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Deliberate control of the breath (breathwork) has recently received an unprecedented surge in public interest and breathing techniques have therapeutic potential to improve mental health. Our meta-analysis primarily aimed to evaluate the efficacy of breathwork through examining whether, and to what extent, breathwork interventions were associated with lower levels of self-reported/subjective stress compared to non-breathwork controls. We searched PsycInfo, PubMed, ProQuest, Scopus, Web of Science, ClinicalTrials.gov and ISRCTN up to February 2022, initially identifying 1325 results. The primary outcome self-reported/subjective stress included 12 randomised-controlled trials ( k  = 12) with a total of 785 adult participants. Most studies were deemed as being at moderate risk of bias. The random-effects analysis yielded a significant small-to-medium mean effect size, g  = − 0.35 [95% CI − 0.55, − 0.14], z  = 3.32, p  = 0.0009, showing breathwork was associated with lower levels of stress than control conditions. Heterogeneity was intermediate and approaching significance, χ 2 11  = 19, p  = 0.06, I 2  = 42%. Meta-analyses for secondary outcomes of self-reported/subjective anxiety ( k  = 20) and depressive symptoms ( k  = 18) showed similar significant effect sizes: g  = − 0.32, p  < 0.0001, and g  = − 0.40, p  < 0.0001, respectively. Heterogeneity was moderate and significant for both. Overall, results showed that breathwork may be effective for improving stress and mental health. However, we urge caution and advocate for nuanced research approaches with low risk-of-bias study designs to avoid a miscalibration between hype and evidence.

Mindfulness-based interventions (MBIs) can reduce risk of depressive relapse for people with a history of recurrent depression who are currently well. However, the cognitive, affective and motivational features of depression and anxiety might render MBIs ineffective for people experiencing current symptoms. This paper presents a meta-analysis of randomised controlled trials (RCTs) of MBIs where participants met diagnostic criteria for a current episode of an anxiety or depressive disorder. Post-intervention between-group Hedges g effect sizes were calculated using a random effects model. Moderator analyses of primary diagnosis, intervention type and control condition were conducted and publication bias was assessed. Twelve studies met inclusion criteria (n = 578). There were significant post-intervention between-group benefits of MBIs relative to control conditions on primary symptom severity (Hedges g = -0.59, 95% CI = -0.12 to -1.06). Effects were demonstrated for depressive symptom severity (Hedges g = -0.73, 95% CI = -0.09 to -1.36), but not for anxiety symptom severity (Hedges g = -0.55, 95% CI = 0.09 to -1.18), for RCTs with an inactive control (Hedges g = -1.03, 95% CI = -0.40 to -1.66), but not where there was an active control (Hedges g = 0.03, 95% CI = 0.54 to -0.48) and effects were found for MBCT (Hedges g = -0.39, 95% CI = -0.15 to -0.63) but not for MBSR (Hedges g = -0.75, 95% CI = 0.31 to -1.81). This is the first meta-analysis of RCTs of MBIs where all studies included only participants who were diagnosed with a current episode of a depressive or anxiety disorder. Effects of MBIs on primary symptom severity were found for people with a current depressive disorder and it is recommended that MBIs might be considered as an intervention for this population.

