Creative Education
2012. Vol.3, Special Issue, 959-970
Published Online October 2012 in SciRes (http://www.SciRP.org/journal/ce) http://dx.doi.org/10.4236/ce.2012.326146
Measurement Properties of the Arabic Lebanon Version of the
Pediatric Quality of Life Inventory 4.0 Generic Core Scales for
Young Child (5 - 7 Years), and Child Aged 8 - 12 Years: Quality
of Life in Urban and Rural Children in Lebanon
Ibtissam Sabbah1, Hala Sabbah2, Sanaa Sabbah3, Hussein Akoum1, Nabil Droubi1*,
Mariette Mercier4
1Faculty of Public Health, Lebanese University, Saida, Lebanon
2Faculty of Economic Sciences and Business Administration, Lebanese University,
Nabatieh, Lebanon
3Doctoral School of Literature, Humanities & Social Sciences—Lebanese University, and Institute of Social
Science—Lebanese University, Nabatieh, Lebanon
4Department of Biostatistics, Faculty of Medicine and Pharmacy, Franche Comte Univerity, Besançon, France
Received August 25th, 2012; revised September 24th, 2012; accepted October 9th, 2012
Background: Health-related quality of life (HRQOL) is recognized as an important health outcome
measurement for pediatric patients. HRQOL in children is needed to gain a better understanding of the
impact of public policies, interventions, therapies, and the prediction of health and social care need. In
view of the lack of reliable HRQOL instruments for children in Arabic, the present study aims to translate
the PedsQLTM4.0 self-report and proxy-report for young child (aged 5 - 7 years), and child (aged 8 - 12
years), evaluate psychometric properties of the Arabic Lebanon version; and to evaluate HRQOL of chil-
dren in rural and urban areas in Lebanon. Methods: PedsQLTM4.0 was translated and adapted into Arabic
using the standard approach provided by Varni J. W. The Arabic version was administered to a represen-
tative sample of 368 children aged 5 - 12 years and their parents. The psychometric properties were then
evaluated. Results: The rate of missing data for self-report and proxy-report was very low (0.51% and
0.46% of items). All child self-report, and parent proxy-report subscales exceeded the minimum reliabil-
ity standard of 0.70 for alpha coefficient, except emotional subscale of young child self-report and
proxy-report, and, the social subscale of child self-report (alphas ranging from 0.60 to 0.66). Factor
analysis yielded patterns of factor correlation comparable to the original version. The emotional function-
ing of children is low, where most children feel afraid, sad, and angry. Children resident in rural areas had
higher social scores than those in urban areas. The HRQOL of girls is higher than boys; Children under-
going treatment for cancer rated their HRQOL as poorer in all dimensions. Conclusions: The results
support the validity of the PedsQLTM4.0 self-report and proxy-report Arabic version. Habitat has a minor
influence on HRQOL of children. Further psychometric evaluation in a larger sample of children, in other
departments of Lebanon is recommended to provide firmer conclusions.
Keywords: PedsQLTM4.0; Health Related Quality of Life; Urban; Cross-Sectional Study; Arabic Lebanon;
Young Child
Introduction
The last decade has witnessed a dramatic increase in the de-
velopment and utilization of pediatric health-related quality of
life (HRQOL) measures (Varni, Burwinkle, & Lane, 2005;
Varni, Limbers, & Burwinkle, 2007; Solans et al., 2008; MAPI
Research Institute) that focuses on individual’s subjective
evaluation of physical and psychological status and overall
sense of well-being (Sabbah et al., 2003; Mistry, Stevens, &
Gorelick, 2009; Giannakopoulos et al., 2009; Stevanovic, 2009)
(Eshaghi, Ramezani, Shahsanaee, & Pooya, 2006; Berkes et al.,
2010). International studies on HRQOL in children are needed
to gain a better understanding of the impact of public policies,
interventions, therapies (Schmidt, Wenninger, Niemann, Wahn,
& Staab, 2009), evaluation of interventions, and the prediction
of health and social care need (Sabbah et al., 2003; Hatzmann,
Maurice-Stam, Heymans, & Grootenhuis, 2009; Panepinto,
Hoffmann, & Pajewski, 2009).
However, HRQOL research in children presents many chal-
lenges as for age specification, and the proxy report problem
(Varni et al., 2007; Verrips et al., 1999; Matza, Swensen, Flood,
Secnik, & Leidy, 2004; Tarride et al., 2010). Many existing
questionnaires and scoring systems for adults are not applicable
to children. Also, it may be difficult in some cases to separate
the true effect of a healthcare intervention from the normal
development of the children (e.g. autonomy behavior; Verrips
et al., 1999; Tarride et al., 2010). The parent proxy-report in-
struments are required in situations when children are unable to
provide self-report (Varni et al., 2007; Solans et al., 2008), in
*Corresponding author.

I. SABBAH ET AL.
case of children are too ill, unwilling or lacking the necessary
language skills (Solans et al., 2008).
Appropriate HRQOL measures should be available across
different cultures. HRQOL tools must always be adapted when
used in a new environment, because the perception of quality of
life differs according to the individual situations (Sabbah et al.,
2003; Stevanovic, 2009; Matza et al., 2004; Bollinger, Power,
Aaronson, Cella, & Anderson, 1996; Varni, Burwinkle, Seid, &
Skarr, 2003; Varni, et al., 1999; Varni, et al., 2001; Varni, et al.,
2002; Chan, Mangione-Smith, Burwinkle, Rosen, & Varni,
2005; Varni & Limbers, 2009; Torres et al., 2009; Reinfjell,
Diseth, Veenstra, & Vikan, 2006). Translation should not only
ensure measurement equivalence between the original and new
versions, but also respecting the cultural distinctions of the new
ones. Cross-cultural adaptation is necessary in order to make
possible the collection of information in other cultures (Ste-
vanovic, 2009; Torres et al., 2009).
Several generic instruments are available to assess children’s
HRQOL based on self-reports as well as proxy-reports from
parents (Stevanovic, 2009; Verrips et al., 1999; Torres et al.,
2009) (http://www.pedsql.org) (Estrada et al., 2010; Harrison et
al., 2010). For our purpose, the PedsQL4.0 generic module
represented a particularly attractive generic measure as it has
been widely used in children and adolescent integrating generic
core scales and disease-specific modules into one measurement
system it is translated into many international languages
(Berkes et al., 2010; Reinfjellet al., 2006; Sato et al., 2010)
(http://www.pedsql.org) (Upton et al., 2005; Gkoltsiou et al.,
2008; Bek, Simsek, Erel, Yakut, & Uygur, 2009). To the au-
thors’ knowledge, the Arabic version has not previously been
assessed for validity and reliability in Lebanon. In view of the
lack of reliable HRQOL instruments for children in Arabic, and
to facilitate the sharing of data across international borders, the
aim of the present study is 1) to investigate the validity and
reliability of an adapted Arabic translation of the PedsQLTM4.0
Child (CF) and Proxy Form (PF) as a population health out-
come measure in Lebanese children; 2) the second objective is
to assess the HRQOL of Lebanese children as well as the cross
sectional relationship with a selected list of socioeconomic
variables, environmental variables, in particular the type of
habitat (urban vs. rural area), and health variables; 3) to explore
the influence of chronic disease related factors on child
HRQOL. We hypothesized that gender (female vs. male), habi-
tat (urban vs. rural), socio-economic conditions of households,
and having a chronic illness (e.g. cancer, asthma, rhinitis) in-
fluenced HRQOL directly.
Method
This study is divided into two phases: Phase I, the cross-
cultural adaptation, which involves the translation procedures
and preliminary probe in the target population; and phase II,
which involves the reliability and validation.
The PedsQLTM4.0 core Version was administered according
to the terms of the user agreement between the authors and
distributors, which approved the cultural adaptation, and vali-
dation of the Peds 4.0 into Arabic.
PedsQLTM4.0
The HRQOL study described in this paper was carried out
using the PedsQLTM4.0 (CF & PF), developed by Dr. James W.
