Understanding Information Preferences, Risk Perceptions, and Tradeoffs When Making Decisions About Multi-cancer Early Detection Tests
Investigating Information Preferences, Risk Perceptions, and Tradeoffs in Multi-Cancer Early Detection Decisions: A Randomized Vignette Trial
研究概览
地位
条件
详细说明
研究类型
注册 (估计的)
阶段
- 不适用
联系人和位置
学习联系方式
- 姓名:Christine M Gunn, PhD
- 电话号码:603-646-5430
- 邮箱:Christine.M.Gunn@dartmouth.edu
学习地点
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New Hampshire
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Lebanon、New Hampshire、美国、03756
- Dartmouth College
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接触:
- Christine M Gunn, PhD
- 电话号码:603-646-5430
- 邮箱:Christine.M.Gunn@dartmouth.edu
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接触:
- Laura B Beidler, MPH
- 电话号码:603-646-5611
- 邮箱:laura.beidler@dartmouth.edu
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参与标准
资格标准
适合学习的年龄
- 成人
- 年长者
接受健康志愿者
描述
Inclusion Criteria:
- Aged 40-74
- Speak English or Spanish
Exclusion Criteria:
- Prior diagnosis of cancer (with the exception of non-melanoma skin cancers)
- Previous use of a Multi-Cancer Early Detection (MCED) test.
学习计划
研究是如何设计的?
设计细节
- 主要用途:卫生服务研究
- 分配:随机化
- 介入模型:阶乘赋值
- 屏蔽:单身的
武器和干预
参与者组/臂 |
干预/治疗 |
|---|---|
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实验性的:Arm 1: High, High, High
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The test performance data presented in the vignette will focus on established evidentiary standards for the evaluation of screening tests: Sensitivity, specificity, positive and negative predictive values, and the ability of tests to find specific cancers and more early-stage cancers.
The high numerical detail condition will utilize these numbers and present them according to the decision aid criteria for presenting treatment option data and addressing health literacy.
The high numerical data will use diagnostic workup data from the most up-to-date findings at the time of survey fielding.
Data will be presented on the number of positive tests, follow up included (type and properties of tests), likelihood of receiving each type of test upon a positive findings, and data on median length of time to diagnostic resolution for both true positives and false positives.
Cost estimates will include insurance and out of pocket costs associated with various pathways of diagnostic workup.
The investigators will use test cost estimates based on market rates and insurance coverage mandates at the time of fielding the survey.
The high numerical data condition will provide precise estimates conditioned on level of workup and insurance coverage.
As above, the final content will be informed by new information that may be gleaned from ongoing studies.
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实验性的:Arm 2: High, High, Low
|
The test performance data presented in the vignette will focus on established evidentiary standards for the evaluation of screening tests: Sensitivity, specificity, positive and negative predictive values, and the ability of tests to find specific cancers and more early-stage cancers.
The high numerical detail condition will utilize these numbers and present them according to the decision aid criteria for presenting treatment option data and addressing health literacy.
The high numerical data will use diagnostic workup data from the most up-to-date findings at the time of survey fielding.
Data will be presented on the number of positive tests, follow up included (type and properties of tests), likelihood of receiving each type of test upon a positive findings, and data on median length of time to diagnostic resolution for both true positives and false positives.
The low numerical data will provide broad ranges of diagnostic costs, indicating what costs are covered by insurance, and which are not.
|
|
实验性的:Arm 3: High, Low, Low
|
The test performance data presented in the vignette will focus on established evidentiary standards for the evaluation of screening tests: Sensitivity, specificity, positive and negative predictive values, and the ability of tests to find specific cancers and more early-stage cancers.
The high numerical detail condition will utilize these numbers and present them according to the decision aid criteria for presenting treatment option data and addressing health literacy.
The low numerical data will provide broad ranges of diagnostic costs, indicating what costs are covered by insurance, and which are not.
The low numerical detail condition will describe the possibility of further testing (more blood tests, imaging, and/or procedures) that may be required if the multi-cancer early detection (MCED) test has a positive finding, in line with prior studies communicating about MCED test workup.
|
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实验性的:Arm 4: High, Low, High
|
The test performance data presented in the vignette will focus on established evidentiary standards for the evaluation of screening tests: Sensitivity, specificity, positive and negative predictive values, and the ability of tests to find specific cancers and more early-stage cancers.
The high numerical detail condition will utilize these numbers and present them according to the decision aid criteria for presenting treatment option data and addressing health literacy.
Cost estimates will include insurance and out of pocket costs associated with various pathways of diagnostic workup.
The investigators will use test cost estimates based on market rates and insurance coverage mandates at the time of fielding the survey.
The high numerical data condition will provide precise estimates conditioned on level of workup and insurance coverage.
As above, the final content will be informed by new information that may be gleaned from ongoing studies.
The low numerical detail condition will describe the possibility of further testing (more blood tests, imaging, and/or procedures) that may be required if the multi-cancer early detection (MCED) test has a positive finding, in line with prior studies communicating about MCED test workup.
|
|
实验性的:Arm 5: Low, High, High
|
The high numerical data will use diagnostic workup data from the most up-to-date findings at the time of survey fielding.
Data will be presented on the number of positive tests, follow up included (type and properties of tests), likelihood of receiving each type of test upon a positive findings, and data on median length of time to diagnostic resolution for both true positives and false positives.
Cost estimates will include insurance and out of pocket costs associated with various pathways of diagnostic workup.
The investigators will use test cost estimates based on market rates and insurance coverage mandates at the time of fielding the survey.
The high numerical data condition will provide precise estimates conditioned on level of workup and insurance coverage.
As above, the final content will be informed by new information that may be gleaned from ongoing studies.
