Evidence Literacy

Common misunderstandings

Short corrections to recurring mistakes in the way scientific findings, risk figures and vaccine-safety information are described.

Timing and cause

“It happened after vaccination, so vaccination caused it.”

More accurate: timing is relevant, but sequence alone does not establish causation. Investigators also consider expected background rates, comparison groups, alternative explanations, biological plausibility and the wider evidence.

Safety reports

“Every Yellow Card report is a confirmed side effect.”

More accurate: Yellow Card reports record suspected adverse reactions. They help detect possible signals, but an individual report does not by itself establish that a medicine or vaccine caused the event.

Safety signals

“A safety signal means a danger has been proven.”

More accurate: a signal is information that warrants investigation. Regulators assess the pattern and other available evidence before deciding whether a causal relationship is supported.

Report totals

“A larger report count automatically means a larger risk.”

More accurate: a count needs context, including how many people were exposed, reporting patterns, time periods, duplication, background rates and whether the events were causally assessed.

Single studies

“One published study settles the question.”

More accurate: an individual study should be judged on its design, relevance, precision and risk of bias, then considered alongside other studies and systematic reviews.

Authority

“A claim is true because an expert or institution said it.”

More accurate: expertise and institutional responsibility provide context, but conclusions should still be traceable to methods, data, evidence reviews and stated uncertainty.

Statistical results

“Statistically significant means important and certainly true.”

More accurate: statistical significance does not show the size, practical importance or freedom from bias of an effect. Read the effect estimate, absolute numbers, confidence interval and study limitations.

No significant result

“Not statistically significant proves there is no effect.”

More accurate: a non-significant result may reflect no effect, limited precision or insufficient data. The estimate and confidence interval show which effects remain compatible with the data.

Correlation

“If two trends move together, one must cause the other.”

More accurate: correlation can arise from causation, reverse causation, confounding, coincidence or analytical choices. Further evidence is needed to distinguish these explanations.

Evidence hierarchy

“Lower-ranked evidence is worthless.”

More accurate: different evidence types serve different purposes. Case reports and spontaneous reports can raise questions or signals; stronger comparative designs are usually needed to estimate risk or support causal conclusions.

Related sources and guides

MHRA — Yellow Card scheme

WHO — adverse-event causality assessment

ANTIVAX.co.uk — How to interpret evidence

ANTIVAX.co.uk — How to read Yellow Card reports

Educational scope

This page explains general evidence concepts. It does not assess personal symptoms, provide a diagnosis or replace advice from a suitably qualified healthcare professional.