Characteristics and influencing factors of demoralization in patients with lung cancer: A latent class analysis

潜在类模型 习得的无助感 肺癌 应对(心理学) 苦恼 失调家庭 临床心理学 医学 多项式logistic回归 社会阶层 心理学 肿瘤科 数学 统计 计算机科学 机器学习 法学 政治学
作者
Yu Hong,B. Ye,Jia Lin,Qiu Hong Chen,Juan Zhang,Wei‐Ti Chen,Fei Fei Huang
出处
期刊:Psycho-oncology [Wiley]
卷期号:33 (3) 被引量:5
标识
DOI:10.1002/pon.6312
摘要

Abstract Objective Demoralization has garnered increasing attention in recent years as a significant psychological distress. This study aims to identify latent classes of demoralization in lung cancer patients using Latent Class Analysis (LCA) from a person‐centered perspective and to explore the factors influencing the latent classes of demoralization. Methods A cross‐sectional study using convenience sampling was conducted among 567 lung cancer patients in three tertiary hospitals in China. LCA was employed to classify heterogeneous classes of demoralization. Multinomial logistic regression analyses were performed to explore the associations between demographic and clinical characteristics, as well as physical symptoms, resilience, family function, and coping strategies, with class membership in the identified heterogeneous subgroups of lung cancer patients. Results Three latent classes of demoralization were identified: the high demoralization group (Class 1, 14.8%), the moderate demoralization‐distress and helplessness group (Class 2, 37.2%), and the low demoralization group (Class 3, 48.0%). In comparison to Class 3, lung cancer patients with hypertension, higher core symptom burden, poorer resilience, dysfunctional family dynamics, and resignation coping were more likely to belong to Class 1 and Class 2. Conclusions The demoralization patterns in lung cancer patients were varied. Targeted intervention should be developed based on the characteristics of each class, and timely attention should be paid to high‐risk patients.
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
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
刚刚
刚刚
zibizheng发布了新的文献求助10
1秒前
司忆完成签到 ,获得积分10
1秒前
Bethune完成签到 ,获得积分10
1秒前
1秒前
d.zhang发布了新的文献求助10
1秒前
sainanTang完成签到,获得积分10
3秒前
3秒前
yy完成签到,获得积分10
3秒前
FashionBoy应助qjm采纳,获得10
4秒前
CipherSage应助吕佳恒采纳,获得10
4秒前
坚定的惜海完成签到,获得积分20
4秒前
5秒前
5秒前
LingC完成签到,获得积分10
6秒前
6秒前
dandany完成签到,获得积分10
7秒前
科研通AI2S应助lusgul采纳,获得10
8秒前
8秒前
8秒前
光亮蜗牛完成签到 ,获得积分10
9秒前
搞怪代桃完成签到 ,获得积分20
9秒前
9秒前
10秒前
吴祥佳发布了新的文献求助200
10秒前
骑手完成签到,获得积分10
10秒前
11秒前
bob完成签到,获得积分10
11秒前
干雅柏完成签到,获得积分10
12秒前
cc关闭了cc文献求助
12秒前
13秒前
NexusExplorer应助西子阳采纳,获得10
13秒前
义气雍发布了新的文献求助10
13秒前
alittlelulu发布了新的文献求助10
13秒前
14秒前
yolo发布了新的文献求助10
14秒前
草莓熊发布了新的文献求助10
14秒前
干雅柏发布了新的文献求助10
14秒前
14秒前
高分求助中
The organometallic chemistry of the transition metals 7th 666
こんなに痛いのにどうして「なんでもない」と医者にいわれてしまうのでしょうか 510
Seven new species of the Palaearctic Lauxaniidae and Asteiidae (Diptera) 400
Handbook of Laboratory Animal Science 300
Where and how to use plate heat exchangers 300
Fundamentals of Medical Device Regulations, Fifth Edition(e-book) 300
A method for calculating the flow in a centrifugal impeller when entropy gradients are present 240
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 物理 生物化学 纳米技术 计算机科学 化学工程 内科学 复合材料 物理化学 电极 遗传学 量子力学 基因 冶金 催化作用
热门帖子
关注 科研通微信公众号,转发送积分 3702400
求助须知:如何正确求助?哪些是违规求助? 3252259
关于积分的说明 9878647
捐赠科研通 2964370
什么是DOI,文献DOI怎么找? 1625600
邀请新用户注册赠送积分活动 770123
科研通“疑难数据库(出版商)”最低求助积分说明 742869