- ICH GCP
- 미국 임상 시험 레지스트리
- 임상시험 NCT07793539
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
연구 개요
상태
정황
상세 설명
연구 유형
등록 (추정된)
단계
- 해당 없음
연락처 및 위치
연구 연락처
- 이름: Christine M Gunn, PhD
- 전화번호: 603-646-5430
- 이메일: Christine.M.Gunn@dartmouth.edu
연구 장소
-
-
New Hampshire
-
Lebanon, New Hampshire, 미국, 03756
- Dartmouth College
-
연락하다:
- Christine M Gunn, PhD
- 전화번호: 603-646-5430
- 이메일: Christine.M.Gunn@dartmouth.edu
-
연락하다:
- Laura B Beidler, MPH
- 전화번호: 603-646-5611
- 이메일: laura.beidler@dartmouth.edu
-
-
참여기준
자격 기준
공부할 수 있는 나이
- 성인
- 고령자
건강한 자원 봉사자를 받아들입니다
설명
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.
공부 계획
연구는 어떻게 설계됩니까?
디자인 세부사항
- 주 목적: 건강 서비스 연구
- 할당: 무작위
- 중재 모델: 요인 할당
- 마스킹: 하나의
무기와 개입
참가자 그룹 / 팔 |
개입 / 치료 |
|---|---|
|
실험적: Arm 1: High, High, 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.
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.
|
|
실험적: 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.
|
|
실험적: 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.
|
|
실험적: 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.
|
|
실험적: 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.
|
|
실험적: 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.
|
|
실험적: 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.
|
|
실험적: 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.
|
연구는 무엇을 측정합니까?
주요 결과 측정
결과 측정 |
측정값 설명 |
기간 |
|---|---|---|
|
Decisional Conflict
기간: 24 hours
|
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).
|
24 hours
|
2차 결과 측정
결과 측정 |
측정값 설명 |
기간 |
|---|---|---|
|
Screening Intentions
기간: 24 hours
|
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).
|
24 hours
|
|
Informed Subscale of the Decisional Conflict Scale
기간: 24 hours
|
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).
|
24 hours
|
|
Uncertainty Subscale of the Decisional Conflict Scale
기간: 24 hours
|
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).
|
24 hours
|
공동 작업자 및 조사자
연구 기록 날짜
연구 주요 날짜
연구 시작 (추정된)
기본 완료 (추정된)
연구 완료 (추정된)
연구 등록 날짜
최초 제출
QC 기준을 충족하는 최초 제출
처음 게시됨 (실제)
연구 기록 업데이트
마지막 업데이트 게시됨 (실제)
QC 기준을 충족하는 마지막 업데이트 제출
마지막으로 확인됨
추가 정보
이 연구와 관련된 용어
기타 연구 ID 번호
- STUDY00033796
- 1R01CA317672 (미국 NIH 보조금/계약)
개별 참가자 데이터(IPD) 계획
개별 참가자 데이터(IPD)를 공유할 계획입니까?
IPD 계획 설명
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 공유 기간
IPD 공유 액세스 기준
IPD 공유 지원 정보 유형
- 연구_프로토콜
- ANALYTIC_CODE
약물 및 장치 정보, 연구 문서
미국 FDA 규제 의약품 연구
미국 FDA 규제 기기 제품 연구
이 정보는 변경 없이 clinicaltrials.gov 웹사이트에서 직접 가져온 것입니다. 귀하의 연구 세부 정보를 변경, 제거 또는 업데이트하도록 요청하는 경우 register@clinicaltrials.gov. 문의하십시오. 변경 사항이 clinicaltrials.gov에 구현되는 즉시 저희 웹사이트에도 자동으로 업데이트됩니다. .