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计算机定制的肺癌筛查决策支持工具:基于社区的试点随机对照试验。

Computer-Tailored Decision Support Tool for Lung Cancer Screening: Community-Based Pilot Randomized Controlled Trial.

机构信息

Memorial Sloan Kettering Cancer Center, New York, NY, United States.

Indiana University School of Informatics and Computing, Indianapolis, IN, United States.

出版信息

J Med Internet Res. 2020 Nov 3;22(11):e17050. doi: 10.2196/17050.

Abstract

BACKGROUND

Lung cancer screening is a US Preventive Services Task Force Grade B recommendation that has been shown to decrease lung cancer-related mortality by approximately 20%. However, making the decision to screen, or not, for lung cancer is a complex decision because there are potential risks (eg, false positive results, overdiagnosis). Shared decision making was incorporated into the lung cancer screening guideline and, for the first time, is a requirement for reimbursement of a cancer screening test from Medicare. Awareness of lung cancer screening remains low in both the general and screening-eligible populations. When a screening-eligible person visits their clinician never having heard about lung cancer screening, engaging in shared decision making to arrive at an informed decision can be a challenge. Methods to effectively prepare patients for these clinical encounters and support both patients and clinicians to engage in these important discussions are needed.

OBJECTIVE

The aim of the study was to estimate the effects of a computer-tailored decision support tool that meets the certification criteria of the International Patient Decision Aid Standards that will prepare individuals and support shared decision making in lung cancer screening decisions.

METHODS

A pilot randomized controlled trial with a community-based sample of 60 screening-eligible participants who have never been screened for lung cancer was conducted. Approximately half of the participants (n=31) were randomized to view LungTalk-a web-based tailored computer program-while the other half (n=29) viewed generic information about lung cancer screening from the American Cancer Society. The outcomes that were compared included lung cancer and screening knowledge, lung cancer screening health beliefs (perceived risk, perceived benefits, perceived barriers, and self-efficacy), and perception of being prepared to engage in a discussion about lung cancer screening with their clinician.

RESULTS

Knowledge scores increased significantly for both groups with greater improvement noted in the group receiving LungTalk (2.33 vs 1.14 mean change). Perceived self-efficacy and perceived benefits improved in the theoretically expected directions.

CONCLUSIONS

LungTalk goes beyond other decision tools by addressing lung health broadly, in the context of performing a low-dose computed tomography of the chest that has the potential to uncover other conditions of concern beyond lung cancer, to more comprehensively educate the individual, and extends the work of nontailored decision aids in the field by introducing tailoring algorithms and message framing based upon smoking status in order to determine what components of the intervention drive behavior change when an individual is informed and makes the decision whether to be screened or not to be screened for lung cancer.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/resprot.8694.

摘要

背景

肺癌筛查是美国预防服务工作组(USPSTF)的 B 级推荐,已被证明可降低约 20%的肺癌相关死亡率。然而,决定是否进行肺癌筛查是一个复杂的决策,因为存在潜在风险(例如,假阳性结果、过度诊断)。共同决策被纳入肺癌筛查指南,并且首次成为医疗保险癌症筛查测试报销的要求。在一般人群和有筛查资格的人群中,对肺癌筛查的认识仍然很低。当有筛查资格的人去看医生时,他们从未听说过肺癌筛查,那么要达成知情决策,共同决策可能会具有挑战性。需要有方法来有效地为这些临床接触做好患者准备,并支持患者和临床医生进行这些重要的讨论。

目的

本研究旨在评估一种符合国际患者决策辅助工具标准的计算机定制决策支持工具的效果,该工具符合国际患者决策辅助工具标准的认证标准,将为个人提供准备,并支持在肺癌筛查决策中进行共同决策。

方法

一项采用社区为基础的、从未接受过肺癌筛查的 60 名有筛查资格的参与者的试点随机对照试验。参与者被随机分为两组,大约一半(n=31)的参与者观看 LungTalk-一种基于网络的定制计算机程序-而另一半(n=29)观看美国癌症协会提供的关于肺癌筛查的一般信息。比较的结果包括肺癌和筛查知识、肺癌筛查健康信念(感知风险、感知益处、感知障碍和自我效能)以及对与医生讨论肺癌筛查的准备程度。

结果

两组的肺癌和筛查知识得分均显著增加,其中接受 LungTalk 的组得分增加幅度更大(2.33 分比 1.14 分)。感知自我效能和感知益处朝着预期的方向改善。

结论

LungTalk 通过广泛解决肺部健康问题,在进行胸部低剂量计算机断层扫描的背景下,超越了其他决策工具,该扫描有可能发现除肺癌以外其他值得关注的情况,从而更全面地教育个人,并通过引入基于吸烟状况的定制算法和信息框架,扩展了该领域非定制决策辅助工具的工作,以确定当个人获得信息并决定是否筛查肺癌时,哪些干预组件会推动行为改变。

国际注册报告标识符(IRRID):RR2-10.2196/resprot.8694。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5ee4/7671845/6ef5995005e6/jmir_v22i11e17050_fig1.jpg

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