To investigate this, we conducted a p-curve analysis (Simonsohn, Nelson, & Simmons, 2014) on the results reported by Travica et al.(2019) using the p-checker Shiny app (Schönbrodt, 2018). A p-curve analysis examines the frequency distribution of statistically significant (p≤. 05) p values. A strong positive skew (ie, a far larger proportion of p values<. 025 than>. 025) on the p-curve suggests that there is evidential value in the included results. Conversely, for a uniform distribution (ie, flatter than expected if the studies were powered at 33%) indicates that the results have no evidential value. Lastly, if the distribution is negatively skewed (ie, a larger proportion of p values>. 025 than<. 025), this is indicative of no evidential value and intense p-hacking (where analyses are conducted repeatedly until a statistically significant result is observed; Simonsohn et al., 2014). P-curve uses Z-tests to test for each of these. The p-curve analysis reported that the included studies do not contain evidential value (Z= 0.782, p=. 783), and that the distribution of p values was flatter than would be expected if studies were powered at 33%, indicating no evidential value (Z=-3.052, p=. 001). There was no evidence of negative skewness, suggesting no evidence of p-hacking (Z=-0.782, p=. 217). To reproduce and observe a visual representation of these results, see https://osf. io/b4z98/. Although these results reveal no evidential value in published research examining associations between blueberry consumption and cognitive performance and mood, it is important to note that the research does not suggest that there is no association (nor does it imply anything regarding the quality of the systematic review). However, if a true effect exists, the