Stress, depression, and anxiety among working populations can result in reduced work performance and increased absenteeism. Although there is evidence that these common mental health problems are preventable and treatable in the workplace, uptake of psychological treatments among the working population is low. One way to address this may be the delivery of occupational digital mental health interventions. While there is convincing evidence for delivering digital psychological interventions within a health and community context, there is no systematic review or meta-analysis of these interventions in an occupational setting. The aim of this study was to identify the effectiveness of occupational digital mental health interventions in enhancing employee psychological well-being and increasing work effectiveness and to identify intervention features associated with the highest rates of engagement and adherence. A systematic review of the literature was conducted using Cochrane guidelines. Papers published from January 2000 to May 2016 were searched in the PsychINFO, MEDLINE, PubMed, Science Direct, and the Cochrane databases, as well as the databases of the researchers and relevant websites. Unpublished data was sought using the Conference Proceedings Citation Index and the Clinical Trials and International Standard Randomized Controlled Trial Number (ISRCTN) research registers. A meta-analysis was conducted by applying a random-effects model to assess the pooled effect size for psychological well-being and the work effectiveness outcomes. A positive deviance approach was used to identify those intervention features associated with the highest rates of engagement and adherence. In total, 21 randomized controlled trials (RCTs) met the search criteria. Occupational digital mental health interventions had a statistically significant effect post intervention on both psychological well-being (g=0.37, 95% CI 0.23-0.50) and work effectiveness (g=0.25, 95% CI 0.09-0.41) compared with the control condition. No statistically significant differences were found on either outcome between studies using cognitive behavioral therapy (CBT) approaches (as defined by the authors) compared with other psychological approaches, offering guidance compared with self-guidance, or recruiting from a targeted workplace population compared with a universal workplace population. In-depth analysis of the interventions identified by the positive deviance approach suggests that interventions that offer guidance are delivered over a shorter time frame (6 to 7 weeks), utilize secondary modalities for delivering the interventions and engaging users (ie, emails and text messages [short message service, SMS]), and use elements of persuasive technology (ie, self-monitoring and tailoring), which may achieve greater engagement and adherence. This review provides evidence that occupational digital mental health interventions can improve workers' psychological well-being and increase work effectiveness. It identifies intervention characteristics that may increase engagement. Recommendations are made for future research, practice, and intervention development.

Perinatal mental health difficulties are associated with adverse consequences for parents and infants. However, the potential risks associated with the use of psychotropic medication for pregnant and breastfeeding women and the preferences expressed by women for non-pharmacological interventions mean it is important to ensure that effective psychological interventions are available. It has been argued that mindfulness-based interventions may offer a novel approach to treating perinatal mental health difficulties, but relatively little is known about their effectiveness with perinatal populations. This paper therefore presents a systematic review and meta-analysis of the effectiveness of mindfulness-based interventions for reducing depression, anxiety and stress and improving mindfulness skills in the perinatal period. A systematic review identified seventeen studies of mindfulness-based interventions in the perinatal period, including both controlled trials (n = 9) and pre-post uncontrolled studies (n = 8). Eight of these studies also included qualitative data. Hedge's g was used to assess uncontrolled and controlled effect sizes in separate meta-analyses, and a narrative synthesis of qualitative data was produced. Pre- to post-analyses showed significant reductions in depression, anxiety and stress and significant increases in mindfulness skills post intervention, each with small to medium effect sizes. Completion of the mindfulness-based interventions was reasonable with around three quarters of participants meeting study-defined criteria for engagement or completion where this was recorded. Qualitative data suggested that participants viewed mindfulness interventions positively. However, between-group analyses failed to find any significant post-intervention benefits for depression, anxiety or stress of mindfulness-based interventions in comparison to control conditions: effect sizes were negligible and it was conspicuous that intervention group participants did not appear to improve significantly more than controls in their mindfulness skills. The interventions offered often deviated from traditional mindfulness-based cognitive therapy or mindfulness-based stress reduction programmes, and there was also a tendency for studies to focus on healthy rather than clinical populations, and on antenatal rather than postnatal populations. It is argued that these and other limitations with the included studies and their interventions may have been partly responsible for the lack of significant between-group effects. The implications of the findings and recommendations for future research are discussed.

Mindfulness practice has been widely adopted by healthcare staff, being grounded in evidence and supported by national guidelines. However, certain fundamental factors are not well understood, including attitudes towards mindfulness in-groups. The aim of this project was to explore the nature of social identification with mindfulness in-groups in relation to engagement with mindful practices. Twenty healthcare staff from three healthcare Trusts were recruited to engage in semi-structured interviews of one-hour duration. Transcripts of these interviews were then subjected to reflexive thematic analysis. Social identification was simultaneously rich and fluid, with some tentative evidence of positive boosts to psychological engagement tempered by dissonance about current physical engagement levels. Healthcare and mindfulness identities complemented, in that being aided doing, aligning values and aspirations, although clashes also presented through culture, depending on one's sense of connection/disconnection. Employers and trainers could consider implementing strategies to enhance social identification with mindfulness in-groups. Further research should also explore whether strength of social identification translates into improved engagement with mindful practices.

