Distortion refers to any systematic alteration, misrepresentation, or deviation from accurate or truthful representation of data, structure, signal, or interpretation in a scientific context.

• Data distortion: Manipulation or misrepresentation of datasets (e.g. selective reporting, cherry-picking).
• Interpretative distortion: Drawing conclusions not supported by the data; overgeneralization.
• Methodological distortion: Applying a method inappropriately, leading to skewed or invalid results.
• Imaging distortion: Artifacts or spatial inaccuracies introduced by equipment or reconstruction algorithms (e.g. in MRI or CT).
• Statistical distortion: Misuse of statistical methods that bias outcomes (e.g. improper p-value interpretation).

• Misleading readers, clinicians, or policymakers.
• Undermining reproducibility and scientific integrity.
• Eroding public and academic trust in research.