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Piloting the Geographic Information System (GIS) Methodology as an Analytic Tool for Subjective Wellbeing Research

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Abstract

This article introduces the Geographic Information System (GIS) methodology to Subjective Wellbeing (SWB) research. The interactive mapping and analysis tools of GIS are combined with SWB to demonstrate an alternative method of data analysis and presentation encompassing spatial context. The SWB of the Victorian population was measured using a representative state wide telephone survey conducted for the wider Community Indicators Victoria project. GIS methodology is used for the presentation and analysis of population SWB collected from 24,000 Victorians and mapped according to 79 Local Government Areas. The advantages of the alternative method of data presentation are discussed and the wellbeing of the state considered within geographical context. Future applications for the use of GIS and SWB are discussed, including diagnostic and outcome measures for government policy and planning.

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Notes

  1. www.communityindicators.net.au

  2. www.esri.com

References

  • Albrecht, J., & Ramasubramanian, L. (2004). The moving target: a geographic index of relative wellbeing. Journal of Medical Systems, 28(4), 371–384.

    Article  Google Scholar 

  • Andrews, F. M., & Withey, S. B. (1976). Social indicators of well-being: American's perceptions of life quality. New York: Plenum.

    Google Scholar 

  • Australian Bureau of Statistics (2008). Melbourne: a social Atlas, 2006.

  • Blunsdon, B., & Davern, M. (2007). Measuring wellness through interdisciplinary community development: linking the physical, economic and social environment. Journal of Community Practice, 15(1-2), 217–238.

    Article  Google Scholar 

  • Bradburn, N. M., & Caplovitz, D. (1965). Reports on happiness: a pilot study of behaviour related to mental health. Chicago: Aldine.

    Google Scholar 

  • Brereton, F., Clinch, P., & Ferreira, S. (2008). Happiness, geography and the environment. Ecological Economics, 65, 386–396.

    Article  Google Scholar 

  • Campbell, A., Converse, P. E., & Rodgers, W. L. (1976). The quality of American life: perceptions, evaluations, and satisfactions. New York: Sage.

    Google Scholar 

  • Chaix, B., Merlo, J., Subramanian, S. V., Lynch, J., & Chauvin, P. (2005). Comparison of a spatial perspective with the multilevel analytical approach in neighborhood studies: the case of mental and behavioral disorders due to psychoactive substance use in Malmo, Sweden, 2001. Amercian Journal of Epidemiology, 162(2), 171–182.

    Article  Google Scholar 

  • Cummins, R. A. (2009). Encouraging governments to enhance the happiness of their nation: step 1: understand subjective wellbeing. Social Indicators Research, 91(1), 23–36.

    Article  Google Scholar 

  • Cummins, R. A., Eckersley, R., Pallant, J., Van Vugt, J., & Misajon, R. (2003). Developing a national index of subjective wellbeing: the Australian unity wellbeing index. Social Indicators Research, 64(2), 159–190.

    Article  Google Scholar 

  • Cummins, R. A., Woerner, J., Gibson, A., Weinberg, M., Collard, J., & Cheste, M. (2009). Australian unity wellbeing index: Report 21.0—“The Wellbeing of Australians—gambling, chocolate and swine flu”: Australian Centre on Quality of Life, School of Psychology, Deakin University.

  • Davern, M., Cummins, R. A., & Stokes, M. (2007). Subjective wellbeing as an affective/cognitive construct. Journal of Happiness Studies, 8(4), 429–449.

    Article  Google Scholar 

  • DeNeve, K. M., & Cooper, H. (1998). The happy personality: a meta-analysis of 137 personality traits and subjective well-being. Psychological Bulletin, 124(2), 197–229.

    Article  Google Scholar 

  • Diener, E., & Ryan, K. (2009). Subjective well-being: a general overview. South African Journal of Psychology, 39(4), 391–406.

    Google Scholar 

  • Diener, E., Suh, E. M., Lucas, R. E., & Smith, H. L. (1999). Subjective well-being: three decades of progress. Psychological Bulletin, 125(2), 276–302.

    Article  Google Scholar 

  • Gurin, G., Veroff, J., & Feld, S. (1960). Americans view their mental health: a nationwide interview survey. Joint commission on mental illness and health series. Oxford: Basic.

    Google Scholar 

  • Headey, B. (2006). Subjective well-being: revisions to dynamic equilibrium theory using national panel data and panel regression methods. Social Indicators Research, 79(3), 369–403.

