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Likert scales are frequently used in public health research, but are subject to scale perception bias. This study sought to explore scale perception bias in quality-of-life (QoL) self-assessment and assess its relationships with commuting mode in the Sydney Travel and Health Study.
Multilevel ordinal logistic regression analysis was used to analyse the association between two global QoL items about overall QoL and health satisfaction, with usual travel mode to work or study. Anchoring vignettes were applied using parametric and simpler nonparametric methods to detect and adjust for differences in reporting behaviour across age, sex, education, and income groups.
The anchoring vignettes exposed differences in scale responses across demographic groups. After adjusting for these biases, public transport users (OR = 0.37, 95 % CI 0.21–0.65), walkers (OR = 0.44, 95 % CI 0.24–0.82), and motor vehicle users (OR = 0.47, 95 % CI 0.25–0.86) were all found to have lower odds of reporting high QoL compared with bicycle commuters. Similarly, the odds of reporting high health satisfaction were found to be proportionally lower amongst all competing travel modes: motor vehicle users (OR = 0.31, 95 % CI 0.18–0.56), public transport users (OR = 0.34, 95 % CI 0.20–0.57), and walkers (OR = 0.35, 95 % CI 0.20–0.64) when compared with cyclists. Fewer differences were observed in the unadjusted models.
Application of the vignettes by the two approaches removed scaling biases, thereby improving the accuracy of the analyses of the associations between travel mode and quality of life. The adjusted results revealed higher quality of life in bicycle commuters compared with all other travel mode users.
Murray, C. J., Tandon, A., Salomon, J. A., Mathers, C. D., Sadana, R. (2002). Cross-population comparability of evidence for health policy. In C. J. Murray & D. E. Evans (Eds.), Health systems performance assessment: Debates, methods and empiricism (pp. 705–713). Geneva: World Health Organization. http://www.who.int/health_financing/documents/cov-hspa/en/. Accessed 15 April 2015.
King, G., Murray, C. J., Salomon, J. A., & Tandon, A. (2004). Enhancing the validity and cross-cultural comparability of measurement in survey research. American Political Science Review, 98(01), 191–207. CrossRef
Araña, J. E., & León, C. J. (2012). Scale-perception bias in the valuation of environmental risks. Applied Economics, 44(20), 2607–2617. CrossRef
Cummins, R. A. (2013). Subjective well-being, homeostatically protected mood and depression: A synthesis. In A. Delle Fave (Ed.), The exploration of happiness (pp. 77–95). Amsterdam: Springer.
Sadana, R. (2000). Comparative analyses of more than 50 household surveys on health status. Geneva: World Health Organization.
Layes, A., Asada, Y., Kepart, G. (2012). Whiners and deniers–what does self-rated health measure? Social Science & Medicine, 75(1), 1–9.
Taillefer, M.-C., Dupuis, G., Roberge, M.-A., & LeMay, S. (2003). Health-related quality of life models: Systematic review of the literature. Social Indicators Research, 64(2), 293–323. CrossRef
Veenhoven, R. (2000). The four qualities of life. Journal of Happiness Studies, 1(1), 1–39. CrossRef
Salomon, J. A., Tandon, A., Murray, C. J. (2001). Using vignettes to improve cross-population comparability of health surveys: Concepts, design, and evaluation techniques. Global Programme on Evidence for Health Policy Discussion Paper. 41. http://www.who.int/healthinfo/paper41.
Grol-Prokopczyk, H., Freese, J., & Hauser, R. M. (2011). Using anchoring vignettes to assess group differences in general self-rated health. Journal of Health and Social., 52(2), 246–261. CrossRef
Angelini, V., Cavapozzi, D., Corazzini, L., & Paccagnella, O. (2013). Do Danes and Italians rate life satisfaction in the same way? Using vignettes to correct for individual-specific scale biases. Oxford Bulletin of Economics and Statistics, 76(5), 643–666. CrossRef
Dowd, J. B., & Todd, M. (2011). Does self-reported health bias the measurement of health inequalities in US adults? evidence using anchoring vignettes from the health and retirement study. Journals of Gerontology—Series B Psychological Sciences and Social Sciences, 66 B(4), 478–489. CrossRef
Hirve, S., Gomez-Olive, X., Oti, S., Debpuur, C., Juvekar, S., Tollman, S., et al. (2013). Use of anchoring vignettes to evaluate health reporting amongst adults aged 50 years and above in Africa and Asia–testing assumptions. Global Health Action, 6, 21064.
