Comments for Julie (Week 5)
22 Wednesday Feb 2012
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in22 Wednesday Feb 2012
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in19 Sunday Feb 2012
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inIn short, yes it is ethically ok to use internet sources as data for qualitative data. Much of what is written on the internet is public, everyone has access to view things written on forums and in chat rooms. However, psychologists still need to stick to the ethical guidelines when conducting any research.
Researchers need to make sure that, if they are using internet sources to provide them with data, confidentiality is adhered to. This means that whether or not the participants are aware of their data being used in a study, they must not be identifiable, which mean that the researcher may be unable to directly quote what has been said. Also, the researcher must ensure that the research being conducted is beneficial to society and not harmful to the individual. Additionally, researchers must conduct their research with integrity ensuring that everything is reported honestly and correctly so not to misrepresent information.
One area of concern among many regarding using internet sources as qualitative data, is that it is not possible to gain informed consent from participants. However, there are some exceptions to this and one of them is that informed consent does not need to be obtained if observing natural behaviour, i.e. everyday behaviour such as social interaction in a coffee shop. There if it is acceptable for this form of public behaviour to be watched without consent then surely information that is published on the public internet should also be an exception to the rule?
While using internet sources as data may be ethically ok, I think that the issue surrounding this type of data is the reliability and validity because it may be impossible to actually verify participants identities.
10 Friday Feb 2012
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in05 Sunday Feb 2012
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inNow the simple answer to this question is no. Causality cannot be established just because there is a correlation.
When a researcher conducts a correlational study they are measuring variables that already naturally exist, such as height and IQ, to see whether there is a relationship between the variables. These types of studies cannot explain the relationship between variables, the research has no control of the variables and they are not manipulated in any way, like in a laboratory experiment.
So, the aim of the research is purely to see whether there is a relationship. This relationship can be either positive, as one variable increases the other tends to increase too i.e. as the height of individuals increase their IQ tends to increase too; or negative, as one variable increases the other tends to decrease i.e. as the shoe size of individuals increase their IQ tends to decrease.A correlation can lie anywhere between 0 and 1 (or minus 1 depending on the direction of the relationship); 0 meaning that there is no relationship between variables (see first graph below for an example of no correlation); 1 (or minus 1) meaning that there is a perfect relationship between variables, so as one variable increases the other will always increase too (or decrease depending on the direction of the relationship. See second picture below for an example of a perfect correlation). Generally a good correlation is shaped like an American football when plotted on a scatterplot, at 0.7 (see third picture below).
However, as briefly mentioned above laboratory experiments can establish causality, due to the high control the researchers have the ability to manipulate the independent variable and measure the dependent variable. This allows the researcher to compare scores and establish cause and effect, by manipulating a variable they can see the changes this may have in another variable. So a lab experiment only measures one variable where as a correlation measures two (as they naturally occur).
So, if correlations cannot establish cause-and-effect why are they so useful?
Correlations allow you to make predictions. For example, Berman, Jobes & Silverman (2006) found a relationship between specific behaviour and imminent suicide attempts. While this research is not able to say whether it is the specific behaviour that causes suicide attempts or whether the imminent suicide attempts causes the specific behaviour, it does allow clinicians, psychiatrist etc to spot the warning signs. If they know what types of behaviours are linked to imminent suicide attempts then they can potentially prevent it from occurring.
Furthermore, correlations are useful as a starting point in areas that have not been previously studied. The researcher can first of all establish whether there is a relationship between the two variables of interest and, if there is, lead onto an experimental study in order to see which variable causes the effect in the other. Also, sometimes it is unethical or not possible to manipulate some variables therefore correlations are handy as the researcher measures naturally occurring variables. An example would be if you wanted to study whether there was a relationship between criminal recidivism and IQ.
The main reason for why correlations cannot show cause-and-effect is because of the third-variable problem. Due to the lack of control it is unknown to the researcher whether a third variable is causing the negative or positive relationship between variables; therefore it may be an indirect relationship.
Berman, A.L., Jobes, D. A., & Silverman, M. M. (2006). Adolescent suicide: assessment and intervention. Washington, DC: American Psychological Association.