Suchergebnisse

Zusammenfassung. Die meisten der derzeit verfügbaren Mehriteminstrumente zur Erfassung des Wohlbefindens und der gesundheitsbezogenen Lebensqualität sind sehr lang und umfangreich, während kürzere Verfahren oft Einbußen in der Messpräzision bedingen. Die Messungen der unterschiedlichen Verfahren sind darüber hinaus kaum vergleichbar. Diese Nachteile schränken die praktische Anwendbarkeit der Wohlbefindensmessung für wissenschaftliche sowie klinische Untersuchungen ein. Am Beispiel des internationalen KIDSCREEN Projektes wird aufgezeigt, wie moderne Verfahren der Item-Response Theorie (IRT), des Itembanking und des Computer Adaptiven Testens (CAT) zur Lösung der genannten Probleme beitragen können. Die 6 Items der IRT skalierten Skala Psychisches Wohlbefinden des KIDSCREEN-52 Lebensqualitätsinstruments konnten mit weiteren 20 Items von 5 anderen Lebensqualitätsinstrumenten auf eine gemeinsame Metrik kalibriert werden. Die entwickelte Itembank erhöht die Reliabilität der Messung von α = .81 auf α = .92, ermöglicht eine individuelle Diagnostik und die Vergleichbarkeit der Messergebnisse über die Instrumente. Die Itembank kann als Grundlage für einen Computer Adaptiven Test (CAT) psychischen Wohlbefindens verwendet werden.

OBJECTIVE: The European Organisation for Research and Treatment of Cancer (EORTC) QLQ-C30 health-related quality of life questionnaire is one of the most widely used cancer-specific health-related quality of life questionnaires worldwide. General population norm data can facilitate the interpretation of QLQ-C30 data obtained from cancer patients. This study aimed at systematically collecting norm data from the general population to develop European QLQ-C30 norm scores and to generate comparable norm data for individual countries in Europe and North America. METHODS: We collected QLQ-C30 data from the general population across 11 European Union (EU) countries, Russia, Turkey, Canada and United States (n > /= 1000/country). Representative samples were stratified by sex and age groups (18-39, 40-49, 50-59, 60-69 and > /= 70 years). After applying weights based on the United Nations population distribution statistics, we calculated QLQ-C30 domain scores to generate a 'European QLQ-C30 Norm' based on the EU countries. Further, we calculated QLQ-C30 norm scores for all 15 individual countries. RESULTS: A total of 15,386 respondents completed the online survey. For the EU sample, most QLQ-C30 domains showed differences by sex/age, with men scoring somewhat better health than women, while age effects varied across domains. Substantially larger differences were seen in inter-country comparisons, with Austrian and Dutch respondents reporting consistently better health compared with British and Polish respondents. CONCLUSIONS: This study is the first to systematically collect EORTC QLQ-C30 general population norm data across Europe and North America applying a consistent data collection method across 15 countries. These new norm data facilitate valid intra-country as well as inter-country comparisons and QLQ-C30 score interpretation.

OBJECTIVE: The computer-adaptive test (CAT) of the European Organisation for Research and Treatment of Cancer (EORTC), the EORTC CAT Core, assesses the same 15 domains as the EORTC QLQ-C30 health-related quality of life questionnaire but with increased precision, efficiency, measurement range and flexibility. CAT parameters for estimating scores have been established based on clinical data from cancer patients. This study aimed at establishing the European Norm for each CAT domain based on general population data. METHODS: We collected representative general population data across 11 European Union (EU) countries, Russia, Turkey, Canada and the United States (n > /= 1000/country; stratified by sex and age). We selected item subsets from each CAT domain for data collection (totalling 86 items). Differential item functioning (DIF) analyses were conducted to investigate cross-cultural measurement invariance. For each domain, means and standard deviations from the EU countries (weighted by country population, sex and age) were used to establish a T-metric with a European general population mean = 50 (standard deviation = 10). RESULTS: A total of 15,386 respondents completed the online survey (n = 11,343 from EU countries). EORTC CAT Core norm scores for all 15 countries were calculated. DIF had negligible impact on scoring. Domain-specific T-scores differed significantly across countries with small to medium effect sizes. CONCLUSION: This study establishes the official European Norm for the EORTC CAT Core. The European CAT Norm can be used globally and allows for meaningful interpretation of scores. Furthermore, CAT scores can be compared with sex- and age-adjusted norm scores at a national level within each of the 15 countries.