Cross-cultural measurement invariance of the Quality of Life Enjoyment and Satisfaction Questionnaire-Short form across ten countries: the application of Bayesian approximate measurement invariance

BACKGROUND: The Quality of Life Enjoyment and Satisfaction Questionnaire-Short Form (Q-LES-Q-SF) is the most frequently used generic quality of life (QOL) measure in many countries and cultures worldwide. However, no single study has been carried out to investigate whether this questionnaire performs similarly across diverse cultures/countries. Accordingly, this study aimed to assess the cross-cultural measurement invariance of the Q-LES-Q-SF across ten different countries. METHODS: The Q-LES-Q-SF was administrated to a sample of 2822 university students from ten countries: Bangladesh, Brazil, Croatia, India, Nepal, Poland, Serbia, Turkey, the United Arab Emirates, and Vietnam. The Bayesian approximate measurement invariance approach was used to assess the measurement invariance of the Q-LES-Q-SF. RESULTS: Approximate measurement invariance did not hold across the countries for the Q-LES-Q-SF, with only two out of 14 items being non-invariant; namely items related to doing household and leisure time activities. CONCLUSIONS: Our findings did not support the cross-cultural measurement invariance of the Q-LES-Q-SF; thus, considerable caution is warranted when comparing QOL scores across different countries with this measure. Item rewording and adaptation along with calibrating non-invariant items may narrow these differences and help researchers to create an invariant questionnaire for reliable and valid QOL comparisons across different countries

Cross-cultural measurement invariance of the Quality of Life Enjoyment and Satisfaction Questionnaire-Short form across ten countries: the application of Bayesian approximate measurement invariance

Background The Quality of Life Enjoyment and Satisfaction Questionnaire-Short Form (Q-LES-Q-SF) is the most frequently used generic quality of life (QOL) measure in many countries and cultures worldwide. However, no single study has been carried out to investigate whether this questionnaire performs similarly across diverse cultures/countries. Accordingly, this study aimed to assess the cross-cultural measurement invariance of the Q-LES-Q-SF across ten different countries. Methods The Q-LES-Q-SF was administrated to a sample of 2822 university students from ten countries: Bangladesh, Brazil, Croatia, India, Nepal, Poland, Serbia, Turkey, the United Arab Emirates, and Vietnam. The Bayesian approximate measurement invariance approach was used to assess the measurement invariance of the Q-LES-Q-SF. Results Approximate measurement invariance did not hold across the countries for the Q-LES-Q-SF, with only two out of 14 items being non-invariant; namely items related to doing household and leisure time activities. Conclusions Our findings did not support the cross-cultural measurement invariance of the Q-LES-Q-SF; thus, considerable caution is warranted when comparing QOL scores across different countries with this measure. Item rewording and adaptation along with calibrating non-invariant items may narrow these differences and help researchers to create an invariant questionnaire for reliable and valid QOL comparisons across different countries

Estimating global injuries morbidity and mortality: Methods and data used in the Global Burden of Disease 2017 study

Background: While there is a long history of measuring death and disability from injuries, modern research methods must account for the wide spectrum of disability that can occur in an injury, and must provide estimates with sufficient demographic, geographical and temporal detail to be useful for policy makers. The Global Burden of Disease (GBD) 2017 study used methods to provide highly detailed estimates of global injury burden that meet these criteria. Methods: In this study, we report and discuss the methods used in GBD 2017 for injury morbidity and mortality burden estimation. In summary, these methods included estimating cause-specific mortality for every cause of injury, and then estimating incidence for every cause of injury. Non-fatal disability for each cause is then calculated based on the probabilities of suffering from different types of bodily injury experienced. Results: GBD 2017 produced morbidity and mortality estimates for 38 causes of injury. Estimates were produced in terms of incidence, prevalence, years lived with disability, cause-specific mortality, years of life lost and disability-adjusted life-years for a 28-year period for 22 age groups, 195 countries and both sexes. Conclusions: GBD 2017 demonstrated a complex and sophisticated series of analytical steps using the largest known database of morbidity and mortality data on injuries. GBD 2017 results should be used to help inform injury prevention policy making and resource allocation. We also identify important avenues for improving injury burden estimation in the future. © Author(s) (or their employer(s)) 2020. Re-use permitted under CC B Y. Published by BMJ