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. 2011 Nov;51(7):856-861.
doi: 10.1016/j.paid.2011.07.020.

Mindfulness predicts less texting while driving among young adults: Examining attention- and emotion-regulation motives as potential mediators

Greg Feldman  1 , Jeff Greeson, Megan Renna, Kendra Robbins-Monteith
Affiliations

Mindfulness predicts less texting while driving among young adults: Examining attention- and emotion-regulation motives as potential mediators

Greg Feldman et al. Pers Individ Dif. 2011 Nov.

Abstract

Many young adult drivers read and send text messages while driving despite clear safety risks. Understanding predictors of texting-while-driving may help to indentify relevant targets for interventions to reduce this dangerous behavior. The present study examined whether individual differences in mindfulness is associated with texting-while-driving in a sample of young-adult drivers. Using path analysis, we tested whether this relationship would be mediated by the degree to which individuals use text-messaging as a means of reducing unpleasant emotions (emotion-regulation motives) and the degree to which individuals limit texting in order to focus on present-moment experiences (attention-regulation motives). Individuals lower in mindfulness reported more frequent texting-while-driving and this relationship appeared to be mediated primarily by emotion-regulation motives. Results may help inform the development of mindfulness-based interventions to prevent texting-while-driving.

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Figures

Figure 1
Figure 1
Results of path analysis testing direct and indirect effects of mindfulness on texting-while-driving. Path coefficients are standardized regression (β) weights. Solid arrows represent statistically significant associations (p < .05). Dashed arrows represent non-significant (ns) relationships (p > .05). In the path from Mindfulness to Texting-While-Driving Frequency, the value in parentheses reflects the association of these two variables prior to adding the two mediators (attention- and emotion-regulation motives), controlling for the three remaining variables in the model. * p < .05, **p < .01, ***p <.001.
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