Self-Report Characterization of Meditation Practice as a Predictor of Dispositional Mindfulness, Interpersonal Mindfulness, and Mental Health

Increasing dispositional mindfulness is the primary goal of all mindfulness-based interventions. However, it is not entirely clear which specific characteristics of meditation practice predict improvements in mindfulness. This is relevant for characterization of the participants as well as for intervention designs. In this study, we explored the predictive value of different self-report questions characterizing previous meditation experience over dispositional mindfulness, interpersonal mindfulness, and mental health.

Using a cross-sectional design with a sample size of 1099 and machine learning, 28 questions (independent variables) characterizing meditation practice were used to predict 21 dependent variables distributed in three categories: dispositional mindfulness (eight variables), interpersonal mindfulness (five variables), and mental health (eight variables). We conducted variable screening using a conditional random forest algorithm to identify the five most relevant independent variables for each group of dependent variables.

The findings indicate that out of the 28 independent variables characterizing meditation practice, only five were significant predictors of the three categories of dependent variables. These predictors include the time lapse since starting meditation, practice frequency, the role assigned to meditation in daily life, the relation with meditation, and the ability to count the number of breaths without getting distracted.

Five self-report questions in relation to meditation practice were reliable predictors of dispositional mindfulness, interpersonal mindfulness, and mental health. The results highlight the need for further exploration of how individuals’ relationships with their meditation practice influence meditation outcomes.