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High ventilation breathwork with retention (HVBR) has been growing in popularity over the past decade and might be beneficial for mental and physical health. However, little research has explored the potential therapeutic effects of brief, remotely delivered HVBR and the tolerability profile of this technique. Accordingly, we investigated the effects of a fully-automated HVBR protocol, along with its tolerability, when delivered remotely in a brief format. This study (NCT06064474) was the largest blinded randomised-controlled trial on HVBR to date in which 200 young, healthy adults balanced for gender were randomly allocated in blocks of 2 by remote software to 3 weeks of 20 min daily HVBR (fast breathing with long breath holds) or a placebo HVBR comparator (15 breaths/min with short breath holds). The trial was concealed as a fast breathwork study wherein both intervention and comparator were masked, and only ~ 40% guessed their group assignment with no difference in accuracy between groups. Both groups reported analogous credibility and expectancy of benefit, subjective adherence, positive sentiment, along with short- and long-term tolerability. At post-intervention (primary timepoint) for stress level (primary outcome), we found no significant group × time interaction, F(1,180) = 1.98, p = 0.16, ηp2 = 0.01, d = 0.21), nor main effect of group, (F = 0.35, p = 0.55, ηp2

BackgroundStress, 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. ObjectiveThe 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. MethodsA 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). ResultsThe 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. ConclusionsA 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: Veterinary professionals experience higher psychological distress and lower wellbeing compared with the general population. Identifying workplace stressors is key to understanding and alleviating these difficulties. Objective: Identify the severity of workplace stressors in veterinary professions across different levels of professional experience. Method: A cross‐sectional quantitative design was utilised via administration of a veterinary stressor questionnaire that measured the severity of 93 generic and veterinary‐specific workplace stressors. Results: A total of 658 participants reported stressor severity score. Factor analysis revealed four main stressor categories: workload and job demands, client relations stress, performance and accountability, patient care challenges. An inverse relationship was found between experience level and stressor severity scores. Furthermore, the most severe stressors varied as a function of career stage. Findings and implications: Stressor severity tends to decrease with increasing experience levels. Stressors can be categorised by theme and unique stressor profiles can be derived for practitioners according to experience level. This knowledge can assist in the design and delivery of workplace support initiatives. Conclusions: Identify key stressors across different levels of experience is important in focusing efforts to support people in the workplace. [ABSTRACT FROM AUTHOR]