Differential reduction of psychological distress by three different types of meditation-based mental training programs: A randomized clinical trial

Objective: There is little knowledge about which types of meditation-based training are effective for alleviating which facets of psychological distress. We investigated shared and specific effects of three meditation-based training programs on distress. Method: 332 healthy adults were assigned to a retest control cohort or to one of three 3-month mental training cohorts including: the cultivation of mindfulness-based attention (Presence), socio-affective skills such as compassion (Affect), or metacognitive skills such as perspective taking (Perspective). A battery of 68 self-reported distress measures was collected. Data were analyzed using machine learning methods, identifying the cohort allocation based on distress change scores. Results: Supporting only specific and not shared alleviation effects, the classifiers identified significantly above chance Presence from Affect and Affect from Perspective, but they did not identify the training cohorts from the retest cohorts. Conclusions: The classifiers revealed stable module-associated distress change profiles, which could help to precisely choose meditation-based interventions to target individuals’ specific distress patterns. (AU)

Differential reduction of psychological distress by three different types of meditation-based mental training programs: A randomized clinical trial.

Objective: There is little knowledge about which types of meditation-based training are effective for alleviating which facets of psychological distress. We investigated shared and specific effects of three meditation-based training programs on distress. Method: 332 healthy adults were assigned to a retest control cohort or to one of three 3-month mental training cohorts including: the cultivation of mindfulness-based attention (Presence), socio-affective skills such as compassion (Affect), or metacognitive skills such as perspective taking (Perspective). A battery of 68 self-reported distress measures was collected. Data were analyzed using machine learning methods, identifying the cohort allocation based on distress change scores. Results: Supporting only specific and not shared alleviation effects, the classifiers identified significantly above chance Presence from Affect and Affect from Perspective, but they did not identify the training cohorts from the retest cohorts. Conclusions: The classifiers revealed stable module-associated distress change profiles, which could help to precisely choose meditation-based interventions to target individuals' specific distress patterns.

Empathy and correct mental state inferences both promote prosociality.

In a world with rapidly increasing population that competes for the earth's limited resources, cooperation is crucial. While research showed that empathizing with another individual in need enhances prosociality, it remains unclear whether correctly inferring the other's inner, mental states on a more cognitive level (i.e., mentalizing) elicits helping behavior as well. We applied a video-based laboratory task probing empathy and a performance measure of mentalizing in adult volunteers (N = 94) and assessed to which extent they were willing to help the narrators in the videos. We replicate findings that an empathy induction leads to more prosocial decisions. Crucially, we also found that correct mentalizing increases the willingness to help. This evidence helps clarify an inconsistent picture of the relation between mentalizing and prosociality.