Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| Name | Class |
|---|---|
| Dartmouth-Hitchcock Medical Center | OTHER |
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
The probably most commonly used measure for expressing the pay-offs of early detection and treatment are survival rates. Yet, over time and groups this metric comes with several biases and thus, is not reliable for judging such benefits. Epidemiologists recommend using reduction of disease-specific mortality rates instead, which is unbiased. The purpose of the study is to investigate how primary care physicians understand and use different survival measures for determining the benefit of cancer screening tests.
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| Label | Type | Description | Intervention Names |
|---|---|---|---|
| mortality*incidence*5-year survival*early stage | Physicians will be faced in scenarios about screening with information on mortality and 5-year survival, followed by information on mortality*incidence and 5-year survival*early stage in a random order. |
Not provided
| Measure | Description | Time Frame |
|---|---|---|
| Number of Physicians (=Participants) Recommending the Screening | The aim of the study was to learn how different medical cancer screening statistics would influence doctors' recommendation behavior and their effectiveness judgments of screening tests. For that reason the online survey study presented physicians with four different medical statistics (e.g., 5-year survival) within four successive scenarios and asked after each scenario whether they would recommend the screening to a (hypothetical) patient given the data. Options to answer are: Definitely yes, Probably yes, Probably no, Definitely no, Can't decide. | 25 minutes (mean duration of the survey) |
| Measure | Description | Time Frame |
|---|---|---|
| Number of Physicians (= Participants) Assuming a Benefit of Screening | Physicians are faced with four different medical statistics about the effect of screening (e.g., 5-year survival) within four successive scenarios and after each scenario asked whether they assume the screening to be beneficial given the statistical information. Options to answer are: yes, no, can't decide. If yes, then participants are further asked to describe this benefit by the following categories: Very large, large, moderate, small, very small. |
Not provided
Inclusion Criteria:
Exclusion Criteria:
Not provided
Not provided
301 primary care physicians (internal, general, and family medicine physicians)
Not provided
| Name | Affiliation | Role |
|---|---|---|
| Odette Wegwarth, Dr. | Max Planck Institute for Human Development | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Max Planck Institute for Human Development | Berlin | 14195 | Germany |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 22393129 | Derived | Wegwarth O, Schwartz LM, Woloshin S, Gaissmaier W, Gigerenzer G. Do physicians understand cancer screening statistics? A national survey of primary care physicians in the United States. Ann Intern Med. 2012 Mar 6;156(5):340-9. doi: 10.7326/0003-4819-156-5-201203060-00005. |
| Label | URL |
|---|---|
| Principal investigator's webpage | View source |
Not provided
Inclusion criteria: Physicians in internal, family and general medicine. Exclusion criteria: All physicians other than internal, family and general medicine physicians are excluded from participation because these usually are not offering cancer screening to there patients in the setting of primary care
Sample frame is the Harris Interactive Physician Panel Harris Interactive AG will draw a simple random sample U.S. internal and family medicine physicians from their Physician Panel and e-mail them an invitation and a link to the online-survey
Not provided
| ID | Title | Description |
|---|---|---|
| FG000 | Mortality*Incidence*5-year Survival*Early Detection Rate | The study-conducted as an online survey study-investigated the influence that different medical statistics such as 5-year survival rates would have on physicians' recommendation behavior for screening and on their judgment of screening's effectiveness. The survey introduced hypothetical scenarios in which a hypothetical patient was requesting a physician's advice on whether to have a screening test. To make that decision the participants (=physicians) were presented with different statistics and then asked if they would recommend the screening to the hypothetical patient and how effective they think the screening would be in reducing cancer mortality. The online survey did not ask any sensitive data. |
| Title | Milestones | Reasons Not Completed | ||||||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Overall Study |
|
|
Not provided
Not provided
| ID | Title | Description |
|---|---|---|
| BG000 | Mortality*Incidence*5-year Survival*Early Detection Rate | The study-conducted as an online survey study-investigated the influence that different medical statistics such as 5-year survival rates would have on physicians' recommendation behavior for screening and on their judgment of screening's effectiveness. The survey introduced hypothetical scenarios in which a hypothetical patient was requesting a physician's advice on whether to have a screening test. To make that decision the participants (=physicians) were presented with different statistics and then asked if they would recommend the screening to the hypothetical patient and how effective they think the screening would be in reducing cancer mortality. The online survey did not ask any sensitive data. |
