observationsbias

Observationsbias is a form of bias in data collection and interpretation in which the observer's expectations, beliefs, or prior knowledge influence what is recorded or how it is judged. The term is often used interchangeably with observer bias or observational bias, and it can affect both qualitative judgments and quantitative measurements. The bias arises when cognitive processes shape how observations are described, classified, or reported, rather than reflecting objective reality.

Causes include expectations about group differences, a desire to support a hypothesis, cues from the experimental setting, or inconsistent application of scoring criteria. It can manifest during data collection, coding of qualitative data, rating scales, or interpretation of ambiguous observations. The presence of knowledge about treatment conditions or study aims can amplify selective attention to confirmatory patterns.

Examples include clinicians rating patient outcomes more positively after knowing a patient received an active therapy, or researchers coding behaviors in a way that fits a preconceived category. In field studies, observers may notice and record familiar phenomena more readily, leading to inflated estimates of occurrence.

Mitigation relies on design and procedures that reduce subjectivity. Blinding assessors to study hypotheses or treatment allocation, using standardized and objective measurement protocols, and preregistering analysis plans help. Employing multiple independent raters with assessment of inter-rater reliability, automating measurements where feasible, and preregistered reporting further limit bias. Transparent documentation of coding schemes and rationale enhances reproducibility.

Impact: observationsbias can threaten validity and reliability, particularly in exploratory research or small samples. See also observer bias, measurement bias, observer-expectancy effect, Hawthorne effect.