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The Psychogeriatric Assessment Scales: a multidimensional alternative to categorical diagnoses of dementia and depression in the elderly

Published online by Cambridge University Press:  09 July 2009

A. F. Jorm*
Affiliation:
NH & MRC Social Psychiatry Research Unit, The Australian National University, Canberra and the Department of Geriatric Medicine, Repatriation General Hospital Concord, Sydney, Australia; Institutions Universitaires de Gériatrie de Genève, Geneva, Switzerland.
A. J. Mackinnon
Affiliation:
NH & MRC Social Psychiatry Research Unit, The Australian National University, Canberra and the Department of Geriatric Medicine, Repatriation General Hospital Concord, Sydney, Australia; Institutions Universitaires de Gériatrie de Genève, Geneva, Switzerland.
A. S. Henderson
Affiliation:
NH & MRC Social Psychiatry Research Unit, The Australian National University, Canberra and the Department of Geriatric Medicine, Repatriation General Hospital Concord, Sydney, Australia; Institutions Universitaires de Gériatrie de Genève, Geneva, Switzerland.
R. Scott
Affiliation:
NH & MRC Social Psychiatry Research Unit, The Australian National University, Canberra and the Department of Geriatric Medicine, Repatriation General Hospital Concord, Sydney, Australia; Institutions Universitaires de Gériatrie de Genève, Geneva, Switzerland.
H. Christensen
Affiliation:
NH & MRC Social Psychiatry Research Unit, The Australian National University, Canberra and the Department of Geriatric Medicine, Repatriation General Hospital Concord, Sydney, Australia; Institutions Universitaires de Gériatrie de Genève, Geneva, Switzerland.
A. E. Korten
Affiliation:
NH & MRC Social Psychiatry Research Unit, The Australian National University, Canberra and the Department of Geriatric Medicine, Repatriation General Hospital Concord, Sydney, Australia; Institutions Universitaires de Gériatrie de Genève, Geneva, Switzerland.
J. S. Cullen
Affiliation:
NH & MRC Social Psychiatry Research Unit, The Australian National University, Canberra and the Department of Geriatric Medicine, Repatriation General Hospital Concord, Sydney, Australia; Institutions Universitaires de Gériatrie de Genève, Geneva, Switzerland.
R. Mulligan
Affiliation:
NH & MRC Social Psychiatry Research Unit, The Australian National University, Canberra and the Department of Geriatric Medicine, Repatriation General Hospital Concord, Sydney, Australia; Institutions Universitaires de Gériatrie de Genève, Geneva, Switzerland.
*
1 Address for correspondence: Dr A. F. Jorm, NH&MRC Social Psychiatry Research Unit, The Australian National University, Canberra, ACT 0200, Australia.

Synopsis

The Psychogeriatric Assessment Scales (PAS) provide an assessment of the clinical changes seen in dementia and depression. Principal components analysis and latent trait analysis were used to develop a set of scales to summarize these clinical changes. There are three scales derived from an interview with the subject (Cognitive Impairment, Depression, Stroke) and three from an interview with an informant (Cognitive Decline, Behaviour Change, Stroke). Results are reported on the reliability and validity of these scales using data from clinical samples in Sydney and Geneva and a population sample from Canberra. The scales were found to have excellent validity when judged against clinical diagnoses of dementia and depression and could distinguish Alzheimer's from vascular dementia. Cut-off points were developed to indicate correspondence between scale scores and clinical diagnoses. Percentile rank norms were developed from the Canberra population sample. The PAS is easy to administer and score and can be used by lay interviewers after training. It is intended for application both in research and in services for the elderly.

