Interpretation of evidence in data by untrained medical students: a scenario-based study
<p>Abstract</p> <p>Background</p> <p>To determine which approach to assessment of evidence in data - statistical tests or likelihood ratios - comes closest to the interpretation of evidence by untrained medical students.</p> <p>Methods</p> <p>Emp...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2010-08-01
|
| Series: | BMC Medical Research Methodology |
| Online Access: | http://www.biomedcentral.com/1471-2288/10/78 |
| _version_ | 1831678435887415296 |
|---|---|
| author | Perneger Thomas V Courvoisier Delphine S |
| author_facet | Perneger Thomas V Courvoisier Delphine S |
| author_sort | Perneger Thomas V |
| collection | DOAJ |
| description | <p>Abstract</p> <p>Background</p> <p>To determine which approach to assessment of evidence in data - statistical tests or likelihood ratios - comes closest to the interpretation of evidence by untrained medical students.</p> <p>Methods</p> <p>Empirical study of medical students (N = 842), untrained in statistical inference or in the interpretation of diagnostic tests. They were asked to interpret a hypothetical diagnostic test, presented in four versions that differed in the distributions of test scores in diseased and non-diseased populations. Each student received only one version. The intuitive application of the statistical test approach would lead to rejecting the null hypothesis of no disease in version A, and to accepting the null in version B. Application of the likelihood ratio approach led to opposite conclusions - against the disease in A, and in favour of disease in B. Version C tested the importance of the p-value (A: 0.04 versus C: 0.08) and version D the importance of the likelihood ratio (C: 1/4 versus D: 1/8).</p> <p>Results</p> <p>In version A, 7.5% concluded that the result was in favour of disease (compatible with p value), 43.6% ruled against the disease (compatible with likelihood ratio), and 48.9% were undecided. In version B, 69.0% were in favour of disease (compatible with likelihood ratio), 4.5% against (compatible with p value), and 26.5% undecided. Increasing the p value from 0.04 to 0.08 did not change the results. The change in the likelihood ratio from 1/4 to 1/8 increased the proportion of non-committed responses.</p> <p>Conclusions</p> <p>Most untrained medical students appear to interpret evidence from data in a manner that is compatible with the use of likelihood ratios.</p> |
| first_indexed | 2024-12-20T04:59:40Z |
| format | Article |
| id | doaj.art-f82c99d6ab9141ab98f0e256a3ce1ca3 |
| institution | Directory Open Access Journal |
| issn | 1471-2288 |
| language | English |
| last_indexed | 2024-12-20T04:59:40Z |
| publishDate | 2010-08-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Medical Research Methodology |
| spelling | doaj.art-f82c99d6ab9141ab98f0e256a3ce1ca32022-12-21T19:52:36ZengBMCBMC Medical Research Methodology1471-22882010-08-011017810.1186/1471-2288-10-78Interpretation of evidence in data by untrained medical students: a scenario-based studyPerneger Thomas VCourvoisier Delphine S<p>Abstract</p> <p>Background</p> <p>To determine which approach to assessment of evidence in data - statistical tests or likelihood ratios - comes closest to the interpretation of evidence by untrained medical students.</p> <p>Methods</p> <p>Empirical study of medical students (N = 842), untrained in statistical inference or in the interpretation of diagnostic tests. They were asked to interpret a hypothetical diagnostic test, presented in four versions that differed in the distributions of test scores in diseased and non-diseased populations. Each student received only one version. The intuitive application of the statistical test approach would lead to rejecting the null hypothesis of no disease in version A, and to accepting the null in version B. Application of the likelihood ratio approach led to opposite conclusions - against the disease in A, and in favour of disease in B. Version C tested the importance of the p-value (A: 0.04 versus C: 0.08) and version D the importance of the likelihood ratio (C: 1/4 versus D: 1/8).</p> <p>Results</p> <p>In version A, 7.5% concluded that the result was in favour of disease (compatible with p value), 43.6% ruled against the disease (compatible with likelihood ratio), and 48.9% were undecided. In version B, 69.0% were in favour of disease (compatible with likelihood ratio), 4.5% against (compatible with p value), and 26.5% undecided. Increasing the p value from 0.04 to 0.08 did not change the results. The change in the likelihood ratio from 1/4 to 1/8 increased the proportion of non-committed responses.</p> <p>Conclusions</p> <p>Most untrained medical students appear to interpret evidence from data in a manner that is compatible with the use of likelihood ratios.</p>http://www.biomedcentral.com/1471-2288/10/78 |
| spellingShingle | Perneger Thomas V Courvoisier Delphine S Interpretation of evidence in data by untrained medical students: a scenario-based study BMC Medical Research Methodology |
| title | Interpretation of evidence in data by untrained medical students: a scenario-based study |
| title_full | Interpretation of evidence in data by untrained medical students: a scenario-based study |
| title_fullStr | Interpretation of evidence in data by untrained medical students: a scenario-based study |
| title_full_unstemmed | Interpretation of evidence in data by untrained medical students: a scenario-based study |
| title_short | Interpretation of evidence in data by untrained medical students: a scenario-based study |
| title_sort | interpretation of evidence in data by untrained medical students a scenario based study |
| url | http://www.biomedcentral.com/1471-2288/10/78 |
| work_keys_str_mv | AT pernegerthomasv interpretationofevidenceindatabyuntrainedmedicalstudentsascenariobasedstudy AT courvoisierdelphines interpretationofevidenceindatabyuntrainedmedicalstudentsascenariobasedstudy |