Profile of subjective quality of life and its correlates in a nation-wide sample of high school students in an Arab setting using the WHOQOL-Bref

<p>Abstract</p> <p>Background</p> <p>The upsurge of interest in the quality of life (QOL) of children is in line with the 1989 Convention on the Rights of the Child, which stressed the child's right to adequate circumstances for physical, mental, and social development. The study's objectives were to: (i) highlight how satisfied Kuwaiti high school students were with life circumstances as in the WHOQOL-Bref; (ii) assess the prevalence of at risk status for impaired QOL and establish the QOL domain normative values; and (iii) examine the relationship of QOL with personal, parental, and socio-environmental factors.</p> <p>Method</p> <p>A nation-wide sample of students in senior classes in government high schools (N = 4467, 48.6% boys; aged 14-23 years) completed questionnaires that included the WHOQOL-Bref.</p> <p>Results</p> <p>Using Cummins' norm of 70% - 80%, we found that, as a group, they barely achieved the well-being threshold score for physical health (70%), social relations (72.8%), environment (70.8%) and general facet (70.2%), but not for psychological health (61.9%). These scores were lower than those reported from other countries. Using the recommended cut-off of <1<it>SD </it>of population mean, the prevalence of at risk status for impaired QOL was 12.9% - 18.8% (population age-adjusted: 15.9% - 21.1%). In all domains, boys had significantly higher QOL than girls, mediated by anxiety/depression; while the younger ones had significantly higher QOL (<it>p </it>< 0.001), mediated by difficulty with studies and social relations. Although poorer QOL was significantly associated with parental divorce and father's low socio-economic status, the most important predictors of poorer QOL were perception of poor emotional relationship between the parents, poor self-esteem and difficulty with studies.</p> <p>Conclusion</p> <p>Poorer QOL seemed to reflect a circumstance of social disadvantage and poor psychosocial well-being in which girls fared worse than boys. The findings indicate that programs that address parental harmony and school programs that promote study-friendly atmospheres could help to improve psychosocial well-being. The application of QOL as a school population health measure may facilitate risk assessment and the tracking of health status.</p

Regression models for ordinal response variables

Regression models for ordinal response variables are available since the late 1980s, and many statistical software packages have been upgraded to perfom these calculations. However, ordinal regression still seems to be overlooked in health sciences. This might be due to the available literatur, which is critizised to be too technical and hard to understand for endusers. Thus, the aim of this paper is to give an overview of popular ordinal regression models and to outline the advantages of its model results. First, the characteristics and interpretations of the "proportional odds model" are presented. The model is exemplary applied to variables of a dataset. A focus is set to the interpretation of the model results. Secondly, the characteristics and interpretations of the "continuation ratio model" are presented. Again, the model is exemplary applied to variables of a dataset, while the focus is set to the interpretation of the model results. The results of both models are contrasted to results of ordinary logistic regression and discussed with respect of their differences.Verfahren zur Auswertung ordinaler Variablen mittels Regressionsanalysen sind seit ca. 25 Jahren in der Literatur beschrieben, und viele Statistik-Softwarepakete wurden in den letzten Jahren um die Funktion dieser speziellen Art der Regression erweitert. Dennoch hält sich der Einsatz der Verfahren bisweilen stark in Grenzen. Dies mag daran liegen, dass die vorhandene Literatur zu spezialisiert und für den Anwender nur schwer verständlich ist. Ziel des Artikels ist es daher, die gängigen Verfahren der ordinalen Regression vorzustellen sowie den Nutzen ihrer Ergebnisse an Beispielen zu verdeutlichen. Der Artikel versteht sich als praktische Einführung in das Thema und beschreibt nacheinander die Methoden der "Proportional Odds Models" sowie der "Continuation Ratio Models". Beide Methoden werden beispielhaft angewendet, wobei ein Fokus auf die Interpretation der Modellergebnisse gelegt wird. Die Modellergebnisse beider Verfahren werden den Ergebnissen von alternativen logistischen Regressionsanalysen gegenübergestellt und hinsichtlich ihrer Unterschiede diskutiert