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The Nuremberg Code

The Nuremberg Code (from Katz, J., (1972). Experimentation with human beings. New York: Russell Sage Foundation.) has been introduced in Nuremberg in 1947, after discovering a number of atrocities and other crimes that happened during the WWII. This code is thought to be one of the bases of the today’s ethical standards in psychological as well as the medical research.The idea of this code is very similar to the Helsinki Declaration (www.wma.net). The point for all the ethical guidelines we need to follow is to reduce the risk to participants. Development of ethical guidelines was essential especially after the horrible experiments carried out during the WWII. There are also more recent experiments which show the extremes of the researcher’s carelessness such as the Stamford Prison experiment carried out by Zimbardo.

This code contains 10 points and I’m going to describe them briefly here.

1.       Inform consent needs to be obtained from each participant. Therefore all participants should have legal capacity to give consent (must be 18 years of age or above) and seen capable of making decisions for themselves.

2.       Research should not be random and unnecessary and should be beneficial.

3.        An experiment should be designed on the basis of the results of previous animal studies, as well as the knowledge of the field, so that any problems can be anticipated  in advance.

4.       An experiment should be designed to so that the participants can avoid being physically or mentally injured.

5.       If there is a prior study risk of death or a disabling injury the testing cannot be conducted.

6.       The magnitude of risk shall never exceed the humanitarian importance of the problem the experiment seeks to solve.

7.       Adequate preparation for the experiment should be made in order to protect the participants from possibility of injury, death or disability.

8.       Highest care must be taken of the participants during experiments, and experimenters should always be scientifically qualified to test participants.

9.       The participants should be aware of the fact that they can withdraw from the experiment when they feel the continuation is impossible.

10.   The experimenter during any study must be prepared to end the study when they professionally judge that continuation could lead the participants to an injury or even death.

 

All these relate to the 5 principles of ethics: Beneficence and non-malificence, fidelity and integrity, justice, respect for other’s rights and dignity.

 

So in summary the Nuremberg Code is the basis of today’s ethical guidelines. It has been introduced after crimes that some researchers committed (thinking they could get away without taking any consequences). I truly believe that ethical guidelines are absolutely necessary; otherwise no one would participate in experiments these days knowing what happen in the past.

Thanks for spending your time reading my blog.

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Dear Kat,

Here are the links to the comments I’ve made this week.
http://hb90.wordpress.com/2011/10/28/is-it-dishonest-to-remove-outliers/#comments
https://kmusial.wordpress.com/2011/11/25/qualitative-research-isnt-as-scientific-as-quantitative-methods/#comments
https://kmusial.wordpress.com/2011/10/13/is-it-possible-to-prove-research-hypothesis/#comments
http://lon03.wordpress.com/2011/10/14/outliers…-how-to-detect-them-and-when-it’s-dishonest-to-remove-them/#comments
http://mballen91.wordpress.com/2011/10/14/ethical-guidlines-one-rule-too-many/#comment-38
http://lon03.wordpress.com/2011/12/09/ethics/#comment-16

This is a type of question that the answer depends on the person. It is therefore very difficult to say either yes, or no without getting any objections. The funds for research not just psychological must be provided- no doubt about it. How would scientists otherwise come up with new drugs? Of course a lot of people may say something like: “Okay, I agree for some percentage of my tax money to be spent on e.g. breast cancer research but not anything else”. I’m afraid nobody gets any choice over what their tax will be spent on. If someone wishes to support breast cancer research they can do so, by donating extra money. Some will say:”Yeah but studying breast cancer is an advanced research, but should taxpayers still fund the basic research?”My answer is yes. Before scientists become scientists, they need to be trained, and the best way to get experienced is to practice (with the basic research).
Everyone pays tax. People get taxes taken off their salaries, they pay council taxes, VAT when buying all sort of items in the shops and also taxes on cigarettes, alcohol or petrol etc. All the money is collected by the government and then spent on all sort of things such as health, education, transport, crime prevention, housing, army, etc. Research, even basic is one of those things.
The statement says, should the taxpayers support the basic research, but they do not have the choice really. At the end of the day this is to help the society. Even the basic (as well as the advanced) research might have some impact on e.g. the psychology field, and be very beneficial. If the research is funded aiming to help all the taxpayers then why would people protest? Yes, of course it is their money, but the funds must come from somewhere. Even if taxpayers were to protest and the research would no longer be funded from the tax, where would the money come from? Or would there be no research carried out? No cancer cure in future, no help in case of pestilence, no drugs to treat new illnesses.
Just before I get criticized for saying that all research should be funded I need to justify that the research carried on by private companies such as cigarettes or alcohol companies, should be funded by the owners of the companies, not the taxpayers. This is both because these products generate huge income, and since they are privately owned why would people agree for them to use the public money to fund their research?
I believe that people should not complain about their tax money being spent on research because the aim of research is to make people’s lives easier. To give the doctors a chance to help their patients etc. As long as the tax money is not spent on things like Halloween candy, but something as important as research people shouldn’t protest.
http://www.ird.govt.nz/taxagents/tax-technical-info/prov-tax/
http://finance.yahoo.com/taxes/article/102817/How-Your-Tax-Dollars-Are-Spent
http://psychology.about.com/od/aindex/g/appres.htm
http://www.textbookofbacteriology.net/resantimicrobial.html

