Cross-cultural validity of four quality of life scales in persons with spinal cord injury

<p>Abstract</p> <p>Background</p> <p>Quality of life (QoL) in persons with spinal cord injury (SCI) has been found to differ across countries. However, comparability of measurement results between countries depends on the cross-cultural validity of the applied instruments. The study examined the metric quality and cross-cultural validity of the Satisfaction with Life Scale (SWLS), the Life Satisfaction Questionnaire (LISAT-9), the Personal Well-Being Index (PWI) and the 5-item World Health Organization Quality of Life Assessment (WHOQoL-5) across six countries in a sample of persons with spinal cord injury (SCI).</p> <p>Methods</p> <p>A cross-sectional multi-centre study was conducted and the data of 243 out-patients with SCI from study centers in Australia, Brazil, Canada, Israel, South Africa, and the United States were analyzed using Rasch-based methods.</p> <p>Results</p> <p>The analyses showed high reliability for all 4 instruments (person reliability index .78-.92). Unidimensionality of measurement was supported for the WHOQoL-5 (Chi²= 16.43, df = 10, p = .088), partially supported for the PWI (Chi²= 15.62, df = 16, p = .480), but rejected for the LISAT-9 (Chi²= 50.60, df = 18, p = .000) and the SWLS (Chi²= 78.54, df = 10, p = .000) based on overall and item-wise Chi²tests, principal components analyses and independent t-tests. The response scales showed the expected ordering for the WHOQoL-5 and the PWI, but not for the other two instruments. Using differential item functioning (DIF) analyses potential cross-country bias was found in two items of the SWLS and the WHOQoL-5, three items of the LISAT-9 and four items of the PWI. However, applying Rasch-based statistical methods, especially subtest analyses, it was possible to identify optimal strategies to enhance the metric properties and the cross-country equivalence of the instruments post-hoc. Following the post-hoc procedures the WHOQOL-5 and the PWI worked in a consistent and expected way in all countries.</p> <p>Conclusions</p> <p>QoL assessment using the summary scores of the WHOQOL-5 and the PWI appeared cross-culturally valid in persons with SCI. In contrast, summary scores of the LISAT-9 and the SWLS have to be interpreted with caution. The findings of the current study can be especially helpful to select instruments for international research projects in SCI.</p

Understanding human functioning using graphical models

<p>Abstract</p> <p>Background</p> <p>Functioning and disability are universal human experiences. However, our current understanding of functioning from a comprehensive perspective is limited. The development of the International Classification of Functioning, Disability and Health (ICF) on the one hand and recent developments in graphical modeling on the other hand might be combined and open the door to a more comprehensive understanding of human functioning. The objective of our paper therefore is to explore how graphical models can be used in the study of ICF data for a range of applications.</p> <p>Methods</p> <p>We show the applicability of graphical models on ICF data for different tasks: Visualization of the dependence structure of the data set, dimension reduction and comparison of subpopulations. Moreover, we further developed and applied recent findings in causal inference using graphical models to estimate bounds on intervention effects in an observational study with many variables and without knowing the underlying causal structure.</p> <p>Results</p> <p>In each field, graphical models could be applied giving results of high face-validity. In particular, graphical models could be used for visualization of functioning in patients with spinal cord injury. The resulting graph consisted of several connected components which can be used for dimension reduction. Moreover, we found that the differences in the dependence structures between subpopulations were relevant and could be systematically analyzed using graphical models. Finally, when estimating bounds on causal effects of ICF categories on general health perceptions among patients with chronic health conditions, we found that the five ICF categories that showed the strongest effect were plausible.</p> <p>Conclusions</p> <p>Graphical Models are a flexible tool and lend themselves for a wide range of applications. In particular, studies involving ICF data seem to be suited for analysis using graphical models.</p