Qual Life Res (2007) 16:1239–1249 DOI 10.1007/s11136-007-9230-4
Reliability and validity of the Pediatric Quality of Life InventoryTM (PedsQLTM) Short Form 15 Generic Core Scales in Japan Xiaoli Chen Æ Hideki Origasa Æ Fukiko Ichida Æ Keiko Kamibeppu Æ James W. Varni
Received: 4 January 2007 / Accepted: 24 May 2007 / Published online: 7 July 2007 Springer Science+Business Media B.V. 2007
Abstract Objective To assess the reliability and validity of the Japanese translation version of the Pediatric Quality of Life InventoryTM 4.0 Short Form 15 (PedsQLTM 4.0 SF15). Methods The PedsQLTM 4.0 SF15 was administered to 229 schoolchildren aged 6–13 years and 100 pediatric outpatients aged 5–18 years and their parents. Results Internal consistency reliability exceeded 0.70 for both proxy-reported and self-reported scales. Test–retest reliability demonstrated large values for parent proxy-report (range: 0.68–0.79) and moderate to large values for child self-report (range: 0.46–0.73). Parent proxy-report
X. Chen H. Origasa Faculty of Medicine, Division of Biostatistics and Clinical Epidemiology, University of Toyama, Toyama, Japan F. Ichida Faculty of Medicine, Department of Pediatrics, University of Toyama, Toyama, Japan K. Kamibeppu Faculty of Medicine, Department of Family Nursing, University of Tokyo, Tokyo, Japan J. W. Varni Department of Pediatrics, College of Medicine, Texas A&M University, College Station, Texas, USA
health-related quality of life (HRQOL) was higher than child self-report in all scales except for School Functioning. The correlations between the reports of the parents and children were moderate to high. Gender differences were observed in Social Functioning, School Functioning, and Psychosocial Health Summary, with girls reporting higher HRQOL than boys. Factor analysis indicated that four factors were extracted from the PedsQLTM 4.0 SF15 and these four factors corresponded mainly to the four scales. Known groups validity was established for proxy-report and self-report with higher HRQOL being reported for healthy children than those with psychosomatic complaints including headache and abdominal pain. Conclusion The Japanese translation version of the PedsQLTM 4.0 SF15 demonstrates good reliability and validity and could be used as a measure of HRQOL for transcultural comparisons of pediatric research in school settings and healthcare services research. Keywords Health-related quality of life Children Healthcare Japan PedsQLTM Abbreviations HRQOL PedsQLTM PedsQLTM 4.0 SF15
J. W. Varni Department of Landscape Architecture and Urban Planning, College of Architecture, Texas A&M University, College Station, Texas, USA
Health-Related Quality of Life Pediatric Quality of Life InventoryTM Pediatric Quality of Life InventoryTM 4.0 Short Form 15
Introduction X. Chen (&) Center for Human Nutrition, Department of International Health, Bloomberg School of Public Health, Johns Hopkins University, 615 N. Wolfe Street, Baltimore, MD 21205, USA e-mail:
[email protected]
Health-related quality of life (HRQOL) is an essential health outcome in clinical trials and healthcare. One of the important changes in healthcare in recent years has been
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the move towards assessment of health status and outcome, and measurement of HRQOL is increasingly recognized to provide important information to describe the health status of individuals and populations [1]. HRQOL is generally considered to be a multi-factorial construct that focuses on individuals’ subjective evaluation of their physical health, mental health and social functioning [2–4]. It may be linked with the World Health Organization (WHO) definition of health as ‘‘a state of complete physical, mental, and social well-being, and not merely the absence of disease and infirmity’’ [5]. A large number of studies have focused on the relation between children with specific diseases and their low HRQOL [2, 6]. Pediatric HRQOL is increasingly acknowledged as an important health outcome measure in clinical trials and health services research and evaluation. Numerous generic and disease specific HRQOL instruments have been developed for children and adolescents [7–9]. The Pediatric Quality of Life InventoryTM (PedsQLTM) was developed in the US and was designed to integrate the merits of generic and disease-specific instruments [10]. It has demonstrated satisfactory psychometric properties, both the child self-report and the parent proxyreport being available, and being brief to complete it for children and their parents [10]. The PedsQLTM 4.0 Generic Core Scales, which distinguishes between healthy children and pediatric patients with acute or chronic health conditions, is a pediatric HRQOL instrument for ages 2–18 years [11]. The PedsQLTM 4.0 Short Form 15 (PedsQLTM 4.0 SF15) is a 15-item shortened version of the 23-item PedsQLTM 4.0 Generic Core Scales, characterizing by its brevity, availability of age appropriate versions and parallel forms for child and parent, and acceptable measurement properties [12]. This study investigated the reliability and validity of the Japanese translation of the PedsQLTM 4.0 SF15 in pediatric patients with chronic health problems and schoolchildren in Japan. A priori hypothesis with regards to the empirical factor structure was that we expected to find a four factor structure. We also hypothesized that children without chronic health problems would report higher PedsQLTM 4.0 SF15 scores (better HRQOL) than those with psychosomatic complains (including headache and abdominal pain), as well as those with other chronic health problems who had been to hospital periodically.