Peracchi, F., & Rossetti, C. (2012). Heterogeneity in health responses and anchoring vignettes. Empirical Economics, 42(2), 513–538. CrossRef
Au, N., Lorgelly, P. K. (2014). Anchoring vignettes for health comparisons: An analysis of response consistency. Quality of Life Research, 23(6), 1721–31.
King, G., & Wand, J. (2007). Comparing incomparable survey responses: Evaluating and selecting anchoring vignettes. Political Analysis., 15(1), 46–66. CrossRef
Tandon, A., Murray, C. J., Salomon, J. A., King, G. (2003). Statistical models for enhancing cross-population comparability. In C. J. Murray & D. E. Evans (Eds.), Health systems performance assessment: Debates, methods and empiricism (pp. 727–746). Geneva: World Health Organization. http://www.who.int/healthinfo/paper42. Accessed 17 April 2015.
Frank, L. D. (2000). Land use and transportation interaction implications on public health and quality of life. Journal of Planning Education and Research., 20(1), 6–22. CrossRef
Novaco, R. W., Gonzalez, O. I. (2009). Commuting and well-being. In Y. Amichai-Hamburger (Ed.), Technology and well-being (pp. 174–205). New York: Cambridge University Press.
Renalds, A., Smith, T. H., & Hale, P. J. (2010). A systematic review of built environment and health. Family & Community Health, 33(1), 68–78. CrossRef
Kelly, P., Kahlmeier, S., Götschi, T., Orsini, N., Richards, J., Roberts, N., et al. (2014). Systematic review and meta-analysis of reduction in all-cause mortality from walking and cycling and shape of dose response relationship. International Journal of al Nutrition and Physical Activity, 11(1), 132.
Murphy, B., Herrman, H., Hawthorne, G., Pinzone, T., & Evert, H. (2000). Australian WHOQoL instruments: User’s manual and interpretation guide. Melbourne: Australian WHOQOL Field Study Centre.
Cummins, R. A. (2000). Personal income and subjective well-being: A review. Journal of Happiness Studies, 1(2), 133–158. CrossRef
Rabe-Hesketh, S., & Skrondal, A. (2002). Estimating CHOPIT models in GLLAMM: Political efficacy example from King et al. (2002). London: Institute of Psychiatry, King’s College.
Akaike, H. (1974). A new look at the statistical model identification. Automatic Control, IEEE Transactions on., 19(6), 716–723. CrossRef
Schwarz, G. (1978). Estimating the dimension of a model. The annals of statistics., 6(2), 461–464. CrossRef
Lumley, T., & Scott, A. (2015). AIC and BIC for modeling with complex survey data. Journal of Survey Statistics and Methodology., 3(1), 1–18. CrossRef
Cummins, R. A., Gullone, E., & Lau, A. L. D. (2002). A model of subjective well-being homeostasis: The role of personality. In E. Gullone & R. A. Cummins (Eds.), The universality of subjective wellbeing indicators: Social indicators research series (pp. 7–46). Dordrecht: Kluwer.
Australian Bureau of Statistics. (2014). Australian social trends, July 2013. CAT 4102.0. Canberra: ABS.
Carse, A. (2011). Assessment of transport quality of life as an alternative transport appraisal technique. Journal of Transport Geography, 19(5), 1037–1045. CrossRef
Cavill, N., Kahlmeier, S., Rutter, H., Racioppi, F., & Oja, P. (2008). Economic analyses of transport infrastructure and policies including health effects related to cycling and walking: A systematic review. Transport Policy, 15(5), 291–304. CrossRef
Mulley, C., Tyson, R., McCue, P., Rissel, C., & Munro, C. (2013). Valuing active travel: Including the health benefits of sustainable transport in transportation appraisal frameworks. Research in Transportation Business & Management., 7, 27–34. CrossRef
Delbosc, A. (2012). The role of well-being in transport policy. Transport Policy, 23, 25–33. CrossRef
Gatersleben, B., & Uzzell, D. (2007). Affective appraisals of the daily commute: Comparing perceptions of drivers, cyclists, walkers, and users of public transport. Environment and Behavior, 39(3), 416–431. CrossRef
Tandon A, Murray C, Salomon J, King G. (2001) Statistical methods to enhance cross-population comparability (Global Programme on Evidence for Health Policy Discussion Paper No. 42). Geneva: World Health Organization.
- Correcting bias in self-rated quality of life: an application of anchoring vignettes and ordinal regression models to better understand QoL differences across commuting modes
- Springer International Publishing
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