The low numerical detail condition will describe the potential for false positives and use descriptions to denote qualitatively performance (high, acceptable, moderate, low).
The test performance data presented in the vignette will focus on established evidentiary standards for the evaluation of screening tests: Sensitivity, specificity, positive and negative predictive values, and the ability of tests to find specific cancers and more early-stage cancers.
|
|
实验性的:Arm 6: Low, Low, High
|
Cost estimates will include insurance and out of pocket costs associated with various pathways of diagnostic workup.
The investigators will use test cost estimates based on market rates and insurance coverage mandates at the time of fielding the survey.
The high numerical data condition will provide precise estimates conditioned on level of workup and insurance coverage.
As above, the final content will be informed by new information that may be gleaned from ongoing studies.
The low numerical detail condition will describe the possibility of further testing (more blood tests, imaging, and/or procedures) that may be required if the multi-cancer early detection (MCED) test has a positive finding, in line with prior studies communicating about MCED test workup.
The low numerical detail condition will describe the potential for false positives and use descriptions to denote qualitatively performance (high, acceptable, moderate, low).
The test performance data presented in the vignette will focus on established evidentiary standards for the evaluation of screening tests: Sensitivity, specificity, positive and negative predictive values, and the ability of tests to find specific cancers and more early-stage cancers.
|
|
实验性的:Arm 7: Low, High, Low
|
The high numerical data will use diagnostic workup data from the most up-to-date findings at the time of survey fielding.
Data will be presented on the number of positive tests, follow up included (type and properties of tests), likelihood of receiving each type of test upon a positive findings, and data on median length of time to diagnostic resolution for both true positives and false positives.
The low numerical data will provide broad ranges of diagnostic costs, indicating what costs are covered by insurance, and which are not.
The low numerical detail condition will describe the potential for false positives and use descriptions to denote qualitatively performance (high, acceptable, moderate, low).
The test performance data presented in the vignette will focus on established evidentiary standards for the evaluation of screening tests: Sensitivity, specificity, positive and negative predictive values, and the ability of tests to find specific cancers and more early-stage cancers.
|
|
实验性的:Arm 8: Low, Low, Low
|
The low numerical data will provide broad ranges of diagnostic costs, indicating what costs are covered by insurance, and which are not.
The low numerical detail condition will describe the possibility of further testing (more blood tests, imaging, and/or procedures) that may be required if the multi-cancer early detection (MCED) test has a positive finding, in line with prior studies communicating about MCED test workup.
The low numerical detail condition will describe the potential for false positives and use descriptions to denote qualitatively performance (high, acceptable, moderate, low).
The test performance data presented in the vignette will focus on established evidentiary standards for the evaluation of screening tests: Sensitivity, specificity, positive and negative predictive values, and the ability of tests to find specific cancers and more early-stage cancers.
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研究衡量的是什么?
主要结果指标
结果测量 |
措施说明 |
大体时间 |
|---|---|---|
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Decisional Conflict
大体时间:24 hours
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A validated 10-item scale scored 0-100 that assesses decisional conflict using a 3-point Likert for each item; Includes 4 subscales: informed, uncertainty, values clarity, and support.
The full scale will be administered after the third vignette is presented (Time 3).
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24 hours
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次要结果测量
结果测量 |
措施说明 |
大体时间 |
|---|---|---|
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Screening Intentions
大体时间:24 hours
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Validated 2 item measure including 1-item measuring intentions on 100 point scale and 1 decision question (yes/no/unsure).
This will be assessed at the end of each vignette (Time 1, 2, 3).
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24 hours
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Informed Subscale of the Decisional Conflict Scale
大体时间:24 hours
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3 Items from the Decisional Conflict Scale will measure how informed participants feel about available options for MCED testing, benefits of MCED testing, and risks of MCED testing.
Each is rated on the 3-point scale (yes/no/unsure).
This will be assessed at the end of each vignette (Time 1, 2, 3).
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24 hours
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Uncertainty Subscale of the Decisional Conflict Scale
大体时间:24 hours
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Two items from the Decisional Conflict Scale will measure uncertainty about the decision to use MCED tests.
This will include feeling clear about the best choice for the participant, and feeling sure about what to choose.
Each is rated on the 3-point scale (yes/no/unsure).
This will be assessed at the end of each vignette (Time 1, 2, 3).
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24 hours
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合作者和调查者
研究记录日期
研究主要日期
学习开始 (估计的)
初级完成 (估计的)
研究完成 (估计的)
研究注册日期
首次提交
首先提交符合 QC 标准的
首次发布 (实际的)
研究记录更新
最后更新发布 (实际的)
上次提交的符合 QC 标准的更新
最后验证
更多信息
与本研究相关的术语
其他研究编号
- STUDY00033796
- 1R01CA317672 (美国 NIH 拨款/合同)
计划个人参与者数据 (IPD)
计划共享个人参与者数据 (IPD)?
IPD 计划说明
Based on ethical considerations related to the protection of human subjects, the following data produced during the project will be preserved and shared:
- Survey responses
- Survey weights
- Qualitative interview data, deidentified and without any participant identifiers beyond assigned study group, state, and limited sociodemographic characteristics
The investigators will seek to share as much data as possible while maintaining a de-identified dataset without protected health information. Thus, the final shared data set will not include geographic subdivisions smaller than the state level, dates, birth dates, contact information, or other identification numbers.
Data available to be shared will be archived in the University of Michigan ICPSR data repository, which was chosen for its focus on social and behavioral data that align with the nature of data collected in this project.
IPD 共享时间框架
IPD 共享访问标准
IPD 共享支持信息类型
- 研究方案
- 分析代码
药物和器械信息、研究文件
研究美国 FDA 监管的药品
研究美国 FDA 监管的设备产品
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