Observer-Expectancy Effects in Research

Discusses the importance of avoiding observer-expectancy effects when evaluating facilitated communication.

Defined as the influence of the observer's expectations on the behavior of the subjects in an experiment.
Assessing the impact of observer knowledge on experiment outcomes is critical.

Hypothesis: Subjects receiving treatment A will smile more than those receiving treatment B.
If the researcher expects treatment A to produce more smiles, this may unconsciously affect their behavior towards participants in both groups.
- Example: The researcher might smile more at treatment A subjects, who in turn, may smile back more due to the positive feedback, leading to erroneous conclusions.
This would create an illusion that treatment A was responsible for the increased smiling, instead of the researcher’s own influence.

Observers' expectations can not only alter subjects' behaviors but also influence how observers interpret those behaviors.
Referring back to the smiling experiment, an observer's expectation might skew their interpretations. - E.g., ambiguous facial expressions might be interpreted as smiles in one condition and as neutral or negative in another, depending on the observer's biases.

Best practice to eliminate these effects is to keep observers blind to the experimental conditions that could lead to bias.
In typical between-groups experiments, the blind observer does not know which subjects received which treatments, eliminating the basis for biased expectations.
In the hypothetical smiling experiment, if the observer is unaware of the treatment assignment, bias is effectively reduced.

Reference to DiMascio's study on depression treatments:
- Clinicians who evaluated the patients’ depression post-treatment were blind to the treatment conditions to avoid observer-expectancy effects.
- Patients were instructed to avoid discussing their treatment during evaluation interviews, ensuring evaluators remained unbiased.

Always implement strategies that ensure both observers and subjects are unaware of conditions that could lead to expectancy biases.
This involves blinding in experimental designs to guarantee more reliable and valid results.