Background
The advances in cancer treatment over the past decades have increased the survival rate in childhood cancer. As of today four out of five children survive their cancer diagnosis, however with the risk of physical, neurocognitive and psychosocial long term side effects. The psychosocial consequences of pediatric cancer are well documented, as are the needs for routinely systematic assessments to follow up on psychosocial health for both patients and their families [
8].
The increased survivorship as well as the documented side effects of chemotherapy and radiation have placed emphasis on the concept of health related quality of life (HRQOL) in pediatric cancer patients, both during and after treatment [
18,
6,
13,
16].
The HRQOL concept encompasses the dimension physical functioning, including health status and functional status, as well as the dimension psychosocial functioning, including emotional-, social and role functioning [
20]. Although sometimes used interchangeably with the concept quality of life (QOL) HRQOL has been suggested to be the appropriate term for QOL dimensions expedient to the health care services [
21].
HRQOL instruments for the pediatric population generally comprise patient self-reports and parent proxy-reports. The cross-informant variance that has been well documented in both adult and pediatric samples has also been shown to be present in pediatric HRQOL instruments. Typically, there is a stronger correlation in domains reflecting external behaviors, such as physical functioning, and a weaker correlation in domains reflecting internal behaviors such as emotional and social functioning as well as pain symptoms [
5]. These results underline the importance of utilizing patient self-reports as a standard for measuring HRQOL in pediatric populations even though parent proxy- reports may be warranted in cases where the child itself is too young, too cognitively impaired, too fatigue or too ill to complete the questionnaires [
21,
9].
The Pediatric Quality of Life Inventory (PedsQL) is a modular instrument, designed to integrate generic and disease specific measures, and includes both self- and proxy-reports [
19]. The instrument originates from The Pediatric Cancer Quality of Life Inventory (PCQL) that was designed to take into account not only the biomedical end points, such as response rate and survival, but also to focus on behavioral and emotional problems in order to capture the daily health related problems that pediatric cancer patients face [
18]. Today the PedsQL instrument targets not only pediatric cancer but has been modified to cover other chronic health conditions as well, and has been translated and evaluated in a number of languages [
23,
22,
9,
16,
14,
15].
The increased use of patient-reported outcome measures in both clinical and research settings requires instruments with appropriate and well documented psychometric properties [
4].
The overall aim of this study was to translate the Pediatric Quality of Life Inventory 3.0 Cancer Module Scales (PedsQL 3.0) to Swedish and to assess reliability and a limited validity in a sample of Swedish children diagnosed with cancer.
Methods
Participants
Data for the psychometric analysis was collected among patients at the Pediatric Oncology clinic at the Queen Silvia Children’s Hospital, Sahlgrenska University Hospital, Gothenburg, Sweden. The sample consisted of in total 140 families of which 94 agreed to participate, including 63 children aged 5 to 18 years and 94 parents. Inclusion criterions for the children were; current age 2–18 years, fluency in the Swedish language and a pediatric cancer diagnosis. Inclusion criterions for the parents were; fluency in the Swedish language. Children with developmental disability and/or intellectual disability were excluded, as well as children with another significant medical disease.
Procedure
The original version of the PedsQL Cancer Module was translated into Swedish in 2012 using forward and backward translation. The Swedish version of the questionnaire was administered to 20 families at the Pediatric Oncology clinic at The Queen Silvia Children’s Hospital, and was then followed up by structured interviews in order to detect any difficulties with the Swedish translation [
10]. Some minor changes were made and reported to the MAPI Institute. After this process, the MAPI Research Institute gave approval to go ahead with the psychometric analysis of the Swedish PedsQL 3.0.
The data for the psychometric analysis was collected during the period September 2012 to January 2015 at the Pediatric Oncology Clinic at The Queen Silvia Children’s Hospital, where patients and their parents were recruited during pre-scheduled outpatient visits. Written consent was signed individually by the children (8–18 years) and their parents.
