医学
生活质量(医疗保健)
癌症治疗
老年学
癌症
家庭医学
护理部
内科学
作者
Winnie K.W. So,Carmen W.H. Chan,Kai Chow Choi,Rayman W.M. Wan,Suzanne S. S. Mak,Sek Ying Chair
出处
期刊:Cancer Nursing
[Lippincott Williams & Wilkins]
日期:2012-12-20
卷期号:36 (3): E23-E32
被引量:53
标识
DOI:10.1097/ncc.0b013e318263f28e
摘要
Although advanced cancer treatments prolong survivors' lives, a significant proportion experienced poorer health-related quality of life (HRQoL) than general populations. Identifying their needs is essential to develop a health service delivery model to improve patient outcomes.The objective of this study was to examine the perceived unmet needs and HRQoL of Chinese cancer survivors who completed treatment less than 1 year ago.Three hundred seventy-six participants completed a self-report survey: the 34-item Supportive Care Needs Survey, the supplementary module of access to healthcare and ancillary support services, and the Functional Assessment of Cancer Therapy: General. Descriptive statistics were used to examine the prevalence of unmet needs. Multivariable logistic regressions were conducted to identify participants' characteristics that were associated with unmet needs. Multiple linear regression was used to delineate which domains of unmet needs were significantly associated with HRQoL with adjustment for potential confounding factors.Healthcare information was the most common unmet needs among the survivors. Age, stage of cancer, and remission were significantly associated with 1 or more unmet need domains. Participants with unmet needs in physical, psychological, and patient care domains, on average, have poorer HRQoL.Chinese cancer survivors have various unmet needs that might have adverse effects on their HRQoL. Younger age, more advanced stages of cancer, and remission were factors contributing to further unmet needs.The results provided useful information on the special needs of survivors that may affect their HRQoL, enabling clinicians to plan better how to allocate existing limited resources to those who most require them.
科研通智能强力驱动
Strongly Powered by AbleSci AI