In research, what does a confidence interval that crosses 1 indicate about a treatment's effect?

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A confidence interval that crosses 1 indicates that there is no statistically significant effect of the treatment being studied. When considering ratios, such as odds ratios, relative risks, or hazard ratios, a value of 1 implies no effect; thus, when the confidence interval includes 1, it suggests that the true effect of the treatment could be 1, meaning there is a possibility that the treatment does not have any difference compared to the control or placebo.

For example, if a confidence interval for a treatment's effect is reported as 0.8 to 1.2, since it crosses 1, this indicates that, statistically, the effect could range from a potential reduction in risk (0.8) to no effect (1.0), and even a potential increase in risk (1.2). Hence, because it overlaps with 1, one cannot conclude that the treatment has a definitive positive or negative impact, confirming that there is no statistically significant effect observed in the study. Understanding this concept is crucial in interpreting research results effectively in clinical practice.