Varni. The PedsQLTM during the previous 4 weeks version is a
23-item reliable, validated pediatric HRQOL instrument, offered
in both child-report and parent-proxy report formats, with age-
appropriate versions. The child report is available for children
between 5 - 18 years, divided into the 5 - 7 (young child), 8 - 12
(child), and 13 - 18 years (adolescent) age groups. The parent-
proxy forms may be used for children 2 - 18 years of age; with
a 2 - 4 years (toddler) version. The PedsQLTM measures HRQOL
in four domains: physical functioning, emotional functioning,
social functioning, and school functioning. Items are scored
from 0 to 4, with a score of 0 indicating “never a problem”, and
4 representing “always a problem”. Individual item scores are
computed as the following steps: Items are reverse-scored and
linearly transformed to a 0 - 100 scale (0 = 100, 1 = 75, 2 = 50,
3 = 25, 4 = 0), so that higher scores indicate better HRQOL.
Scale Scores are computed as the sum of the items divided by
the number of items answered (this accounts for missing data).
If more than 50% of the items in the scale are missing, the
Scale Score is not computed. The PedsQLTM4.0 yields 3 sum-
mary scores: a total scale score (average of all items in the
questionnaire), a physical health summary score (physical do-
main), and a psychosocial health summary score (combination
of emotional, social, and school domains).
Participants
From March to June 2010, we performed a cross sectional
study of a sample of the Lebanese children and their parent’s
resident in South Lebanon (except Palestinian camps) (Bureau
Centrale de la Statistique au Liban, 2006). A supplementary
sample of child currently under treatment for cancer and one of
their parents were designed to oversample the chronic condi-
tions child data especially child with cancer in active period of
treatment, derived from referral center in Lebanon to treat chil-
dren with cancer.
The sampling in the general population was random and at
several levels: county, city (in urban areas) or village (in rural
areas), quarter, household and individual (Sabbah et al., 2003;
Sabbah et al., 2007). In the absence of reliable census data in
the various communities, the random sampling of households
was done according to the “itinerary method” (Rumeau-Rou-
quette et al., 1993). This sample would allow us to detect a 10
point difference between groups with a fixed norm (a general
population), assuming two-sided significance of 5%, with 80%
power (Sabbah et al., 2003; Ware, 1997). A sample size of 300
participants was found to fulfill these inputs, taking into ac-
count the proportion of urban (U) to rural (R) residents. In total,
we selected 100 families in urban and 200 families in rural
areas. The sample of children was taken within the families
according to the number (n) of children in the family: one child
was selected if n ≤ 2; two if 3 < n < 4 and three if n ≥ 5. Inclu-
sion criteria were: 1) young children (ages 5 - 7), children (ages
8 - 12) years at the time of the visit and one of their parents; 2)
the children lived at home; 3) parents and children were able to
understand and fill out the questionnaire in Arabic. Persons
(children and parents) unable to read the questionnaire who
were also hard of hearing were excluded, as were very ill or
hospitalized patients, severely mentally handicapped and sub-
jects unable to understand Arabic as a consequence of either
physical or cognitive impairment (Sabbah et al., 2003). If the
child was not home at the time of the initial call, the research
assistant arranged for a call at another time.
The cancer sample was recruited from the unit center at re-
960

I. SABBAH ET AL.
ferral hospitals in Lebanon. A sample size of 40 cancer subjects
was to be able to reject the null hypothesis (Vanderbilt Univer-
sity). Patients were eligible if they were: 1) 5 to 12 years of age;
2) greater than one month post-diagnosis and currently receiv-
ing treatment for a cancer diagnosis; and 3) physically able to
complete the questionnaire.
The informed consent was obtained from parents, children,
and health organization managers (when appropriate) before the
administration of the questionnaires.
After identifying eligible subjects, the PedsQLTM4.0 (CF &
PF) was administered by self-administration or face-to-face in-
terviews. Children between 5 and 7 years of age were inter-
viewed by one interviewer.
Additionally, the parents completed a form that contained
demographics, socio-economic questions, and the perception of
the financial, overall QoL, and overall health status (Ware,
1997). This form also has questions about their child included
socio demographic, scholarship, information concerning school
type (private/public), means of transport to school. Health prob-
lems were measured with a list of known health problems that
the children face (World Health Organization (WHO), 1993).
The declared obesity by calculating the body mass index (BMI
≥ 95th percentile) is also measured (Giampietro et al., 2002;
Children’s BMI Group Calculator, 2007).
Cultural Ad a p ta ti o n o f the PedsQLTM4.0 i nto Arabic
The translation of the PedsQLTM4.0 from English to Arabic
was performed according to the procedures recommended by
the author (Varni, 1998-2012). In the first phase, the PedsQLTM4.0
English versions were translated by two native Arabic, and
bilingual individuals independent of one another. Once the two
translations were completed to each version of child and prox-
ies report, discrepancies between them were resolved by a
committee consisting of the translators and 3 further individuals
not involved in the translation process. They agreed on a single
reconciled version which was a conceptually equivalent transla-
tion to the original English version and written in an easily
understood language for the children. Then, the Arabic versions
of the PedsQLTM4.0 were back-translated by a native English
speaker living in Lebanon, who was unaware of the original
English language document, and a fluent in English that carried
out a second back-translation version. The 4 backward transla-
tions were then reviewed by two of the authors of this paper.
The aim of this phase was to ascertain that the translation was
fully comprehensible and the concordance with the English
version was attained and to resolve the discrepancies between
the back translation and the original document. Following this
phase, a second meeting was held with the participation of all
the translators and researchers. The purpose of this meeting was
to reach a final consensus. The last stage of the adaptation
process was to test the pre-final version in a pilot study. The
questionnaire was administered to a group (37 × 2 subjects) of
children and parents. They are lay native Arabic speakers. For
each item the group was asked to consider each question in a
critical manner and explain how it was understood. Overall,
few problems were noted. Discrepancies were resolved by
group consensus. Because of the difficulties related to Arabic
grammar and to the style of Arabic writing, two other Arabic
linguistics experts also reviewed the translated versions. They
checked the spelling, grammar of the forward versions, and the
final Arabic versions. After some modification on wording and
proofreading, the final version was forwarded to the MAPI
Research Institute, which gave the approval for the psychomet-
ric probe of the Arabic versions of the Lebanese PedsQL4.0
(CF & PF).
Globally, the adaptation did not cause any particular prob-
lems, and the Arabic versions of PedsQLTM4.0 Child and Par-
ent Reports for young Children (aged 5 - 7), Children (aged 8 -
12) forms achieved satisfactory concept and semantic equiva-
lence when compared to the original instruments, proving the
questionnaires could be applied for the assessment of reliability
and validity of these versions on Lebanese children and their
parents: The format, instructions, Likert response scale, and
scoring method for the PedsQLTM4.0 Generic Core Scales are
identical to the original version, with higher scores indicating
better HRQOL.
Indeed, with regard to the translation of the questionnaire for
our study, some responses related to cultural differences are
observed. The expression “do chores” was problematic. In the
Lebanese culture, boys are not expected to do chores related to
household; therefore, it was necessary to give examples to
mothers so that it would be accepted more like “Do chores”
(like pick up his toys, work in the garden, sort bed...), in addi-
tion, the servants do chores in households. Some problems
related to the autonomy concept: the question related to “having
a bath alone” didn’t give a clear idea about reality since most
mothers don’t allow their kids to have a bath on their own even
if they’re physically able to do so, just because they are worried
that the kid might hurt himself or might not clean himself prop-
erly. This may be the reason to underestimate the physical
health scores in Lebanese children.
Certain items were confusing to the parent child (aged 8 - 12
and 5 - 7 years). In case of auto administered questionnaire, the
Items written in positive ways as: some physical functioning
items, getting along with other children, keeping up when
playing with other children, paying attention in class; keeping
up with schoolwork is answered in a positive manner. These
items must be worded: we have to put “difficulty to” or
“didn’t” before: get along... So, a higher pre-coded item value
indicates a poorer health state. In general, no questions were
irrelevant, and the respondents found the questions suitable for
their children. Also, the interview was considered by many
parents as a worthy experience since it enabled them to have a
better communication with their children and to know more
about their feelings in depth.
S tatistical Analysis
First, HRQOL scales were constructed, and missing data
were imputed based on the standard guidelines. Scores for
HRQL were calculated using the PedsQLTM developer’s guide-
lines.
Data analysis included descriptive statistics (frequency dis-
tribution, ceiling and floor effects, means and SD). Acceptable
floor or ceiling effects are less than or equal to 20% (Bollinger,
Power, Aaronson, Cella, & Anderson, 1996).
