
fatigue
POMS
PROMIS
(child)
Q-sort task
PedsQL 3.0
ESRD
Module
(child)
Energy and related
capacity for physical
functioning; fatigue
related to
psychosocial
functioning; fatigue
uniquely associated
with anemia and/or
treatment
Not specified
Tiredness, lack of
energy, impact on
activities
Not specified
Not specified
Other Constructs
5–18
12–18
8–17
12–17
8–18
Participant
Age Range
5–18 (1)
None
8–17 (1)
None
None
Total fatigue (1 or 6;
0–4 or 0–100 mm)
Dimension (n = items,
range)
Visual analog
Response
Options
1 mo
General fatigue (4;
0–100)
5-point Likert
5-point Likert
1 wk or 4 wk Total fatigue (5 or 15;
not specified) as
subdomain total of
scale with 6 domains
5-point Likert
1 wk
Fatigue (34/10, short
form/15, CAT) as
subdomain total of
scale with 6
domains; fatigue
item bank: tiredness
(39); energy (14);
total (39; mean of 50
and SD of 10)
1 wk
Total fatigue (37; factor Rank order 24 to
array 22 to +2)
+4
Present state
Healthy
Recall Period
Controls
Age Range
(n = studies)
Renal disease
Hematology/
oncology
Hematology/
oncology;
musculoskeletal
Hematology/
oncology;
neurologic
disease
Obesity; diabetes,
type 1; other
chronic health
Health Conditions
Assessed
CAT, computerized adaptive testing; CFS, chronic fatigue syndrome.
a Based on earlier work by Elbers et al,37 the theoretical construct of fatigue was categorized as impact of fatigue on daily life, fatigue severity, or factors influencing fatigue.
b Goretti et al4 included children younger than 17 y, 11 mo. Age range was not specified.
Severity of
fatigue
Construct
Assesseda
VAS
Measure
TABLE 3 Continued
Not specified
Not specified
Not specified
Not specified
Difficult
Difficult
25 min
Difficult
younger
children, 15
or 32 min
adolescents
Computer
literacy,
computer,
screen, and
mouse
access
Easy
Moderate
Ease of
Scoring
Not specified
Not specified
Time to
Complete
Not specified
Not specified
Administration
Burden
e1022
CRICHTON et al
Severity of
fatigue;
impact of
fatigue
FS-P
Severity of
fatigue;
impact of
fatigue
Severity of
fatigue;
impact of
fatigue
Severity of
fatigue;
impact of
fatigue
FACIT-F
(modified
parent)
a
Sleep and
tiredness;
cognitive
function
Not specified
Not specified
Not specified
Lack of energy
Tiredness; lack of
energy; impact
on activities
7–18
2–18
2–18
1–12
5–18
7–18 (1)
2–18 (1)
7–18 (2)
7–18
2–18
2–18 (11)
Healthy
Controls
Age Range
(n = studies)
2–18
Participant
Age Range
24 h or
1 wk
1 mo
1 wk
4 wk
1 wk
1 mo
24 h or
1 wk
1 mo
Recall
Period
Response
Options
Fatigue intensity (9, 10 or
18; 9–36)
General fatigue (4; 0–100)
4-point Likert
5-point Likert
Total fatigue (2; not
5-point Likert
specified) subdomain of
scale with 13 domains
Total fatigue (13; 0–52) as 5-point Likert
subdomain total of scale
with 5 domains
Total fatigue (4; 0–100) as 5-point Likert
subdomain total of scale
with 7 domains
Lack of energy (11);
5-point Likert
tiredness (23); total
or 4-point
fatigue (34) (mean of 50,
Likert
SD of 10)
(physical
health)
5-point Likert
Intensity (14, 17, or 18
items; 14–17 or 18–90);
total (18; 17–85 or 0–68)
General fatigue (6); sleep/ 5-point Likert
rest fatigue (6); cognitive
fatigue (6) (total = 18;
0–100)
Dimension (n = Items,
Range)
Administration
Burden
Hematology/oncology
Renal disease
Hematology/oncology
Musculoskeletal
Other chronic health
Neuromotor
Not specified
5 min
Time to
Complete
Easy
Difficult
Ease of
Scoring
Not specified
Not specified
Not specified
Not specified
Not specified
Not specified
Easy
Difficult
Easy
30 min
Difficult
including
consent
Computer
12–22 min
Difficult
literacy;
(PROMIS I);
computer
30–40 min
screen;
(PROMIS II)
mouse access
all
domains
Not specified
Not specified Difficult
Not specified
Not specified
Hematology/oncology;
neurologic disease;
rheumatological disease;
obesity; chronic pain;
brain injury; heart
diseases (congenital);
diabetes, type 1;
gastroenterology
Hematology/oncology
Not specified
Health Conditions
Assessed
Based on earlier work by Elbers et al,37 the theoretical construct of fatigue was categorized as impact of fatigue on daily life, fatigue severity, or factors influencing fatigue.