    Article  Google Scholar 

  • Hirshorn, B. A., & Stewart, J. E. (2003). Geographic information systems in community-based gerontological research and practice. Journal of Applied Gerontology, 22(1), 134–151.

    Article  Google Scholar 

  • Holden, M. (2009). Community interests and indicator system success. Social Indicators Research, 92(3), 429–448.

    Article  Google Scholar 

  • Jones, P. A. (2007). Researching the geography of mental wellbeing. Journal of Mental Health, 16(4), 439–443.

    Article  Google Scholar 

  • Kelly, J. G. (2003). Science and community psychology: social norms for pluralistic inquiry. American Journal of Community Psychology, 31(3-4), 213–217.

    Article  Google Scholar 

  • Koivumaa-Honkanen, H., Honkanen, R., Antikainen, R., Hintikka, J., Laukkanen, E., Honkalampi, K., et al. (2001). Self-reported life satisfaction and recovery from depression in a 1-year prospective study. Acta Psychiatrica Scandinavica, 103(1), 38–44.

    Article  Google Scholar 

  • Koivumaa-Honkanen, H., Kaprio, J., Honkanen, R., Viinamaki, H., & Koskenvuo, M. (2004). Life satisfaction and depression in a 15-year follow-up of healthy adults. Social Psychiatry and Psychiatric Epidemiology, 39(12), 994–999.

    Article  Google Scholar 

  • Luke, D. A. (2005). Getting the big picture in community science: methods that capture context. American Journal of Community Psychology, 35(3-4), 185–200.

    Article  Google Scholar 

  • Mason, M., Cheung, I., & Walker, L. (2004). Substance use, social networks and the geography of urban adolescents. Substance Use & Misuse, 39(10-12), 1751–1777.

    Article  Google Scholar 

  • Michalos, A. C. (1985). Multiple disrepancies theory (MDT). Social Indicators Research, 16(4), 347–413.

    Article  Google Scholar 

  • Ormsby, T., Napoleon, E., & Burke, R. (2003). Getting to know ArcGIS desktop: basics of ArcView, ArcEditor and ArcInfo (2nd ed.). Redlands: CA ESRI.

    Google Scholar 

  • Ramos, O. T., & Jones, K. (2005). Comprehensive community indicators systems. National Civic Review, 94(2), 74–77.

    Article  Google Scholar 

  • Rush, B., Veldhuizen, S., & Adlaf, E. (2007). Mapping the prevalence of problem gambling and its association with treatment accessibility and proximity to gambling venues. Journal of Gambling Issues, 20, 193–213.

    Article  Google Scholar 

  • Talen, E., & Shah, S. (2007). Neighborhood evaluation using GIS—An exploratory study. Environment and Behavior, 39(5), 583–615.

    Article  Google Scholar 

  • Tilt, J. H., Unfried, T. M., & Roca, B. (2007). Using objective and subjective measures of neighborhood greenness and accessible destinations for understanding walking trips and BMI in Seattle, Washington. Amercian Journal of Health Promotion, 21(4), 371–379.

    Google Scholar 

  • Van Hemert, D. A., Van de Vijver, F. J. R., & Poortinga, Y. H. (2002). The Beck depression inventory as a measure of subjective well-being: a cross-national study. Journal of Happiness Studies, 3(3), 257–286.

    Article  Google Scholar 

  • Wiseman, J., Heine, W., Langworthy, A., McLean, N., Pyke, J., Raysmith, H., et al. (2006). Developing a Community Indicators Framework for Victoria: The final report of the Victorian Community Indicators Project (VCIP).

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Authors and Affiliations

  1. McCaughey Centre: VicHealth Centre for the Promotion of Mental Health and Community Wellbeing, School of Population Health, University of Melbourne, Melbourne, Victoria, 3010, Australia

    Melanie T. Davern

  2. Department of Human Services, Victoria, Australia

    Xiaogang Chen

Authors
  1. Melanie T. Davern
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  2. Xiaogang Chen
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Correspondence to Melanie T. Davern.

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Davern, M.T., Chen, X. Piloting the Geographic Information System (GIS) Methodology as an Analytic Tool for Subjective Wellbeing Research. Applied Research Quality Life 5, 105–119 (2010). https://doi.org/10.1007/s11482-010-9095-5

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  • DOI: https://doi.org/10.1007/s11482-010-9095-5

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