The acceptability of the Peds 4.0 (CF & PF) was tested by
studying the percentage of refusals, the percentage of missing
items, the percentage of complete questionnaires, the time taken
to complete the questionnaire (Varni & Burwinkle, 2006), as
well as the acceptability questionnaire, which comprises the
percentage of disturbing items, items that were hard to under-
stand or confusing, and the willingness to fill out the question-

I. SABBAH ET AL.
naire a second time (Sabbah et al., 2003).
Items factor analyses were performed using 23 items for
child and proxy report. Principal component analysis with
varimax rotation was carried out on correlation among items to
compare the factorial structure of data with that obtained from
the American instrument.
Reliability was assessed by tests of internal consistency us-
ing Cronbach’s α coefficient. Values ≥ 0.70 are considered ac-
ceptable for comparisons between groups (Sabbah, 2003; Ware,
1997; Varni et al., 2006; Nunnally & Bernstein, 1994; Cron-
bach, 1951).
The construct validity was assessed utilizing the known
groups (Ware, 1997; Varni et al., 2006) by making the asso-
ciation between the socio demographic parameters, environ-
mental variables and health problems. This analysis was con-
ducted using F tests from analysis of variance, and chi-square
or Fisher’s Exact Tests when appropriate.
Effect size between health and cancer children sample was
calculated. Effects sizes are designated as small (0.2), medium
(0.5) and large (0.8) (Varni et al., 2003; Varni et al., 2006). The
size of the standard error of the measurement (SEM) is deter-
mined by the reliability of that score (Varni et al., 2003; Ware,
1997; Nunnally et al., 1994). We also explored cut-off points
for at-risk status for impaired HRQOL by examining the
PedsQL4.0 scale scores for 1 SD (standard deviation) below the
mean of the total population sample.
Agreement between child self-report and parent proxy-report
was assessed through the Spearman’s correlation coefficient
with thresholds for poor (0.10 - 0.29), medium (0.30 - 0.49),
and large (≥50) (Ware, 1997; Varni et al., 2006).
Quality of Lif e Acco rdi ng to Habitat
The validity of known groups makes it possible to evaluate at
the same time the QoL according to habitat, i.e. urban vs. rural.
Multivariate analysis was performed to test the effect of habitat
on all domains of the PedsQL4.0 child and proxy inventory.
The adjustments were performed by generalized linear model
(GLM of SPSS). As four levels of cluster sampling were used,
the cluster effect may be considered very low and thus was not
specifically taken into account in the statistical analysis. Be-
use of multiple testing, a p-value < 0.01 was considered to be
significant. All data were recorded, and tabulated for analysis
using the SPSS statistical package program (version 16.0. SPSS
Inc., Chicago, IL, USA).
Results
Sample Characteristics
The majority of the population welcomed the study. The ac-
ceptability in general population is very high (88.0%). 71.2% of
families participated in the survey live in rural area. Concerning
cancer children and parents’ of 38 eligible populations ap-
proached for the study, 81.6% agreed to participate. Reason for
refusal was not given by potential participants. In total, 295
families accepted to participate, corresponding to 368 children
of which there are 91.6% in the community. 230 (78.0%) fami-
lies had only 1 child and one parent participated. The main
respondent of the parent proxy-report was mothers (82.7%),
fathers (13.9%), and others relatives (2.7%). The mean number
of child in the family is 3.41 (SD = 1.60) [range 1 to 10], the
mean age of mothers and fathers was respectively 37.5 (SD =
6.5) years, and 43.24 (SD = 7.0) years. 58.6% of the families
reported having experienced a disease during the last 12 months
in the family. 23.6% of fathers were educated to primary level
or lower, and 2.8% were illiterate. 28.3% of the mothers have
university and higher level of education, and there was no sig-
nificant difference between rural and urban environment in this
regard; 71.7% mothers were housewives. 47.2% of the families
studied were not registered with the social security. The parents
of cancer children under treatment reported worse financial
status where 32.3% declared their financial status is very poor
and poor, bad quality of life (22.6% vs. 3.8%; p < 0.001) and
health status than the parents in the community.
The population of children ranged in age from 4.11 (0.3%) to
13 (0.8%) years, with an average age of 8.33 years (SD = 2.31,
median = 8.0 years). 46.2% were girl. Young child (aged 5 - 7)
comprised near the half (45.4%) of the sample of children.
73.6% were in private school, and 7.6% go to school walking.
Self-reported diseases and symptoms were numerous declared
by 39.8% of children (Table 1). The oncology children present
with acute Lymphocytic leukemia (n = 31), brain tumor (n = 1),
and other cancers (n = 2).
Table 1.
Children characteristics according to urban and rural areas.
Total
n (%) Urban n (%) Rural n (%) p-value
Gender
Boy
Girl
198 (53.8)
170 (46.2)
56 (52.8)
50 (47.2)
141 (54.0)
120 (46.0)
0.83
Age group
5 - 7 years
8 - 12 years
167 (45.4)
201 (54.6)
51 (48.1)
55 (51.9)
116 (44.4)
145 (55.6)
0.52
School
Private
Public
NA
270 (73.6)
94 (25.6)
3 (0.8)
87 (82.1)
18 (17.0)
1 (0.9)
183 (70.1)
76 (29.1)
2 (0.8)
0.05
Rhinitis
Yes
No
44 (12.0)
324 (88.0)
16 (15.1)
90 (84.9)
28 (10.7)
233 (89.3)
0.24
Asthma
Yes
No
23 (6.3)
345 (93.7)
09 (8.5)
97 (91.5)
14 (5.4)
247 (94.6)
0.26
Visual disorders
Yes
No
33 (9.0)
345 (91.0)
12 (11.3)
94 (88.7)
21 (8.3)
240 (92.0)
0.32
Hearing disorders
Yes
No
11 (3.0)
357 (97.0)
07 (6.6)
99 (93.4)
04 (1.5)
257 (98.5)
0.01
Cancer
Yes
No
34 (9.2)
334 (90.8)
15 (14.2)
91(85.8)
18 (6.9)
243 (93.1)
0.03
Total 3681 (100)106 (100) 261 (100.0 )
Notes and abbreviations: NA: not applicable; 1 missing value according to envi-
ronment. Others morbidities as reported as the following: Obesity (BMI ≥ 95
percentile) 24%, epilepsy (0.9%), hyperactivity (1.5%), insomnia (0.6%), teeth
problem (0.9%), cardiac (1.2%), urinary disease (1.2%), skin disease as urticaria
(3.0%), migraine (2.4%), ENT (2.7%), and rheumatic disease and cough (0.9%)
respectively.
962

I. SABBAH ET AL.
Psychometric Properties of the PedsQLTM4.0
No-one refused to answer the questions of the Peds 4.0 (CF
& PF). The Child and Proxy questionnaires were completed
respectively in 93.8% and 93.2% of cases. There was no sig-
nificant difference between the number of missing items of self
administered questionnaires and those administered by an in-
terviewer of the child (6.5% vs. 6.2%; p = 0.46), and proxy
(6.8% vs. 6.6%; p = 0.28) report. The amount of missing data
for child and proxy questionnaire was very low, at only 0.51%
and 0.46% of all answered. In both questionnaires, the missing
data were spread evenly over the different scales with a mini-
mum of 0 and maximum 2.4%; which indicates that the ques-
tionnaire had good acceptability.
The average time of completion of the Peds Child version
was 7.8 minutes (SD = 3.33, median = 7.0). 45.8% of the child
aged 8 - 12 years self administered the questionnaire. 42.6% of
the parents’ questionnaires were self-administered and the av-
erage time of completion of the Peds proxy was 5.8 minutes
(SD = 2.61, median = 5.0).
Furthermore, 0.76% of items were considered to be confus-
ing by the child. The three most frequently quoted items were:
worry about what will happen to you (35.9%), I find difficulty
coping with other children (20.3%) and it’s hard to follow other
kids while playing with them (7.8%). Concerning the proxy
questionnaires, 9.8% of parents considered that most of items
must be reversed items (positive items), especially the physical
items. Nearly All respondents (97.8% of the children and
98.4% of the parents) accepted to fill out the questionnaire for a
second time.
The item mean, and standard deviation of the child and proxy
questionnaire tended to be comparable with few exceptions.
