Efficacy of an artificial intelligence-based program for managing fatigue in Chinese young breast cancer survivors: a randomized controlled trial

IF 8.1 1区 医学 Q1 HEALTH CARE SCIENCES & SERVICES The Lancet Regional Health: Western Pacific Pub Date : 2025-02-01 Epub Date: 2025-02-17 DOI:10.1016/j.lanwpc.2024.101288
Yun Hu , Joshua Wiley , Lulu Jiang , Ran Yi , Eun-Ok Im
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Abstract

Background

Fatigue is a common problem among breast cancer survivors, particularly among young breast cancer survivors (YBCSs) who often juggle work and family responsibilities. This demographic frequently experiences high levels of fatigue, which adversely impacts their quality of life. The study aimed to examine the effectiveness of an artificial intelligence (AI) -based program in managing cancer-related fatigue among Chinese YBCSs.

Methods

A randomized clinical trial was conducted from Jan2021 to Dec 2022, involving 115 YBCSs. The intervention group received multimodal support combing artificial intelligence (AI) interaction and humanities skills, while the control group received online information support only for 12 weeks. The outcomes were measured using the BFI (Fatigue, primary), and the FACT-B (quality of life, secondary). An intention-to treat approach was used to analyze differences in fatigue and quality of life.

Findings

Both groups showed improvements in fatigue score(p<0.05) from baseline(T0) to 4 weeks(T1) and 12 weeks(T2). Notably, at the 12-week mark, the intervention group demonstrated a more substantial reduction in fatigue compared to the control group. Additionally, the intervention group experienced a greater increase in quality of life from T1 to T2 (β=15.384, 95% CI:13.028–17.740, P<.001).

Interpretation

This study demonstrates that an AI-based program could help effectively manage fatigue, subsequently enhancing the quality of life among YBCSs. The integration of AI and humanities skills offers a promising approach to improving health outcomes in this vulnerable population.
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基于人工智能的项目对中国年轻乳腺癌幸存者疲劳管理的有效性:一项随机对照试验
疲劳是乳腺癌幸存者的一个普遍问题,尤其是年轻的乳腺癌幸存者(YBCSs),他们经常要兼顾工作和家庭责任。这一人群经常经历高度疲劳,这对他们的生活质量产生了不利影响。该研究旨在研究基于人工智能(AI)的程序在管理中国ybcs癌症相关疲劳方面的有效性。方法于2021年1月至2022年12月进行随机临床试验,纳入115例ybcs。干预组接受人工智能交互与人文技能相结合的多模式支持,对照组仅接受12周的在线信息支持。结果使用BFI(疲劳,主要)和FACT-B(生活质量,次要)进行测量。采用意向治疗方法分析疲劳和生活质量的差异。两组患者疲劳评分较基线(T0)至4周(T1)和12周(T2)均有改善(p<0.05)。值得注意的是,在12周时,干预组表现出比对照组更明显的疲劳减轻。此外,干预组从T1到T2的生活质量有更大的提高(β=15.384, 95% CI: 13.028-17.740, P<.001)。本研究表明,基于人工智能的程序可以帮助有效地管理疲劳,从而提高ybcs的生活质量。人工智能与人文技能的结合为改善这一弱势群体的健康状况提供了一种有希望的方法。
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来源期刊
The Lancet Regional Health: Western Pacific
The Lancet Regional Health: Western Pacific Medicine-Pediatrics, Perinatology and Child Health
CiteScore
8.80
自引率
2.80%
发文量
305
审稿时长
11 weeks
期刊介绍: The Lancet Regional Health – Western Pacific, a gold open access journal, is an integral part of The Lancet's global initiative advocating for healthcare quality and access worldwide. It aims to advance clinical practice and health policy in the Western Pacific region, contributing to enhanced health outcomes. The journal publishes high-quality original research shedding light on clinical practice and health policy in the region. It also includes reviews, commentaries, and opinion pieces covering diverse regional health topics, such as infectious diseases, non-communicable diseases, child and adolescent health, maternal and reproductive health, aging health, mental health, the health workforce and systems, and health policy.
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