One of two research nurses informed the participating families about the study and distributed the PedsQL 4.0 and PedsQL 3.0 to children and parents. The parents were also asked to fill out a form with background variables, such as age, gender and the child’s cancer diagnosis. In the age group 2–4 years, parents alone participated. In the age group 5–7 years the children filled out the questionnaires separately from the parents, with the assistance from a research nurse, who provided help with reading and clarifying the questions. The children in the age group 8–18 years filled out the questionnaires independently, with a nurse available to assist.
Measures
The PedsQL 4.0
The PedsQL 4.0 measures generic quality of life and includes both self- (child) and proxy- (parent) reports [
19]. The Swedish version of the instrument has been shown to have satisfactory reliability estimates as well as satisfactory internal consistency reliability, for both child- and parent-reports, with Cronbach’s alpha values exceeding 0.70 [
12]. The PedsQL 4.0 consists of 23 items (21 items in the age group 2–4 years old), covered by four scales: (1) physical functioning (eight items), (2) emotional functioning (five items), (3) social functioning (five items), and (4) school functioning (five items, three items in the age group 2–4 years).
The PedsQL 4.0 utilize a five-point Likert scale (ranging from 0 = never to 4 = almost always) for all versions, except for the child -report version 5–7 years where a 3-point Likert scale (where 0 = not at all, 2 = sometimes, 4 = a lot) is used together with a visual aid (happy face, neutral face and sad face). The items are reverse-scored and linearly transformed to a 0–100 scale (0 = 100, 1 = 75, 2 = 50, 3 = 25, 4 = 0), where higher scores indicate better HRQOL [
14,
15].
The PedsQL 3.0
The PedsQL 3.0 was designed to evaluate disease specific HRQOL in children with cancer aged 2–18 years and includes both self- (child) and proxy- (parent) reports. Varni [
20] reported satisfactory psychometric properties in a sample of pediatric cancer patients and their parents with average α-values of 0.72 for child -reports and 0.87 for parent reports for most scales. The sample consisted of all diagnostic groups and included newly diagnosed patients, recurrent patients as well as patients who were long term of treatment. The PedsQL 3.0 consists of 27 items covered by five scales: (1) pain and hurt (two items), (2) nausea (five items), (3) procedural anxiety (three items), (4) treatment anxiety (three items), (5) worry (three items), (6) cognitive problems (five items), (7) perceived physical appearance (three items) and (8) communication (three). The PedsQL 3.0 utilize a five-point Likert scale (ranging from 0 = never to 4 = almost always) for all versions, except for the child report version 5–7 years where a 3-point Likert scale (where 0 = not at all, 2 = sometimes, 4 = a lot) is used together with a visual aid (happy face, neutral face and sad face). The items are reverse-scored and linearly transformed to a 0–100 scale (0 = 100, 1 = 75, 2 = 50, 3 = 25, 4 = 0), where higher scores indicate better HRQOL.
Statistical methods
SPSS version 22 for Windows was used for statistical analysis. Descriptive statistics were calculated for the background variables gender, age and cancer diagnosis. Internal consistency of the PedsQL 3.0 was assessed with Cronbach’s α for both child- and parent-reports in order to ensure that the items in the scale measure the same underlying concept [
3]. Construct validity was determined by using the convergent validation approach, using the PedsQL 4.0 as the criterion variable. Finally, a paired samples t-test was used to test for differences between child- and parent-reports of cancer-specific HROQL.
Ethics approval and consent to participate
The study has been approved by the Regional Ethical Review Board in Gothenburg (DNR: 004–10).
Discussion
This study examined the psychometric properties of the Swedish version of the PedsQL 3.0, Cancer Module. It was found that the Total Scale Score exceeded the criteria for satisfactory internal consistency, with Cronbach’s alpha values ranging from 0.91 to 0.94 for self- and proxy reports. Similarly, most of the subscales reached satisfactory estimates with Cronbach’s α values at or above 0.70. These results are in line with previous reports on the psychometric properties of disease-specific modules of the PedsQL [
14‐
16,
9,
19] and confirm the reliability of the Swedish version of the Cancer Module Scale. When looking at the child- and parent -reports in each age-group most of the Cronbach’s α values are still satisfactory, with the exception of the values in the parent reports in the age group 2–4 years, which are below acceptable alpha values.
