Effects of compassion meditation on a psychological model of charitable donation.

Abstract

Compassion is critical for societal wellbeing. Yet, it remains unclear how specific thoughts and feelings motivate compassionate behavior, and we lack a scientific understanding of how to effectively cultivate compassion. Here, we conducted 2 studies designed to a) develop a psychological model predicting compassionate behavior, and b) test this model as a mediator of a Compassion Meditation (CM) intervention and identify the "active ingredients" of CM. In Study 1, we developed a model predicting compassionate behavior, operationalized as real-money charitable donation, from a linear combination of self-reported tenderness, personal distress, perceived blamelessness, and perceived instrumental value of helping with high cross-validated accuracy, r = .67, p < .0001. Perceived similarity to suffering others did not predict charitable donation when controlling for other feelings and attributions. In Study 2, a randomized controlled trial, we tested the Study 1 model as a mediator of CM and investigated active ingredients. We compared a smartphone-based CM program to 2 conditions-placebo oxytocin and a Familiarity intervention-to control for expectancy effects, demand characteristics, and familiarity effects. Relative to control conditions, CM increased charitable donations, and changes in the Study 1 model of feelings and attributions mediated this effect (pab = .002). The Familiarity intervention led to decreases in primary outcomes, while placebo oxytocin had no significant effects on primary outcomes. Overall, this work contributes a quantitative model of compassionate behavior, and informs our understanding of the change processes and intervention components of CM. (PsycINFO Database Record

Empathic Care and Distress: Predictive Brain Markers and Dissociable Brain Systems

“…Separately, we found that self-reported care and distress both positively predicted increased donation, although care was a stronger predictor. This both confirms previous reports that increased distress predicts helping (i.e., Ashar, Andrews-Hanna, Yarkoni, et al, 2016) and lends credence to prior arguments that empathic care rather than distress is the primary motivator of altruism (Ashar, Andrews-Hanna, Dimidjian, et al, 2016; Batson, 2011; Singer & Klimecki, 2014). …”

“…It was also positively correlated with empathic care, though more weakly than in the original neuroimaging sample. These results suggest that the empathic distress marker is most closely related to a non-specific negative arousal in response to others’ suffering, in line with how we and others have conceptualized empathic distress (Ashar, Andrews-Hanna, Yarkoni, et al, 2016; Ashar, Andrews-Hanna, Dimidjian, et al, 2016; Batson, 2011; Singer & Klimecki, 2014). …”

“…This can enable a cumulative science that ultimately produces rigorously validated markers ready for translational use. In the domain of empathy, validated predictive markers may aid in the diagnosis or prognosis of empathy-related disorders (i.e., autism or psychopathy), serve as proximal biological targets for interventions seeking to enhance compassion (Ashar, Andrews-Hanna, Yarkoni, et al, 2016; Klimecki et al, 2012, 2014; Lutz et al, 2008; Weng et al, 2013), or as targets for biofeedback-based training programs aiming to enhance empathy (Moll et al, 2014; Yao et al, 2016). The markers presented here are a first step in a cumulative process of refinement and validation.…”

“…Conflicting evidence suggests that distress predicts both escape behavior (Batson, 2011; Batson et al, 1987) and helping behavior (Ashar, Andrews-Hanna, Yarkoni, et al, 2016) and that charitable donation is motivated by brain activity related to both positive affect (Genevsky & Knutson, 2015; Genevsky et al, 2013) and negative affect (Sawe & Knutson, 2015). …”

Focus on the breath: Brain decoding reveals internal states of attention during meditation

“…This may partly explain why clinical outcomes are heterogenous, and effect sizes of mindfulness-based interventions are moderate 17 . The framework can thus be adapted to measure other meditative attentional qualities (e.g., meta-awareness 33 and nonjudgment 24,25 ), as well as different types of meditation practice (e.g., open monitoring 3,7 and compassion 4,6 ), and be used to track person-specific skills and clinical outcomes. By developing measures to precisely assess the attentional qualities cultivated by meditation, we will gain the measurement power needed to rigorously test the mechanisms through which meditation may improve health and well-being.…”