Background: Family caregivers remain closely involved in communication, care planning, and shared decision-making in long-term care (LTC) facilities. In this context, the quality of the relationship between family caregivers and professional staff may influence trust, collaboration, and satisfaction with care. However, few instruments have been specifically adapted to assess caregiver–staff relationship quality in Taiwanese LTC settings. Objectives: This study aimed to culturally adapt and preliminarily validate the Family Caregiver Relationship Quality (FCRQ) Scale for use in Taiwanese LTC facilities. Methods: A cross-sectional psychometric validation study was conducted with 205 primary family caregivers recruited from 20 LTC facilities in Taiwan. The original Relationship Quality Scale was adapted to the LTC context through contextual revision, expert review, bilingual verification, and pilot testing. Psychometric evaluation included confirmatory factor analysis, internal consistency assessment, convergent validity, and structural equation modelling with Bollen–Stine bootstrap correction to address potential non-normality. Results: The initial 16-item model required refinement, and three items with low standardized factor loadings were removed. The revised 13-item model met the prespecified fit criteria and showed acceptable internal consistency and convergent validity. The retained items reflected three conceptually related domains of relationship quality: trust, commitment, and satisfaction. Overall, the findings provided preliminary psychometric support for the adapted scale in Taiwanese LTC settings. Conclusions: The adapted FCRQ Scale may be a useful tool for assessing caregiver–staff relationship quality in Taiwanese long-term care facilities, particularly in the context of shared decision-making and family-centred care. Nevertheless, the findings should be interpreted as preliminary, and further validation in larger and more diverse samples is needed before broader clinical or research application.
Building similarity graph...
Analyzing shared references across papers
Loading...
Chen et al. (Fri,) studied this question.
www.synapsesocial.com/papers/69e471c5010ef96374d8e021 — DOI: https://doi.org/10.3390/healthcare14081068
Pai-Yueh Chen
Ying-Hua Chao
Yi-Jen Huang
Healthcare
National Yang Ming Chiao Tung University
Taipei Medical University
National Defense Medical Center
Building similarity graph...
Analyzing shared references across papers
Loading...