IDEAS home Printed from https://ideas.repec.org/a/eee/socmed/v65y2007i3p524-535.html
   My bibliography  Save this article

Biographical disruption associated with multiple sclerosis: Using propensity scoring to assess the impact

Author

Listed:
  • Green, Gill
  • Todd, Jennifer
  • Pevalin, David

Abstract

Chronic illness such as multiple sclerosis (MS) is often associated with 'biographical disruption', a concept that is derived from qualitative narrative analyses examining how people make sense of their illness in the context of their lives [Bury, M. (1982). Chronic illness as biographical disruption. Sociology of Health and Illness, 4, 167-182]. This paper attempts to operationalise the idea of disruption to one's life trajectory in quantitative analysis by examining the social, economic and emotional disruption associated with MS. A number of studies have suggested that it impacts negatively on employment, income and sexual relationships; however previous research has been based upon samples of people with MS (pwMS), with a dearth of studies comparing pwMS with the general population. This study reports a systematic comparison of MS and non-MS households to enable the impact of MS to be quantified in terms of household composition and marital status; household income; economic activity; and to determine whether biographical disruptions such as relationship breakdown or unemployment are more or less prevalent among those affected by MS compared to the general population. The MS sample came from randomly selected members of the UK MS Society (n=783) and those accessing the MS Society website (n=133). Data for the general population came from the 2001/02 British General Household Survey (GHS). Cases from the MS Society sample were matched using propensity scoring with cases from the GHS. The results of the matched analysis show that both men and women with MS are significantly less likely to be employed than those in the general population and are significantly more likely to have a 'below average' household income, despite the fact that they are in a higher social class and have higher educational levels than people in the general population. Differences between the MS and GHS samples in terms of marital status become non-significant when socio-demographic variables are controlled for using propensity scoring. This study provides robust evidence on how MS impacts on and disrupts the life of the person with MS and their household in terms of income and employment.

