In cancer research, observer bias can manifest in several ways:
Data Collection: Researchers may unintentionally record data in a way that supports their hypotheses. For example, they might focus more on positive outcomes or ignore negative results. Diagnosis: When diagnosing cancer, physicians might interpret ambiguous test results in a way that aligns with their expectations, leading to overdiagnosis or underdiagnosis. Treatment Efficacy: Researchers may overestimate the effectiveness of a new treatment if they expect it to work, which can lead to the premature adoption of ineffective therapies.