Material and methods Participants Participants were children aged 5–18 years and their parents. Schoolchildren were recruited from an elementary
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school. A total of 256 questionnaires were distributed to 1st–6th grade children aged 6–13 years. Respondents completed the questionnaires anonymously, recording their individual ID number. In total, 229 children and their parents were available. Of these, 155 respondents answered the questionnaire again with one month interval. Based on the frame of the PedsQLTM items for proxy-report and selfreport (e.g., In the past one month, how much of a problem has this been for your child/you…) [10], the one-month interval was used to examine test–retest reliability of the PedsQLTM 4.0 SF15. Subjects with chronic health problems were recruited from pediatric outpatient clinic in a typical university hospital. Those with mental conditions potentially affecting growth and development were excluded from this study. Subjects were children aged 5–18 years who had been seen as outpatients at the hospital for scheduled healthy checkup (3.1%), heart disease (59.8%), renal disease (10.2%), Kawasaki disease(6.2%), asthma (6.2%), allergic disorders (6.2%), and 8.3% of these subjects had two diseases or more. Measures The PedsQLTM 4.0 SF15 includes parallel child self-reports (ages range 5–18 years) and parent proxy-reports. The items for child self-report and parent proxy-report are essentially identical, differing only in developmentally appropriate language and first or third person tense [11]. The instructions ask how much of a problem each item has been during the past one month. A five-point response scale is used. The response scale for each item was ‘‘never’’ (0), ‘‘almost never’’ (1), ‘‘sometimes’’ (2), ‘‘often’’ (3), and ‘‘almost always’’ (4). Responses were transformed to 100, 75, 50, 25, and 0, respectively, resulting in a scale range of 0–100, with higher scores indicating better HRQOL. The PedsQLTM 4.0 SF15 encompasses the following subscales: Physical Functioning (5 items), Emotional Functioning (4 items), Social Functioning (3 items), and School Functioning (3 items). Scale scores are computed as the sum of the items divided by the number of items answered. According to the manual of the instrument the scale score is not computed if more than a half of items in the scale are missing [10, 13]. Two summaries and one overall score can be computed as well. The Physical Health Summary Score (5 items) is the same as the Physical Functioning Subscale. The Psychosocial Health Summary Score (10 items) is computed as the sum of the items divided by the number of items answered in the Emotional, Social, and School Functioning subscales. Total Scale Scores for child selfreport and parent proxy-report were also calculated. In order to evaluate the known groups validity of the PedsQLTM 4.0 SF15, psychosomatic symptoms were also
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assessed with the use of the following questions that asked participants to report on the frequency of headache and abdominal pain [14]: ‘‘In the last 6 months, how often had you had headache/abdominal pain?’’ The response categories were: ‘‘about every day’’, ‘‘more than once a week’’, ‘‘about every week’’, ‘‘about every month’’, and ‘‘rarely or never’’. The first four responses were combined to divide children into two groups: with and without headache/ abdominal pain. In addition to PedsQLTM 4.0 SF15 and psychosomatic symptoms, all families were required to complete a brief questionnaire concerning demographic information and child health (including chronic health condition diagnosed by doctors: asthma, heart disease, etc). Based on this, children with any chronic health problems were categorized to the group with chronic health problems. Procedure Translation Translation followed recommended guidelines [11]. The process included forward and backward translation and pilot administration of the Japanese version of PedsQLTM, and the back translation and revised measure were reviewed by the developer of the original instrument who recommended further modifications [10]. School setting assessment The school was sampled as a convenient one located in Toyama city, Japan. The PedsQLTM 4.0 SF15 was sent in a packet to the primary school and dispatched to children by teachers. Based on our simplified study protocol, teachers in the school were instructed to explain the survey’s aims to children. A letter was included in the packet explaining the survey study, the confidentiality with which their data would