Final answer:
Biases in epidemiological studies may arise from sampling bias, self-selection in internet surveys, and response biases such as the "Bradley effect." Selection bias can also stem from differences in technology access and the timing of survey execution.
Step-by-step explanation:
Bias in epidemiological studies usually results from systematic errors in the design, conduct, or analysis of research that leads to conclusions that are systematically different from the truth. Sampling bias is a common issue, where some members of a population are less likely to be chosen for a study than others, which can occur when not all members have an equal chance of being selected. This can lead to misleading conclusions about the population in question. For example, conducting a survey only during noon lunchtime hours ignores the input of students with different schedules.
To minimize bias, researchers should identify and manage potential biases within their work. Critical evaluation and acknowledging inherent biases are part of refining the research process. One must be cautious of large internet surveys, as they often contain self-selection bias because participation is voluntary and not random. Surveys can also suffer from response biases like the "Bradley effect", where individuals may not disclose their true preferences due to the desire to provide socially acceptable answers.
Differences in access to technology, such as having a telephone or being listed in a directory, contribute to selection bias. Moreover, the timing of contact attempts, such as phone calls, can further skew the representative nature of the sample, hence affecting the study's validity.