Article Analysis – Probability and Decision-making

Article One: Summary, Main Points, and Thoughts and Perspectives

In the article “Current Best Practice for Presenting Probabilities in Patient Decision Aids: Fundamental Principles,” Bonner et al. (2021) review the currently available evidence on the application of numerical probabilities in patient decision aids. The authors view the use of evidence in shared decision-making as a way to improve the patient’s understanding of the situation and improve their decision-making. Through a collaborative approach with various experts in risk communication from different countries, they identified 5 critical issues out of 10 topics. The identified best practices for presenting probabilities to aid patient decision-making include having clear guidance, such as addressing the patient’s numerical skills, contextualizing the probabilities, and presenting to the patients the uncertainty and risk of particular decisions over time. The authors recommend following a consistent pattern to support comparisons of unbiased decision options. It is also important to clearly interpret and explain numbers to the patients. The article has clearly explained the evidence behind the use of probabilities as aids to patient decision-making processes and the best practices to improve numeracy in patient decisions.

Article Two: Summary, Main Points, and Thoughts and Perspectives

In the article, “(Peterson et al., 2021) explore and present their argument clearly on how understanding how people, whether individuals or as a group, make decisions can be improved through the use of large datasets to power machine-learning algorithms. The ability to understand and make human decisions whether in the social, science, or engineering fields, remains the utmost goal of either field. There are multiple decision models that focus on helping understand these human decision patterns. However, such theories and models are limited when it comes to accounting for patterns in decision-making. From the authors’ perspectives, as machine learning uses huge amounts of data, machine learning can be leveraged to develop interpretable and more predictive psychological decision-making theories. The use of large-scale experiments and machine learning can help not only develop more quantitative decision-making models but also help improve existing decision-making theories. From a personal perspective, machine learning using human behavioral data can predict how people make decisions as it is easier to process huge amounts of data and identify patterns present in made decisions.

References

Bonner, C., Trevena, L. J., Gaissmaier, W., Han, P. K. J., Okan, Y., Ozanne, E., Peters, E., Timmermans, D., & Zikmund-Fisher, B. J. (2021). Current Best Practice for Presenting Probabilities in Patient Decision Aids: Fundamental Principles. Medical Decision Making : An International Journal of the Society for Medical Decision Making, 41(7), 821–833. https://doi.org/10.1177/0272989X21996328

Peterson, J. C., Bourgin, D. D., Agrawal, M., Reichman, D., & Griffiths, T. L. (2021). Using large-scale experiments and machine learning to discover theories of human decision-making. Science, 372(6547), 1209–1214. https://doi.org/10.1126/SCIENCE.ABE2629/SUPPL_FILE/ABE2629-PETERSON-SM.PDF

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Question

Probability and Decision-making

Instructions
Article Analysis
Using the South University Online Library find two peer-reviewed journal articles interpreting probability, or decision-making. In your synopsis, you will include:

A summary of each of the journal articles
The main points discussed in each of the journal articles and how they relate to the week’s course and text readings
Your thoughts and perspectives regarding the concepts covered in each of the journal articles