BACKGROUND: Spiritual dimensions such as hope, meaning in life and self-transcendence have been found to be predictors of successful ageing, life satisfaction and well-being in older individuals. Connectedness and communicating with others have been seen to facilitate hope, meaning in life and self-transcendence among nursing home patients. AIMS: This study aimed to investigate the associations between hope, meaning in life, self-transcendence and nurse-patient interaction in a nursing home population. DESIGN AND METHODS: A cross-sectional design was employed, collecting data in 44 different Norwegian nursing homes (NHs) from 250 patients who met the inclusion criteria. Approval by all regulatory institutions dealing with research issues in Norway and the Management Unit at the 44 NHs was obtained. A sample of 202 cognitively intact nursing home patients responded to the Herth Hope Index, the Purpose in Life test, the Self-Transcendence Scale and the Nurse-Patient Interaction Scale. A structural equation model (SEM) of the hypothesized relationships between the constructs was tested. RESULTS: The SEM model fit well with the present data. Significant direct relationships of nurse-patient interaction on hope, meaning in life and self-transcendence were displayed. Meaning and the interconnectedness dimension of hope appeared to be particularly dynamic resources, revealing significant influences on all the constructs in the SEM model tested. CONCLUSION: Nurse-patient interaction influences hope, meaning in life and self-transcendence in cognitively intact nursing home patients and might be an important resource in relation to patients' health and global well-being. Thus, care providers are above all fundamental for nursing home patients. Advancing caregivers' interacting and communicating skills might facilitate patients' health and global well-being and inspire professional caregivers as they perform their daily care practices. More research of the effectiveness of such strategies is greatly needed. LIMITATIONS: The SEM model tested comprised 20 variables, indicating a desirable sample size of n = 200, while the present effective sample was n = 187. Also, cross-sectional data do not allow making conclusion on the causality.
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