A mixed-method, comparative analysis of hispanic/Latino/a, Spanish-speaking patient and white, English-speaking patient perceptions of patient-centered care

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Authors: Ashley K. Barrett, Nina Um
Cited by: 1
References: 61

Abstract

This study uses mixed-method, cross-cultural data and a culture-centered approach (CCA) to analyze how U.S. Hispanic/Latino/a, Spanish-speaking (H/L, SS, n = 138) and White, English-speaking (White, ES, n = 124) patients uniquely construct patient-centered care (PCC). We also examine the socio-cultural and health inequity variables associated with PCC experiences for both patient groups. T-test and regression analyses reveal that perceived discrimination and language and cultural discordance significantly and negatively predicted PCC for H/L, SS patients and provider intercultural communication competency positively predicted PCC for both patient groups. Socio-cultural variables related to power, self-construal, and time were generally not significantly tied to PCC experiences for either group. However, a LIWC thematic analysis of H/L, SS patients’ open responses revealed that cultural philosophies of fatalismo, respecto, and familia undergirded their PCC constructions and meanings. Thematic results of White, ES patients revealed their PCC accounts were situated within a service model to healthcare that prioritized putting patients first, making sure patients felt comfortable, and engaging patients through compassionate communication. Theoretically, this study evidences the value of using the CCA to study PCC, advances our socio-cultural understanding of PCC, and reveals how the health inequities that U.S. H/L, SS patients confront are related to their PCC conceptualizations.

Fields of Study & Subjects

Interpreting and Communication in Healthcare Cultural Competency in Health Care Migration Health and Trauma

Publication details

Journal / source
Journal of International and Intercultural Communication
Publisher
Informa UK Limited
Volume
19
Issue
1
Pages
143–170
Publication date
2 January 2026
Language
EN