Factor analysis of the 23 items of the child questionnaire
yielded a four factor solution corresponding to the hypothesized
scale of health underlying the PedsQL4.0 except for the item
“hurt or ache” which loaded with emotional functioning more
than its rotated principal component. Concerning proxy ques-
tionnaire, all items loaded on the a priori dimensions except for
“hurt or ache” and “low energy” which loaded with emotional
functioning more than its specific factor, and for “cannot do
things” which loaded higher with physical functioning than its
hypothesized scale (Table 2).
Tables 3 and 4 present means, SDs of the PedsQL4.0 scores
for CF and PF for the total sample, community (general popu-
lation), and pediatric cancer sample.
Cronbach’s alpha coefficients were high for all subscales
(range 0.70 to 0.89), except the emotional scales for child
(0.64), and proxy (0.60) questionnaire. It is very high (>0.9) for
school functioning of pediatric cancer children. The reliability
coefficients are calculated only for those cases where all items
have been completed (Table 5).
Effect size is ranged from 1.0 SD units (Psychosocial Health
scale) to 2 SD units (School Functioning), and reflects substan-
tial physical and psycho morbidity. Indeed these differences are
medium (0.5 and lower) for Emotional and Social Functioning
(Table 4). The size of the confidence interval around an indi-
vidual score shows improvement and worsening based on
change of one standard error of measurement or larger (Table
5). The PedsQL 4.0 cut-off point scores for both CF and PF are
presented in Table 5.
The overall scale intercorrelations across the ages are large
(0.5 and more) indicating good agreement between child and
parent reports and, generally consistent with other PedsQL4.0
studies (Table 6).
Quality of Lif e Acco rdi ng to Habitat (Urban vs. Rur al
Area)
In the level of households, we observed a few difference be-
tween urban and rural areas especially father’s education where
we observed more illiterate and elementary level in rural area
(25.6% vs. 19.1%), and more university level in urban area
(36.0% vs. 19.6%; p < 0.05); social security affiliation (64.4%
in urban vs. 47.5% in rural area; p < 0.01) and nationality
(where most of the non Lebanese fathers are in urban areas). No
differences concerning age, gender of children according to
urban and rural areas (Table 1).
We assessed also the construct validity utilizing the known
groups. Concerning the child report, the scores of the Peds 4.0
increase with age (8 - 12 years vs. 5 - 7 years). The level of
education of mother influences the physical scales scores for
child and proxy report (p = 0.02). The global assessment of
QoL of parents was statistically significantly related to social
functioning scores of CF (p < 0.05) and physical functioning (p
≤ 0.01) of the PF. The number of children in the families was
positively associated with PedsQL total and physical domain
scores. It was also associated with higher school functioning
scores (p ≤ 0.01) in the point of view of parents. Females had
slightly higher HRQoL scores in the school functioning domain.
Children who have family (with both father and mother) have
higher emotional and social scores than children in families
where parents are divorcees or widow(er)s. After adjustment
for the other socio-demographic variables it was found that,
with the exception of the social scale (p < 0.05), the place of
residence (urban vs. rural) has no influences on either Peds
scales scores.
Concerning self-reported morbidity, there were statistically
significant differences between healthy and chronically ill chil-
dren. Children who had a health problem (asthma, rhinitis, vis-
ual disorders,) had poorer scores on 3 or more dimensions of
the PedsQL4.0 Generic Core Scales. The children with asthma,
even outside attacks, had a negative impact on the, total, physi-
cal, psychosocial and emotional functioning. In addition there
were large statistically significant differences between “healthy”
and cancer children for most subscales except the social and
emotional functioning of the child report (Table 7).
Discussion and Conclusion
The aim of our study was to adapt the PedsQLTM4.0 (CF and
PF) into Arabic for young (5 - 7 years), and children (8 - 12
years), assess its psychometric properties, and evaluate HRQOL
in urban and rural Lebanese population.
The translated version retained the properties of the original
version. The acceptability was in general very good. This rein-
forces the expected validity (face validity), confirm the absence
of problems related to translation (Sabbah et al., 2003), and
suggest that children and parents are willing and able to provide
good-quality data regarding the child’s HRQOL.
The internal consistency reliabilities generally exceeded the
recommended minimum alpha coefficient standard for group
comparison of 0.70 (Sabbah et al., 2003; Varni et al., 2003;
Ware, 1997; Nunnally et al., 1994). Indeed, Ware (1997), con-
idered the reliability of 0.5 or above is acceptable. However, s

I. SABBAH ET AL.
964
Table 2.
Items mean (SD), and principal component analysis with varimax rotation of the PedsQL4.0 for child self-reports and parent proxy-report.
Child report Proxy report
Rotated principal component1 Rotated principal component1
Item
Items mean (SD)
Physical EmotionalSchoolSocial
Items mean (SD)
Physical Emotional SchoolSocial
Walk 88.3 (24.7) 0.72 0.12 82.0 (29.1) 0.77 0.16 0.17
Run 81.5 (30.9) 0.75 0.20 79.6 (31.5) 0.82 0.20 0.13
Do sports 84.4 (28.6) 0.76 0.19 79.4 (31.6) 0.78 0.17 0.11
Lift som ething heavy 60.0 (34.4) 0.53 0.18 64.9 (33.0) 0.45 0.28 0.14
Take a bath 75.1 (37.1) 0.56 0.16 0.13 72.6 (37.9) 0.47
Do chores 72.9 (33.0) 0.43 0.14 0.17 68.8 (34.3) 0.53 0.12 0.17
Hurt or ache 76.2 (31.4) 0.28 0.49 79.6 (26.5) 0.26 0.45 0.13
Low energy 75.8 (28.8) 0.46 0.43 0.24 80.7 (26.7) 0.32 0.56 0.21 0.13
Feel afraid 66.6 (32.2) 0.55 65.2 (30.4) 0.47 −0.210.18
Feel sad 70.0 (28.9) 0.73 69.9 (28.9) 0.63 0.18
Feel angry 55.3 (32.0) 0.47 0.25 0.21 54.6 (30.4) 0.52 0.12 0.13
Trouble sleeping 85.0 (26.9) 0.58 84.4 (25.3) 0.54
Worry 78.2 (31.3) 0.15 0.60 0.20 80.1 (30.2) 0.10 0.54
Trouble getting along
with other 83.9 (28.4) 0.16 0.64 84.7 (26.5) 0.22 0.10 0.17 0.69
Kids do not w ant to be
my friend 85.0 (27.4) 0.10 0.13 0.75 89.8 (22.2) 0.14 0.13 0.76
Kids tease me 85.4 (25.4) 0.35 0.58 89.9 (20.4) −0.15 0.22 0.13 0.67
Cannot do things 83.9 (27.2) 0.36 0.29 0.28 0.37 87.7 (23.7) 0.43 0.34 0.24 0.36
Hard to keep up when I play 83.3 (27.8) 0.35 0.11 0.20 0.50 84.8 (25.7) 0.43 0.14 0.55
Hard to pay atten tion in
class 79.8 (29.8) 0.77 0.12 79.4 (29.4) 0.15 0.82 0.17
forget things 74.1 (27.9) 0.21 0.56 0.20 75.8 (27.4) 0.72 0.25
Trouble keeping up with my
schoolwork 78.4 (30.7) 0.16 0.75 0.16 79.9 (29.9) 0.24 0.79 0.20
Miss school because of not
feeling well 76.5 (30.9) 0.22 0.19 0.67 81.2 (28.1) 0.11 0.46 0.60
Miss school to go to the
doctor 67.4 (31.8) 0.33 0.17 0.50 72.2 (29.9) 0.22 0.48 0.44
Notes and abbreviations: Strong association (r > 0.70); moderate association (0.30 < r < 0.70); weak association (r < 0.30). 1Correlation between each item and rotated
principal component. Blanks in the table indicate low correlations (<0.10). The percentage of measured variance explained by these four factors for child report is 44.75%;
The first component explain 13.95%, second (11.31%), third (11.04%) and the fourth (8.45%); The percentage of measured variance explained by these four factors for
proxy report is 48.4%: The first component explains 14.7%, second (12.2%), third (11.9%) and the fourth (9.6%).
according to Varni and al. (2002), the emotional, and social
subscales (α < 0.70) may be utilized with a caveat until further
testing is conducted, and then should be used only for descrip-
tive or exploratory analyses. In our study the quality of life of
children is deteriorated, especially the emotional functioning
scale score, where most children feel afraid, sad, and angry.
The responses did not differ from fixed responses, which could
negatively bias the Cronbach’s α (Fong et al., 2010).