FS-S
PedsQL ESRD
(parent)
Severity of
fatigue
Severity of
fatigue;
impact of
fatigue
EOSQ
PedsQL 3.0 CP
Module
(parent)
PROMIS
(parent)
Severity of
fatigue;
impact of
fatigue
PedsQL MFS
(parent)
Other Constructs
Cognitive and
physical
weariness; effort
and assistance
needed to do
usual activities;
needing rest and
feeling angry;
avoiding social
activities
Not specified Not specified
Construct
Assesseda
Measure
TABLE 4 Characteristics of Included Parent and Other Report Fatigue Instruments
TABLE 5 Respondent Types Within Studies
Respondent
No. (%) of Studies
Child only
Child and parent
Parent only
36 (40)
33 (37)
15 (17)
unique in using staff-rated
instruments (Fig 3).
Dimensions of Fatigue Assessed
Most instruments assessed impact of
fatigue on daily life and fatigue
severity (14; 70%). Few (4; 20%)
assessed fatigue severity symptoms
only, and no instruments assessed
impact of fatigue on daily life in
isolation. Although item content
related to these dimensions, scoring
rarely reflected the dimensionality of
the constructs assessed, and items for
most instruments (14; 70%) were
summed into a total fatigue score.
A minority (6; 30%) consisted of
scores for multiple fatigue dimensions:
5 child-report measures summed
items into 2 to 4 dimensions, and
1 parent report measure summed items
into fatigue dimensions (3). There was
insufficient information on item
content for 2 instruments (10%).
Developmental Framework
Overall, participant age was skewed
toward children 12 years and older
(Fig 4). Healthy control participants
were included in 23 of 81 studies for
which age range could be extracted
(29%). Self-report of fatigue is
challenging in younger children, and
only 4 (33%) child report instruments
were identified in use between 5 and
7 years of age. Greater administration
burden was commonly noted because
items need to be read aloud to
children or administrators need to be
available to note children’s verbal
responses. In contrast, 4 (57%) parent
report instruments were identified to
assess fatigue symptoms in children as
young as 2 years of age.
Synthesis of Results
Psychometric Properties
A synthesis summary of the
investigated methodological
PEDIATRICS Volume 135, number 4, April 2015
properties of measures and
methodological quality of the
included studies is provided in
Table 6. Full details of the resultant
COSMIN ratings for each study (per
measurement property and
questionnaire) are provided in
Supplemental Tables 7–26. The
quality of evidence available across
questionnaires varied by
measurement properties as shown,
and no single instrument
demonstrated positive findings across
all properties. Content validity was
rated for all instruments and revealed
the most promising evidence.
Although assessed in several
instruments, poor results were found
for internal consistency. This was
primarily because studies did not test
for unidimensionality (factor
analysis), or because despite
completing factor analysis and
evidence of more than 1 factor, items
were summarized into a single score.
Cultural validity was not considered,
and COSMIN items were used to rate
the quality of the translation across
all studies with cultural validity data.
Few studies revealed information
about measurement error, reliability,
or responsiveness. There was limited
evidence of the floor and ceiling
effects across studies, with ,5% of
included studies providing
information.