Homework for my TA

Dear Kat,

here are the links to the comments due in Week 9

Awaiting moderation:

http://mballen91.wordpress.com/2011/10/14/ethical-guidlines-one-rule-too-many/

Awaiting moderation:

http://hb90.wordpress.com/2011/10/28/is-it-dishonest-to-remove-outliers/

Awaiting moderation:

http://em2904.wordpress.com/2011/10/28/dealing-with-outliers/

http://emilyjchurchill.wordpress.com/2011/10/14/is-it-dishonest-to-remove-outliers/

http://francesdevine.wordpress.com/2011/10/14/is-it-wrong-to-remove-outliers-from-data/#comments

https://kmusial.wordpress.com/2011/10/28/is-it-dishonest-to-remove-outliers-from-your-data/#comments

 

Before giving an opinion on this statement it is worth looking at both qualitative and quantitative research methods.

Qualitative Methods

Qualitative research methods can be described as an attempt to explain behavior in a holistic approach. It is concentrated on the ‘why’, not the ‘how’ of a topic, by analyzing the unstructured information. Qualitative studies are usually conducted on a small scale and used to explore a hypothesis. In qualitative research what matters most is that was said than how many times something happened.  Qualitative research seeks to understand the deeply hidden motivations of the target group. They allow obtaining the knowledge about the (emotional) sensitivity thresholds, barriers, attitudes, evaluations, desires and needs of the target group. These methods are therefore mainly used when there is a need for in-depth information. The so called projection techniques are often used in qualitative research that allows you to ask questions in an indirect way. This form of questions (“not direct”) encourages the participants to transfer (project) their hidden or unconscious motives, beliefs, attitudes and feelings associated with the test subject. The basic projection techniques are: associations with the brand association with pictures, a portrait of Chinese, completion is pictures, personification, collage.

The advantages and Disadvantages of Qualitative research:

Advantages: Uses subjective information, it is not limited to the rigidly definable variables, exploring new areas of research, and building new theories.

Disadvantages: ‘Classical’ researchers can have difficulties in understanding this kind of research, there is an unavoidable risk of building up a researcher bias, very difficult to replicate.

In psychology Qualitative methods concentrate on categorising and describing the data, are used to analyse text, conversation or speech (interviews very often recorded or taped). Data is most often collected in natural settings and in field experiments. Qualitative methods produce flexible and subjective data. Transferring the speech into writing is very time consuming and has to be done very accurately.

 

Quantitative methods

 

Quantitative studies allow measuring the extent of the phenomenon, in terms of quantitative variables. Hence, the question most often correspond to how many, who and where.

The main aim of the quantitative research methods is to determine the relationship between two things: a dependent or outcome variable, and an independent variable, in a population. Quantitative research designs can be either experimental (subjects measured before and after a treatment) or descriptive (subjects usually measured once). Experiment are used to establishes causality, whereas descriptive studies are used to establish only the associations the between variables. It often requires recruiting hundreds or even thousands of participants (which reduces the likelihood of biases).

 

Advantages: comprehensive answer can be reached after statistical analysis, results may be legally published and discussed, if the study was properly designed, then the results produced, can be viewed as unbiased and real.

Disadvantages: can be very expensive, and extremely time consuming, need to be carefully planned, very often extensive statistic analysis is necessary. Can be a give a very hard time to non mathematicians. Most of the time produces only yes or no response.

 

Researchers can also use mixed method designs, which are the combinations of both qualitative and quantitative research methods, at all stages of data collection and analysis. The main advantage of using this method is that it overcomes the downsides of both qualitative and quantitative on their own.

