Response Conversion for Improving Comparability of International Physical Activity Data

Background: Many questionnaires for measuring physical activity (PA) exist. This complicates the comparison of outcomes. Methods: In 8 European countries, PA was measured in random samples of 600 persons, using the IPAQ as a 'bridge' to historical sets of country-specific questions. We assume that a unidimensional scale of PA ability exists on which items and respondents can be placed, irrespective of country, culture, background factors, or measurement instrument. Response Conversion (RC) based on Item Response Theory (IRT) was used to estimate such a common PA scale, to compare PA levels between countries, and to create a conversion key. Comparisons were made with Eurobarometer (IPAQ) data. Results: Appropriateness of IRT was supported by the existence of a strong first dimension established by principal component analysis. The IRT analysis resulted in 1 common PA scale with a reasonable fit and face validity. However, evidence for cultural bias (Differential Item Functioning, DIF) was found in all IPAQ items. This result made actual comparison between countries difficult. Conclusions: Response Conversion can improve comparability in the field of PA. RC needs common items that are culturally unbiased. Wide-scale use of RC awaits measures that are more culturally invariant (such as international accelerometer data). © 2012 Human Kinetics, Inc

Advancing the Sustainable Development Goal for Education Through Developmentally Informed Approaches to Measurement

Abstract: While the past decade has seen increased global efforts to develop reliable and valid measures of developmental phenomena for use in diverse populations within and across countries, the UN Sustainable Development Goals (SDG), and in particular the education goal (SDG4) have revealed a dearth of meaningful and valid measures and indicators to monitor countries’ progress toward achieving the 10 SDG4 targets. Developmental science can a) inform the choice of outcomes, processes, and mechanisms that yield the greatest promise in advancing countries ability to formulate solutions; and b) provide guidance on how to measure educational phenomena to ensure maximum policy relevance. Moving forward, developmental science will need to provide rigorous evidence on measures that incorporate the principles of bioecological frameworks on human development and learning to capture the complexity of the multi-level, multi-dimensional, dynamic processes of development and learning that are relevant to achieving SDG4. The chapter concludes with specific recommendations for how developmental scientists can ensure that their research is directly relevant to and can best support the SDG process

Measuring global physical health in children with cerebral palsy: illustration of a multidimensional bi-factor model and computerized adaptive testing

PURPOSE: The purpose of this study was to apply a bi-factor model for the determination of test dimensionality and a multidimensional CAT using computer simulations of real data for the assessment of a new global physical health measure for children with cerebral palsy (CP). METHODS: Parent respondents of 306 children with cerebral palsy were recruited from four pediatric rehabilitation hospitals and outpatient clinics. We compared confirmatory factor analysis results across four models: (1) one-factor unidimensional; (2) two-factor multidimensional (MIRT); (3) bi-factor MIRT with fixed slopes; and (4) bi-factor MIRT with varied slopes. We tested whether the general and content (fatigue and pain) person score estimates could discriminate across severity and types of CP, and whether score estimates from a simulated CAT were similar to estimates based on the total item bank, and whether they correlated as expected with external measures. RESULTS: Confirmatory factor analysis suggested separate pain and fatigue sub-factors; all 37 items were retained in the analyses. From the bi-factor MIRT model with fixed slopes, the full item bank scores discriminated across levels of severity and types of CP, and compared favorably to external instruments. CAT scores based on 10- and 15-item versions accurately captured the global physical health scores. CONCLUSIONS: The bi-factor MIRT CAT application, especially the 10- and 15-item version, yielded accurate global physical health scores that discriminated across known severity groups and types of CP, and correlated as expected with concurrent measures. The CATs have potential for collecting complex data on the physical health of children with CP in an efficient manner

Early Childhood Assessments of Community Pediatric Professionals Predict Autism Spectrum and Attention Deficit Hyperactivity Problems

<p>For clinically referred children with Autism Spectrum Disorder (ASD) or Attention Deficit/Hyperactivity Disorder (ADHD) several early indicators have been described. However, knowledge is lacking on early markers of less severe variants of ASD and ADHD from the general population. The aim of the present study is to identify early indicators of high risk groups for ASD and ADHD problems based on routine data from community pediatric services between infancy and age four. Data are from 1,816 participants who take part in Tracking Adolescents' Individual Lives Survey (TRAILS), a longitudinal study. Information on early developmental factors was extracted from charts of routine Preventive Child Healthcare (PCH) visits. To assess ASD and ADHD problems, respectively, we used the Children's Social Behavior Questionnaire (CSBQ) and the Child Behavior Checklist (CBCL), filled out by parents three times between the ages of 11 and 17. Note that these are parent ratings and not diagnostic instruments performed by trained clinicians. Male gender, low birth weight, low level of education of the mother, social, behavioral, language, psychomotor and eating problems significantly predicted ASD problems (odds ratios (OR) between 1.34 and 2.41). ADHD problems were also predicted by male gender and low level of education of the mother and by maternal smoking during pregnancy, good gross motor skills in first year, early attention and hyperactivity problems, and absence of parent-reported positive behavior (ORs between 1.36 and 1.74). Routine data on early childhood from PCH services are predictive for ASD and ADHD problems in adolescents in the general population. The PCH services are a useful setting to identify high risk groups, and to monitor them subsequently.</p>