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      Physical relaxation for occupational stress in healthcare workers: A systematic review and network meta‐analysis of randomized controlled trials

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          Abstract

          <div class="section"> <a class="named-anchor" id="joh212243-sec-0001"> <!-- named anchor --> </a> <h5 class="section-title" id="d12163657e268">Objectives</h5> <p id="d12163657e270">Work related stress is a major occupational health problem that is associated with adverse effects on physical and mental health. Healthcare workers are particularly vulnerable in the era of COVID‐19. Physical methods of stress relief such as yoga and massage therapy may reduce occupational stress. The objective of this systematic review and network meta‐analysis is to determine the effects of yoga, massage therapy, progressive muscle relaxation, and stretching on alleviating stress and improving physical and mental health in healthcare workers. </p> </div><div class="section"> <a class="named-anchor" id="joh212243-sec-0002"> <!-- named anchor --> </a> <h5 class="section-title" id="d12163657e273">Methods</h5> <p id="d12163657e275">Databases were searched for randomized controlled trials on the use of physical relaxation methods for occupational stress in healthcare workers with any duration of follow‐up. Meta‐analysis was performed for standard mean differences in stress measures from baseline between subjects undergoing relaxation vs non‐intervention controls. Network meta‐analysis was conducted to determine the best relaxation method. </p> </div><div class="section"> <a class="named-anchor" id="joh212243-sec-0003"> <!-- named anchor --> </a> <h5 class="section-title" id="d12163657e278">Results</h5> <p id="d12163657e280">Fifteen trials representing 688 healthcare workers were identified. Random‐effects meta‐analysis shows that physical relaxation methods overall reduced measures of occupational stress at the longest duration of follow‐up vs baseline compared to non‐intervention controls (SMD −0.53; 95% CI [−0.74 to −0.33]; <i>p</i> &lt; .00001). On network meta‐analysis, only yoga alone (SMD −0.71; 95% CI [−1.01 to −0.41]) and massage therapy alone (SMD −0.43; 95% CI [−0.72 to −0.14]) were more effective than control, with yoga identified as the best method ( <i>p</i>‐score = .89). </p> </div><div class="section"> <a class="named-anchor" id="joh212243-sec-0004"> <!-- named anchor --> </a> <h5 class="section-title" id="d12163657e289">Conclusion</h5> <p id="d12163657e291">Physical relaxation may help reduce occupational stress in healthcare workers. Yoga is particularly effective and offers the convenience of online delivery. Employers should consider implementing these methods into workplace wellness programs. </p> </div>

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          Psychological distress, coping behaviors, and preferences for support among New York healthcare workers during the COVID-19 pandemic

          Objective The mental health toll of COVID-19 on healthcare workers (HCW) is not yet fully described. We characterized distress, coping, and preferences for support among NYC HCWs during the COVID-19 pandemic. Methods This was a cross-sectional web survey of physicians, advanced practice providers, residents/fellows, and nurses, conducted during a peak of inpatient admissions for COVID-19 in NYC (April 9th–April 24th 2020) at a large medical center in NYC (n = 657). Results Positive screens for psychological symptoms were common; 57% for acute stress, 48% for depressive, and 33% for anxiety symptoms. For each, a higher percent of nurses/advanced practice providers screened positive vs. attending physicians, though housestaff's rates for acute stress and depression did not differ from either. Sixty-one percent of participants reported increased sense of meaning/purpose since the COVID-19 outbreak. Physical activity/exercise was the most common coping behavior (59%), and access to an individual therapist with online self-guided counseling (33%) garnered the most interest. Conclusions NYC HCWs, especially nurses and advanced practice providers, are experiencing COVID-19-related psychological distress. Participants reported using empirically-supported coping behaviors, and endorsed indicators of resilience, but they also reported interest in additional wellness resources. Programs developed to mitigate stress among HCWs during the COVID-19 pandemic should integrate HCW preferences.
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            Ranking treatments in frequentist network meta-analysis works without resampling methods

            Background Network meta-analysis is used to compare three or more treatments for the same condition. Within a Bayesian framework, for each treatment the probability of being best, or, more general, the probability that it has a certain rank can be derived from the posterior distributions of all treatments. The treatments can then be ranked by the surface under the cumulative ranking curve (SUCRA). For comparing treatments in a network meta-analysis, we propose a frequentist analogue to SUCRA which we call P-score that works without resampling. Methods P-scores are based solely on the point estimates and standard errors of the frequentist network meta-analysis estimates under normality assumption and can easily be calculated as means of one-sided p-values. They measure the mean extent of certainty that a treatment is better than the competing treatments. Results Using case studies of network meta-analysis in diabetes and depression, we demonstrate that the numerical values of SUCRA and P-Score are nearly identical. Conclusions Ranking treatments in frequentist network meta-analysis works without resampling. Like the SUCRA values, P-scores induce a ranking of all treatments that mostly follows that of the point estimates, but takes precision into account. However, neither SUCRA nor P-score offer a major advantage compared to looking at credible or confidence intervals. Electronic supplementary material The online version of this article (doi:10.1186/s12874-015-0060-8) contains supplementary material, which is available to authorized users.
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              Indirect and mixed-treatment comparison, network, or multiple-treatments meta-analysis: many names, many benefits, many concerns for the next generation evidence synthesis tool.

              The ever increasing number of alternative treatment options and the plethora of clinical trials have put systematic reviews and meta-analysis under a new perspective by emphasizing the need to make inferences about competing treatments for the same condition. The statistical component in reviews that compare multiple interventions, network meta-analysis, is the next generation evidence synthesis toolkit which, when properly applied, can serve decision-making better than the established pairwise meta-analysis. The criticism and enthusiasm for network meta-analysis echo those that greeted the advent of simple meta-analysis. The main criticism is associated with the difficulty in evaluating the assumption underlying the statistical synthesis of direct and indirect evidence. In the present article, the assumption of the network meta-analysis are presented using various formulations, the statistical and nonstatistical methodological considerations are elucidated, and the progress achieved in this field is summarized. Throughout, focus is put on highlighting the analogy between the concerns and difficulties that the scientific community had some time ago when advancing from individual trials to their quantitative synthesis via meta-analysis and those currently expressed about the transition from head-to-head meta-analyses to network meta-analysis. Copyright © 2012 John Wiley & Sons, Ltd.
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                Author and article information

                Contributors
                (View ORCID Profile)
                Journal
                Journal of Occupational Health
                Jrnl of Occup Health
                Wiley
                1341-9145
                1348-9585
                January 2021
                July 07 2021
                January 2021
                : 63
                : 1
                Affiliations
                [1 ]Administration Division Southern Nevada Health District Las Vegas NV USA
                [2 ]Department of Exercise Science Florida Atlantic University Boca Raton FL USA
                [3 ]School of Life Sciences University of Nevada Las Vegas Las Vegas NV USA
                [4 ]Department of Veterans Affairs Orlando VA Healthcare System Orlando FL USA
                Article
                10.1002/1348-9585.12243
                737403c5-973b-4c5c-b1fb-fcad61aea5d9
                © 2021

                http://creativecommons.org/licenses/by/4.0/

                http://doi.wiley.com/10.1002/tdm_license_1.1

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