The presence of a relation between the dimensions of Peds
4.0 and the sociodemographic and clinical parameters is an
important finding as such instruments could be used in thera-
peutic evaluations (Upton et al., 2005; Ware, 1997; Dean et al.,
2010). Our results are in contrast with other results that have
failed to observe gender differences (Varni et al., 2007; Varni et
al., 2003) or found fewer negative associations (Reinfjell et al.,
2006; Villalonga-Olives et al., 2010). This finding might be
explained by changes in the traditional gender differences of
coping with life events in childhood, modifications in social
resources, and gender role expectations in the millennium
(Villalonga-Olives et al., 2010). he education of mother, fam- T

I. SABBAH ET AL.
Table 3.
Description of scales scores of the PedsQL4.0 for child self-report and parent proxy-report.
All Lebanese sample (n = 368) Young child (5 - 7 years) (n = 167) C hil d 8 - 12 years (n = 201)
Scale Mean (SD) % Floor/Ceiling Mean (SD) % Floor/Ceiling Mean (SD) % Floor/Ceiling
Child self-repor t (n = 368)
Total score 76.7 (14.2) 0.0/0.0 74.0 (13.4) 0.0/0.0 78.9 (14.5) 0.0/0.0
Physical healt h 76.7 (19.0) 0.3/6.5 73.1 (19.3) 0.0/4.2 79.7 (18.3) 0.5/8.5
Psychosoc ial he alt h 76.7 (14.7) 0.0/0.8 74.6 (14.2) 0.0/1.2 78.4 (15.0) 0.0/0.5
Emotional fu nc tio nin g 70.8 (19.3) 0.0/6.5 70.0 (19.8) 0.0/11.4 71.6 (18.8) 0.0/2.5
Social functioning 84.2 (17.7) 0.0/32.1 81.3 (18.5) 0.0/27.5 86.6 (16.7) 0.0/35.8
School functioning 4 74.9 (21.5) 2.2/11.5 72.1 (22.6) 3.0/11.5 77.3 (20.3) 1.5/11.6
Proxy-re port (n = 36 6)
Total score 77.6 (14.4) 0.0/0.8 76.6 (14.0) 0.0/0.0 78.4 (14.8) 0.0/1.5
Physical healt h 76.1 (19.9) 0.5/9.3 74.0 (18.8) 0.6/7.2 77.9 (20.6)ǂ 0.5/11.1
Psychosoc ial he alt h 78.4 (14.2) 0.0/1.4 78.1 (14.3) 0.0/0.0 78.8 (14.2) 0.0/2.5
Emotional fu nc tio nin g 70.9 (18.0) 0.0/4.9 70.8 (17.5) 0.0/4.8 70.9 (18.4) 0.0/5.0
Social functioning 87.1 (17.1) 0.3/40.7 85.9 (18.4) 0.6/38.3 88.1 (15.8) 0.0/42.7
School functioning 77.4 (21.6) 2.5/13.2 77.4 (22.4) 3.0/13.9 77.5 (21.0) 2.0/12.6
Table 4.
Descriptive and effect size of the PedsQL4.0 scales child self-report and parent proxy-report: Healthy and cancer children sample.
Cancer child Healthy child (Did not have cancer)
n Mean SD n Mean SD Difference Effect size† T scores p-value*
Child self-report
Total score 34 62.2 20.5 334 78.2 12. 6 15.9 1.27 −6.6 <0.001
Physical healt h 34 58.6 26.9 334 78. 6 17.0 19.9 1.17 −6.1 <0.001
Psychosoc ial he alt h 34 64.3 20.9 334 77.9 13.4 13.7 1.00 −5.3 <0.001
Emotional fu nc tio nin g 34 63.7 26.4 334 71.6 18.3 7.9 0.43 −2.3 0.02
Social functioning 34 80.9 21.0 334 84.5 17.3 3.6 0.21 −1.1 0.25
School functioning 30 44.2 32.9 334 77.7 17.8 33.4 1.87 −9.0 <0.001
Parent proxy-report
Total score 32 58.7 19.5 334 79.4 12.5 20.7 1.66 −8.5 <0.001
Physical healt h 32 51.6 28.5 334 78.5 18.1 26.9 1.49 −7.9 <0.001
Psychosoc ial he alt h 32 62.8 19.1 334 80.0 12.7 17.2 1.35 −7.0 <0.001
Emotional fu nc tio nin g 32 60.8 21.3 334 71.8 17.3 11.1 0.64 −3.4 <0.001
Social functioning 32 78.8 23.0 334 87.9 16.2 9.0 0.56 −2.9 <0.01
School functioning 29 45.9 35.0 334 80.2 17.6 34.3 1.95 −9.1 <0.001
Note: *p-value statistical significance. †Effect sizes are designated as small (0.20), medium (0.50), and large (0.80). Effect size was calculated by taking the difference
between the healthy sample mean and the sample with health conditions mean, divided by the healthy sample standard deviation.

I. SABBAH ET AL.
Table 5.
PedsQLTM4.0 generic core scales internal consistency reliability by age group and minimal clinically important difference (SEM) for child self-report
and parent proxy-report Lebanese sample.
Chronbach alpha (n) Cut-off point scores
>1 SD* of the total sample
Scale Total sample Young ch ild 5 - 7 Child 8 - 12
SEM of the
total sam ple Cut off n (%)
Self-report
Total score 0.84 (348) 0.80 (159) 0.86 (189) 5.70 62.48 57 (15.5)
Physical healt h 0.76 (363) 0.73 (165) 0.80 (198) 9.25 57.72 55 (14.9)
Psychosoc ial he alt h 0.78 (351) 0.73 (159) 0.81 (192) 6.90 61.94 62 (16.8)
Emotional fu nc tio nin g 0.64 (363) 0.62 (164) 0.66 (199) 11.56 51.58 70 (19.0)
Social functioning 0.66 (364) 0.63 (167) 0.68 (197) 10.36 66.50 58 (15.8)
School functioning 0.73 (358) 0.72 (161) 0.74 (197) 11.15 53.39 52 (14.3)
Proxy-report
Total score 0.86 (342) 0.84 (158) 0.87 (184) 5.48 63.19 49 (13.4)
Physical healt h 0.79 (357) 0.75 (163) 0.83 (194) 9.07 56.23 47 (12.8)
Psychosoc ial he alt h 0.79 (350) 0.78 (162) 0.80 (188) 6.44 64.25 54 (14.8)
Emotional fu nc tio nin g 0.60 (366) 0.59 (167) 0.61 (199) 7.20 52.9 62 (16.9)
Social functioning 0.73 (357) 0.76 (164) 0.70 (193) 8.91 69.99 47 (12.8)
School functioning 0.79 (359) 0.82 (165) 0.76 (194) 9.93 55.8 54 (14.9)
Note: *SEM indicates Standard Error of Measurement and was derived by multiplying the standard deviation by the square root of (1-Cronbach alpha reliability coefficient).
The PedsQL4.0 scores in the column represent the transformed value of 1 SEM. For example, a change in PedsQL4.0 Total Scale Score for child self-report of 5.70 repre-
sents a minimal clinically important difference [18]. *1 SD (standard deviation) demonstrates the scores that fall 1 SD below the population sample mean and represent an
at- risk status for impaired health-related quality of life.
Table 6.
Spearman correlation coefficients between PedsQL4.0 scales for child
self-report parent proxy-report.
Scale Total
(5 - 12 year s) Young child Child (8 - 12 year s)
Total score 0.69** 0.63** 0.73**
Physical healt h 0.61** 0.53** 0.67**
Psychosoc ial he alt h 0.66** 0.63** 0.70**
Emotional fu nc tio nin g 0.51** 0.48** 0.53**
Social functioning 0.51** 0.42** 0.59**
School functioning 0.66** 0.67** 0.67**
Notes and Abbreviations: **All correlations are significant at the P, 0.01 levels
(2-tailed). Effect sizes are designated as small (0.10), medium (0.30), and large
(0.50).
ily situation of parents and the perception of the QoL of parents
influence the quality of life of their children. This is in concor-
dance with previous study in Lebanon using SF-36 (Sabbah et
al., 2003). Prior research has shown that the family members
influence each other mutually (Hatzmann et al., 2009; Pane-
pinto et al., 2009; Duhamel, 2007), therefore, the family with
children who have a chronic disease may have greater family
burden, and need social support (Hatzmann et al., 2009; Pane-
pinto et al., 2009). As has been reported in several studies
(Dean et al., 2010; Abdel Hai, Taher, & Fattah, 2010; Farnik et
al., 2010), it is well established that children with chronic con-
ditions have significant impairments in HRQoL. As expected,
self-reported scores for overall HRQOL of cancer children were
more impaired than those of healthy children (Eiser, Eiser, &
Stride, 2005; Sung et al., 2009; Sandeberg, Johansson, Hagell,
& Wettergren, 2010; Varni, Limbers, & Burwinkle, 2007).
