1. A Cross-National Analysis of the Psychometric Properties of the Geriatric Anxiety Inventory
- Author
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Rob H. S. van den Brink, Alexandra Champagne, Loeki P. R. M. Pelzers, Astrid Lugtenburg, Karen Blank, Somboon Jarukasemthawee, Mario Fluiter, Sherry A. Beaudreau, Renata Kochhann, Richard C. Oude Voshaar, Oscar Ribeiro, Elisabeth Kuan Tai Ow, Gerard J. Byrne, Gretchen J. Diefenbach, Lei Feng, Knut Engedal, Jerson Laks, Anette Bakkane Bendixen, Helge Molde, Nancy A. Pachana, Patrick Gosselin, Analuiza Camozzato, Paul Naarding, Rochele Paz Fonseca, Kullaya Pisitsungkagarn, Andrés Losada, Torbjørn Torsheim, Philippe Landreville, María Márquez-González, Narahyana Bom de Araujo, Inger Hilde Nordhus, Nattasuda Taephant, Interdisciplinary Centre Psychopathology and Emotion regulation (ICPE), and Clinical Cognitive Neuropsychiatry Research Program (CCNP)
- Subjects
Cross-Cultural Comparison ,Male ,Social Psychology ,Psychometrics ,unidimensional ,g factor ,Anxiety ,The Journal of Gerontology: Psychological Sciences ,03 medical and health sciences ,0302 clinical medicine ,medicine ,invariance ,Humans ,Measurement invariance ,030212 general & internal medicine ,Geriatric Assessment ,Aged ,Aged, 80 and over ,Psychiatric Status Rating Scales ,Variance (accounting) ,Confirmatory factor analysis ,Clinical Psychology ,Research studies ,bifactor ,Female ,measurement ,Geriatrics and Gerontology ,medicine.symptom ,Psychology ,Factor Analysis, Statistical ,Gerontology ,030217 neurology & neurosurgery ,Cross national ,Clinical psychology - Abstract
Objectives Assessing 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. Method Using 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. Results Across 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. Discussion Although 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.
- Published
- 2020