There was robust evidence for the
measurement properties of the
PedsQL MFS and the FS-C/FS-P. The
PedsQL MFS (child and parent
versions) was the only included
instrument to have strong evidence of
reliability, and the only instrument to
have strong evidence across
a number of dimensions of
assessment. There were positive
ratings for reliability, content validity,
and hypothesis testing for the PedsQL
MFS. Despite the overall rating for
reliability, internal consistency
coefficient (ICC) values varied across
different populations assessed from
low to high (eg, 0.27–0.93 for total
fatigue).23,125 Additionally, variability
with age has been noted.64 There was
limited evidence for the structural
validity of the child version fitting
a bifactor model (3 subscales: general
fatigue, sleep-rest fatigue, and
cognitive fatigue and a total fatigue
score),122 lending new support to
previous research finding good to
excellent internal consistency
statistics (Cronbach a values between
0.70 and 0.95). Strong evidence for
hypothesis testing validity for the
PedsQL MFS was evident, although
internal consistency and
measurement error of the PedsQL
MFS require further research. The
data for these measurement
properties were gathered in children
with numerous health conditions,
noted in Tables 3 and 4.
The FS-C, FS-A, and FS-P (standard
and 24-hour formats) demonstrated
robust measurement properties,
notably content validity. There was
moderate evidence for the structural
validity of the child and parent forms,
but limited evidence for the
structural validity of the adolescent
form. Internal consistency and
reliability data were mixed; although
internal consistency statistics were
good (0.70 or greater),79–81,107,113
these statistics were calculated based
on the total fatigue scores, despite
findings of a 3-factor model for the
FS-C and a 4-factor model for the FSA.79,80 One study revealed adequate
reliability statistics for the FS-A,
presenting pooled data from a series
of studies, and variable agreement
between parent and child were found
across included studies (ICC values
0.13–0.65).79 The Fatigue Scale-Staff
(FS-S) demonstrated moderate
evidence for internal consistency and
content validity and limited evidence
for structural validity.38,68,75,79 The
assessed evidence for FS-C, FS-A, and
FS-P was gathered exclusively in
studies of children with hematology/
oncology diagnoses, limiting
generalizability of findings to other
health conditions.
The Patient-Reported Outcomes
Measurement Information System
e1023
FIGURE 4
Age range representation for clinical and healthy participants in included studies (proportion of studies, %). Mean age data for participants set out for
81 studies; no mean age participant data reported for 8 studies. Mean age data for controls set out for 26 studies; no mean age control data reported for
63 studies.
(PROMIS)77,88,89,114,123 is a newly
developed outcome measure (fatigue
subscale). Among identified studies,
those that used PROMIS were the
only ones to employ item response
theory for statistical analysis. More
published information was available
for the child version, with positive
ratings evident for content validity
and hypothesis testing. However,
there were also some positive
findings for the content and validity
of the PROMIS parent report. Overall,
properties were given largely
indeterminate ratings because the
measurement properties have not yet
been evaluated. Evidence was
gathered in study populations of
children with mixed health
conditions.
There was limited evidence for
hypothesis testing validity of the
Checklist Individual Strength-20 (CIS20)7,17,101,102,117,119–121 in children
with neurologic disorders and chronic
fatigue syndrome. Overall findings for
the scale were equivocal.
Some disease-specific instruments
demonstrated positive ratings for
content validity in these specific
populations (eg, the PedsQL 3.0
Cerebral Palsy Module [PedsQL 3.0
CP Module]11,12 and the Early Onset
TABLE 6 Levels of Evidence for the Overall Quality of the Measurement Property per Instrument
Instrument Namea
Internal
Consistency
Reliability
Measurement
Error
Content
Validity
Structural
Validity
Hypothesis
Testing
Cross Cultural
Validity
Responsiveness
PedsQL MFS (parent)
PedsQL MFS (child)
FS-C or FS-C 24 h
FS-A or FS-A 24 h
FS-P or FS-P 24 h
FS-S
Chalder Fatigue Scale
CIS-20
PROMIS (child)
PROMIS (parent)
FSS
PedsQL 3.0 CP Module (parent)
PedsQL 3.0 CP Module (child)
VAS
POMS
FACIT-F (modified parent)
Q-sort
PedsQL ESRD (parent)
PedsQL ERSD (child)
EOSQ (parent)
?
?
2
?
?
++
?
?
?
?
?
?
?
?
?
+
?
?
?
?
+++
+++
?
2
?
?
?
?
+
?
?
2
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
+++
+++
+++
+++
+++
++
?
?
+++
++
?
++
+
?
?
+
+
+
+
++
?
+
++
+
++
+
?
?
?
?
?
?
?
?
?
?
?
?
?
?
+++
+++
+
+
+
?
2
+
++
?
2
+/2
+
?
?
?
?
?
