A Cross-National Analysis of the Psychometric Properties of the Geriatric Anxiety Inventory

Helge MoldePhD, Inger Hilde NordhusPhD, Torbjørn TorsheimPhD, Knut EngedalPhD, Anette Bakkane BendixenMD, Gerard J ByrnePhD, María Márquez-GonzálezPhD, Andres LosadaPhD, Lei FengPhD, Elisabeth Kuan Tai OwPhD, Kullaya PisitsungkagarnPhD, Nattasuda TaephantPhD, Somboon JarukasemthaweePhD, Alexandra ChampagneDPsy, Philippe LandrevillePhD, Patrick GosselinPhD, Oscar RibeiroPhD, Gretchen J DiefenbachPhD, Karen BlankMD, Sherry A BeaudreauPhD, Jerson LaksPhD, Narahyana Bom de AraújoPhD, Rochele Paz FonsecaPhD, Renata KochhannPhD, Analuiza CamozzatoPhD, Rob H S van den BrinkPhD, Mario FluiterMD, Paul NaardingPhD, Loeki P R M PelzersMD, Astrid LugtenburgMD, Richard C Oude VoshaarPhD, Nancy A PachanaPhD and Shevaun NeupertPhD

The Journals of Gerontology: Series B, 2020, vol. 75, issue 7, 1475-1483

Abstract: ObjectivesAssessing late-life anxiety using an instrument with sound psychometric properties including cross-cultural invariance is essential for cross-national aging research and clinical assessment. To date, no cross-national research studies have examined the psychometric properties of the frequently used Geriatric Anxiety Inventory (GAI) in depth.MethodUsing data from 3,731 older adults from 10 national samples (Australia, Brazil, Canada, The Netherlands, Norway, Portugal, Spain, Singapore, Thailand, and United States), this study used bifactor modeling to analyze the dimensionality of the GAI. We evaluated the “fitness” of individual items based on the explained common variance for each item across all nations. In addition, a multigroup confirmatory factor analysis was applied, testing for measurement invariance across the samples.ResultsAcross samples, the presence of a strong G factor provides support that a general factor is of primary importance, rather than subfactors. That is, the data support a primarily unidimensional representation of the GAI, still acknowledging the presence of multidimensional factors. A GAI score in one of the countries would be directly comparable to a GAI score in any of the other countries tested, perhaps with the exception of Singapore.DiscussionAlthough several items demonstrated relatively weak common variance with the general factor, the unidimensional structure remained strong even with these items retained. Thus, it is recommended that the GAI be administered using all items.

Keywords: bifactor; invariance; measurement; multigroup; unidimensional (search for similar items in EconPapers)
Date: 2020
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