The folklore of the “Swift” effect – lessons for medical research and clinical practice

Taylor Swift’s presence at National Football League (NFL) games was reported to have a causal effect on the performance of Travis Kelce and the Kansas City Chiefs. Critical examination of the supposed “Swift effect” provides some surprising lessons relevant to the scientific community. Here, we present a formal analysis to determine whether the media narrative that Swift’s presence at NFL games had any impact on player or team performance – and draw parallels to scientific journalism and clinical research. We performed a quasi-experimental study, using covariate matching. Linear mixed effects models were used to determine how Swift’s presence or absence in Swift-era games influence Kelce’s performance, relative to historical data. Additionally, a binary logistic regression model was developed to determine if Swift’s presence influenced the Chief’s game outcomes, relative to historical averages. Across multiple matching approaches, analyses demonstrated that Kelce’s yardage did not significantly differ when Taylor Swift was in attendance (n = 13 games) relative to matched pre‐Swift games. Although a decline in Kelce’s performance was observed in games without Swift (n = 6 games), the statistical significance of this finding varied by the matching algorithm used, indicating inconsistency in the effect. Similarly, Swift’s attendance did not result in a significant increase in the Chiefs’ likelihood of winning. Together, these findings suggest that the purported “Swift effect” is not supported by robust evidence. The weak statistical evidence that spawned the concept of the “Swift effect” is rooted in a constellation of fallacies common to medical journalism and research – including over-simplification, sensationalism, attribution bias, unjustified mechanisms, inadequate sampling, emphasis on surrogate outcomes, and inattention to comparative effectiveness. Clinicians and researchers must be vigilant to avoid falling victim to the “Swift effect,” since failure to scrutinize available evidence can lead to acceptance of unjustified theories and negatively impact clinical decision-making.