be treated, and that the school teachers or school staff would not see their information. The participants could further contact the researchers to obtain additional information. When parents or guardians and children completed the survey, they were asked to seal the envelope in which to return the survey to the research team. One month after the first survey was completed, the test–retest survey was conducted in 155 children (boys: 48.4%) and their parents (response rate: 67.7%) in the same school by the same way. Clinical setting assessment Subjects were identified when they were present at a university hospital. Written informed consents were obtained from the parents or guardians, and assents were obtained
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from children over 13 years of age. Parents and children completed the PedsQLTM 4.0 SF15 separately. A research assistant administered the PedsQLTM 4.0 SF15 for children aged 5–7 years and was available to assist the selfadministered instrument for those aged 8–18 years. The protocol was approved by the Institutional Review Board at Toyama University, Toyama. Statistical analysis Feasibility was determined from the percentage of missing values for items. Based on the percentage of scores at extremes of the scaling range, ceiling and floor effects were determined by using 15% as the recommended critical value for the largest proportion of the study population that should score at the highest or lowest possible scale levels [15]. Internal consistency reliability was determined by Cronbach’s a coefficient [16]. Test–retest reliability was assessed by calculating Pearson correlation coefficients. Values for Pearson correlation coefficients are designated as small (0.10–0.29), medium (0.30–0.49), and large (‡0.50) [17]. Parent/child concordance of parent proxyreport and child self-report for subscale and total scores was examined by Pearson correlation coefficients. Multitrait-Multimethod was conducted to compute parent–child intercorrelations between and among subscales of PedsQLTM 4.0 SF15. Factor analyses were performed using the principal component analysis with oblique (promax) rotation to examine factor validity. Factors which gained an eigenvalue more than 1.0 were retained. Known groups validity was examined through a comparison of children with and without psychosomatic complaints, as well as the comparison of healthy children and those with chronic health conditions using the t-test. Gender difference, parent proxy-report and child self-report in the PedsQLTM 4.0 SF15 scores were also examined using the t-test. We also conducted analysis of covariance (ANCOVA) to control for the potential age differences when comparing the average of HRQOL across both schoolchildren and pediatric outpatients. Statistical analyses were conducted using the SPSS 10.0 Japanese version and SAS 8.02 for Windows. P values of less than 0.05 were considered to be statistically significant.
Results From 369 families approached, a total of 329 were recruited to the study (response rate: 89.2%). In the school setting, 256 children aged 6–13 years and their families were contacted and 229 of them (boys: 49.8%) answered their questionnaires (response rate: 89.5%). In the clinical
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setting, 113 pediatric outpatients aged 5–18 years and their parents were contacted and 100 of them (boys: 47.0%) were eligible to participate in the survey (response rate: 88.5%). The majority of parent proxy-reports were completed by mothers (85%), 10% by fathers, and 5% by other guardians such as grandparents. For child self-report, the mean age of all participants were 11.5 years old (mean deviation: 3.2). Missing responses for all items were rare, with a range of 0.0–1.6% for parent proxy-report and child self-report. In the clinical sample, item level missing for the PedsQLTM 4.0 SF15 ranged from 0.0% to 4.0%.
scores, internal consistency reliability alpha coefficients were slightly higher for parent proxy-report (range: 0.81– 0.86) than for child self-report (range: 0.71–0.79). Test–retest reliability Pearson correlation coefficients between test and retest ranged from 0.68 to 0.79 for parent proxy-report and 0.46 to 0.73 for child self-report (Table 3). Test–retest reliability demonstrated mainly larger values for parent proxyreport than for child self-report. There were no differences in the mean scores between test and retest surveys for proxy-report. Except for Physical Health, significant differences were found between the two surveys in other scales for self-report (all P < 0.05).