School functioning was most impacted by chronic health condi-
tions, as reflected by the higher rates of school absences (Dean
et al., 2010), and quit of school. It should be noted that 11.6%
of Lebanese pediatric cancer were outside the school and at risk
to be illiterate people.
The PedsQL4.0 scales scores of Lebanese children were
lower than those of US (Varni et al., 2003), and UK (Upton et
al., 2005) children. This was also observed for Lebanese people
aged 14 year and more using the SF-36 Health survey (Sabbah
et al., 2003), which could be due to factors such as stress, mor-
bidity of the parents (Duhamel, 2007), war status, lack of health
coverage (Sabbah et al., 2007), lack of public green spaces
(Costa, Vescina, & Barcellos Pinheiro, 2010), and comorbidities
(Sabbah et al., 2003; Varni et al., 2003; Upton et al., 2005).
Additionally, the physical functioning of children is low. It may
be related to their autonomic behavior e.g. parents consider that
most children are incapable to take a bath alone. This in part
may also be explained by the high number of servants in
households (Bureau Centrale de la statistique au Liban, 2006).
The social scale scores are high in general population and in ill
hildren (effect ceiling). This is related to the oriental culture c
966

I. SABBAH ET AL.
Table 7.
Influence of habitat on the Peds scale scores: Multivariate analysis results (generalized linear model).
Child self-report
Total score P hysic al healthP syc hosocial healthEmotional functioningSocial functioning School
functioning
Gender
−5.4
[−9.40 - −1.36]**
Age −4.1
[−7.44 - −0.84]***
−6.9
[−11.43 - −2.47]** −0.3 [−5.18 - 4.62]ǂ:
−5.2
[−9.67 - −0.72]***
Habitat (urban /rural) −3.7
[−7.82 - 0.42]ǂ:
−5.2
[−9.32- −1.09]***
School (private/public) 2.5
[−2.32 - 7.33]
4.9
[0.09 - 9.74]***
5.2
[−0.06 - 10.53]***
# child 1.1
[0.20 - 1.98]***
1.9
[0.66 - 3.08]**
Mother’s education
(secondary and low-
est/university) −6.2
[−11.70 - −0.80]**
Parents’ marital status
(married/divorced, widow)
10.3
[−0.10 - 20.73]*** 15.3 [2.24 - 28.94]***
11.9
[−2.38 - 26.22]ǂ:
QoL perception
Asthma −6.9
[−12.55 - −1.31]**
−10.2
[−17.82 - −2.57]**
−5.2
[−11.28 - 0.91]ǂ
−12.2
[−20.57 - 3.90]**
−6.7
[−14.29 - 0.94]ǂ
Rhinitis −4.9
[−9.12 - −0.68]*** −5.9 [−10.47 - −1.32]**
−11.0
[−17.21 - −4.69]*
Visual disorder −6.0
[−10.92 - −1.11]**
−7.0
[−13.65 - −0.34]***
−5.5
[−10.79 - −0.15]*** −6.9 [−13.55 - −0.24]***
Cancer (yes /.no) −15.8
[−21.30 - −10.29]*
−18.6
[−26.11 - −11.18]*
−14.3
[−20.23 - −8.30]*
−9.6
[−17.81 - −1.49]*** −33.5 [−41.69 - −25.30]*
Self reported
questionnaire (Y/N) 4.2
[0.43 - 7.95]*** 4.7 [0.63 - 8.79]**
10.5
[−1.94 - 22.91]ǂ: 6.7 [1.09 - 12.29]***
R square 0.248 0.236 0.188 0.117 0.124 0.291
Parent proxy-re port
Gender
−5.9
[−9.99 - 1.82]**
Age −3.40
[−6.20 - −0.60]***
−6.8
[−10.67 - −2.83]**
−3.7
[−7.31 - 0.10]***
0.2
[−4.05 - 4.34]ǂ:
habitat
School 3.3
[−0.42 - 6.94]ǂ:
7.4
[1.99 - 12.88]**
# child 0.98
[0.08 - 1.88]*** 0.95 [0.09 - 1.92]***
1.6
[0.27 - 2.98]***
Mother’s education
(secondary and lowest/university)
−4.50
[−8.63 - −0.37]***
−8.6
[−14.39 - −2.82]**
−0.5
[−6.75 - 5.66]ǂ:
Parents’ marital status
(Married/Divorced, Widow)
9.13
[-0.67- 18.93]ǂ: 14.5 [4.55 - 24.47]** 24.0 [11.34 - 36.61]*
17.3
[2.53 - 32.00]***
QoL perception −7.95
[−14.98 - −0.93]***
−15.2
[−25.03 - −5.34]** −8.7
[−18.35 - 0.98] ǂ:
Poor Mild high −1.2
[−4.73 - 2.24]1***
−1.5
[−6.34 - 3.42]1 −1.9 [−6.69 - 2.87] 1
Asthma −7.7
[−13.36 - 1.96]**
−8.4
[−16.40 - 0.42]***
−7.2
[−13.01 - 1.42]**
−14.1
[−21.91 - −6.26]*
Rhinitis
−5.0
[−10.84 - 0.90]ǂ
Visual disorder
Cancer −19.8
[−25.49 - −14.15]*
−24.7
[−32.67 - −16.78]*
−17.2
[−22.94 - −11.42]*
−9.1
[−16.83 - −1.28]***
−7.6
[−14.95 - −0.34]***
−35.4
[−43.93 - −26.89]*
Self-reported questionnaire
R square 0.263 0.242 0.221 0.129 0.137 0.264
Notes and abbreviations: (Y/N) = Yes/No; obesity was excluded because high rate of missing value (17.1%). Profession was excluded because high association with social
security status. *p < 0.001; **p < 0.01; ***p < 0.05; ǂp: 0.05 - 0.10; blanks in table indicate a non-significant GLM for the all scale in that test. No statistically significant
relationship established between Education of father, Mother’s Job , Social Security coverage, Financial status, Hearing disorder and all scales scores of the Peds 4.0 self
report and proxy report, then excluded from the table.

I. SABBAH ET AL.
where relationships are very close especially in case of an ill-
ness. It was also observed for Lebanese SF-36 social scores
(Sabbah et al., 2003). A minor difference between urban and
rural areas is also observed for the different scales scores of the
SF-36 in Lebanon (Sabbah et al., 2003), and for the morbidity
(Sabbah et al., 2007). These findings confirm the demographic
and epidemiological transition phenomenon occurred in Leba-
non (Sabbah et al., 2003). This is in contrast with the Turkish
population where Oguzturk (2008) found that both socio-eco-
nomic status and quality of life were poorer in rural areas.
The strength of the present study is that it is representative of
the general population, thus able to make inferences based on
the available observations (Villalonga-Olives et al., 2010).
There are some limitations in the present study. It is limited to
South Lebanon, because of a lack of resources. To continue the
validation, it is necessary to include an assessment of its re-
sponsiveness to change of the group over time. Self-reporting
of diseases as a measurement of health status also presents
some limitations (Sabbah et al., 2003). Some HRQOL scales
were skewed, which is to be expected in a general population.
However, the parametric techniques that were applied are quite
robust, and have been demonstrated to be adequate in analyzing
skewed data if sample size is large enough (Verrips et al., 1999).
The PedsQL Total Score reliability coefficients were calculated
only for those cases where all items have been completed
(Ware, 1997). An algorithm must be recommended to substitute
a personspecific estimate for any missing item when the re-
spondent answered at least 50 percent of the items in a scale,
then it is possible to derive scale scores for nearly all respon-
dents across the PedsQL4.0 scales (Ware, 1997). Finally, the
absence of a generic valid reference instrument in Arabic in
Lebanon remains a major obstacle for the establishment of
concurrent validity as well as predictive validity.
