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

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. ), this study used bifactor modelling 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 (MG-CFA) 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.

Psychometric properties of the new Persian version of the Geriatric Anxiety Inventory (GAI-PV) and its short form (GAI -PV-SF)

“…Nonetheless, as presented in the results, items 12 and 18 had low factor loading, and excluding item 18 appeared to improve the goodness of fit. This is in agreement to the study by Molde et al who performed a cross-national analysis of the psychometric properties of the GAI using data from samples in 10 different countries; although they concluded that the instrument can be more unidimensional without items 7, 12, and 18, they suggested that these candidate items be retained to avoid decreased content validity [3]. The weak factor loading of these items appears to be connected to study participants' interpretation and perception of their contents.…”

“…The test-retest reliability for the long version of GAI-PV was excellent (Spearman correlation coefficient of 0.97), and these results are in agreement with those presented by Pachana et al in the original development paper [4]. The reliability estimates with the Italian and Australian versions were lower than the original and current Persian version, however, they were still in the acceptable range (0.86 and 0.76, respectively) [3,4,27]. The test-retest reliability was very good for the GAI-SF-PV as well (0.88, p<0.0001).…”

Assessment of anxiety in older adults: psychometric properties and relationships with self-reported functional impairment

“…Confirmatory factor analyses (CFA) were conducted to evaluate the model fit of prior published models to determine whether the models demonstrated adequate fit in the present sample given previous mixed findings (e.g. Molde et al, 2019). Total fit indices (i.e.…”

“…The current leading model for the GAI within the literature is a bifactor model that includes all items and has a strong general factor (Molde et al, 2017(Molde et al, , 2019. The number of specific factors has been found to be different across countries in a large international sample, however, the USA sample demonstrated three specific factors (Molde et al, 2019). Although not stated by the authors, the content in these three factors appears to be cognitive, affective, and somatic.…”

“…For example, a study by Johnco and colleagues (2015) found a one-factor structure, whereas findings by Diefenbach and colleagues (2014) found a four-factor structure. The current leading model for the GAI within the literature is a bifactor model that includes all items and has a strong general factor (Molde et al, 2017(Molde et al, , 2019. The number of specific factors has been found to be different across countries in a large international sample, however, the USA sample demonstrated three specific factors (Molde et al, 2019).…”