A Personalized, SMS-Based Conversational Agent to Address Sleep Disturbance in Breast Cancer Survivors: Protocol for a Pilot Waitlist Randomized Controlled Trial (Preprint)

Author:

Tsai Chi-shan,Szewczyk Warren,Drerup Michelle,Liao Jason,Vasbinder AlexiORCID,Greenlee Heather,Heffner Jaimee LORCID,Yung Rachel,Reding Kerryn W.

Abstract

BACKGROUND

Sleep disturbance is one of the most common health concerns reported by breast cancer (BC) survivors and is associated with poor quality of life (QoL) and greater mortality after treatment. Cognitive behavior therapy for insomnia (CBTi) has shown efficacy for improving sleep and quality of life for BC survivors. Considered the gold standard insomnia treatment, CBTi can be delivered remotely, including via digital intervention. Despite the potential for wider dissemination of CBTi via digital means, these modalities have unique challenges, including technology barriers and poor adherence. We developed a conversational agent (CA) to deliver CBTi via short message service (SMS), supported by mobile-ready web content. Named “Cecebot”, this CA delivers sleep education, implements sleep compression, provides just-in-time intervention on sleep-disrupting behaviors, and includes enhanced support for physical activity (PA) beyond what is typically included in CBTi. This represents a novel modality for a CBTi and PA intervention in BC survivors.

OBJECTIVE

We aim to examine the safety and acceptability of the Cecebot intervention for BC survivors with symptoms of insomnia and explore intervention efficacy.

METHODS

This trial will recruit 60 BC survivors who are experiencing moderate to severe sleep disturbance. Participants will be assigned to the Cecebot intervention or waitlist control group at a 1:1 ratio. The treatment group will receive Cecebot intervention during weeks 1-6 of the study, while the waitlist control condition will receive the Cecebot intervention during weeks 6-12. The Cecebot intervention utilizes SMS technology paired with Fitbit. Participants will be assessed at baseline, week 6, and week 12. Measurements will include feasibility and acceptability, and explore the effect of a Cecebot intervention.

RESULTS

Recruitment of participants began in Spring 2024. The completion of data collection is anticipated to be by Winter 2025.

CONCLUSIONS

The study results will give insight into the potential for an SMS-based conversational agent to improve sleep in BC survivors with sleep disturbances.

Publisher

JMIR Publications Inc.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3