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Initial Validation of a Patient-Reported Compassion Measure in a Mandarin-Speaking Long-Term Care Patient Population

Overview
Journal J Nurs Meas
Specialty Nursing
Date 2023 Jun 23
PMID 37353318
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Abstract

Compassion is increasingly considered essential to quality nursing care and is a concept that is strongly embedded across cultures, including Chinese culture. The Patient Compassion Model (PCM) depicts the unique yet overlapping domains of compassion. The Sinclair Compassion Questionnaire (SCQ) was directly developed and validated from this empirical model. In this study, we sought to establish initial validation of a translated SCQ among Mandarin-speaking patients by assessing the transferability of the PCM and the clinical sensibility of the SCQ. Forward and back-translation of the PCM and SCQ were performed in accordance with World Health Organization guidelines. Qualitative interviews were used to assess the transferability of the PCM with conceptualizations of compassion within a Chinese context. Cognitive interviews were conducted to assess the clarity, readability, wording, questions, and response scales of the Mandarin translation of the SCQ. Qualitative data were analyzed using constant comparative analysis, and cognitive interviews were analyzed using framework analysis. The original categories of the PCM were verified in this Mandarin-speaking patient population. Specifically, participants' understanding of compassion is described as consisting of healthcare provider virtues, emphasizing the importance of a virtuous response that sought to understand the individual and their unique needs, to relationally communicate from a place of shared humanity and to ameliorate suffering. Participants were able to answer, comprehend, and endorse all 15 Mandarin SCQ items, resulting in no modifications to the Mandarin SCQ. This study provides initial validation of the Mandarin SCQ and PCM. Future studies should consider further establishing the validity and reliability of the Mandarin SCQ among a larger Chinese patient population.

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