In conclusion, the study supports the acceptability, reliability,
and validity of the PedsQL4.0 Generic Core Scales as a child
self-report and parent proxy-report HRQOL measurement in-
strument for pediatric population health in Arabic Lebanon.
Further psychometric evaluation in a large sample of children,
in other departments of Lebanon is recommended to provide
firmer conclusions.
Acknowledgements
The authors wish to acknowledge the help and support of the
team of the Mapi Research Trust Institute, and Mr. James W.
Varni. We are grateful to the subjects who participated in this
survey, to F. Badran for her help with translation and advice on
the manuscript, to A. Badran, M. A. Sabbah for their help with
the translation of the PedsQLTM4.0. I would also like to thank
the interviewers who helped to carry out this study.
REFERENCES
Abdel Hai, R., Taher, E., & Fattah, M. A. (2010). Assessing validity of
the adapted Arabic Paediatric Asthma quality of life questionnaire
among Egyptian children with asthma. Eastern Mediterranean
Health Journal, 16, 274-280.
Bek, N., Simsek, E., Erel, S., Yakut, Y., & Uygur, F. (2009). Turkish
version of impact on family scale: A study of reliability and validity.
Health and Quality of Life Outcomes, 7, 7 pp.
doi:10.1186/1477-7525-7-4
Berkes, A., Pataki, I., Kiss, M., Kemény, C., Kardos, L., Varni, J. W.,
& Mogyorósy, G. (2010). Measuring health-related quality of life in
Hungarian children with heart disease: Psychometric properties of
the Hungarian version of the pediatric quality of life inventory TM
4.0 generic core scales and the cardiac module. Health and Quality of
Life Outcomes, 8, 12p. doi:10.1186/1477-7525-8-14
Bollinger, M., Power, M. J., Aaronson, N. K., Cella, D. F., & Anderson
R. T. (1996). Creating and evaluating cross-cultual instruments. In: B.
Spilker (Ed.), Quality of Life and Pharmacoeconomics in Clinical
Trials (2nd ed., pp. 659-668). PA: Lippincott-Raven Publishers.
Bureau Centrale de la Statistique au Liban (2006). Annuaire, 15-23.
http://www.localiban.org/IMG/pdf/La_Structure_Demographique_Li
banaise.pdf
Chan, K. S., Mangione-Smith, R., Burwinkle, T. M., Rosen, M., &
Varni, J. W. (2005). The PedsQLTM: Reliability and validity of the
short-form generic core scales and asthma module. Medical Care, 43,
256-265. doi:10.1097/00005650-200503000-00008
Sarah E. B. (2007). Expert committee recommendations regarding the
prevention, assessment, and treatment of child and adolescent over-
weight and obesity: Summary report. Pediatrics, 120, s164-s192.
doi:10.1542/peds.2007-2329C
Costa, S. A. L. M., Vescina, L., & Barcellos Pinheiro, M. D. (2010).
Environmental restoration of urban rivers in the metropolitan region
of Rio de Janeiro, Brazil. Environment Urban/Urban Environment, 4,
a13-a26. http://www.vrm.ca/cyber_pub.asp?
Cronbach, L. J. (1951). Coefficient alpha and the internal structure of
tests. Psychometrika, 16, 297-334. doi:10.1007/BF02310555
Dean, B. B., Calimlim, B. C., Sacco, P., Aguilar, D., Maykut, R., &
Tinkelman, D. (2010). Uncontrolled asthma: Assessing quality of life
and productivity of children and their caregivers using a cross-sec-
tional internet-based survey. Health and Quality of Life Outcomes, 8,
10. doi:10.1186/1477-7525-8-96
Duhamel F. (2007). La relation entre la problématique de santé et la
famille. In F. Duhamel (Ed.), Gaeten Morin Editeur la Santé et la
Famille une Approche Systémique en Soins Infirmiers (pp. 3-22).
Gaëtan Morin éditeur, CA: Chenelière education.
Eiser, C., Eiser, J. R., & Stride, C. B. (2005). Quality of life in children
newly diagnosed with cancer and their mothers. Health and Quality
of Life Outcomes, 3, 5 pp. doi:10.1186/1477-7525-3-29
Eshaghi, S.-R., Ramezani, M. A., Shahsanaee, A., & Pooya, A. (2006).
Validity and reliability of the short form—36 items questionnaire as
a measure of quality of life in elderly Iranian population. American
Journal of Applied Sciences, 3, 1763-1766.
Estrada, M.-D., Rajmil, L., Serra-Sutton, V., Tebe, C., Alonso, J.,
Herdman, M., & Starfield, B. (2010). Reliability and validity of the
Spanish version of the child health and illness profile (CHIP)
child-edition, parent report form (CHIP-CE/PRF). Health and Qual-
ity of Life Outcomes, 8, 9 pp. doi:10.1186/1477-7525-8-78
Farnik, M., Brozek, G., Pierzchala, W., Zejda, J. E., Skrzypek, M., &
Walczak, L. (2010). Development, evaluation and validation of a
new instrument for measurement quality of life in the parents of
children with chronic disease. Health and Quality of Life Outcomes,
8, 9 pp. doi:10.1186/1477-7525-8-151
Fong, D. Y. T., Ho, S., & Lam, T. (2010). Evaluation of internal reli-
ability in the presence of inconsistent responses. Health and Quality
of Life Outcomes, 8. doi:10.1186/1477-7525-8-27
Giampietro, O., Virgone, E., Carneglia, L., Griesi, E., Calvi, D., &
Matteucci, E. (2002). Anthropometric indices of school children and
familiar risk factors. Preventive Medicine, 35, 492-498.
http://www.sciencedirect.com/science.
doi:10.1006/pmed.2002.1098
Giannakopoulos, G., Dimitrakaki, C., Pedeli, X., Kolaitis, G., Rotsika,
V., Ravens-Sieberer, U., & Tountas Y. (2009). Adolescents’ wellbe-
ing and functioning: Relationships with parents’ subjective general
physical and mental health. Health and Quality of Life Outcomes, 7,
9 pp. doi:10.1186/1477-7525-7-100
Gkoltsiou, K., Dimitrakaki, C., Tzavara, C., Papaevangelou, V., Varni,
J. W., & Tountas, Y. (2008). Measuring health-related quality of life
in Greek children: Psychometric properties of the Greek version of
the pediatric quality of life inventoryTM 4.0 generic core scales.
Quality of Life Research, 17, 299-305.
doi:10.1007/s11136-007-9294-1
968

I. SABBAH ET AL.
Harrison, M. J., Lunt, M., Verstappen, S. M. M., Watson, K. D., Bans-
back, N. J., & Symmons, D. P. M. (2010). Exploring the validity of
estimating EQ-5D and SF-6D utility values from the health assess-
ment questionnaire in patients with inflammatory arthritis. Health
and Quality of Life Outcomes, 8, 8 pp.
doi:10.1186/1477-7525-8-21
Hatzmann, J., Maurice-Stam, H., Heymans, H. S. A., & Grootenhuis, M.
A. (2009). A predictive model of health related quality of life of
parents of chronically ill children: The importance of care-depend-
ency of their child and their support system. Health and Quality of
Life Outcomes, 7.
doi:10.1186/1477-7525-7-72
MAPI Institute. Questionnaires and Translations.
http://www.mapi-institute.com/questionnaires-and-translation.
Matza, L. S., Swensen, A. R, Flood, E. M, Secnik, K., & Leidy, N. K.
(2004). Assessment of health-related quality of life in children: A re-
view of conceptual, methodological, and regulatory issues. Value in
Health, 7, 79-92. doi:10.1111/j.1524-4733.2004.71273.x
Mistry, R. D., Stevens, M. W., & Gorelick, M. H. (2009). Health-related
quality of life for pediatric emergency department febrile illnesses:
An evaluation of the pediatric quality of life inventory™ 4.0 generic
core scales. Health and Quality of Life Outcomes, 7, 9 pp.
doi:10.1186/1477-7525-7-5
Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric Theory (3rd ed.).
New York: McGraw-Hill.
Oguzturk, O. (2008). Differences in quality of life in rural and urban
populations. Clinical and Investigative Medicine, 31, E346-E350.