| Units | Counts |
|---|---|
| Participants |
|
| Title | Description | Population Description | Parameter Type | Dispersion Type | Unit of Measure | Calculate Percentage | Denominator Units Selected | Denominators | Classes |
|---|---|---|---|---|---|---|---|---|---|
| Age, Categorical | Count of Participants |
| Type | Title | Description | Population Description | Reporting Status | Anticipated Posting Date | Parameter Type | Dispersion Type | Unit of Measure | Calculate Percentage | Time Frame | Units Analyzed | Denominator Units Selected | Arm/Group Information | Denominators | Classes | Analyses | ||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Primary | Number of Physicians (=Participants) Recommending the Screening | The aim of the study was to learn how different medical cancer screening statistics would influence doctors' recommendation behavior and their effectiveness judgments of screening tests. For that reason the online survey study presented physicians with four different medical statistics (e.g., 5-year survival) within four successive scenarios and asked after each scenario whether they would recommend the screening to a (hypothetical) patient given the data. Options to answer are: Definitely yes, Probably yes, Probably no, Definitely no, Can't decide. | We calculated that a sample size of 300 physicians was needed to have 90% power to detect differences of 20% or higher in the proportion of respondents correctly answering questions about the different cancer statistics (2-sided alpha of .05). | Posted | Aug 2011 | Number | participants | 25 minutes (mean duration of the survey) |
|
Not provided
Serious and/or other non-serious adverse events were not collected/not assessed because it was assume that the online survey study, which introduced hypothetical patient cases to doctors, would not results in any adverse events or put the participating doctors at risk.
Not provided
| ID | Title | Description | Deaths (Affected) | Deaths (At Risk) | Serious Events (Affected) | Serious Events (At Risk) | Other Events (Affected) | Other Events (At Risk) |
|---|---|---|---|---|---|---|---|---|
| EG000 | Mortality*Incidence*5-year Survival*Early Detection Rate | The study-conducted as an online survey study-investigated the influence that different medical statistics such as 5-year survival rates would have on physicians' recommendation behavior for screening and on their judgment of screening's effectiveness. The survey introduced hypothetical scenarios in which a hypothetical patient was requesting a physician's advice on whether to have a screening test. To make that decision the participants (=physicians) were presented with different statistics and then asked if they would recommend the screening to the hypothetical patient and how effective they think the screening would be in reducing cancer mortality. The online survey did not ask any sensitive data. |
Not provided
Not provided
Mistaken exclusion of "exclusively outpatient" physicians due to a programming mistake of the online survey screener
| Title | Organization | Phone | Extension | |
|---|---|---|---|---|
| Dr. Odette Wegwarth | Max Planck Institute for Human Development, Harding Center for Risk Literacy | +49-30-82406 | 695 | wegwarth@mpib-berlin.mpg.de |
Not provided
Not provided
Not provided
Not provided
| 25 minutes (mean duration of the survey) |
| Hit the survey after closure |
|
| Participants |
|
| Age Continuous | Mean | Standard Deviation | years |
|
| Sex: Female, Male | Count of Participants | Participants |
|
| Region of Enrollment | Number | participants |
|
The survey introduced four different cancer statistics in scenarios about 2 different screening tests. To mask the fact that all statistics stemmed from prostate cancer screening, screening in the scenarios were labeled "X" and "Z". The survey then introduced test Z, whose effectiveness was described in terms of a reduction of cancer mortality. After responding to the series of outcome questions about test Z, physicians received additional information on the cancer incidence, again followed by the outcome questions. In the next scenario, the survey introduced test X, whose effectiveness was described in terms of an increase in 5-year survival and, in the next step, with additional information on early detection rates. After each step, doctors had to respond to the same outcome questions as they had for test Z. Please not, information on test X and test Z were randomly presented to control for order effects. |
|
|
|
| Secondary | Number of Physicians (= Participants) Assuming a Benefit of Screening | Physicians are faced with four different medical statistics about the effect of screening (e.g., 5-year survival) within four successive scenarios and after each scenario asked whether they assume the screening to be beneficial given the statistical information. Options to answer are: yes, no, can't decide. If yes, then participants are further asked to describe this benefit by the following categories: Very large, large, moderate, small, very small. | Not Posted | Aug 2011 | Number | participants | 25 minutes (mean duration of the survey) |
| 0 |
| 0 |
| 0 |
| 0 |
Not provided
Not provided
Not provided