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Related Experiment Video

Updated: Jun 23, 2026

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods

Published on: September 19, 2012

Communicating benefit and risk.

Trevor Baglin¹

¹Department of Haematology, Cambridge University Hospitals NHS Trust, Addenbrooke's Hospital, Cambridge, UK. trevor.baglin@addenbrookes.nhs.uk

British Journal of Haematology

|May 15, 2009

Summary

This summary is machine-generated.

Clinicians need better training in understanding and communicating clinical trial results, including risks and benefits. Effective patient communication requires using absolute risk and clear probabilities, not just relative risk, to improve shared decision-making.

Related Experiment Videos

Last Updated: Jun 23, 2026

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods

Published on: September 19, 2012

Area of Science:

Medical Research Methodology
Clinical Communication
Biostatistics

Background:

Effective clinical trial reporting and patient engagement in treatment decisions are crucial.
Clinicians require a solid understanding of benefit-risk estimates and communication strategies.
Inadequate study design and reporting are linked to biased treatment effect estimates.

Purpose of the Study:

To highlight the importance of clinicians' knowledge of clinical trial data.
To emphasize the need for improved communication of treatment benefits and risks to patients.
To address the challenges in conveying statistical uncertainty in clinical decision-making.

Main Methods:

Review of current practices in clinical trial reporting and clinician training.
Analysis of the impact of study design and reporting on treatment effect estimates.
Examination of effective methods for communicating risk and benefit information to patients.

Main Results:

A gap exists in clinicians' basic understanding of study design and analysis.
Poor reporting and design practices correlate with biased estimates of treatment effects.
Communicating results effectively involves using absolute risk, common denominators, and considering treatment duration.

Conclusions:

Enhanced clinician training in biostatistics and research methodology is essential.
Clearer communication of absolute risks and uncertainties improves patient understanding and shared decision-making.
Addressing reporting and design flaws is key to reducing bias in treatment effect estimation.