Compassion has long been regarded as a core part of our humanity by contemplative traditions, and in recent years, it has received growing research interest. Following a recent review of existing conceptualisations, compassion has been defined as consisting of the following five elements: 1) recognising suffering, 2) understanding the universality of suffering in human experience, 3) feeling moved by the person suffering and emotionally connecting with their distress, 4) tolerating uncomfortable feelings aroused (e.g., fear, distress) so that we remain open to and accepting of the person suffering, and 5) acting or being motivated to act to alleviate suffering. As a prerequisite to developing a high quality compassion measure and furthering research in this field, the current study empirically investigated the factor structure of the five-element definition using a combination of existing and newly generated self-report items. This study consisted of three stages: a systematic consultation with experts to review items from existing self-report measures of compassion and generate additional items (Stage 1), exploratory factor analysis of items gathered from Stage 1 to identify the underlying structure of compassion (Stage 2), and confirmatory factor analysis to validate the identified factor structure (Stage 3). Findings showed preliminary empirical support for a five-factor structure of compassion consistent with the five-element definition. However, findings indicated that the 'tolerating' factor may be problematic and not a core aspect of compassion. This possibility requires further empirical testing. Limitations with items from included measures lead us to recommend against using these items collectively to assess compassion. Instead, we call for the development of a new self-report measure of compassion, using the five-element definition to guide item generation. We recommend including newly generated 'tolerating' items in the initial item pool, to determine whether or not factor-level issues are resolved once item-level issues are addressed.

Breathwork may offer simple tools for stress resilience. We conducted the largest parallel randomised-controlled trial on breathwork to date (NCT05676658) wherein 400 participants on the research platform Prolific were randomised, in blocks of 2 via remote software, to coherent breathing at ~ 5.5 breaths/min or a matched attention-placebo at 12 breaths/min, for ~ 10 min/day over 4 weeks. Participants were blinded to their allocated interventions, both of which were paced with equal inhalation:exhalation ratios. There were no differences on credibility and expectancy of benefit between conditions. At the primary timepoint post-intervention for the primary outcome subjective stress, there was no significant group by time interaction ( F (1,377) = 0.089, p  = 0.765, η p 2  < 0.001) nor main effect of group ( F  = 0.002, p  = 0.961, η p 2  < 0.001), however there was a significant main effect of time ( F  = 72.1, p  < 0.001, η p 2  = 0.161). Similar results were found at 1-month follow-up for stress and for secondary outcomes of anxiety, depression and wellbeing. There were overall improvements on these mental health and wellbeing outcomes from baseline to post-intervention and follow-up across both groups, yet the magnitude of this improvement was not different between arms. Accordingly, we found no measurable effect of coherent breathing over and above a well-designed breathwork placebo at improving mental health and wellbeing. Methodological considerations and recommendations for robust future research are discussed. Funder: Sasakawa Young Leaders Fellowship Fund, Tokyo, Japan.