 

After looking at both research methods none of them is more or less scientific, because both have advantages and disadvantages. Just because qualitative methods don’t use numbers straight away, and that they do not involve testing 1000 participants it does not simply mean it is less scientific. Qualitative methods provide with more details about the problem, and details that any researcher would have never been able to gain using quantitative research.

Further reading:

–          http://www.qsrinternational.com/what-is-qualitative-research.aspx

–          http://www.sportsci.org/jour/0001/wghdesign.html

–          Brink, H. (1991). Quantitative vs. qualitative research. Nursing RSA, 6, 14-18.

–          http://siteresources.worldbank.org/INTUKRAINE/Resources/328335-1212401346836/1MixedMethods.pdf

–          http://www.nova.edu/ssss/QR/QR8-1/labuschagne.html

–          http://www.okstate.edu/ag/agedcm4h/academic/aged5980a/5980/qualrsch/QUALRSCH/sld010.htm

–          http://www.experiment-resources.com/quantitative-research-design.html

 

Homework for my TA

Dear Kat, Here are links to the blogs, I have left comments on (Weeks 4/5)

http://statsbloggy.wordpress.com/2011/10/14/is-it-dishonest-to-remove-outliers-andor-transform-data/

http://statsblog2011.wordpress.com/2011/10/14/just-because-its-significant-doesnt-mean-its-significant-discuss/

http://skakov87.wordpress.com/2011/10/14/is-it-possible-to-prove-research-hypothesis/

http://roisin07m.wordpress.com/2011/10/12/week-3-wildcard-blog-is-it-dishonest-to-remove-outliers-from-data/

http://psychrno.wordpress.com/2011/10/14/is-it-dishonest-to-remove-outliers/

http://dsm1lp.wordpress.com/2011/10/14/should-the-taxpayer-support-basic-research-or-should-the-research-funding-emphasis-be-placed-on-applied-research-in-which-the-beneficiaries-are-clear/

http://skakov87.wordpress.com/2011/10/14/is-it-possible-to-prove-research-hypothesis/

Before answering this question it is worth explaining what outliers are, and how do they occur.

Outliers are data points which differ extremely from the other data. Outliers are caused simply by chance, measuring or sampling error. As to removing outliers the decision is generally left to the researcher. This is because an outlier might be caused by the instrumentation e.g. low battery in a scale, when measuring weight. This will mean that such an outlier is caused by an error and is not a true score that can be easily re-measured to get exactly the same result. However an outlier might also be a real data point, caused by extremely intelligent (or relatively non intelligent) individual. Removing such an outlier would have been dishonest, because it means removing a real data point- manipulating the data. Normal distribution contains extreme scores at both ends of the slope. This means that the extreme scores are not an effect of poor concentration during the study, but they represent the real score for that particular individual (1).

 

 It is very difficult and time consuming to detect outliers, especially when you have a data containing e.g. 80 000 scores from 150 participants. Rousseeuw and Leroy (1996) described ways of detecting outliers (2). 

 

There are different ways of dealing with outliers, other than simply getting rid of them. This might sometimes cause problems, because they might be real scores. What we can do to deal with them is to use robust statistics such as median, instead of mean. Median is not as sensitive to outliers as mean, because it is the point in the middle and an outlier only pushes it slightly by 1 place. Whereas mean takes into account the value of all numbers, therefore a single outlier can strongly affect the data (3).Another way of dealing with outliers is using nonparametric tests (4). The reason for this is that they do not require assumption of the normality or homogeneity of variance, and again use median instead of mean.

 

When carrying out a research it is very important to get valid results. Therefore accurate data needs to back them up. It is the researcher’s responsibility to judge all the outliers and to decide whether to get rid of them or ‘work around them’. It is not dishonest to remove an outlier as long as a researcher has some evidence to suspect that such an outlier is not a real data point.

 

Further reading:


(1)          http://stattrek.com/help/glossary.aspx?target=normal_distribution


(2)          Rousseeuw, P., &  Leroy, A. (1996). Robust Regression and Outlier Detection. John Wiley &       Sons., 3rd edition.

(3)          http://www.ltcconline.net/greenl/courses/201/descstat/mean.htm

(4)          http://www.une.edu.au/WebStat/unit_materials/c6_common_statistical_tests/nonparametr ic_test.html

(5)         http://statistics.laerd.com/statistical-guides/pearson-correlation-coefficient-statistical-guide-              2.php

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