In this study, we examined the current practice and alternative methods for interpreting nonsignificant findings inpsychological research. The traditional null-hypothesis testing presents a challenge for researchers to interpret nonsignificantfindings. We reviewed the abstracts of all empirical articles published in three high-esteem psychological journals in 2015and selected those which referred to a nonsignificant result (N=134).We found that the majority of the statements interpretedthe results only within the sample, yet in 23% the authors inferred from the results to the absence of an effect. Bayes factoranalyses on these statistics indicated that the support of these results for the null-hypothesis is strong only in 4%, moderate in70% and anecdotal in 26%. The results revealed that Bayes factor analysis can help researchers in interpreting nonsignificantresults and also highlight that psychological studies with traditional sample sizes are unlikely to present strong evidence for thenull-hypothesis.