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Développement et validation d’une classification québécoise des résidences privées avec services accueillant des personnes âgées*

Published online by Cambridge University Press:  20 January 2014

Catherine Lestage ,
Nicole Dubuc  and
Gina Bravo
Catherine Lestage*
Affiliation:
Faculté de médecine et des sciences de la santé de l’Université de Sherbrooke Centre de recherche sur le vieillissement du Centre de santé et de services sociaux de l’Institut universitaire de gériatrie de Sherbrooke
Nicole Dubuc
Affiliation:
Faculté de médecine et des sciences de la santé de l’Université de Sherbrooke Centre de recherche sur le vieillissement du Centre de santé et de services sociaux de l’Institut universitaire de gériatrie de Sherbrooke
Gina Bravo
Affiliation:
Faculté de médecine et des sciences de la santé de l’Université de Sherbrooke Centre de recherche sur le vieillissement du Centre de santé et de services sociaux de l’Institut universitaire de gériatrie de Sherbrooke
*
†Correspondence and requests for reprints should be sent to / La correspondance et les demandes de tirés à part sont à adresser à: Catherine Lestage, PhD. Faculté de médecine et des sciences de la santé de l’Université de Sherbrooke 3001, 12e avenue Nord Sherbrooke, QC J1H 5N4 ([email protected])
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Abstract

Private Residential Care Facilities (RCFs) fill the gap between independent community living and institutional settings for seniors. There are marked differences between RCFs which make them difficult to compare. To address this issue, the objective of this study was to develop and validate a classification of RCFs based on their physical and organizational environments. RCF owners across Quebec were invited to complete a questionnaire that described the setting’s physical and organizational environment. Different combinations of cluster analysis methods and statistical parameters were used to identify plausible classifications. The final choice was made by an expert committee. Overall, 552 owners returned the questionnaire. Three plausible classifications were submitted to the committee. The selected classification included five clusters that differed with regard to admission criteria, services offered and recreational activities. This classification could help health professionals select the RCF that best responds to older adults’ needs.

Résumé

Les résidences privées pour personnes âgées (RPA) sont une option entre le domicile et les centres d’hébergement de soins de longue durée. Elles sont hétérogènes, ce qui complexifie leur comparaison. Objectif. Développer et valider une classification de RPA basée sur leur environnement physique et organisationnel. Méthodes. Les propriétaires d’une RPA du Québec ont été invités à remplir un questionnaire qui dresse un portrait de l’environnement physique et organisationnel du milieu. Plusieurs méthodes d’analyses de classification automatisée et différents critères statistiques ont servi à identifier les classifications potentielles. Le choix final a été confié à un groupe d’experts. Résultats. 552 propriétaires ont retourné le questionnaire. Trois classifications ont été soumises aux experts. Celle retenue contient 5 groupes qui se distinguent par la clientèle hébergée, les services offerts et les loisirs. Conclusion. Cette classification pourra aider les professionnels à choisir la RPA qui répond le mieux aux besoins d’une personne âgée.

Keywords

aginganalysis of automatic classificationclassificationelderlyorientation processprivate residences for the agedvieillissementanalyses de classification automatiséeclassificationpersonnes âgéesprocessus d’orientationrésidences privées
Type
Articles
Information
Canadian Journal on Aging / La Revue canadienne du vieillissement , Volume 33 , Issue 1 , March 2014 , pp. 72 - 83
Copyright
Copyright © Canadian Association on Gerontology 2013 

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Footnotes

*

Catherine Lestage tient à remercier les Instituts de recherche en santé du Canada ainsi que les Fonds de la recherche en santé du Québec pour l’octroi des bourses de formation de doctorat.

