SCI2010 Lecture Notes - Lecture 10: Nuremberg, Stanford Prison Experiment, Cognitive Bias

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Week 10 Ethics of Human Experimentation
Lecture 1 Framework for Ethics of Human Experimentation
Factors in Ethical Biomedical Research
Nuremburg Code (1947)
Code to protect human subjects in experiments originated at Nazi trials
‘…voluntary consent of the human subject is absolutely essential’.
Nuremburg code: 10 key points
1. Voluntary
2. Fruitful results
3. Design based on prior knowledge
4. No unnecessary suffering
5. Not allowed if death/disability is likely
6. Humanitarian importance (risk/benefit)
7. Adequate facilities to protect subject
8. Scientifically qualified persons
9. Subject can opt out
10. Must be stopped if likely to result in injury, or death to experimental subject
Helsinki Declaration updated regularly
o Basis of all experimentation involving humans
o Consent must be informed
o Purpose
Distinguishes between therapeutic and non-therapeutic research
Hwang Woo-Suk unethical
o Used 2,000 fresh eggs from 129 women donors fellow workers and
students
o Did not follow Helsinki Declaration
Informed Consent in Trials
Informed consent includes telling the patient the following about the study:
o Purpose
o All procedures
o Funding arrangements
o Possible benefits
o Possible risks
Informed consent
E.g. FaceBook’s emotion experiment
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Document Summary

Lecture 1 framework for ethics of human experimentation. Nuremburg code (1947: code to protect human subjects in experiments originated at nazi trials. Voluntary consent of the human subject is absolutely essential". Informed consent includes telling the patient the following about the study: purpose, all procedures, funding arrangements, possible benefits, possible risks. 1996: meningitis epidemic in kano, nigeria: tested for new antibiotic, 200 children took part, 11 died, half got rocephin, half trovan, trial stopped after 2 weeks. Important distinction between humanitarian mission and clinical trial. Lecture 2 bias in science reporting: reasons and consequences. Publication bias: tendency of certain types of trials (such as those with the largest effect sizes) to be published more often. Increases the risk that the observed effect might not reflect the true effect: may negatively impact consistency, precision, magnitude of effect, reliance on meta-analyses to compile results from many experiments can exacerbate this bias.

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