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Assessment of data quality in a multi-centre cross-sectional study of participation and quality of life of children with cerebral palsy

Authors :
Parkes Jackie
Fauconnier Jérôme
Michelsen Susan I
Beckung Eva
Arnaud Catherine
McManus Vicki
Parkinson Kathryn
Dickinson Heather
Schirripa Giorgio
Thyen Ute
Colver Allan
Source :
BMC Public Health, Vol 6, Iss 1, p 273 (2006)
Publication Year :
2006
Publisher :
BMC, 2006.

Abstract

Abstract Background SPARCLE is a cross-sectional survey in nine European regions, examining the relationship of the environment of children with cerebral palsy to their participation and quality of life. The objective of this report is to assess data quality, in particular heterogeneity between regions, family and item non-response and potential for bias. Methods 1,174 children aged 8–12 years were selected from eight population-based registers of children with cerebral palsy; one further centre recruited 75 children from multiple sources. Families were visited by trained researchers who administered psychometric questionnaires. Logistic regression was used to assess factors related to family non-response and self-completion of questionnaires by children. Results 431/1,174 (37%) families identified from registers did not respond: 146 (12%) were not traced; of the 1,028 traced families, 250 (24%) declined to participate and 35 (3%) were not approached. Families whose disabled children could walk unaided were more likely to decline to participate. 818 children entered the study of which 500 (61%) self-reported their quality of life; children with low IQ, seizures or inability to walk were less likely to self-report. There was substantial heterogeneity between regions in response rates and socio-demographic characteristics of families but not in age or gender of children. Item non-response was 2% for children and ranged from 0.4% to 5% for questionnaires completed by parents. Conclusion While the proportion of untraced families was higher than in similar surveys, the refusal rate was comparable. To reduce bias, all analyses should allow for region, walking ability, age and socio-demographic characteristics. The 75 children in the region without a population based register are unlikely to introduce bias.

Details

Language :
English
ISSN :
14712458 and 42678390
Volume :
6
Issue :
1
Database :
Directory of Open Access Journals
Journal :
BMC Public Health
Publication Type :
Academic Journal
Accession number :
edsdoj.59fcec82fefc426783904a89f387c0ee
Document Type :
article
Full Text :
https://doi.org/10.1186/1471-2458-6-273