References

Références

Aldenderfer, M. S., & Blashfield, R. K. (1984). Cluster analysis. Beverly Hills, CA: Sage.CrossRefGoogle Scholar
Brawley, E. C. (2001). Environmental design for Alzheimer’s disease: A quality of life issue. Aging Mental Health, 5(1 Suppl), S79–S83.CrossRefGoogle ScholarPubMed
Calinski, T., & Harabasz, J. (1974). A dendrite method for cluster analysis. Communications in Statistics, 3(1), 1–27.Google Scholar
Castle, N. G., & Sonon, K. E. (2007). The search and selection of assisted living facilities by elders and family. Medical Care, 45(8), 729–738.Google Scholar
Charpentier, M., Delli-Colli, N., et Dalpé, L. (2000). L’orientation des personnes âgées en perte d’autonomie dans un contexte de rareté des ressources publiques d’hébergement. Intervention, 112, 70–77.Google Scholar
Clatworthy, J., Buick, D., Hankins, M., Weinman, J., & Horne, R. (2005). The use and reporting of cluster analysis in health psychology: A review. British Journal of Health Psychology, 10(3), 329–358.Google Scholar
Conseil des, Aînés. (2007). État de situation sur les milieux de vie substituts pour les aînés en perte d’autonomie. Québec: Gouvernement du Québec.Google Scholar
Degenholtz, H. B., Miller, M. J., Kane, R. A., Cutler, L. J., & Kane, R. L. (2006). Developing a typology of nursing home environments. Journal of Housing for the Elderly, 20(1/2), 5–29.Google Scholar
Delli-Colli, N., Dubuc, N., et Caron, C. (2006). Qu’advient-il des personnes âgées orientées en résidence privée à la suite d’un séjour en courte durée? Intervention, 124, 33–41.Google Scholar
Dillman, D. (2000). Mail and internet surveys: The tailored design method. New York: John Wiley & Sons.Google Scholar
Dolnicar, S. (2002). A review of unquestioned standards in using cluster analysis for data-driven market segmentation. Paper presented at the Australian and New Zealand Marketing Academy Conference, 3 au 5 décembre 2002, Melbourne.Google Scholar
Dolnicar, S. (2003). Using cluster analysis for market segmentation: Typical misconceptions, established methodological weaknesses and some recommendations for improvement. Australasian Journal of Market and Social Research, 11(2), 5–12.Google Scholar
Edwards, P., Roberts, I., Clarke, M., DiGiuseppi, C., Pratap, S., Wentz, R., et al. (2007). Methods to increase response rates to postal questionnaires. The Cochrane Database of Systematic Reviews, 18(2), MR000008.Google Scholar
Everitt, B., Landau, S., & Leese, M. (2001). Cluster analysis. London: Oxford University Press.Google Scholar
Gold, D. T., Sloane, P. D., Mathew, L. J., Bledsoe, M. M., & Konanc, D. A. (1991). Special care units: A typology of care settings for memory-impaired older adults. The Gerontologist, 31(4), 467–475.Google Scholar
Gordon, A. (1999). Classification (2nd ed.). London: Chapman & Hall/CRC.Google Scholar
Grant, L. (1998). Beyond the dichotomy: An empirical typology of Alzheimer’s care in nursing homes. Research on Aging, 20(5), 569–592.Google Scholar
Hair, J., Black, W., Babin, B., & Anderson, R. (2010). Multivariate data analysis (7th ed.) Upper Saddle River, NJ: Prentice Hall.Google Scholar
Hox, J., & De Leeuw, E. (1994). A comparison of nonresponse in mail, telephone, and face-to-face surveys: Applying multilevel models to meta-analysis. Quality and Quantity, 28(4), 329–344.Google Scholar
Iwarsson, S. (2005). A long-term perspective on person-environment fit and ADL dependence among older Swedish adults. The Gerontologist, 45(3), 327–336.Google Scholar
Kane, R. A., Kling, K. C., Bershadsky, B., Kane, R. L., Giles, K., Degenholtz, H. B., et al. (2003). Quality of life measures for nursing home residents. The Journal of Gerontology. Series A, Biological Sciences and Medical Sciences, 58(3), 240–248.Google Scholar
Kaufman, L., & Rousseeuw, P. (1990). Finding groups in data: An introduction to cluster analysis. New York: Wiley-Interscience.Google Scholar
Kettenring, J. (2006). The practice of cluster analysis. Journal of Classification, 23(1), 3–30.CrossRefGoogle Scholar
Kovacs, F., Legany, C., & Babos, A. (2006). Cluster validity measurement techniques. Proceedings of the 5th WSEAS International Conference on Artificial Intelligence, Knowledge Engineering and Data Bases (pp. 388–393). Stevens Point, WI, États-Unis: World Scientific and Engineering Academy and Society.Google Scholar
Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33(1), 159–174.Google Scholar
Lange, T., Roth, V., Braun, M., & Buhmann, J. (2004). Stability-based validation of clustering solutions. Neural Computation, 16(6), 1299–1324.Google Scholar
Lawton, M. P. (1983). Environment and other determinants of well-being in older people. The Gerontologist, 23(4), 349–357.Google Scholar
Lawton, M. P., Weisman, G. D., Sloane, P. D., & Calkins, M. P. (1997). Assessing environments for older people with chronic illness. Journal of Mental Health and Aging, 3(1), 83–100.Google Scholar
Lestage, C., Dubuc, N., & Bravo, G. (2008). Identifying characteristics of residential care facilities relevant to the placement process of seniors. Journal of the American Medical Directors Association, 9(2), 95–101.Google Scholar
Lestage, C., Dubuc, N., Bravo, G. (2009). Development and reliability of a questionnaire for describing residential care facilities for seniors. The Journal of Nutrition, Health & Aging, 13(1), p. S280.Google Scholar
Milligan, G. (1980). An examination of the effect of six types of error perturbation on fifteen clustering algorithms. Psychometrika, 45(3), 325–342.Google Scholar
Milligan, G., & Cooper, M. (1985). An examination of procedures for determining the number of clusters in a data set. Psychometrika, 50(2), 159–179.Google Scholar
Milligan, G., & Cooper, M. (1988). A study of standardization of variables in cluster analysis. Journal of Classification, 5(2), 181–204.Google Scholar
Ministère de la Santé et des Services sociaux. (2003). Chez soi: Le premier choix. La politique de soutien à domicile. Québec, QC: La Direction des communications du ministère de la Santé et des Services sociaux du Québec.Google Scholar
Ministère de la Santé et des Services sociaux. (2011). Bulletin d’information présentant des statistiques de base sur l’hébergement et l’habitation des personnes âgées en perte d’autonomie. Québec, QC: Service du développement de l’information.Google Scholar
Park, N. S., Zimmerman, S., Sloane, P. D., Gruber-Baldini, A. L., & Eckert, J. K. (2006). An empirical typology of residential care/assisted living based on a four-state study. The Gerontologist, 46(2), 238–248.Google Scholar
Parker, C., Barnes, S., McKee, K., Morgan, K., Torrington, J., & Tregenza, P. (2004). Quality of life and building design in residential and nursing homes for older people. Ageing & Society, 24(6), 941–962.Google Scholar
Punj, G., & Stewart, D. (1983). Cluster analysis in marketing research: Review and suggestions for application. Journal of Marketing Research, 20(2), 134–148.Google Scholar
Regnier, V. A., & Scott, A. C. (2001). Creating a therapeutic environment: Lessons from Northern European models. In Zimmerman, S., Sloane, P. D., & Eckert, J. K. (Eds.), Assisted living: Needs, practices, and policies in residential care for the elderly (pp. 53–77). Baltimore: Johns Hopkins University Press.Google Scholar
Salem, S., & Nandi, A. (2009). Development of assessment criteria for clustering algorithms. Pattern Analysis & Applications, 12(1), 79–98.Google Scholar
Shih, T., & Fan, X. (2009). Comparing response rates in e-mail and paper surveys: A meta-analysis. Educational Research Review, 4(1), 26–40.Google Scholar
Société Alzheimer du Canada. (2010). Raz-de-marée: Impact de la maladie d’Alzheimer et des affections connexes au Canada. récupéré 12 juillet 2012, à partir de www.alzheimer.ca.Google Scholar
Statistique Canada. (2010). Estimates of population, by age group and sex for July 1, Canada, provinces and territories, annual. récupéré 27 septembre 2012, à partir de www23.statcan.gc.ca/imdb/p2SV.pl?Function=getSurvey&SDDS=3604&Item_Id=1533&lang=en. Statistics Canada.Google Scholar
Weissert, W. G., & Musliner, M. C. (1992). Case mix adjusted nursing-home reimbursement: A critical review of the evidence. Milbank Quarterly, 70(3), 455–490.Google Scholar
Xu, R., & Wunsch, D. (2008). Recent advances in cluster analysis. International Journal of Intelligent Computing and Cybernetics, 1(4), 484–508.Google Scholar
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