ArticleBehavior research methods2016
The effectiveness of argumentation in tutorial dialogues with an Intelligent Tutoring System for genetic risk of breast cancer.
Article in Behavior research methods, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed, 10 citations in OpenAlex.
- Understanding the landscape of web-based medical misinformation about vaccination.Behavior research methods · 2023Article
- Adapting a Theoretically-Based intervention for underserved clinical populations at increased risk for hereditary Cancer: Lessons learned from thePreventive medicine reports · 2022Article
- A Web-Based Tailored Intervention to Support Illness Management in Patients With an Acute Coronary Syndrome: Pilot Study.JMIR cardio · 2017Article
- Understanding Genetic Breast Cancer Risk: Processing Loci of theLearning and individual differences · 2016Article
- Individual differences in risk perception and misperception of COVID-19 in the context of political ideology.Applied cognitive psychologyArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
BRCA Gist is an Intelligent Tutoring System that helps women understand issues related to genetic testing and breast cancer risk. In two laboratory experiments and a field experiment with community and web-based samples, an avatar asked 120 participants to produce arguments for and against genetic testing for breast cancer risk. Two raters assessed the number of argumentation elements (claim, reason, backing, etc.) found in response to prompts soliciting arguments for and against genetic testing for breast cancer risk (IRR=.85). When asked to argue for genetic testing, 53.3 % failed to meet the minimum operational definition of making an argument, a claim supported by one or more reasons. When asked to argue against genetic testing, 59.3 % failed to do so. Of those who failed to generate arguments most simply listed disconnected reasons. However, participants who provided arguments against testing (40.7 %) performed significantly higher on a posttest of declarative knowledge. In each study we found positive correlations between the quality of arguments against genetic testing (i.e., number of argumentation elements) and genetic risk categorization scores. Although most interactions did not contain two or more argument elements, when more elements of arguments were included in the argument against genetic testing interaction, participants had greater learning outcomes. Apparently, many participants lack skills in making coherent arguments. These results suggest an association between argumentation ability (knowing how to make complex arguments) and subsequent learning. Better education in developing arguments may be necessary for people to learn from generating arguments within Intelligent Tutoring Systems and other settings.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.