Suppr超能文献

个体背景对癌症幸存者和照护者未满足需求的影响——一项混合方法分析。

Impact of individual background on the unmet needs of cancer survivors and caregivers - a mixed-methods analysis.

机构信息

Department of Clinical Oncology, Yamagata University, Faculty of Medicine, Yamagata, Japan.

Cancer Prevention and Cancer Control Division, Kanagawa Cancer Center, Research Institute, 2-3-2 Nakao, Asahi-ku, Yokohama, Kanagawa, 241-8515, Japan.

出版信息

BMC Cancer. 2020 Mar 30;20(1):263. doi: 10.1186/s12885-020-06732-5.

Abstract

BACKGROUND

Cancer survivors and their caregivers may have various unmet needs that are medically difficult to solve. Previous studies have suggested the relations between individuals' backgrounds and their unmet needs. We conducted a large-scale analysis to clarify the influence of individuals' backgrounds, primarily cancer type, on specific types of unmet needs.

METHODS

Using a mixed-methods approach, we analyzed records of first-time callers to a cancer-focused telephone consultation service that was provided by the Kanagawa Cancer Clinical Research Information Organization from October 2006 to May 2014. The qualitative approach concerned extracting unmet needs mentioned in each consultation and classifying them into themes of specific needs, while the quantitative approach comprised multi-variated analysis of the relationships between the frequency by which the needs in each theme arose and the associated callers' backgrounds.

RESULTS

A total of 1938 consultation cases were analyzed. In the qualitative analysis, the needs were classified into 16 themes. The mean number of unmet needs for each caller was 1.58 (standard deviation = 0.86). In the multi-variated analysis, caregivers for colorectal cancer survivors had a lower frequency of "emotional/mental health" needs (OR: 0.31, 95%CI: 0.11-0.88, p = 0.028) than did caregivers for breast-cancer survivors. Nevertheless, this was the only significant difference in needs frequency among callers (including survivors and their caregivers) with specific cancer types. Meanwhile, there significant difference in the frequency of occurrence of each unmet need theme was found among items concerning other background elements. Among survivors, sex was related to the frequency of needs among "physical" and "resources" themes, and "emotions/mental health"; their age group with "employment"; treatment course with "physical" and "resources" themes and "cure"; residence with "physical" themes; presence of symptom with "physical," "education/information," "resources," "emotions/mental health," and "cure" themes.

CONCLUSIONS

This large-scale study suggests that cancer type is not a significant factor for specific unmet needs and that individuals' backgrounds and presence of symptoms play a more important role. Through this study, it was found that instruments to predict people's needs and a system to provide individualized cancer care across cancer types should be developed in the future.

摘要

背景

癌症幸存者及其照顾者可能存在各种难以通过医学手段解决的未满足需求。先前的研究表明,个体背景与未满足需求之间存在关联。我们进行了一项大规模分析,旨在阐明个体背景(主要是癌症类型)对特定类型未满足需求的影响。

方法

采用混合方法,我们分析了 2006 年 10 月至 2014 年 5 月期间,由神奈川癌症临床研究信息组织提供的癌症专项电话咨询服务中首次来电者的记录。定性方法涉及提取每次咨询中提到的未满足需求,并将其归类为特定需求主题;定量方法则包括对每个主题出现的需求频率与来电者背景之间的关系进行多变量分析。

结果

共分析了 1938 例咨询案例。在定性分析中,需求被分为 16 个主题。每位来电者的未满足需求平均数为 1.58(标准差=0.86)。在多变量分析中,结直肠癌幸存者的照顾者的“情绪/心理健康”需求频率较低(OR:0.31,95%CI:0.11-0.88,p=0.028),而乳腺癌幸存者的照顾者则较高。然而,这是特定癌症类型来电者(包括幸存者及其照顾者)中唯一一项需求频率存在显著差异的因素。同时,在与其他背景元素相关的项目中,也发现了每个未满足需求主题的发生频率存在显著差异。在幸存者中,性别与“身体”和“资源”主题以及“情绪/心理健康”主题的需求频率有关,年龄与“就业”主题有关,治疗过程与“身体”和“资源”主题以及“治愈”主题有关,居住地与“身体”主题有关,症状与“身体”、“教育/信息”、“资源”、“情绪/心理健康”和“治愈”主题有关。

结论

这项大规模研究表明,癌症类型并不是特定未满足需求的重要因素,个体背景和症状的存在起着更为重要的作用。通过这项研究,发现未来应该开发预测人们需求的工具以及跨癌症类型提供个性化癌症护理的系统。

相似文献

引用本文的文献

本文引用的文献

1
Cancer Survivorship.癌症幸存者关怀
N Engl J Med. 2018 Dec 20;379(25):2438-2450. doi: 10.1056/NEJMra1712502.
5
Young adult cancer survivors and work: a systematic review.年轻成年癌症幸存者与工作:一项系统综述。
J Cancer Surviv. 2017 Dec;11(6):765-781. doi: 10.1007/s11764-017-0614-3. Epub 2017 May 6.
7
Identity threat and stigma in cancer patients.癌症患者的身份威胁与污名化
Health Psychol Open. 2014 Sep 25;1(1):2055102914552281. doi: 10.1177/2055102914552281. eCollection 2014 Jul.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验