In psychological research with human subjects, experimenters need to anticipate potential artifacts that may be attributable to the social context of such research. Called research artifacts in this review, they are essentially uncontrolled, systematic errors (or biases) that threaten the degree of validity of statements made about whether changes in one variable result in changes in another variable. This discussion focuses on a proposed Markov-like model emphasizing three mediating variables that operate in a theoretical chain of events. One variable refers to the likelihood of the subject's receptivity to task-orienting cues (called demand characteristics), or incidental hints about the experimenter's expectations. A second variable refers to the likelihood of the subject's motivation (or willingness) to comply with those cues or hints. A third variable refers to the likelihood of the subject's capability of responding in accordance with the cues or hints. These three variables are discussed along with strategies that researchers can use to break the chain of events.