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A Bifactor and item response analysis of the geriatric anxiety inventory

Published online by Cambridge University Press:  20 June 2017

H. Molde Open the ORCID record for H. Molde [Opens in a new window] ,
K. M. Hynninen ,
T. Torsheim ,
A.B. Bendixen ,
K. Engedal ,
N.A. Pachana  and
I. H. Nordhus
H. Molde*
Affiliation:
Department of Clinical Psychology, University of Bergen, Bergen, Norway
K. M. Hynninen
Affiliation:
Department of Clinical Psychology, University of Bergen, Bergen, Norway NKS Olaviken Gerontopsychiatric Hospital, Askøy, Norway
T. Torsheim
Affiliation:
Department of Psychosocial Science, University of Bergen, Bergen, Norway
A.B. Bendixen
Affiliation:
Norwegian National Advisory Unit for Aging and Health, Vestfold Hospital and Department of Geriatric Medicine, Oslo University Hospital, Oslo, Norway
K. Engedal
Affiliation:
Norwegian National Advisory Unit for Aging and Health, Vestfold Hospital and Department of Geriatric Medicine, Oslo University Hospital, Oslo, Norway
N.A. Pachana
Affiliation:
School of Psychology, University of Queensland, Brisbane, Australia
I. H. Nordhus
Affiliation:
Department of Clinical Psychology, University of Bergen, Bergen, Norway Department of Behavioural Sciences in Medicine, University of Oslo, Oslo, Norway
*
Correspondence should be addressed to: Helge Molde, Department of Clinical Psychology, Christiesgate 12, 5020 BERGEN, Norway. Phone: +0047 55588682. Email: [email protected].
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Abstract

Background:

Due to previously reported mixed findings, there is a need for further empirical research on the factorial structure of the commonly used Geriatric Anxiety Inventory (GAI). Therefore, the psychometric properties of the GAI and its short form version (GAI-SF) were evaluated in a psychogeriatric mixed in-and-out patient sample (n = 543).

Methods:

Unidimensionality was tested using a bifactor analysis. Rasch modeling was used to assess scale properties. Sex, cognitive functioning and depressive symptoms were tested for differential item functioning (DIF).

Results:

The bifactor analysis identified an essential unidimensional (general) factor structure but also specific local factors. The general factor comprises all the 20 items as one factor, and the results showed that the variance in the general and specific factors (subscale) scores is best explained by the single general factor. These findings were demonstrated for both versions of the GAI. Furthermore, the Rasch models identified extensive item overlap, indicating redundant items in the full version of the GAI. The GAI-SF also seems to extract much of the same information as the full form. Test scores and items have the same meaning for older adults across different demographic status.

Conclusion:

The findings support the use of a total sum score for both GAI and GAI-SF. Notably, when using the GAI-SF, no information is lost, in comparison with the full scale, thus, supporting the option of choosing the short form (version) when considered most appropriate in demanding clinical contexts.

Keywords

anxietypsychiatrygeriatricitem-responseRaschbifactorpsychometricunidimensional
Type
Research Article
Information
International Psychogeriatrics , Volume 29 , Issue 10 , October 2017 , pp. 1647 - 1656
Copyright
Copyright © International Psychogeriatric Association 2017 

