![]() ![]() Unfortunately, when this happens, the data collected is inaccurate and therefore not very informative. The more participants know, the more likely it is that they will try to “help” the researcher by behaving in the way they think the researcher wants them to. While some information about the study must be divulged to the participants for ethical reasons, it is ideal for participants to know as little as possible about the nature of the research being done. Typically seen in psychological research, demand characteristics are subtle cues from the experimenter that may give the participants some idea of what the study is about. Demand characteristicsĭemand characteristics are a form of response bias that may give rise to the observer expectancy effect. The observer expectancy effect arises due to demand characteristics, which are subtle cues given by the researcher to the participant about the nature of the study, as well as confirmation bias, which is when the researcher collects and interprets data in a way that confirms their hypothesis and ignores information that contradicts it. ![]() In this way, you may affect the behaviors of both groups, ultimately compromising the accuracy and generalizability of your results. On the other hand, you’ll expect participants getting the real medication to be less stressed and treat them like they’re more relaxed or ask them leading questions that hint that they should be more relaxed. Since you expect the placebo group to be more stressed, you might treat them like they are more stressed, which may cue them to act more tense than they normally would. Even if the participants all think they’re receiving the actual medication, you might unconsciously treat the two groups differently. For example, if you’re running a study examining the effects of a certain new medication on participants’ stress levels, you’ll probably expect participants receiving the medication to be less stressed than those receiving a placebo pill. A key factor of research design is figuring out how to avoid accidentally influencing participants. If you have ever worked in a research lab, you’re probably quite familiar with this phenomenon. ![]()
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