Suggested Citation

  • Green, Gill & Todd, Jennifer & Pevalin, David, 2007. "Biographical disruption associated with multiple sclerosis: Using propensity scoring to assess the impact," Social Science & Medicine, Elsevier, vol. 65(3), pages 524-535, August.
    • Handle: RePEc:eee:socmed:v:65:y:2007:i:3:p:524-535
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0277-9536(07)00120-7
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Kobelt, Gisela & Lindgren, Peter & Smala, Antje & Jönsson, Bengt, 2000. "Costs and Quality of Life in Multiple Sclerosis. A Cross-Sectional Observational Study in Germany," SSE/EFI Working Paper Series in Economics and Finance 399, Stockholm School of Economics.
    2. Kobelt, Gisela & Lindgren, Peter & Parkin, David & Francis, David A. & Johnson, Michael & Bates, David & Jönsson, Bengt, 2000. "Costs and Quality of Life in Multiple Sclerosis. A Cross-Sectional Observational Study in the UK," SSE/EFI Working Paper Series in Economics and Finance 398, Stockholm School of Economics.
    3. Rajeev H. Dehejia & Sadek Wahba, 2002. "Propensity Score-Matching Methods For Nonexperimental Causal Studies," The Review of Economics and Statistics, MIT Press, vol. 84(1), pages 151-161, February.
    4. Dyck, Isabel, 1995. "Hidden geographies: The changing lifeworlds of women with multiple sclerosis," Social Science & Medicine, Elsevier, vol. 40(3), pages 307-320, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. B. Svendsen & N. Grytten & L. Bø & H. Aarseth & T. Smedal & K-M. Myhr, 2018. "The economic impact of multiple sclerosis to the patients and their families in Norway," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 19(9), pages 1243-1257, December.
    2. Nelsensius Klau Fauk & Lillian Mwanri & Hailay Abrha Gesesew & Paul Russell Ward, 2023. "Biographical Reinvention: An Asset-Based Approach to Understanding the World of Men Living with HIV in Indonesia," IJERPH, MDPI, vol. 20(16), pages 1-16, August.
    3. Tan, Catherine D., 2018. "“I'm a normal autistic person, not an abnormal neurotypical”: Autism Spectrum Disorder diagnosis as biographical illumination," Social Science & Medicine, Elsevier, vol. 197(C), pages 161-167.
    4. Campbell, Chadwick K., 2021. "Structural and intersectional biographical disruption: The case of HIV disclosure among a sample of black gay and bisexual men," Social Science & Medicine, Elsevier, vol. 280(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gisela Kobelt & Jenny Berg & Peter Lindgren & M. Battaglia & C. Lucioni & A. Uccelli, 2006. "Costs and quality of life of multiple sclerosis in Italy," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 7(2), pages 45-54, July.
    2. Gisela Kobelt & Jenny Berg & Peter Lindgren & Bengt Jönsson, 2006. "Costs and quality of life in multiple sclerosis in Europe: method of assessment and analysis," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 7(2), pages 5-13, July.
    3. Turner, Alex J. & Fichera, Eleonora & Sutton, Matt, 2021. "The effects of in-utero exposure to influenza on mental health and mortality risk throughout the life-course," Economics & Human Biology, Elsevier, vol. 43(C).
    4. François Fall & Akim Almouksit, 2016. "The impact of formal financing on small informal enterprises in Comoros," Working Papers hal-01566389, HAL.
    5. Amarendra Sharma, 2019. "Indira Awas Yojana and Housing Adequacy: An Evaluation using Propensity Score Matching," ASARC Working Papers 2019-05, The Australian National University, Australia South Asia Research Centre.
    6. Sant’Anna, Pedro H.C. & Zhao, Jun, 2020. "Doubly robust difference-in-differences estimators," Journal of Econometrics, Elsevier, vol. 219(1), pages 101-122.
    7. Shapiro, Joseph & Trevino, Jorge Moreno, 2004. "Compensatory education for disadvantaged Mexican students : an impact evaluation using propensity score matching," Policy Research Working Paper Series 3334, The World Bank.
    8. Crooks, Valorie A., 2007. "Exploring the altered daily geographies and lifeworlds of women living with fibromyalgia syndrome: A mixed-method approach," Social Science & Medicine, Elsevier, vol. 64(3), pages 577-588, February.
    9. Nathalie Greenan & Pierre-Jean Messe, 2018. "Transmission of vocational skills in the second part of careers: the effect of ICT and management changes," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 52(1), pages 1-16, December.
    10. Kube, Roland & von Graevenitz, Kathrine & Löschel, Andreas & Massier, Philipp, 2019. "Do voluntary environmental programs reduce emissions? EMAS in the German manufacturing sector," Energy Economics, Elsevier, vol. 84(S1).
    11. Pedro H. C. Sant'Anna & Xiaojun Song & Qi Xu, 2022. "Covariate distribution balance via propensity scores," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(6), pages 1093-1120, September.
    12. Iacus, Stefano M. & Porro, Giuseppe, 2007. "Missing data imputation, matching and other applications of random recursive partitioning," Computational Statistics & Data Analysis, Elsevier, vol. 52(2), pages 773-789, October.
    13. Anjana Susarla & Anitesh Barua, 2011. "Contracting Efficiency and New Firm Survival in Markets Enabled by Information Technology," Information Systems Research, INFORMS, vol. 22(2), pages 306-324, June.
    14. Slottje, Daniel J. & Millimet, Daniel L. & Buchanan, Michael J., 2007. "Econometric analysis of copyrights," Journal of Econometrics, Elsevier, vol. 139(2), pages 303-317, August.
    15. Sourafel Girma & Steve Thompson & Peter Wright, 2006. "International Acquisitions, Domestic Competition and Firm Performance," International Journal of the Economics of Business, Taylor & Francis Journals, vol. 13(3), pages 335-349.
    16. Dugstad, Anders & Grimsrud, Kristine & Kipperberg, Gorm & Lindhjem, Henrik & Navrud, Ståle, 2020. "Acceptance of wind power development and exposure – Not-in-anybody's-backyard," Energy Policy, Elsevier, vol. 147(C).
    17. Tymon Słoczyński, 2015. "The Oaxaca–Blinder Unexplained Component as a Treatment Effects Estimator," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(4), pages 588-604, August.
    18. K. Poehlmann & R. Helm & O. Mauroner & J. Auburger, 2021. "Corporate spin-offs’ success factors: management lessons from a comparative empirical analysis with research-based spin-offs," Review of Managerial Science, Springer, vol. 15(6), pages 1767-1796, August.
    19. Hämäläinen, Kari & Ollikainen, Virve, 2004. "Differential Effects of Active Labour Market Programmes in the Early Stages of Young People's Unemployment," Research Reports 115, VATT Institute for Economic Research.
    20. Lin, Jenny X. & Lincoln, William F., 2017. "Pirate's treasure," Journal of International Economics, Elsevier, vol. 109(C), pages 235-245.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:socmed:v:65:y:2007:i:3:p:524-535. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/315/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.