PO.CL11.02 · 临床研究
一项文化定制的基于技术的癌症疼痛管理项目对亚裔美国乳腺癌生存者按社会心理因素划分的生活质量的影响
The impact of a culturally tailored technology-based cancer pain management program on the quality of life by psychosocial factors among Asian American breast cancer survivors
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摘要 Abstract
中文摘要
背景：乳腺癌生存者在治疗和生存过程中面临维持生活质量的挑战。尤其是亚裔美国乳腺癌生存者，她们经常遭遇社会支持受限以及难以获得充分的情感与实际支持的困境。文化障碍往往是这些困境的主要原因。本研究旨在探讨一项文化定制的基于技术的癌症疼痛管理项目对亚裔美国乳腺癌生存者按社会心理因素划分的生活质量（QoL）的影响。
方法：本研究是一项针对亚裔美国女性乳腺癌生存者的正在进行的随机对照试验的一部分。数据在为期3个月的干预过程中于T0（基线）、T1（1个月后；干预期间）和T2（3个月后；干预后）采集。本分析仅纳入完成干预的57名参与者的数据。所用工具包括感知孤立量表（PIS）、关于态度、自我效能、感知障碍和社会影响的问卷（QASPS），以及癌症治疗功能评估量表-乳腺癌（FACT-B）。使用基线数据进行K均值聚类分析。使用R中的NbClust包选择最佳聚类数（k=2）。参与者被划分为两个聚类，然后与干预交叉，形成共四个组。使用线性混合模型（LMM）检验时间、聚类和干预之间的交互效应，以考察纵向轨迹。
结果：K均值分析得出两个聚类。聚类1（n=18；CAI=9，CAPA=9）表现出更高的孤独感、更低的社会支持、更弱的积极态度和自我效能，以及更多的感知障碍，而聚类2（n=39；CAI=26，CAPA=13）则表现出相反的模式。LMM分析显示时间和聚类对QoL有显著影响。在两组中，QoL均随时间改善（T1对比T0：p=.003，T2对比T0：p<.001）。聚类2报告的QoL高于聚类1（聚类2对比聚类1：p=.002）。除Time 2 × Cluster 2交互作用（p=.040）外，未发现其他显著的交互效应。
结论：本研究表明，无论参与者社会心理因素水平如何，基于技术的干预都能对乳腺癌生存者的QoL产生积极影响。然而，由于样本量小以及聚类之间的不平衡，解释结果时需要谨慎。未来研究应纳入足够大的样本量，以确认CAI干预的长期效果。
查看英文原文 English abstract
Background: Breast cancer survivors face challenges in maintaining their quality of life during their treatment and survivorship process. Especially, Asian American breast cancer survivors frequently encounter constrained social supports and difficulties in accessing adequate emotional and practical support. Cultural barriers are often the major cause of the difficulties. This study aimed to explore the impact of a culturally tailored technology-based cancer pain management program on the quality of life (QoL) by psychosocial factors among Asian American breast cancer survivors.
Methods: This is a part of an ongoing randomized controlled trial among Asian American women breast cancer survivors. Data was collected at T0 (baseline), T1 (after 1 month; during intervention), and T2 (after 3 months; post intervention) during the 3-month intervention process. Only the data from 57 participants who completed the intervention were included in this analysis. The instruments included the Perceived Isolation Scale, (PIS) and the Questions on Attitudes, Self-Efficacy, Perceived Barriers, and Social Influences (QASPS), and the Functional Assessment of Cancer Therapy Scale-Breast Cancer (FACT-B). K-means cluster analysis was conducted using baseline data. The optimal number of clusters (k=2) was selected using NbClust package in R. The participants were classified into two clusters, which were then crossed with the interventions form a total of four groups. Longitudinal trajectories were examined using linear mixed model (LMM) to test interaction effects between Time, Cluster, and Intervention
Results: Two clusters emerged from the K-means analysis. Cluster 1 (n=18; CAI=9, CAPA=9) showed higher loneliness, lower social support, less positive attitude and self-efficacy, and more perceived barriers, whereas Cluster 2 (n=39; CAI=26, CAPA=13) showed the opposite pattern. LMM analysis revealed significant effects of Time and Cluster on the QoL. In both groups, the QoL improved over time (T1 vs T0: p =.003, T2 vs T0: p <.001). Cluster 2 reported higher QoL (Cluster 2 vs Cluster 1: p =.002) than Cluster 1. Except Time 2 x Cluster 2 interaction ( p =.040), no other significant interaction effects were found.
Conclusion: This study demonstrated that technology-based interventions can positively impact QoL for breast cancer survivors, regardless of participants' level of psychosocial factors. However, caution is required when interpreting the results due to the small sample size and imbalance between clusters. Future studies should include a large enough sample size to confirm the long-term effects of Intervention CAI.
利益披露 Disclosure
Y. Kim, None..
J. Baek, None..
D. Kim, None..
S. Ryu, None..
W. Chee, None..
E. Im, None.