Floor and ceiling effects Table 1 shows the floor and ceiling effects of the PedsQLTM 4.0 SF15. None of floor effects were observed, even among those pediatric outpatients (£3.0%). Ceiling effects were observed in the Physical Health and Social Functioning scales for both proxy-report and self-report (range: 19.0–52.4%). No ceiling effects were found for Psychosocial Health and Total Score (£8.0%). For self-report, there were no ceiling effects for Emotional Functioning and School Functioning (£12.7%).
Parent/child concordance and gender difference The multitrait-monomethod correlations ranged from 0.24 to 0.53 for proxy-report and 0.32 to 0.48 for self-report, respectively (Table 4). All multitrait-multimethod correlations were small to medium (range: 0.08–0.33), while the monotrait-multimethod correlations of corresponding scale scores between proxy-report and self-report were medium (range: 0.40–0.47). The overall concordance between parent proxy-report and child self-report for children with chronic health conditions and healthy children was similar. In general, parent proxy-report HRQOL was higher than child self-report in all scales except for Social Functioning scale among total population (Fig. 1). Similar results were observed among children with chronic health problems in the clinical setting.
Internal consistency reliability The internal consistency reliability alpha coefficients are presented for the PedsQLTM SF15 in Table 2. All the parent proxy-report and child self-report scales exceeded the minimum reliability standard required for group comparison of 0.70. Across the PedsQLTM SF15 scales and summary Table 1 Floor and ceiling effects for PedsQLTM 4.0 SF15 (n = 329) Scale
Number of items
Total (n = 329)
School (n = 229)
Hospital (n = 100)
% Floor
% Ceiling
% Floor
% Ceiling
% Floor
% Ceiling
28.0
Proxy-report Physical Health Psychosocial Health Emotional Functioning Social Functioning School Functioning Total Score
5
0.3
45.0
0.0
52.4
1.0
10
0.0
7.9
0.0
7.9
0.0
8.0
4 3
0.0 0.0
14.9 32.5
0.0 0.0
15.3 32.8
0.0 0.0
14.0 32.0
3
0.9
13.7
0.9
11.4
1.0
19.0
15
0.0
7.3
0.0
7.9
0.0
6.0
5
0.0
23.1
0.0
24.9
0.0
19.0
10
0.0
3.1
0.0
3.5
0.0
2.0
Self-report Physical Health Psychosocial Health Emotional Functioning
4
0.6
9.1
0.4
9.2
1.0
9.0
Social Functioning
3
0.6
44.4
0.4
44.1
1.0
45.0
3
0.9
12.5
0.0
12.7
3.0
12.0
15
0.0
2.4
0.0
3.1
0.0
1.0
School Functioning Total Score
% Floor or ceiling: percentage of scores at the extremes of the range
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Table 2 Internal consistency reliability for PedsQLTM 4.0 SF15 (n = 329) Scale
67.0% for proxy-report and 56.9% for self-report, respectively. For proxy-report, all items loaded between 0.41 and 0.95 on their corresponding factors. Item 5 ‘‘hard to do chores around house’’ had the largest cross-loading on two different factors. This item had equivalent and salient cross-loadings on factor 1 (0.41) and factor 2 (0.39). All five of the Physical Functioning items loaded together, as did the Emotional Functioning, Social Functioning, and School Functioning items. For self-report, the range of the highest loadings for each item was from 0.44 to 0.84. All four Emotional Functioning items loaded onto the same factor as the three Social Functioning items. Four of the five Physical Functioning items loaded together, but item 5 ‘‘hard to do chores around house’’ split into different factor. Similarly, two of the three School Functioning items loaded together, but item 14 ‘‘Forget things’’ split into another factor.
