2017
DOI: 10.1080/00223891.2017.1280044
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Assessing the Unidimensionality of Trait Reactance Using a Multifaceted Model Assessment Approach

Abstract: This study employed a multifaceted model assessment approach to investigate the dimensionality and nomological network of a popular measure of trait reactance, the Hong Psychological Reactance Scale (HPRS; Hong & Page, 1989 ). To address confusion regarding the scoring and modeling of the HPRS as well as its limited external validity evidence, we tested competing factor models, diagnosed model-data misfit, examined relationships between competing factor models and key personality traits, and cross-validated th… Show more

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Cited by 13 publications
(25 citation statements)
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“…In the present, relatively large, sample (N ¼ 624), both confirmatory and exploratory factor analyses of the HPRS supported a one-factor solution. This finding contradicts some previous results suggesting a multifactorial structure for the scale (De las Cuevas et al, 2014;Hong & Faedda, 1996;Thomas et al, 2001), but supports (Jonason & Knowles, 2006) or is partly in line with others who advocate the use of a unitary HPRS score (Brown et al, 2011;Moreira et al, 2019;Yost & Finney, 2018). This discrepancy may stem from our use of the polychoric correlation matrix, while most previous studies have assumedly used the Pearson correlation matrix and thus, potentially, underestimated the associations between the ordinal-scale HPRS items.…”
Section: Discussioncontrasting
confidence: 68%
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“…In the present, relatively large, sample (N ¼ 624), both confirmatory and exploratory factor analyses of the HPRS supported a one-factor solution. This finding contradicts some previous results suggesting a multifactorial structure for the scale (De las Cuevas et al, 2014;Hong & Faedda, 1996;Thomas et al, 2001), but supports (Jonason & Knowles, 2006) or is partly in line with others who advocate the use of a unitary HPRS score (Brown et al, 2011;Moreira et al, 2019;Yost & Finney, 2018). This discrepancy may stem from our use of the polychoric correlation matrix, while most previous studies have assumedly used the Pearson correlation matrix and thus, potentially, underestimated the associations between the ordinal-scale HPRS items.…”
Section: Discussioncontrasting
confidence: 68%
“…10 This model did not include items 3, 5, 7, and 10, it achieved good model fit on only one of the fit indices, and it departs from the typical 14-or 11-item versions. The absence of some of the items could in part explain why the reduced unidimensional model showed the best fit, as previous research has suggested that trait reactance is a unidimensional construct, but that the HPRS artificially produces multiple factors due to similar item wording and/or content (Moreira et al, 2019;Yost & Finney, 2018). Therefore, by removing some of the items, the wording/content-specific overlap between the remaining items might have been reduced.…”
Section: Discussionmentioning
confidence: 98%
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