In response to questions regarding the scientific basis for mindfulness-based interventions (MBIs), we evaluated their empirical status by systematically reviewing meta-analyses of randomized controlled trials (RCTs). We searched six databases for effect sizes based on four or more trials that did not combine passive and active controls. Heterogeneity, moderators, tests of publication bias, risk of bias, and adverse effects were also extracted. Representative effect sizes based on the largest number of studies were identified across a wide range of populations, problems, interventions, comparisons, and outcomes (PICOS). A total of 160 effect sizes were reported in 44 meta-analyses ( k = 336 RCTs, N = 30,483 participants). MBIs showed superiority to passive controls across most PICOS ( ds = 0.10–0.89). Effects were typically smaller and less often statistically significant compared with active controls. MBIs were similar or superior to specific active controls and evidence-based treatments. Heterogeneity was typically moderate. Few consistent moderators were found. Results were generally robust to publication bias, although other important sources of bias were identified. Reporting of adverse effects was inconsistent. Statistical power may be lacking in meta-analyses, particularly for comparisons with active controls. Because MBIs show promise across some PICOS, future RCTs and meta-analyses should build on identified strengths and limitations of this literature.
Whereas the extraordinary pressures of the COVID-19 pandemic on student mental health have received considerable attention, less attention has been placed on educator well-being. School system employees play a vital role in society, and teacher levels of well-being are associated with the educational outcomes of young people. We extend extant research on the prevalence and correlates of educator distress during the pandemic by reporting on a pragmatic randomized wait-list controlled trial (N = 662; 64% teachers) of an innovative mental health promotion strategy implemented during the pandemic; a free 4-week smartphone-based meditation app designed to train key constituents of well-being (Healthy Minds Program [HMP]). Following our preregistered analysis plan and consistent with hypotheses, assignment to the HMP predicted significantly larger reductions in psychological distress, our primary outcome, at post intervention (Cohen’s d = −.53, 95% CI [−.69, −.38], p < .001) and at the 3-month follow-up (d = −.33 [−.48, −.18], p < .001). Also consistent with hypotheses, we observed similar indications of immediate and sustained benefit following the HMP on all six preregistered secondary outcomes selected to tap skills targeted in the app (e.g., perseverative thinking, social connection, well-being; absolute ds = .19–.42, all ps < .031 corrected except mindful action at follow-up). We found no evidence for elevated adverse events, and the HMP was equally effective among participants with elevated baseline anxiety and depressive symptoms. These data suggest that the HMP may be an effective and scalable approach to supporting the mental health and well-being of teachers and other school system employees, with implications for employee retention and performance and student outcomes.
The working alliance may be relevant in unguided smartphone-based interventions, but no validated measure exists. We evaluated the psychometric properties of the six-item Digital Working Alliance Inventory (DWAI) using a cross-sectional survey of meditation app users ( n = 290) and the intervention arm of a randomized trial testing a smartphone-based meditation app ( n = 314). Exploratory factor analysis suggested a single-factor solution which was replicated using longitudinal confirmatory factor analysis. The DWAI showed adequate internal consistency and test–retest reliability. Discriminant validity was supported by a lack of association with social desirability, psychological distress, and preference for a waitlist condition. Convergent validity was supported by positive associations with perceived app effectiveness and preference for an app condition. Supporting predictive validity, DWAI scores positively predicted self-reported and objective app utilization. When assessed at Weeks 3 or 4 of the intervention, but not earlier, DWAI scores predicted pre–post reductions in psychological distress.
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