?
?
+
+
+
?
+
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
a Strong +++ or 2 2 2, Consistent findings in multiple studies of good methodological quality or in 1 study of excellent methodological quality; Moderate ++ or 2 2, Consistent findings
in multiple studies of fair methodological quality or in 1 study of good methodological quality; Limited + or 2, 1 study of fair methodological quality; Conflicting +/2, Conflicting findings;
Unknown ?, Only studies of poor methodological quality.
e1024
CRICHTON et al
Scoliosis Questionnaire [EOSQ]),62,127
although lacked other evidence for
the quality of their measurement
properties. However, the majority of
included instruments demonstrated
low ratings overall. There was limited
evidence for the content validity of
the Pediatric Functional Assessment
of Chronic Illness Therapy-Fatigue
(FACIT-F)33,69,92 and the Q-sort92
instruments for use in hematology/
oncology populations, despite no
published evidence for other assessed
measurement properties. There was
no positive evidence for
measurement properties of the
Chalder Fatigue
Scale,58,59,63,90,91,96,106 or the Fatigue
Severity Scale (FSS),4,6,73,87 used in
children with chronic fatigue
syndrome. Often these studies did not
report on measurement properties.
There was also no published evidence
for the measurement properties of
the Profile of Mood States (POMS;
hematology/oncology and
neurology),104,109 the PedsQL End
Stage Renal Disease Module (PedsQL
ERSD) parent or child (renal
disease),62,71,105,127 nor the included
VASs (hematology/oncology and
musculoskeletal illnesses).66,112
Risk of Bias
Risk of bias was identified across
studies for several instruments, due
to reanalysis of participant data
across studies, including PedsQL
MFS,23–25,36,72,93,125 the Fatigue
Scales (child, parent, and
adolescent),81,82 and the CIS20.119,120 Repeated analysis of group
data possibly skews findings and
limits the generalizability of findings
to other populations. Further,
although declared, a primary
researcher holds the copyright for the
PedsQL including PedsQL MFS,23,25,27
PedsQL 3.0 CP Module,11,12 and
the PedsQL ESRD Module.71
DISCUSSION
This study is the first to
systematically review and critically
appraise fatigue instruments across
PEDIATRICS Volume 135, number 4, April 2015
the range of childhood chronic health
conditions and ages. Twenty
instruments (12 child reports, 7
parent reports, and 1 staff report)
were described with reference to
patient characteristics (age and
diagnosis), dimensionality of fatigue
assessed, and child development. This
review provides a thorough and
unique review of childhood fatigue
instruments across conditions, using
standardized published measures to
assess the measurement properties of
these instruments and to assess the
quality of the evidence for these
properties.
In applying COSMIN criteria and
assessing the quality of the study,
evidence for the measurement
properties of the 20 instruments can
be compared. This review did not
identify any child or parent report
instrument that met all of the criteria.
This appraisal highlights key issues in
the assessment of fatigue in
childhood health conditions. It is
widely acknowledged that as
a subjective symptom, fatigue should
be assessed by using self report,
although developmental
considerations necessarily restrict the
feasibility of this in younger children.
However, it is important to recognize
the noted lack of robust evidence for
reliability. Where ICC values were
recorded, they were often low,
indicating lack of agreement between
child and parent report on
assessment instruments, meaning
child and parent report instruments
cannot be directly compared. It is
recommended that parent and child
perspectives be carefully considered
when interpreting findings relating to
fatigue symptoms in children.
Over 14 health conditions were
identified as experiencing symptoms
of fatigue; however, evidence for
instruments varied across these
conditions. Findings from this review
suggest that evidence is limited to
instruments that assess fatigue in
children with hematology/oncology,
and other health conditions.
Specifically, there was support for
the measurement properties of the
PedsQL MFS, and limited evidence
for the PROMIS instrument in
children with a range of chronic
health conditions, and for the FS-C,
FS-P, and the FS-A in children with
cancer. Evidence for instrument
properties in children with chronic
fatigue syndrome was lacking,
despite the high proportion of
studies with this population. Further,
although literature suggests the low
threshold of fatigue symptoms
distinguishes this clinical
condition,133 no reviewed
instruments assessed this. Practicing
clinicians should be aware that
fatigue can arise from many causes
and conditions, and awareness of the
underlying disorder and relevant
clinical features is critical to
selecting the appropriate valid
assessment tool.
