Individual Differences in Dispositional Mindfulness Predict Attentional Networks and Vigilance Performance

Abstract

Abstract Objectives Research addressing the relationship between dispositional mindfulness and objective attention performance remains inconclusive, partly because previous studies used sample sizes possibly leading to underpowered designs. Here, we examined this relationship in a large sample using the ANTI-Vea: a novel cognitive-behavioral task that simultaneously assesses the classic attentional networks—phasic alertness, orienting, executive control—and both the executive and arousal components of vigilance. Methods Two hundred nineteen meditation-naïve participants completed the study. Correlational analyses using Kendall’s Tau were performed between FFMQ scores and ANTI-Vea outcomes. Additional subsidiary correlations were performed between the FFMQ and two self-report measures assessing subjective attentional control and mind-wandering. Benjamini-Hochberg was applied to control de type I error rate. Internal consistency reliability indices were estimated for all measures used to aid the interpretation of the correlational results. Results Higher non-reactivity predicted overall faster reaction times and higher accuracy in attentional networks trials. Higher non-reactivity, as well as higher FFMQ total score, predicted faster reaction time and fewer lapses in arousal vigilance trials, the latter also being negatively associated with describe scores. The magnitude of the correlations ranged from τb = .103 to τb = .119. We found no association between FFMQ scores and executive control or executive vigilance. Conclusions Our results indicate that dispositional mindfulness is linked to improved global attentional and arousal vigilance performance, being non-reactivity to inner experience the key facet driving the association. The absence of association to executive processes is discussed based on the high cognitive demands of the ANTI-Vea task. Pretrial Registration Open Science Framework, https://osf.io/gb6c7