Type
Original Articles
Copyright
Copyright © Cambridge University Press 1995

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References

American Psychiatric Association (1987). Diagnostic and Statistical Manual of Mental Disorders (3rd edn – Revised). DSM-III-R. American Psychiatric Association: Washington, DC.Google Scholar
Copeland, J. R. M., Gurland, B. J., Dewey, M. E., Kelleher, M. J., Smith, A. M. R. & Davidson, I. A. (1987). Is there more dementia, depression and neurosis in New York? A comparative study of the elderly in New York and London using the computer diagnosis AGECAT. British Journal of Psychiatry 151, 466473.CrossRefGoogle ScholarPubMed
Duncan-Jones, P., Grayson, D. A. & Moran, P. A. P. (1986). The utility of latent trait models in psychiatric epidemiology. Psychological Medicine 16, 391405.CrossRefGoogle ScholarPubMed
Folstein, M. F., Folstein, S. E. & McHugh, P. R. (1975). ‘Mini-Mental State’: a practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research 12, 189198.CrossRefGoogle Scholar
Goldberg, D. & Huxley, P. (1992). Common Mental Disorders: A Bio-Social Model. Tavistock/Routledge: London & New York.Google Scholar
Goldberg, D., Bridges, K., Duncan-Jones, P. & Grayson, D. (1988). Detecting anxiety and depression in general medical settings. British Medical Journal 297, 897899.CrossRefGoogle ScholarPubMed
Gustafson, L. & Nilsson, L. (1982). Differential diagnosis of presenile dementia on clinical grounds. Acta Psychiatrica Scandinavica 65, 194209.CrossRefGoogle ScholarPubMed
Hachinski, V. C., Iliff, L. D., Zilhka, E., Du Boulay, G. H., McAllister, V. L., Marshall, J., Russell, R. W. R. & Symon, L. (1975). Cerebral blood flow in dementia. Archives of Neurology 32, 632637.CrossRefGoogle ScholarPubMed
Hanley, J. A. & McNeil, B. J. (1982). The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology 143, 2936.CrossRefGoogle Scholar
Henderson, A. S., Jorm, A. F., Mackinnon, A., Christensen, H., Scott, L. R., Korten, A. E. & Doyle, C. (1993). The prevalence of depressive disorders and the distribution of depressive symptoms in later life: a survey using draft ICD-10 and DSM-III-R. Psychological Medicine 23, 719729.CrossRefGoogle ScholarPubMed
Henderson, A. S., Jorm, A. F., Mackinnon, A., Christensen, H., Scott, L. R., Korten, A. E. & Doyle, C. (1994). A survey of dementia in the Canberra population: experience with ICD-10 and DSM-III-R criteria. Psychological Medicine 24, 473482.CrossRefGoogle ScholarPubMed
Holzer, C. E., Tischler, G. L., Leaf, P. J. & Myers, J. K. (1984). An epidemiologic assessment of cognitive impairment in a community population. Research in Community and Mental Health 4, 332.Google Scholar
Huppert, F. A., Brayne, C. & O'Connor, D. (eds.) (1994). Dementia and Normal Aging. Cambridge University Press: Cambridge.Google Scholar
Jorm, A. F. & Jacomb, P. A. (1989). The Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE): socio-demographic correlates, reliability, validity and some norms. Psychological Medicine 19, 10151022.CrossRefGoogle ScholarPubMed
Jorm, A. F., Scott, R., Cullen, J. S. & Mackinnon, A. J. (1991). Performance of the Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) as a screening test for dementia. Psychological Medicine 21, 785790.CrossRefGoogle ScholarPubMed
Jorm, A. F., Fratiglioni, L. & Winblad, B. (1993). Differential diagnosis in dementia: Principal components analysis of clinical data from a population survey. Archives of Neurology 50, 7277.CrossRefGoogle ScholarPubMed
McDonald, R. P. (1985). Factor Analysis and Related Methods. Lawrence Erlbaum Associates: Hillsdale, New Jersey.Google Scholar
Mackinnon, A., Christensen, H., Cullen, J. S., Doyle, C. J., Henderson, A. S., Jorm, A. F., Korten, A. E. & Scott, L. R. (1993). The Canberra Interview for the Elderly: assessment of its validity in the diagnosis of dementia and depression. Acta Psychiatrica Scandinavica 87, 146151.CrossRefGoogle ScholarPubMed
Mackinnon, A. J., Christensen, H., Jorm, A. F., Henderson, A. S., Scott, R. & Korten, A. E. (1994). A latent trait analysis of an inventory designed to detect symptoms of anxiety and depression using an elderly community sample. Psychological Medicine 24, 977986.CrossRefGoogle ScholarPubMed
Mortimer, J. A. & Graves, A. B. (1993). Education and other socioeconomic determinants of dementia and Alzheimer's disease. Neurology 43 (suppl 4), S39S44.Google Scholar
Mulligan, R., Mackinnon, A., Berney, P. & Giannakopulos, P. (1994). The reliability and validity of the French version of the Canberra Interview for the Elderly. Acta Psychiatrica Scandinavica 89, 268273.CrossRefGoogle ScholarPubMed
Nelson, H. E. & O'Connell, A. (1978). Dementia: the estimation of premorbid intelligence levels using the New Adult Reading Test. Cortex 14, 234244.CrossRefGoogle ScholarPubMed
Roth, M., Tym, E., Mountjoy, C. Q., Huppert, F. A., Hendrie, H.Verma, S. & Goddard, R. (1986). CAMDEX: a standardized instrument for the diagnosis of mental disorder in the elderly with special reference to the early detection of dementia. British Journal of Psychiatry 149, 698709.CrossRefGoogle Scholar
Social Psychiatry Research Unit (1992). The Canberra Interview for the Elderly: a new field instrument for the diagnosis of dementia and depression by ICD-10 and DSM-III-R. Acta Psychiatrica Scandinavica 85, 105113.CrossRefGoogle Scholar
World Health Organization (1993). The ICD-10 Classification of Mental and Behavioural Disorders: Diagnostic Criteria for Research. World Health Organization: Geneva.Google Scholar
Yesavage, J., Brink, T. L., Rose, T. L., Lum, O., Huang, V., Adey, M. & Leiver, V. O. (1983). Development and validation of a geriatric depression screening scale: a preliminary report. Journal of Psychiatric Research 17, 3749.CrossRefGoogle Scholar