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

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

Spatial attentional bias as a marker of genetic risk, symptom severity, and stimulant response in ADHD

Attention-deficit hyperactivity disorder (ADHD) is a heritable childhood onset disorder that is marked by variability at multiple levels including clinical presentation, cognitive profile, and response to stimulant medications. It has been suggested that this variability may reflect etiological differences, particularly, at the level of underlying genetics. This study examined whether an attentional phenotype-spatial attentional bias could serve as a marker of symptom severity, genetic risk, and stimulant response in ADHD. A total of 96 children and adolescents with ADHD were assessed on the Landmark Task, which is a sensitive measure of spatial attentional bias. All children were genotyped for polymorphisms (30 untranslated (UTR) and intron 8 variable number of tandem repeats (VNTRs)) of the dopamine transporter gene (DAT1). Spatial attentional bias correlated with ADHD symptom levels and varied according to DAT1 genotype. Children who were homozygous for the 10-repeat allele of the DAT1 30-UTR VNTR displayed a rightward attentional bias and had higher symptom levels compared to those with the low-risk genotype. A total of 26 of these children who were medication naive performed the Landmark Task at baseline and then again after 6 weeks of stimulant medication. Left-sided inattention (rightward bias) at baseline was associated with an enhanced response to stimulants at 6 weeks. Moreover, changes in spatial bias with stimulant medications, varied as a function of DAT1 genotype. This study suggests an attentional phenotype that relates to symptom severity and genetic risk for ADHD, and may have utility in predicting stimulant response in ADHD.

Response variability in Attention Deficit Hyperactivity Disorder: Evidence for neuropsychological heterogeneity

Response time (RT) variability is a common finding in ADHD research. RT variability may reflect frontal cortex function and may be related to deficits in sustained attention. The existence of a sustained attention deficit in ADHD has been debated, largely because of inconsistent evidence of time-on-task effects. A fixed-sequence Sustained Attention to Response Task (SART) was given to 29 control, 39 unimpaired and 24 impaired-ADHD children (impairment defined by the number of commission errors). The response time data were analysed using the Fast Fourier Transform, to define the fast-frequency and slow-frequency contributions to overall response variability. The impaired-ADHD group progressively slowed in RT over the course of the 5.5 min task, as reflected in this group's greater slow-frequency variability. The fast-frequency trial-to-trial variability was also significantly greater, but did not differentially worsen over the course of the task. The higher error rates of the impaired-ADHD group did not become differentially greater over the length of the task. The progressive slowing in mean RT over the course of the task may relate to a deficit in arousal in the impaired-ADHD group. The consistently poor performance in fast-frequency variability and error rates may be due to difficulties in sustained attention that fluctuate on a trial-to-trial basis. (c) 2006 Elsevier Ltd. All rights reserved.

Response shift in the assessment of quality of life among people attending cardiac rehabilitation

Objectives: To examine whether any response shift in quality of life assessment over the course of a cardiac rehabilitation programme could be explained by changes in individuals’ internal standards (recalibration), values (reprioritization) and/or conceptualization of quality of life and the extent to which any response shift could be explained by health locus of control, optimism and coping strategy. Design: Longitudinal survey design. Methods: The SEIQoL-DW was administered at the beginning and end of a cardiac rehabilitation programme. At the end of the programme, the SEIQoL-DW then-test was also administered to measure response shift. A total of 57 participants completed these measures and other measures to assess health locus of control, optimism and coping. Results: Response shift effects were observed in this population mainly due to recalibration. When response shift was incorporated into the analysis of QoL a larger treatment effect was observed. Active coping as a mechanism in the response shift model was found to have a significant positive correlation with response shift. Conclusion: This study showed that response shift occurs during cardiac rehabilitation. The occurrence of response shift in QoL ratings over time for this population could have implications for the estimation of the effectiveness of the intervention.

Investigating the Interhemisphere 14C Offset in the 1st Millennium AD and Assessment of Laboratory Bias and Calibration Errors

Past measurements of the radiocarbon interhemispheric offset have been restricted to relatively young samples because of a lack of older dendrochronologically secure Southern Hemisphere tree-ring chronologies. The Southern Hemisphere calibration data set SHCal04 earlier than AD 950 utilizes a variable interhemispheric offset derived from measured 2nd millennium AD Southern Hemisphere/Northern Hemisphere sample pairs with the assumption of stable Holocene ocean/ atmosphere interactions. This study extends the range of measured interhemispheric offset values with 20 decadal New Zealand kauri and Irish oak sample pairs from 3 selected time intervals in the 1st millennium AD and is part of a larger program to obtain high-precision Southern Hemisphere 14C data continuously back to 200 BC. We found an average interhemispheric offset of 35 ± 6 yr, which although consistent with previously published 2nd millennium AD measurements, is lower than the offset of 55–58 yr utilized in SHCal04. We concur with McCormac et al. (2008) that the IntCal04 measurement for AD 775 may indeed be slightly too old but also suggest the McCormac results appear excessively young for the interval AD 755–785. In addition, we raise the issue of laboratory bias and calibration errors, and encourage all laboratories to check their consistency with appropriate calibration curves and invest more effort into improving the accuracy of those curves.

Assessment of the benefits of Discrete Conditional Survival Models in modelling ambulance response times

Many of the challenges faced in health care delivery can be informed through building models. In particular, Discrete Conditional Survival (DCS) models, recently under development, can provide policymakers with a flexible tool to assess time-to-event data. The DCS model is capable of modelling the survival curve based on various underlying distribution types and is capable of clustering or grouping observations (based on other covariate information) external to the distribution fits. The flexibility of the model comes through the choice of data mining techniques that are available in ascertaining the different subsets and also in the choice of distribution types available in modelling these informed subsets. This paper presents an illustrated example of the Discrete Conditional Survival model being deployed to represent ambulance response-times by a fully parameterised model. This model is contrasted against use of a parametric accelerated failure-time model, illustrating the strength and usefulness of Discrete Conditional Survival models.