Mindfulness in health care professionals (HCPs) is often discussed as a tool for improving patient care outcomes, yet there has not been a critical evaluation of the evidence, despite a growing body of research on mindfulness-based interventions (MBIs). Numerous mechanisms exist by which mindfulness in HCPs may have an effect on patient care, and the field lacks an integrated model to guide future investigations into how MBIs may exert effects. The primary goals of this integrative review are to evaluate the evidence for the impact of MBIs in HCPs on patient care outcomes and to propose a causal model to guide future research. Databases were systematically searched for eligible studies investigating either an MBI or a measure of dispositional mindfulness in HCPs on patient care outcomes. Studies were critically evaluated using a previously developed tool. Twenty-six studies were identified (N = 1,277), which provide strong support for effects of mindfulness on HCP-reported patient care. Moderate support was found for patient safety, patient treatment outcomes, and patient-centered care. There was overall weak evidence to support a relationship between HCP-mindfulness on patient satisfaction. Mindfulness in HCPs may be related to several aspects of patient care.

Despite its widespread use, resting-state functional magnetic resonance imaging (rsfMRI) has been criticized for low test-retest reliability. To improve reliability, researchers have recommended using extended scanning durations, increased sample size, and advanced brain connectivity techniques. However, longer scanning runs and larger sample sizes may come with practical challenges and burdens, especially in rare populations. Here we tested if an advanced brain connectivity technique, dynamic causal modeling (DCM), can improve reliability of fMRI effective connectivity (EC) metrics to acceptable levels without extremely long run durations or extremely large samples. Specifically, we employed DCM for EC analysis on rsfMRI data from the Human Connectome Project. To avoid bias, we assessed four distinct DCMs and gradually increased sample sizes in a randomized manner across ten permutations. We employed pseudo true positive and pseudo false positive rates to assess the efficacy of shorter run durations (3.6, 7.2, 10.8, 14.4 minutes) in replicating the outcomes of the longest scanning duration (28.8 min) when the sample size was fixed at the largest (n=160 subjects). Similarly, we assessed the efficacy of smaller sample sizes (n=10, 20, …, 150 subjects) in replicating the outcomes of the largest sample (n=160 subjects) when the scanning duration was fixed at the longest (28.8 min). Our results revealed that the pseudo false positive rate was below 0.05 for all the analyses. After the scanning duration reached 10.8 minutes, which yielded a pseudo true positive rate of 92%, further extensions in run time showed no improvements in pseudo true positive rate. Expanding the sample size led to enhanced pseudo true positive rate outcomes, with a plateau at n=70 subjects for the targeted top one-half of the largest ECs in the reference sample, regardless of whether the longest run duration (28.8 minutes) or the viable run duration (10.8 minutes) was employed. Encouragingly, smaller sample sizes exhibited pseudo true positive rates of approximately 80% for n=20, and 90% for n=40 subjects. These data suggest that advanced DCM analysis may be a viable option to attain reliable metrics of EC when larger sample sizes or run times are not feasible.

Burnout and work-related stress in health-care professionals (HCPs) is a growing concern to the optimal functioning of the health-care system. Mindfulness-based interventions may be well-suited to address burnout in HCPs. The purpose of this study was (1) to quantitatively evaluate the effect of a mindfulness-based intervention for interdisciplinary HCPs over time and at a long-term follow-up and (2) to explore perceived benefits, facilitators, and barriers to the practice of mindfulness at the long-term follow-up. A mixed-method, repeated measures, within-subjects design was used to investigate Mindfulness for Interdisciplinary HCPs (MIHP) at baseline, post-MIHP, and a follow-up (6 months to 1.5 years after MIHP). MIHP is an 8-week, group-based course for interdisciplinary HCPs and students, with weekly meditation training, gentle yoga, and discussions on the application of mindfulness to common stressors faced by HCPs. Main outcome measures were the Maslach Burnout Inventory—Health Services Survey and the Five Facet Mindfulness Questionnaire. A semistructured interview was used to explore participants’ perceptions of sustained effects and practice in the context of HCP work at the long-term follow-up. The study protocol was registered with ClinicalTrials.gov (NCT02736292). Eighteen HCPs (88% female) participated in the study. Significant reductions were found after the intervention for 2 subscales of burnout: depersonalization, F(2, 17) = 5.98, P = .01, and emotional exhaustion, F(2, 17) = 2.64, P = .10. Three facets of dispositional mindfulness showed significant increases at long-term follow-up, act aware: F(2, 15) = 4.47, P = .03, nonjudge: F(2, 15) = 4.7, P = .03, and nonreactivity: F(2, 15) = 3.58, P = .05. Continued practice of skills long term was facilitated by the use of informal practice and perceived improvement in work and personal life. In sum, MIHP improved subscales of burnout and mindfulness. These findings should be further explored with a larger, controlled study. Interventions should focus on developing mindfulness practice that can be integrated into the work of HCPs.

The present study investigated demographic differences in performance validity test (PVT) failure in a Veteran sample.Data were extracted from clinical neuropsychological evaluations. Only veterans...