Symptom clusters in outpatients with cancer using different dimensions of the symptom experience

医学 内科学 星团(航天器) 苦恼 探索性因素分析 癌症 临床心理学 心理测量学 计算机科学 程序设计语言
作者
Carolyn Harris,Kord M. Kober,Bruce A. Cooper,Yvette P. Conley,Anand Dhruva,Marilyn J. Hammer,Steven M. Paul,Jon D. Levine,Christine Miaskowski
出处
期刊:Supportive Care in Cancer [Springer Science+Business Media]
卷期号:30 (8): 6889-6899 被引量:10
标识
DOI:10.1007/s00520-022-07125-z
摘要

Relatively few studies have evaluated for symptom clusters across multiple dimensions. It is unknown whether the symptom dimension used to create symptom clusters influences the number and types of clusters that are identified. Study purposes were to describe ratings of occurrence, severity, and distress for 38 symptoms in a heterogeneous sample of oncology patients (n = 1329) undergoing chemotherapy; identify and compare the number and types of symptom clusters based on three dimensions (i.e., occurrence, severity, and distress); and identify common and distinct clusters.A modified version of the Memorial Symptom Assessment Scale was used to assess the occurrence, severity, and distress ratings of 38 symptoms in the week prior to patients' next cycle of chemotherapy. Symptom clusters for each dimension were identified using exploratory factor analysis.Patients reported an average of 13.9 (±7.2) concurrent symptoms. Lack of energy was both the most common and severe symptom while "I don't look like myself" was the most distressing. Psychological, gastrointestinal, weight gain, respiratory, and hormonal clusters were identified across all three dimensions. Findings suggest that psychological, gastrointestinal, and weight gain clusters are common while respiratory and hormonal clusters are distinct.Psychological, gastrointestinal, weight gain, hormonal, and respiratory clusters are stable across occurrence, severity, and distress in oncology patients receiving chemotherapy. Given the stability of these clusters and the consistency of the symptoms across dimensions, the use of a single dimension to identify these clusters may be sufficient. However, comprehensive and disease-specific inventories need to be used to identify distinct clusters.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
无力回天发布了新的文献求助10
刚刚
刚刚
充电宝应助尺八采纳,获得10
1秒前
chen发布了新的文献求助10
1秒前
心潮澎湃完成签到,获得积分10
1秒前
llk完成签到,获得积分10
1秒前
Fan完成签到 ,获得积分10
1秒前
小作坊钳工完成签到,获得积分10
1秒前
阿秋完成签到,获得积分10
2秒前
搜集达人应助舟遥遥采纳,获得10
2秒前
哒丝萌德发布了新的文献求助10
3秒前
RR完成签到,获得积分10
3秒前
脑洞疼应助闫132采纳,获得10
4秒前
natuki完成签到,获得积分10
4秒前
852应助淡淡的南风采纳,获得10
5秒前
CipherSage应助淡淡的南风采纳,获得10
5秒前
bkagyin应助淡淡的南风采纳,获得10
5秒前
qiao完成签到,获得积分10
5秒前
田様应助淡淡的南风采纳,获得30
5秒前
Owen应助淡淡的南风采纳,获得10
5秒前
Zelytnn.Lo完成签到,获得积分10
5秒前
SophieLiu完成签到,获得积分10
6秒前
浪子应助八宝周采纳,获得10
7秒前
shtatbf完成签到,获得积分0
7秒前
叙白完成签到 ,获得积分10
7秒前
shawn_89完成签到,获得积分10
8秒前
胖虎啊完成签到,获得积分10
9秒前
Ldq关闭了Ldq文献求助
9秒前
江湖护卫舰完成签到 ,获得积分10
10秒前
10秒前
会飞的生菜完成签到,获得积分10
11秒前
BPX完成签到,获得积分10
11秒前
WL完成签到 ,获得积分10
12秒前
充电宝应助那日迈采纳,获得10
12秒前
黄毅完成签到,获得积分10
13秒前
轻松凡英完成签到,获得积分10
13秒前
Niko完成签到,获得积分10
13秒前
66135完成签到,获得积分10
13秒前
林距离完成签到 ,获得积分10
13秒前
岗岗完成签到,获得积分10
14秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Zeolites: From Fundamentals to Emerging Applications 1500
Encyclopedia of Materials: Plastics and Polymers 1000
Architectural Corrosion and Critical Infrastructure 1000
Early Devonian echinoderms from Victoria (Rhombifera, Blastoidea and Ophiocistioidea) 1000
Hidden Generalizations Phonological Opacity in Optimality Theory 1000
Handbook of Social and Emotional Learning, Second Edition 900
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 内科学 生物化学 物理 计算机科学 纳米技术 遗传学 基因 复合材料 化学工程 物理化学 病理 催化作用 免疫学 量子力学
热门帖子
关注 科研通微信公众号,转发送积分 4927274
求助须知:如何正确求助?哪些是违规求助? 4196631
关于积分的说明 13033926
捐赠科研通 3969413
什么是DOI,文献DOI怎么找? 2175332
邀请新用户注册赠送积分活动 1192422
关于科研通互助平台的介绍 1103141