Number Internal consistency reliability of items a coefficient 95% CI
Proxy-report Physical Health
5
0.86
0.82–0.89
10
0.86
0.84–0.88
Emotional Functioning
4
0.81
0.76–0.85
Social Functioning
3
0.86
0.84–0.89
School Functioning
3
0.85
0.81–0.87
Psychosocial Health
Self-report Physical Health
5
0.79
0.74–0.84
10
0.76
0.71–0.80
Emotional Functioning
4
0.77
0.72–0.82
Social Functioning
3
0.73
0.66–0.79
School Functioning
3
0.71
0.62–0.77
Psychosocial Health
Known groups validity
95% CI: 95% confidence interval
Figure 3 demonstrates the comparisons in the PedsQLTM 4.0 SF15 for proxy-report and self-report scores between children with and without headache. Regarding child selfreport, for all scales except for Physical Functioning, children with headache reported lower HRQOL than healthy children. Parents rated lower HRQOL of their children with headache than those without headache in Emotional Functioning and Total Score. In addition, children with abdominal pain self-reported lower HRQOL than their healthy counterparts in all scales except for Physical Health and Social Functioning, while parents reported lower HRQOL of their children with abdominal pain than those healthy children in all scales except for Social Functioning (Fig. 4). Known groups validity was also evaluated through a comparison of healthy children and
There were gender differences in some scales for proxyreport and self-report (Fig. 2). Girls had a higher HRQOL than boys in Social Functioning, School Functioning, and Psychosocial Health. However, no gender differences were found in Physical Health, Emotional Functioning, and Total Score for self-report (all P > 0.05). Similar findings were observed in schoolchildren. Factor validity Factor analysis with oblique rotation shows that four factors would be optimal and were extracted from the PedsQLTM 4.0 SF15 (Table 5). The percentages of the total variance accounted for by the rotated four factors were Table 3 Test–retest reliability of PedsQLTM 4.0 SF15 in school setting (n = 155)
Scale
Number of items
Test Mean (SD)
Retest Mean (SD)
Pearson correlation coefficient
Proxy-report Physical Health
5
92.6 (11.2)
92.6 (11.6)
0.68
10
75.8 (14.0)
77.7 (14.2)
0.78
Emotional Functioning
4
75.4 (16.3)
76.5 (17.0)
0.74
Social Functioning
3
82.7 (16.5)
83.7 (15.3)
0.68
School Functioning
3
69.4 (19.7)
72.5 (19.5)
0.69
15
81.4 (11.3)
81.4 (12.0)
0.79
Psychosocial Health
Total Score Self-report Physical Health
5
83.4 (17.4)
86.4 (16.8)
0.46
10
73.3 (16.6)
80.3 (15.1)
0.73
Emotional Functioning
4
66.6 (21.7)
72.1 (21.0)
0.64
Social Functioning
3
84.8 (18.9)
89.7 (16.0)
0.59
School Functioning
3
70.3 (21.7)
78.9 (21.1)
0.66
15
76.7 (14.5)
81.8 (14.2)
0.70
Psychosocial Health
Total Score
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Table 4 Correlations between parent proxy-report and child self-report of PedsQLTM 4.0 SF15 by Multitrait-Multimethod (n = 329) Scale
Proxy-report Physical Functioning
Self-report Emotional Functioning
Social Functioning
School Functioning
Physical Functioning
Emotional Functioning
Social Functioning
Proxy-report Physical Functioning Emotional Functioning
0.38
Social Functioning
0.34
0.53
School Functioning Self-report
0.24
0.43
0.43
Physical Functioning
0.41
0.33
0.21
0.15
Emotional Functioning
0.15
0.40
0.25
0.22
0.43
Social Functioning
0.21
0.30
0.43
0.31
0.33
0.48
School Functioning
0.08
0.25
0.21
0.47
0.32
0.47
0.38
Multitrait-monomethod correlations are in bold; monotrait-multimethod correlations are underlined; multitrait-multimethod correlations are italicized
90
*
HRQOL score
30
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Ph y
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ng ni
ng io
tio
ni
ea na
lF un
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H ys ic al
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ea l th
10
0
ni ng
20
l th
20 10
Total population (N =329)
ng Sc tio ho ni ol ng Fu Ps nc yc ti o ho ni ng so ci al H ea l th To ta lS co re
40
30
io ni
40
***
50
nc t
50
*
60
na l
HRQOL score
60
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70
Fu nc
***
70
***
80
***
*
So ci al
***
80
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self-report
Fu
90
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proxy-report
1 00
100
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Fig. 1 Comparison of PedsQLTM 4.0 SF15 scores between parent proxy-report and child self-report
Clinical setting (N=100)
* p