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References

Bendixen, A. B. and Engedal, K. (2015). Anxiety among older psychiatric patients: a hidden comorbidity?. Aging & Mental Health, 9, 1–8.Google Scholar
Bendixen, A. B., Hartberg, C. B., Selbæk, G. and Engedal, K. (2016). Symptoms of anxiety in older adults with depression, dementia, or psychosis: a principal component analysis of the Geriatric anxiety inventory. Dementia and Geriatric Cognitive Disorders, 42, 310–322.CrossRefGoogle Scholar
Boddice, G., Pachana, N. A. and Byrne, G. J. (2008). The clinical utility of the Geriatric anxiety inventory in older adults with cognitive impairment. Nursing Older People, 20, 36–40.Google Scholar
Bond, T. G. and Fox, C. M. (2007). Applying the Rasch Model, 2nd edn.. Mahwah, NJ: Lawrence Erlbaum.Google Scholar
Bryant, C., Jackson, H. and Ames, D. (2008). The prevalence of anxiety in older adults: methodological issues and a review of the literature. Journal of Affective Disorders, 109, 233–250.CrossRefGoogle Scholar
Byers, A. L., Yaffe, K., Covinsky, K. E., Friedman, M. B. and Bruce, M. L. (2010). High occurrence of mood and anxiety disorders among older adults: the national comorbidity survey replication. Archives of General Psychiatry, 67, 489–496.Google Scholar
Byrne, G. J. and Pachana, N. A. (2010). Anxiety and depression in the elderly: do we know any more?. Current Opinion in Psychiatry, 23, 504–509.CrossRefGoogle ScholarPubMed
Byrne, G. J. and Pachana, N. A. (2011). Development and validation of a short form of the Geriatric anxiety inventory – the GAI-SF. International Psychogeriatrics, 23, 125–131.Google Scholar
Byrne, G. J., Pachana, N. A., Goncalves, D. C., Arnold, E., King, R. and Khoo, S. K. (2010). Psychometric properties and health correlates of the Geriatric anxiety inventory in Australian community-residing older women. Aging & Mental Health, 14, 247–254.CrossRefGoogle ScholarPubMed
Diefenbach, G. J., Bragdon, L. B. and Blank, K. (2014). Geriatric anxiety inventory: factor structure and associations with cognitive status. American Journal of Geriatric Psychiatry, 22, 1418–1426.CrossRefGoogle ScholarPubMed
De Beurs, E., Beekman, A. T., van Balkom, A. J., Deeq, D. J., van Dyck, R. and van Tilburg, W. (1999). Consequences of anxiety in older persons: its effect on disability, well-being and use of health services. Psychological Medicines, 29, 583–593.Google Scholar
Finch, W. H. and French, B. F. (2015). Latent Variable Modeling with R. New York: Routledge.CrossRefGoogle Scholar
Gould, C. E., Segal, D. L., Yochim, B. P., Pachana, N. A., Byrne, G. J. and Beaudreau, S. A. (2014). Measuring anxiety in late life: a psychometric examination of the geriatric anxiety inventory and geriatric anxiety scale. Journal of Anxiety Disorders, 28, 804–811.CrossRefGoogle ScholarPubMed
Guan, M. (2016). Factor structure of the Chinese version of the geriatric anxiety inventory. Annals of General Psychiatry, 15. DOI 10.1186/s12991-016-0092-4 Google Scholar
Johnco, C., Knight, A., Tadic, D. and Wuthrich, V. M. (2015). Psychometric properties of the geriatric anxiety inventory (GAI) and its short form (GAI-SF) in a clinical and non-clinical sample of older adults. International Psychogeriatrics, 27, 1089–1097.Google Scholar
Kneebone, I. I., Fife-Schaw, C., Lincoln, N. B. and Harder, H. (2016). A study of the validity and reliability of the geriatric anxiety inventory in screening for anxiety after stroke in older inpatients. Clinical Rehabilitation, 30 (12), 1220–1228.Google Scholar
Loynachan, C., Lee, M., Lamb, M. and Pyykkonen, B. (2016). Factor structure comparison between the beck anxiety inventory and geriatric anxiety inventory for a non-clinical sample of older adults. Abstract: poster session, C-65. Archives of Clinical Neuropsychology, 31, 584–637.CrossRefGoogle Scholar
Lyketsos, C. G. et al. (1999). The general medical health rating: a bedside global rating of medical comorbidity in patients with dementia. Journal of the American Geriatrics Society, 47, 487–91.Google Scholar
Màrquez-Gonzàlez, M., Losada, A., Fernàndez-Fernàndez, V. and Pachana, N. (2012). Psychometric properties of the Spanish version of the geriatric anxiety inventory. International Psychogeriatrics, 24, 137–144.Google Scholar
Molde, H., Hystad, S. W., Pallesen, S., Myrseth, H. and Lund, I. (2010). Evaluating lifetime NODS using Rasch modelling. International Gambling Studies, 10, 189– 202.Google Scholar
Montgomery, S. A. and Åsberg, M. (1979). A new depression scale designed to be sensitive to change. British Journal of Psychiatry, 134, 382–389.Google Scholar
Mueller, A. E. et al. (2015). Geriatric anxiety scale: item response analysis, differential item functioning, and creation of a ten-item short form (GAS-10). International Psychogeriatrics, 27, 1099–1111.Google Scholar
Murphy, L. and Helmick, C. G. (2012). The impact of osteoarthritis in the United States: a population-health perspective. American Journal of Nursing, 112, 13–19.Google Scholar
Pachana, N. A. and Byrne, G. J. (2012). The geriatric anxiety inventory: international use and future directions. Australian Psychologist, 47, 33–38.CrossRefGoogle Scholar
Pachana, N. A., Byrne, G. J., Siddle, H., Koloski, N., Harley, E. and Arnold, E. (2007). Development and validation of the geriatric anxiety inventory. International Psychogeriatrics, 19, 103–114.Google Scholar
R Core Team. (2016). R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0, URL http://www.R-project.org/.Google Scholar
Reise, S. P. (2012). The rediscovery of bifactor measurement models. Multivariate Behavioral Research, 47, 667–696.Google Scholar
Rozzini, L. et al. (2009). Anxiety symptoms in mild cognitive impairment. International Journal of Geriatric Psychiatry, 24, 300–305.Google Scholar
Seignourel, P. J., Kunik, M. E., Snow, L., Wilson, N. and Stanley, M. (2008). Anxiety in dementia: a critical review. Clinical Psychology Review, 28, 1071–1082.Google Scholar
Strobel, C. and Engedal, K. (2008). MMSE-NR: Norsk revidert mini mental status evaluering. Oslo: Nasjonalt kompetansesenter for Aldring og Helse.Google Scholar
Therrien, Z. and Hunsley, J. (2012). Assessment of anxiety in older adults: a systematic review of commonly used measures. Aging & Mental Health, 16, 1–16.Google Scholar
World Health Organization (2016). Process of Translation and Adaption of Instruments. Retrieved from http://www.who.int/substance_abuse/research_tools/translation/en/ Google Scholar
Yan, Y., Xin, T., Wang, D. and Tang, D. (2014). Application of the geriatric anxiety inventory-Chinese version (GAI-CV) to older people in Beijing communities. International Psychogeriatrics, 26, 517–523.Google Scholar