首页> 外文期刊>Stress and health: journal of the International Society for the Investigation of Stress >Cross‐sectional survey of workplace stressors associated with physician burnout measured by the Mini‐Z and the Maslach Burnout Inventory
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Cross‐sectional survey of workplace stressors associated with physician burnout measured by the Mini‐Z and the Maslach Burnout Inventory

机译:与Mini-Z和Maslach Burnout Inventory测量的医生倦怠相关的工作场所压力频道横断面调查

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Abstract Rising physician burnout has adverse effects on healthcare. This study aimed to identify remediable stressors associated with burnout using the 10‐item Mini‐Z and the Maslach Burnout Inventory (MBI), and to compare performance of the Mini‐Z's single‐item burnout metric against the 22‐item MBI. Surveys were emailed to 4,118 clinicians affiliated with an academic health system; 1,252 clicked the link, and 557 responded (completion rate 44%). Four hundred seventy‐five practicing physicians were included: academic faculty (372), hospital employed (52), and private practitioners (81). Prevalence of burnout via the MBI was 56.6%. Predictors of burnout were poor control over workload [OR?=?8.24, 95% CI 4.(81, 14.11)], inefficient teamwork [OR?=?7.61, 95% (CI 3.28, 17.67)], insufficient documentation time [OR?=?5.83, 95% (CI 3.35, 10.15)], hectic‐chaotic work atmosphere [OR?=?3.49, 95% (CI 2.12, 5.74)], lack of value‐alignment with leadership [OR?=?3.27, 95% (CI 2.12, 5.74)], and excessive electronic medical record time at home [OR?=?1.99, 95% CI (1.21, 3.27)]. Academic faculty experienced more burnout than private practitioners (59.9% vs. 42.0%, p ?=?0.013). Odds of burnout associated with stressors were generally concordant via Mini‐Z's burnout metric versus the MBI. The Mini‐Z is a brief, valid method to identify stressors associated with burnout and guide interventions.
机译:摘要崛起的医生倦怠对医疗保健产生不利影响。本研究旨在使用10项Mini-Z和MASLACH BUSTOUT库存(MBI)识别与倦怠相关的可补偿压力,并比较Mini-Z单项烧坏度量对22项MBI的性能。调查被电子邮件发送给4,118名临床医生,隶属于学术卫生系统; 1,252点击该链接,557次响应(完成率44%)。包括四百七十五的实践医生:学术教师(372),医院就业(52)和私人从业者(81)。通过MBI的倦怠患病率为56.6%。倦怠的预测因素对工作负荷进行控制不良[或?=?8.24,95%CI 4.(81,14.11)],效率低下的团队合作[或?7.61,95%(CI 3.28,17.67),文档时间不足[或者?=?5.83,95%(CI 3.35,10.15)],忙乱的工作氛围[或?3.49,95%(CI 2.12,5.74)],与领导力缺乏[或?=? 3.27,95%(CI 2.12,5.74)],以及家中的过度电子医疗记录时间[或?=?1.99,95%CI(1.21,3.27)]。学术教师比私人从业者经历了更多的倦怠(59.9%vs.2.0%,p?= 0.013)。与压力源相关的倦怠的几率通常通过Mini-Z的倦怠度量与MBI进行交作。 Mini-Z是一个简要的有效方法,用于识别与倦怠和引导干预相关的压力源。

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