The PedsQL 3.0 and the generic PedsQL 4.0 total scale scores were strongly correlated for both child- and parent-reports, indicating construct validity and suggesting that cancer related difficulties were strongly related to general HRQOL. Furthermore, all but one subscale, Procedural anxiety, showed significant positive correlations with the generic PedsQL 4.0 total score scale, indicating that these scales independently relate to general HRQOL as assessed by the PedsQL 4.0.
Consistent with other studies in the field the present study found a medium to strong positive correlation between child- and parent-reports for all subscales, strengthening the validity of the PedsQL Cancer module [
16,
9,
20]. The strongest correlations were found for the scales Nausea and Pain and hurt (> 0.60) and the weakest correlation was found for the scale Treatment anxiety (0.32). Except for Pain and hurt, which is typically seen as an internal problem, the intercorrelations reflect previously documented tendencies that external behaviors i.e. physical functioning, predict stronger correlations between child- and proxy-reports compared to more internal behaviors [
5].
Parents reported more overall cancer-specific problems than the children themselves. Specifically, this was true for the scales Pain and hurt, Nausea, Procedural anxiety and Treatment anxiety, whereas no significant differences were found for the scales Worry, Cognitive problems, Physical appearance and communication. This is in line with previous studies on the difference between child- and parent-reports on HROQL, regardless of disease-group. One possible explanation to this is that the parents themselves have low HROQL due to the stress of having a child with a chronic disease and that this affects how they report the child’s well-being (Ingerski et al., [
7]). The parents also carry the burden of responsibility and thus may be more aware of the seriousness of the situation and can foresee different scenarios and consequences, compared to especially younger children who tend to have a more “here and now” mentality. The results show that parent-proxy reports on cancer-specific HROQL may be a valuable tool in cases where the child itself (5–18 years old) for some reason is not able to answer the questionnaires, although it is important to be aware of the possible tendencies described above. In addition, the PedsQL 3.0 child- and parent -reports may serve as valuable tools in clinical practice as a means of addressing and improving the communication between children and parents when it comes to cancer-specific problems.
Some studies have also suggested that the PedsQL Cognitive problems scale can be used as a tool for identifying children in need for more extensive cognitive testing [
11,
2]. Buratti et al. [
2] found strong associations between 15-year old’s reports on the subscale Cognitive problems and their Full Scale Intelligence Quotient (FSIQ) (as measured using the Wechsler Intelligence Scales) as well as moderate to strong associations between the Cognitive problems parent proxy reports and the child’s FSIQ for all ages. Considering the growing body of evidence of the need for neurocognitive evaluations of patients with pediatric cancers affecting the central nervous system this may be an additional area of use for the PedsQL 3.0 and thus also a warranted focus for further studies [
1].
Limitations
The current study had some limitations. First, the study did not present data on test-retest reliability, primarily due to the challenge of being in a clinical context within a large catchment area where patients may have to travel a long way to the hospital setting. This raises ethical considerations of summoning patients and their parents to visits intended solely for test administration. Secondly, even though the overall results indicate satisfactory psychometric properties for all age groups, the parent -reports for the age group 2–4 years did not reach satisfactory alpha values, which needs to be considered when interpreting the results.
Furthermore, there was a lack of demographic data on the parents. Even though the main objective of the study was to analyze psychometric properties, which ought not to be affected by demographics, factors such as family size, age, income and occupation would have been valuable information to include in order to ensure an unbiased sample. Finally, the overall sample size in the current study was not suitable for exploratory factor analysis, therefore this would be a welcome focus for future studies [
17]. Another important contribution to further strengthen the psychometric properties of the Swedish version of the PedsQL 3.0 would be to conduct a study with a comparison control group in order to measure discriminant validity.
Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit
http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (
http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.