Search

Purpose: Different health state utility (HSU) instruments produce different utilities for the same individuals, thereby compromising the intended comparability of economic evaluations of health care interventions. When developing crosswalks, previous studies have indicated nonlinear relationships. This paper inquires into the degree of nonlinearity across the four most widely used HSU-instruments and proposes exchange rates that differ depending on the severity levels of the health state utility scale.Methods: Overall, 7933 respondents from six countries, 1760 in a non-diagnosed healthy group and 6173 in seven disease groups, reported their health states using four different instruments: EQ-5D-5L, SF-6D, HUI-3 and 15D. Quantile regressions investigate the degree of nonlinear relationships between these instruments. To compare the instruments across different disease severities, we split the health state utility scale into utility intervals with 0.2 successive decrements in utility starting from perfect health at 1.00. Exchange rates (ERs) are calculated as the mean utility difference between two utility intervals on one HSU-instrument divided by the difference in mean utility on another HSU-instrument.Results: Quantile regressions reveal significant nonlinear relationships across all four HSU-instruments. The degrees of nonlinearities differ, with a maximum degree of difference in the coefficients along the health state utility scale of 3.34 when SF-6D is regressed on EQ-5D. At the lower end of the health state utility scale, the exchange rate from SF-6D to EQ-5D is 2.11, whilst at the upper end it is 0.38.Conclusion: Comparisons at different utility levels illustrate the fallacy of using linear functions as crosswalks between HSU-instruments. The existence of nonlinear relationships between different HSU-instruments suggests that level-specific exchange rates should be used when converting a change in utility on the instrument used, onto a corresponding utility change had another instrument been used. Accounting for nonlinearities will increase the validity of the comparison for decision makers when faced with a choice between interventions whose calculations of QALY gains have been based on different HSU-instruments. [ABSTRACT FROM AUTHOR]

Objectives: Psychosocial factors are important determinants of an individual's health. This study examines the association between health scores and social network factors on mental health across different life stages.Methods: Data were drawn from the Household Income and Labour Dynamics in Australia survey for adolescents (n = 1739), adults (n = 10,309) and seniors (n = 2287). Hierarchical regression modelling was applied to examine effects within and across age groups. All the variables were derived from the self-completion questionnaire.Results: The social network factors were statistically significant predictors of mental health outcomes for all three life stages. For adolescents, the three social network factors were statistically significant with social isolation having the largest impact (β = -.284, p < .001), followed by social connection (β = .084, p < .001) and social trust having a similar effect (β = .073, p < .001). For adults social isolation had the highest impact (β = -.203, p < .001), followed by social connection (β = .110, p < .001) and social trust (β = .087, p < .001).The results for seniors were social isolation (β = -.188, p < .001), social connection (β = .147, p < .001) and social trust (β = .032, p < .05).Conclusions: After adding the social network factors, the models improved significantly with social isolation playing the most significant role across all life stages, whereas the other social network factors played a differentiated role depending upon the life stage. These findings have practical implications in the design of mental health interventions across different life stages. [ABSTRACT FROM AUTHOR]

Background: The Hospital Anxiety and Depression Scale (HADS) is frequently used in cancer studies, yet its utility for comparing people with cancer with people in the community is uncertain.Methods: HADS scores were obtained from population-based samples of women with (n = 731) and without (n = 158) early-onset breast cancer. Psychometric properties were examined using differential item functioning (DIF) which is the presence of systematic group differences in certain response items independent of the trait being measured.Results: Women with breast cancer scored lower than reference women on anxiety (mean (SD) 7.5 (4.3) vs. 8.2 (4.0); p = 0.06) and depression (3.3 (3.2) vs. 4.2 (3.0); p = 0.003). Group differences remained following adjustment for demographics. Time since diagnosis was not related to anxiety or depression scores. DIF was present in two anxiety and five depression items. Adjustment for DIF did not substantially change the anxiety or depression group differences.Conclusion: Specific sampling or DIF effects do not explain the observation that women with breast cancer have lower levels of anxiety and depression than population controls. The psychometric properties of the HADS appear to be acceptable in these groups. [ABSTRACT FROM AUTHOR]