Panepinto, J. A., Hoffmann, R. G., & Pajewski, N. M (2009). A psy-
chometric evaluation of the PedsQLTM family impact module in par-
ents of children with sickle cell disease. Health and Quality of Life
Outcomes, 7, 11p. http://www.hqlo.com/content/7/1/32.
doi:10.1186/1477-7525-7-32
Reinfjell, T., Diseth, T. H., Veenstra, M., & Vikan, A. (2006). Measur-
ing health-related quality of life in young adolescents: Reliability and
validity in the Norwegian version of the Pediatric Quality of Life In-
ventory™ 4.0 (PedsQL) generic core scales. Health and Quality of
Life Outcomes, 4, 9 pp. doi:10.1186/1477-7525-4-61
Rumeau-Rouquette, C., Blondel, B., Kaminski, M., et al. (1993). Epidé-
miologie Méthodes et Pratique. Paris: Flammarion Medecine Sciences.
Sabbah, I., Drouby, N., Sabbah, S., Retel-Rude, N., & Mercier, M.
(2003). Quality of life in rural and urban populations in Lebanon us-
ing SF-36 health survey. Health and Quality of Life Outcomes, 1,
14p. http://www.hqlo.com/content/1/1/30.
doi:10.1186/1477-7525-1-30
Sabbah, I., Vuitton, D.-A., Droubi, N., Sabbah, S., & Mercier, M.
(2007). Morbidity and associated factors in rural and urban popula-
tions of South Lebanon: A cross-sectional community-based study of
self-reported health in 2000. Tropical Medicine and International
Health, 12, 907-919.
doi:10.1111/j.1365-3156.2007.01886.x
Sandeberg, M. af., Johansson, E. M., Hagell, P., & Wettergren, L.
(2010). Psychometric properties of the DISABKIDS chronic generic
module (DCGM-37) when used in children undergoing treatment for
cancer. Health and Quality of Life Outcomes, 8, 7.
doi:10.1186/1477-7525-8-109
Sato, I., Higuchi, A., Yanagisawa, T., Mukasa, A., Ida, K., Sawamura,
Y., Kamibeppu, K. (2010). Development of the Japanese version of
the pediatric quality of life inventory™ brain tumor module. Health
and Quality of Life Outcomes, 8, 14 pp.
doi:10.1186/1477-7525-8-38
Schmidt, A., Wenninger, K., Niemann, N., Wahn, U., & Staab D.
(2009). Health-related quality of life in children with cystic fibrosis:
Validation of the German CFQ-R. Health and Quality of Life Out-
comes, 7, 10 pp. doi:10.1186/1477-7525-7-97
Solans, M., Pane, S., Estrada, M.-D., Serra-Sutton, V., Berra, S.,
Herdman, M., Alonso, J., & Rajmil, L. (2008). Health-related quality
of life measurement in children and adolescents:A systematic review
of generic and disease-specific instruments. Value in Health, 11,
742-764. doi:10.1111/j.1524-4733.2007.00293.x
Stevanovic, D. (2009). Serbian KINDL questionnaire for quality of life
assessments in healthy children and adolescents: Reproducibility and
construct validity. Health and Quality of Life Outcomes, 7, 7.
doi:10.1186/1477-7525-7-79
Sung, L., Klaassen, R. J., Dix, D., Pritchard, S.,Yanofsky, R., Dzol-
ganovski, B., & Klassen, A. (2009). Identification of paediatric can-
cer patients with poor quality of life. British Journal of Cancer, 100,
82-88. doi:10.1038/sj.bjc.6604826
Tarride, J.-E., Burke, N., Bischof, M., Hopkins, R. B., Goeree, L.,
Campbell, K., & Goeree, R. (2010). A review of health utilities
across conditions common in paediatric and adult populations.
Health and Quality of Life Outcomes, 8, 11 pp.
doi:10.1186/1477-7525-8-12
Torres, C. S., Paiva, S. M., Vale, M. P., Pordeus, I. A., Ramos-Jorge, M.
L., Oliveira, A. C., & Allison, P. J. (2009). Psychometric properties
of the Brazilian version of the child perceptions questionnaire
(CPQ11-14)—Short forms. Health and Quality of Life Outcomes, 7,
7. doi:10.1186/1477-7525-7-43
Upton, P., Eiser, C., Cheung, I., Hutchings, H. A., Jenney, M., Mad-
docks, A., Russell, I. T., & Williams J. G. (2005). Measurement
properties of the UK English version of the pediatric quality of life
inventory 4.0 (PedsQL) generic core scales. Health and Quality of
Life Outcomes, 3, 7 pp. doi:10.1186/1477-7525-3-22
Vanderbilt University, Department of Biostatistics (2009). PS: Power
and Sample Size Calculation.
http://biostat.mc.vanderbilt.edu/wiki/Main/PowerSampleSize.
Varni, J. W. (1998-2012). The PedsQLTM: Measurement model for the
pediatric quality of life inventoryTM. Peds MetricsTM Qualifying the
QualitativeSM. http://www.pedsql.org
Varni, J. W. et al. (1999). The PedsQLTM: Measurement model for the
pediatric quality of life inventory. Medical Care, 37, 126-139.
doi:10.1097/00005650-199902000-00003
Varni, J. W. et al. (2001). The PedsQLTM4.0: Reliability and validity of
the pediatric quality of life inventoryTM version 4.0 generic core
scales in healthy and patient populations. Medical Care, 39, 800-812.
doi:10.1097/00005650-200108000-00006
Varni, J. W. et al. (2002). The PedsQLTM4.0 generic core scales: Sensi-
tivity, responsiveness, and impact on clinical decision-making.
Journal of Behavioral Medicine, 25, 175-193.
doi:10.1023/A:1014836921812
Varni, J. W., Burwinkle, T. M., Katz, E. R., Meeske, K., & Dickinson,
P. (2002). The PedsQLTM in pediatric cancer reliability and validity
of the pediatric quality of life inventory™ generic core scales, multi-
dimensional fatigue scale, and cancer module. Cancer, 94, 2090-
2106. doi:10.1002/cncr.10428
Varni, J. W., Burwinkle, T. M., Seid, M., & Skarr, D. (2003). The
PedsQL4.0 as a pediatric population health measure: Feasibility, re-
liability, and validity. Ambulatory Pediatrics, 3, 329-341.
doi:10.1367/1539-4409(2003)003<0329:TPAAPP>2.0.CO;2
Varni, J. W., Burwinkle, T. M., & Lane, M. M. (2005). Health-related
quality of life measurement in pediatric clinical practice: An ap-
praisal and precept for future research and application. Health and
Quality of Life Outcomes, 3, 9. doi:10.1186/1477-7525-3-34
Varni, J. W., & Burwinkle, T. M. (2006). The PedsQLTM as a pa-
tient-reported outcome in children and adolescents with Attention-
Deficit/Hyperactivity Disorder: A population-based study. Health and
Quality of Life Outcomes, 4, 10 pp. doi:10.1186/1477-7525-4-26
Varni, J. W, Limbers, C., & Burwinkle, T. M. (2007). Literature review:
Health-related quality of life measurement in pediatric oncology:
Hearing the voices of the children. Journal of Pediatric Psychology,
32, 1-13. doi:10.1093/jpepsy/jsm008
Varni, J. W., & Limbers, C. A. (2009). The PedsQLTM4.0 generic core
scales young adult version: Feasibility, reliability and validity in a
university student population. Journal of Health Psychology, 14,
611-622. doi:10.1177/1359105309103580
Verrips, E. G. H, Vogels, T. G. C., Koopman, H. M, Theunissen, N. C.
M, Kamphuis, R. P., Fekkes, M, Wit, J. M., & Verloove-Vanhorick,
P. S. (1999). Measuring health-related quality of life in a child popu-
lation. International Child Health, 9, 188-193.
http://eurpub.oxfordjournals.org/content/9/3/188.full.pdf.
Villalonga-Olives, E., Rojas-Farreras, S., Vilagut, G., Palacio-Vieira, J.

I. SABBAH ET AL.
970
A., Valderas, J., & Herdman, M. (2010). Impact of recent life events
on the health related quality of life of adolescents and youths: The
role of gender and life events typologies in a follow-up study. Health
and Quality of Life Outcomes, 8, 9 pp. doi:10.1186/1477-7525-8-71.
Ware, J. E. Jr. (1997). SF-36 health survey manuel and interpretation
guide. Second printing. Boston, MA: The Health Institute, New
England Center.
World Health Organization (1993). The International Statistical Classi-
fication of Diseases and Related Health Problems (10th revision).
Geneva, Europe: World Health Organization.