2016
DOI: 10.11144/javeriana.upsy15-2.brst
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Brief Resilience Scale: testing its factorial structure and invariance in Brazil

Abstract: a b s T r a C T Across two studies we aimed to provide evidences of validity and reliability for the Brief Resilience Scale (BRS) in Brazil. In study 1, 171 individuals participated (Age M = 21.9, SD = 6.59) and 232 in Study 2 (Age M = 26.3, SD = 7.06). Confirmatory factor analysis (CFA) supported the predicted one-factor solution, with five items and satisfactory internal consistence (α = 0.76). A multi-group CFA revealed partial measurement equivalence between our and the original (USA) versions of the BRS. … Show more

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Cited by 37 publications
(42 citation statements)
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References 32 publications
(39 reference statements)
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“…This means that age comparisons in indicator means and covariances should also be made with caution. Similar findings on strong invariance were also reported by De Holanda Coelho et al (2016) for the Brazilian version. Additionally, BRS scores were reported to differ across gender (Smith et al, 2008;Rodríguez-Rey et al, 2016) and…”
Section: Discussionsupporting
confidence: 89%
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“…This means that age comparisons in indicator means and covariances should also be made with caution. Similar findings on strong invariance were also reported by De Holanda Coelho et al (2016) for the Brazilian version. Additionally, BRS scores were reported to differ across gender (Smith et al, 2008;Rodríguez-Rey et al, 2016) and…”
Section: Discussionsupporting
confidence: 89%
“…The two-factor model showed a consistently adequate fit across all CFA, thus it was considered more reliable. Generally, a discrepancy in the proposed factor structures of BRS emerges from existing empirical literature, suggesting both single factor (Amat, et al, 2014;De Holanda Coelho et al, 2016) and two-factor structures for BRS (Rodríguez-Rey et al, 2016;Chmitorz et al, 2018). We did not evaluate a traditional higher-order CFA model because for a two first-order factorial structure, like BRS, evaluating if the secondorder factor improves the model fit when compared to the first-order solution is not possible due to under-identification (Wang & Wang, 2012;Brown, 2015).…”
Section: Discussionmentioning
confidence: 99%
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