Response bias

Response bias is a general term for a wide range of tendencies for participants to respond inaccurately or falsely to questions. These biases are prevalent in research involving participant self-report, such as structured interviews or surveys. Response biases can have a large impact on the validity of questionnaires or surveys. Response bias can be induced or caused by numerous factors, all relating to the idea that human subjects do not respond passively to stimuli, but rather actively integrate multiple sources of information to generate a response in a given situation. Because of this, almost any aspect of an experimental condition may potentially bias a respondent. Examples include the phrasing of questions in surveys, the demeanor of the researcher, the way the experiment is conducted, or the desires of the participant to be a good experimental subject and to provide socially desirable responses may affect the response in some way. All of these "artifacts" of survey and self-report research may have the potential to damage the validity of a measure or study. Compounding this issue is that surveys affected by response bias still often have high reliability, which can lure researchers into a false sense of security about the conclusions they draw. Because of response bias, it is possible that some study results are due to a systematic response bias rather than the hypothesized effect, which can have a profound effect on psychological and other types of research using questionnaires or surveys. It is therefore important for researchers to be aware of response bias and the effect it can have on their research so that they can attempt to prevent it from impacting their findings in a negative manner. Awareness of response bias has been present in psychology and sociology literature for some time because self-reporting features significantly in those fields of research. However, researchers were initially unwilling to admit the degree to which they impact, and potentially invalidate research utilizing these types of measures.