Claiming that psychological research can be defined as “biased”, is hardly much of a stress on the imagination. Experiments or studies we come across during our degree (or beyond), will always have some element to them that reduces its reliability, validity, generalisability, or ethical approval. In this blog I will outline a few examples of bias in research, some well-known and some not so much, what problems they cause and how they can be rectified.
The most common bias we usually come across is down to the experimenter. For example, when conducting an interview, the researcher could already have preconceived ideas or beliefs about the subject they are talking about. As such, their analysis could be biased as a different researcher may not code a response the same (Freud, 1909). A way to prevent this could be to use inter-rater reliability, whereby two or more individuals code behaviours and then see if their results match (Milgram, 1963). Another method that could be implemented is a double blind procedure, whereby neither the participant nor the researcher know what condition they are taking part in/testing, so the results can’t be altered to correspond with the hypotheses of the study (Lustman et al, 2000).
It has also been observed that over the years, that a heterosexual bias can occur within studies. Indeed, in the 1960’s, homosexuality was considered a mental illness. The reports written in those times considered homosexual people to be hereditarily insane (Moreau, 1887; Szasz, 1974). From studies I have participated in the past, I believe some researchers have managed to neglect the idea that their participants could be attracted to people other than the opposite sex, and how this could have an effect on what they were attempting to measure e.g. trustworthiness. However since then, a plethora of studies have helped change people’s preconceived ideas about this; mainly that it is not so “unnatural” as previously thought (Ford & Beach, 1951). I believe these possible confounding variables could be prevented if homosexual people are taken into consideration when designing a study, so that it does not automatically make the assumption their participants will be straight.
Bias can also be present in the samples taken for experiments. For example, participants that are all males (Milgram, 1963) could mean that the sample in not generalisable to a wider population, and so reduces the usefulness of the study (although, Milgram was attempting to show the inhumane acts done by Nazi Germans was nothing down to the fact they are more obedient than other cultures… and all the sergeants were men). This can obviously be rectified by having an even amount of males and females in each condition you are testing for, as well as using a matched pairs design so that one group is not so different from another on what you are trying to test (Bandura, 1961)
Also, Wilson and Brekke (1994) introduced the idea of mental contamination, that they defined as “the process whereby a person has an unwanted judgment, emotion, or behavior because of mental processing that is unconscious or uncontrollable”. An example of this is what we have been talking about in cognitive psychology; an attentional bottleneck whereby we will gather information from our environment that is important or useful to us. This could be rectified by clearly explaining the procedure to participants, so that they know a bit more about what is happening and so will not get bored and just give up trying.
In conclusion, bias can be present in many different forms and can cause many problems. However, if there are more hard set rules and consideration in studies, there is no reason why it can’t be rectified. What do you guys think? What’s the best way to combat these problems? Thanks for reading.