4.2 Article

Symptom Clusters and Quality of Life in Older Adult Breast Cancer Survivors

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ONCOLOGY NURSING FORUM
卷 38, 期 6, 页码 672-680

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ONCOLOGY NURSING SOC
DOI: 10.1188/11.ONF.672-680

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资金

  1. National Institute on Aging [R01AG022914]
  2. Office of Cancer Survivorship, National Cancer Institute

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Purpose/Objectives: To identify symptom clusters in older adult breast cancer survivors (ages 65-97 years) and examine whether symptom clusters are related to demographic, health, and quality-of-life variables. Design: Factor analysis to identify possible symptom clusters. The resulting clusters then were correlated with quality-of-life measures. Setting: Phone interviews between the participants and a trained research nurse. Sample: 192 breast cancer survivors ((X) over bar age = 70). Methods: This was a secondary data analysis of the baseline measures of demographics, health history, symptom bother, and physical, mental, and existential dimensions of quality of life. Exploratory and confirmatory factor analyses were conducted as well as multiple indicator multiple cause modeling and partial correlation analyses to assess the relationships among clusters and demographic, health history, and quality-of-life measures. Main Research Variables: Self-reported symptom bother, demographics such as age and education level, health history, and quality of life. Findings: Seven clinically distinct symptom clusters tapping 36 different symptoms in older adult breast cancer survivors were found. These symptom clusters were significantly related to multiple dimensions of quality of life. Conclusions: Older adult breast cancer survivors experience multiple concurrent symptoms that appear to cluster. Identifying symptom clusters helps to elucidate possible intersymptom relationships which may lead to the design of more effective symptom management interventions for older adult breast cancer survivors. Implications for Nursing: Older adult breast cancer survivors should be assessed for a wide variety of symptoms if clinicians hope to identify and understand intersymptom relationships. Such assessment would enable more comprehensive symptom management.

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