Health-related quality of life scores of typically developing children and adolescents around the world: a meta-analysis with meta-regression

Ow, Nikki; Mayo, Nancy E.

doi:10.1007/s11136-020-02519-0

Cited by 28 publications

(16 citation statements)

References 110 publications

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“…Women reporting lower scores than men has been demonstrated not only for the PedsQL [ 9 , 10 ], but also for other HS instruments across the world [ 20 – 22 ]. Our finding that sex differences in HS already emerge during childhood is supported by previous studies in clinical groups [ 14 , 23 – 28 ]. Although these studies unanimously concluded that girls report lower scores than boys, their results varied with regard to the specific subscales.…”

Section: Discussionsupporting

confidence: 91%

“…Although these studies unanimously concluded that girls report lower scores than boys, their results varied with regard to the specific subscales. Some studies reported sex differences in Emotional Functioning only [ 14 , 25 ], whereas others showed differences on a larger variety of subscales and on the Total Score [ 23 , 24 , 26 – 28 ].…”

Section: Discussionmentioning

confidence: 99%

“…Discrepancies between studies on HS with regard to sex differences or parent–child agreement can have various causes. HS may be affected by country of residence [ 27 , 28 ], differences over time [ 34 ], socioeconomic status [ 28 ], physical and mental conditions [ 14 , 35 ], a child’s age [ 28 ], and presumably many other factors. These factors need to be taken into account as much as possible when interpreting a study’s results.…”

Section: Discussionmentioning

confidence: 99%

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Sex differences in children's health status as measured by the Pediatric Quality of Life Inventory (PedsQL)™: cross-sectional findings from a large school-based sample in the Netherlands

et al. 2021

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Background Previous research has shown that female adolescents and adults report lower health status than their male peers. Possibly, this discrepancy already develops during childhood. We collected sex-specific data with the Pediatric Quality of Life Inventory (PedsQL) in a large school-based sample. Methods The online version of the PedsQL was administered to healthy Dutch children aged 5–7 years (parent proxy-report), 8–12 years (parent proxy-report and child self-report), and 13–17 years (parent proxy-report and child self-report), recruited through regular primary and secondary schools. Sex differences were assessed using t-tests or Mann–Whitney U-tests. Wilcoxon signed-rank tests and intraclass correlation coefficients served to compare parent proxy-reports with child self-reports. Multivariable linear regression analyses were used to assess the associations of sex of the child, age, and parental educational level with PedsQL scores. Results Eight hundred eighty-two parents and five hundred eighty one children were recruited from 15 different schools in the Netherlands. Parents of 8-to-12-year-olds reported higher scores on School Functioning for girls than for boys (mean difference [MD]: 6.56, p < 0.001). Parents of 13-to-17-year-olds reported lower scores on Physical and Emotional Functioning for girls than for boys (MDs: 2.14 and 5.79, p = 0.014 and p < 0.001, respectively). Girls aged 8–12 years reported lower scores than boys in this age group on Physical Functioning (MD: 3.09, p = 0.005). Girls aged 13–17 years reported lower scores than boys in this age group on Physical Functioning (MD: 3.67, p < 0.001), Emotional Functioning (MD: 8.11, p < 0.001), and the Total Score (MD 3.26, p = 0.004). No sex differences were found in children aged 5–7 years. Agreement between child self-reports and parent proxy-reports was poor to moderate. Conclusions Girls generally had lower PedsQL scores than boys, both in parent proxy-reports and in child self-reports. We recommend to apply sex-specific data when assessing health status using the PedsQL.

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Section: Discussionsupporting

confidence: 91%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Sex differences in children's health status as measured by the Pediatric Quality of Life Inventory (PedsQL)™: cross-sectional findings from a large school-based sample in the Netherlands

et al. 2021

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“…[52][53][54] The PedsQL Emotional Functioning Scale measures this construction of negative affectivity or (10) emotional distress, and hence addresses the need for a measurement scale to include depression and anxiety symptoms in youth with multiple sclerosis. The PedsQL 4.0 Generic Core Scales is one of the most widely used pediatric generic healthrelated quality of life measurement instruments in the world, as confirmed by recent international meta-analysis reviews, 55,56 and provides a relative benchmark for comparing the generic Physical, Emotional, Social, and School Functioning Scales from the PedsQL 4.0 Generic Core Scales in multiple sclerosis with international published findings from other investigators worldwide. 55,56 Study limitations include the generation of items from only one site.…”

Section: Discussionmentioning

confidence: 91%

“…The PedsQL 4.0 Generic Core Scales is one of the most widely used pediatric generic healthrelated quality of life measurement instruments in the world, as confirmed by recent international meta-analysis reviews, 55,56 and provides a relative benchmark for comparing the generic Physical, Emotional, Social, and School Functioning Scales from the PedsQL 4.0 Generic Core Scales in multiple sclerosis with international published findings from other investigators worldwide. 55,56 Study limitations include the generation of items from only one site. However, all patients included in the present investigation fulfilled the diagnostic criteria for pediatric-onset multiple sclerosis in youth.…”

Section: Discussionmentioning

confidence: 91%

PedsQL Multiple Sclerosis Module Domain and Item Development: Qualitative Methods

Gaudioso

Mar

et al. 2021

J Child Neurol

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Background: The objective of this qualitative methods study was to develop the domains and items to support the content validity for the Pediatric Quality of Life Inventory (PedsQL) Multiple Sclerosis Module for youth with pediatric-onset multiple sclerosis. Methods: A literature review of multiple sclerosis–specific questionnaires and clinical research was conducted to generate domains. An expert panel composed of 12 neurologists who were pediatric-onset multiple sclerosis specialists provided feedback on the conceptual framework. Focus interviews with 9 youth with pediatric-onset multiple sclerosis and 6 parents were conducted to develop the relevant domains and item content from the patient and parent perspective. In the cognitive interviews phase, 9 youth with pediatric-onset multiple sclerosis and 6 parents provided feedback on item content, relevance, importance, and understandability of the pediatric-onset multiple sclerosis–specific domains and items. The final interview phase with 5 youth with pediatric-onset multiple sclerosis and 5 parents comprised a pilot testing of the new PedsQL MS Module. Results: Eighteen domains were derived from the qualitative methods with item content saturation achieved at 100 items based on 40 interviews with 23 youth with pediatric-onset multiple sclerosis aged 10-21 years and 17 parents. The domains derived include general fatigue, sleep/rest fatigue, cognitive functioning, tingling sensations, numbness sensations, physical weakness, pain, speech, balance, fine motor, vision, urination, constipation, bowel incontinence, worry, communication, treatment, and medicines. Conclusions: Qualitative methods involving 23 youth with pediatric-onset multiple sclerosis and 17 parents in the domain and item development process support the content validity for the new PedsQL MS Module. Future plans include a national field test of the PedsQL MS Module scales and items.

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Assessing Disease and Health Outcomes

Rapoff¹,

Duncan²,

Karlson³

2023

Issues in Clinical Child Psychology

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Health-related quality of life scores of typically developing children and adolescents around the world: a meta-analysis with meta-regression

Cited by 28 publications

References 110 publications

Sex differences in children's health status as measured by the Pediatric Quality of Life Inventory (PedsQL)™: cross-sectional findings from a large school-based sample in the Netherlands

Sex differences in children's health status as measured by the Pediatric Quality of Life Inventory (PedsQL)™: cross-sectional findings from a large school-based sample in the Netherlands

PedsQL Multiple Sclerosis Module Domain and Item Development: Qualitative Methods

Assessing Disease and Health Outcomes

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