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Cited by 549

The DOI matches its Crossref record; 30 of the 30 references it cites were found in a registry or an index.

Measuring Acculturation: Where We Are and Where We Need to Go

Cabassa, Leopoldo J.·2003·Hispanic Journal of Behavioral Sciences

Abstract

Acculturation measures intend to capture the psychological, behavioral, and attitudinal changes that occur when individuals and groups from different cultures come into continuous contact with each other. This article examines the most prominent theoretical models and assumptions that drive acculturation measures. Examples of Hispanic acculturation measures are used to illustrate how these theoretical foundations are applied in empirical measures. Particular emphasis is given to discussing the strengths and limitations of two bidimensional measures, the Bidimensional Acculturation Scale for Hispanics (BAS) and the Acculturation Rating Scale for Mexican Americans-Revised (ARSMA-II). Recommendations for improving these measures are presented. Moving beyond proxy measures, improving the operationalization of acculturation indicators, and incorporating theoretical models, as well as contextual variables, are the key recommendations presented for improving measures of acculturation.

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Metadata

Authors
Cabassa, L. J.
Venue
Hispanic Journal of Behavioral Sciences
Published
2003-05
Volume
25
Issue
2
Pages
127-146
ISSN
  • 0739-9863 (ISSN-L)
  • 1552-6364
OpenAlex
W2129850968
Cited by
549
References
30
FWCI
59.11
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Measuring Acculturation: Where We Are and Where We Need to Go. https://app.cochat.ai/papers/10.1177/0739986303025002001
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Cabassa, L. J. (2003). Measuring Acculturation: Where We Are and Where We Need to Go. Hispanic Journal of Behavioral Sciences. https://doi.org/10.1177/0739986303025002001

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.