Whether fatigue should be
conceptualized as unidimensional or
multidimensional has been a matter
of considerable debate, and evidently
measurement of fatigue is a complex
issue. Descriptive findings suggest
that this issue is poorly managed
by currently available fatigue
instruments. Notably, studies failed
to confirm the number of fatigue
dimensions (by factor analysis or
other methods), or assessment of
fatigue was conducted by using
instruments in which the number of
scales did not correspond to the
number of dimensions identified in
factor analysis. For example, of the
questionnaires with the most robust
psychometric properties and study
quality, scores are summed to 3
dimensions for the PedsQL MFS, and
a total score for the fatigue scales
(FS-C, FS-A, and FS-P). However, there
is evidence from factor analysis that
both instruments are explained by
3 to 4 factors.79,80,122 Studies beyond
the scope of this review further
suggest multiple factors in fatigue
assessment instruments, with recent
evidence confirming a 3-factor
structure of the PedsQL MFS,134 and
e1025
a 2-factor structure of the PROMIS
scale.2 The field of research is yet to
develop a coherent way of relating
this emerging evidence regarding
fatigue dimensionality with
quantification of symptoms. In
clinical practice, it is important to
recognize the complexity of fatigue,
and to move beyond simplistic
assessment of the symptom to
consider a multidimensional
approach to assessment. Clinicians
should be aware of the different
information provided by the range of
assessment instruments.
This review considered child-specific
issues relating to fatigue assessment.
However, the findings for reviewed
fatigue instruments cannot be
generalized across age ranges
because participants were mainly
older than 12 years of age, and gaps
in the quality of evidence were
identified at key developmental
stages. It is important to identify the
ages in which studies have been
performed because measurement
properties may vary in different age
ranges. Few instruments are
validated for use in younger children,
with robust evidence provided only
by the PedsQL MFS (age range, 2–18
years), and limited evidence
provided by the PedsQL 3.0 CP
Module and the EOSQ. There was
limited reference to healthy control
participants in included studies. It is
crucial to the determination of
excessive fatigue that normal
developmental differences are taken
into account because fatigue is
a symptom that occurs in healthy
populations, and reveals
developmental variation.85,128,135
Further studies are required to
examine fatigue expression across
age groups, including notably
younger children, and make
reference to normal development, to
understand how age affects the
experience of fatigue.
LIMITATIONS
Limitations of this review include
a focus on children 18 years or
younger with different health
conditions. Evidence of
measurement properties in use in
other populations was not
considered. For example, despite
several of these measures being
described in older or healthy
childhood populations, the inclusion
of these findings was beyond the
scope of this review. Care should be
taken when considering the
generalizability of the findings to
other patient groups. Further, the
review was restricted to subjective
measures of fatigue and did not
include studies that have attempted
to measure fatigue objectively.
CONCLUSIONS
There are a large number of
instruments available to measure
fatigue across a range of childhood
health conditions, yet there is limited
evidence for their utility. There was
best evidence for the use of the
PedsQL MFS (parent and child report)
in a range of pediatric chronic health
conditions across childhood, and the
FS-C, FS-A, and FS-P in children with
cancer of school age. Use of other
instruments should be limited to
research into the validity of the
instrument, not patient outcomes.
Further data are required to support
the measurement properties of
instruments used to assess fatigue in
children with chronic fatigue
syndrome, to identify appropriate
tools to assess fatigue in children
younger than school age, and to
clarify the nature of agreement
between child and proxy report
across developmental stages.
ACKNOWLEDGMENT
We thank Poh Chua, Deputy
Librarian, RCH, Melbourne, for her
help in use of the EBSCOhost platform
and search terms.
FINANCIAL DISCLOSURE: The authors have indicated they have no financial relationships relevant to this article to disclose.
FUNDING: Supported in part by a Moving Ahead Seed grant, a National Health and Medical Research Council Postgraduate Scholarship (Dr Crichton, awarded 2014),
Canberra, Australia, a Neurosciences Victoria Brain and Mind Scholarship, Melbourne, Australia (Dr Crichton, awarded 2012), and the Victorian Government
Operations Infrastructure Scheme.
POTENTIAL CONFLICT OF INTEREST: The authors have indicated they have no potential conflicts of interest to disclose.
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