A maintenance program called MBCT-D-TiF, designed for graduates of Mindfulness-Based Cognitive Therapy (MBCT) who want structured guidance to sustain their mindfulness practice, was feasible and acceptable in a pilot test. In round one, 14 participants received the program; in round two, 20 were randomized to the program or a waitlist. Attendance was high: all weekly sessions and at least 75% of monthly sessions. Most participants rated weekly sessions (77.1%) and monthly sessions (66.7%) as very or extremely helpful. Qualitative themes included the group's role in social connection, support, and accountability; mental health benefits such as reduced impact of depression and anxiety; and a need for additional support to maintain home practice after weekly sessions ended.
A 2-minute mindful attention exercise guided by a smartphone app, repeated several times daily for 8 weeks, helped people with chronic low back pain. Pain intensity dropped from 4.8 to 3.1 on a 0-10 scale, and a combined measure of pain intensity and interference (PEG score) improved from 13.7 to 8.4. Twenty-one of 29 participants had at least a 30% improvement in PEG score. Participants reported becoming aware of their usual avoidance of pain, were surprised that pain sensations varied over time, and found that focusing on pain reduced its threat. Many described pain in 3D shapes with changing colors, temperature, and density. The approach may be a beneficial alternative to ignoring or distracting from pain.
Multi-voxel pattern analysis of fMRI data can recognize five internal attentional states—breath attention, mind wandering, self-referential processing, attention to feet, and attention to sounds—in individual participants with accuracy well above chance (over 41% vs. 20% chance). In a mixed sample of 16 experienced meditators and novices, classifiers trained on a directed attention task successfully identified these states in 87.5% of participants. When applied to a separate 10-minute meditation session, the classifiers indicated that participants spent more time attending to breath than mind wandering or self-referential processing. The findings suggest that objective, participant-level measurement of mental states during meditation is feasible, potentially improving assessment of internally-oriented attention cultivated by meditation.
A research framework called Intersectional Neuroscience, which adapts research procedures to be more inclusive of underrepresented groups, was tested in partnership with a diverse U.S. meditation center. The approach used community engagement and individualized multivariate neuroscience methods. With person-centered screening, 15 diverse meditators (80% racial/ethnic minorities, 53% gender and sexual minorities) were recruited and scanned. Machine learning algorithms recognized each meditator's unique brain patterns during breath-focused meditation significantly above chance levels, allowing individual-level attention profiles to be compiled. The study demonstrates feasibility of including diverse participants and developing individualized neural metrics of meditation practice.