Health care workers experience high stress. Accessible, affordable, and effective approaches to reducing stress are lacking. In-person mindfulness-based interventions can reduce health care worker stress but are not widely available or accessible to busy health care workers. Unguided, digital, mindfulness-based self-help (MBSH) interventions show promise and can be flexibly engaged with. However, their effectiveness in reducing health care worker stress has not yet been explored in a definitive trial. This study aimed to investigate the effectiveness of an unguided digital MBSH app (Headspace) in reducing health care worker stress. This was a definitive superiority randomized controlled trial with 2182 National Health Service staff in England recruited on the web and allocated in a 1:1 ratio to fully automated Headspace (n=1095, 50.18%) or active control (Moodzone; n=1087, 49.82%) for 4.5 months. Outcomes were subscales of the Depression, Anxiety, and Stress (primary outcome) Scale short form; Short Warwick Edinburgh Mental Well-being Scale; Maslach Burnout Inventory; 15-item Five-Facet Mindfulness Questionnaire minus Observe items; Self-Compassion Scale-Short Form; Compassionate Love Scale; Penn State Worry Questionnaire; Brooding subscale of the Ruminative Response Scale; and sickness absence. Intention-to-treat analyses found that Headspace led to greater reductions in stress over time than Moodzone (b=-0.31, 95% CI -0.47 to -0.14; P<.001), with small effects. Small effects of Headspace versus Moodzone were found for depression (b=-0.24, 95% CI -0.40 to -0.08; P=.003), anxiety (b=-0.19, 95% CI -0.32 to -0.06; P=.004), well-being (b=0.14, 95% CI 0.05-0.23; P=.002), mindfulness (b=0.22, 95% CI 0.09-0.34; P=.001), self-compassion (b=0.48, 95% CI 0.33-0.64; P<.001), compassion for others (b=0.02, 95% CI 0.00-0.04; P=.04), and worry (b=-0.30, 95% CI -0.51 to -0.09; P=.005) but not for burnout (b=-0.19, -0.04, and 0.13, all 95% CIs >0; P=.65, .67, and .35), ruminative brooding (b=-0.06, 95% CI -0.12 to 0.00; P=.06), or sickness absence (γ=0.09, 95% CI -0.18 to 0.34). Per-protocol effects of Headspace (454/1095, 41.46%) versus Moodzone (283/1087, 26.03%) over time were found for stress, self-compassion, and compassion for others but not for the other outcomes. Engagement (practice days per week) and improvements in self-compassion during the initial 1.5-month intervention period mediated pre- to postintervention improvements in stress. Improvements in mindfulness, rumination, and worry did not mediate pre- to postintervention improvements in stress. No serious adverse events were reported. An unguided digital MBSH intervention (Headspace) can reduce health care workers' stress. Effect sizes were small but could have population-level benefits. Unguided digital MBSH interventions can be part of the solution to reducing health care worker stress alongside potentially costlier but potentially more effective in-person mindfulness-based interventions, nonmindfulness courses, and organizational-level interventions. International Standard Randomised Controlled Trial Number ISRCTN15424185; https://tinyurl.com/rv9en5kc.

Stress, burnout, and mental health problems such as depression and anxiety are common, and can significantly impact workplaces through absenteeism and reduced productivity. To address this issue, organizations must first understand the extent of the difficulties by mapping the mental health of their workforce. Online surveys are a cost-effective and scalable approach to achieve this but typically have low response rates, in part due to a lack of interactivity. Chatbots offer one potential solution, enhancing engagement through simulated natural human conversation and use of interactive features. The aim of this study was to explore if a text-based chatbot is a feasible approach to engage and motivate employees to complete a workplace mental health assessment. This paper describes the design process and results of a pilot implementation. A fully automated chatbot (\"Viki\") was developed to evaluate employee risks of suffering from depression, anxiety, stress, insomnia, burnout, and work-related stress. Viki uses a conversation style and gamification features to enhance engagement. A cross-sectional analysis was performed to gain first insights of a pilot implementation within a small to medium-sized enterprise (120 employees). The response rate was 64.2% (77/120). In total, 98 employees started the assessment, 77 of whom (79%) completed it. The majority of participants scored in the mild range for anxiety (20/40, 50%) and depression (16/28, 57%), in the moderate range for stress (10/22, 46%), and at the subthreshold level for insomnia (14/20, 70%) as defined by their questionnaire scores. A chatbot-based workplace mental health assessment seems to be a highly engaging and effective way to collect anonymized mental health data among employees with response rates comparable to those of face-to-face interviews.

Background: Mental health difficulties are highly prevalent, yet access to support is limited by barriers of stigma, cost, and availability. These issues are even more prevalent in low- and middle-income countries, and digital technology is one potential way to overcome these barriers. Digital mental health interventions are effective but often struggle with low engagement rates, particularly in the absence of human support. Chatbots could offer a scalable solution, simulating human support at a lower cost. Objective: To complete a preliminary evaluation of engagement and effectiveness of Vitalk, a mental health chatbot, at reducing anxiety, depression and stress. Methods: Real world data was analyzed from 3,629 Vitalk users who had completed the first phase of a Vitalk program (“less anxiety,” “less stress” or “better mood”). Programs were delivered through written conversation with a chatbot. Engagement was calculated from the number of responses sent to the chatbot divided by days in the program. Results: Users sent an average of 8.17 responses per day. For all three programs, target outcome scores reduced between baseline and follow up with large effect sizes for anxiety (Cohen's d = −0.85), depression (Cohen's d = −0.91) and stress (Cohen's d = −0.81). Increased engagement resulted in improved post-intervention values for anxiety and depression. Conclusion: This study highlights a chatbot's potential to reduce mental health symptoms in the general population within Brazil. While findings show promise, further research is required.