For patients suffering from refractory diseases, particularly cancer, quality of life, as a major consequence of medical interventions, is of great importance. Unbiased measuring of quality of life changes is thus crucial to them. A prevalent bias related to research on quality of life is the “response shiftâ€. This review article aims to define “response shift†and the challenges to measure it. In addition, it addresses methodological approaches to measuring this bias in observational and clinical studies. “Response shift†indicates changes in person’s health condition as a result of changes in the meanings drawn from the self-assessment of his health condition. These changes are caused by changes in the patients’ criteria upon facing their new conditions and might reflect the measured changes either greater or smaller than they really are. The present article describes the individualized methods, the preference-based methods, the structural equation modeling and the then-test method used for evaluating “response shiftâ€, and discusses their application. Finally, by comparing these subjects, it concludes that the simplest and most efficient approach for evaluating “response shift†is the then-test approach. By emphasizing that these methods should be applied in clinical studies, the present article describes the most significant methods for evaluating “response shiftâ€. Since the effect of “response shift†has been neglected in the majority of studies conducted on quality of life, it is advised that, in longitudinal studies, quality of life changes be interpreted by monitoring the effect of “response shiftâ€.