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Explanatory factors of post-traumatic distress and burnout among hospital staff 6 months after Hurricane Irma in Saint-Martin and Saint-Barthelemy.

ABSTRACT: BACKGROUND:In September 2017, the Hurricane Irma devastated the islands of Saint-Martin and Saint-Barthelemy (French West Indies). This was a particularly distressing time for the local healthcare staff in charge of rescuing the population. The aim of this study was to identify the explanatory factors of post-traumatic distress and burnout in hospital staff. METHODS:An anonymous questionnaire was sent to all 509 hospital workers of Saint-Martin and Saint-Barthelemy. Post-traumatic distress and burnout was assessed using the Post-Traumatic Stress Disorder Checklist (PCL-S) and Copenhagen Burnout Inventory (CBI) scales. Bivariate and multivariate analyses were used to determine the explanatory variables for these two psychological disorders. RESULTS:Two hundred and sixty-two questionnaires were completed (response rate of 51.7%). The explanatory factors of post-traumatic distress were female gender (OR = 12.93, 95% CI: 2.70-232.10), electricity shortages (OR = 2.92, 95% CI: 1.13-8.19) and home damage (OR = 1.16, 95% CI [1.02-1.33]). In parallel, the explanatory factors of burnout were post-traumatic distress (OR: 10.42, 95% CI: 4.72-25.58), female gender (OR = 2,41, 95% CI: 1.24-5.02) and paramedical staff (OR = 2,53, 95% CI: 1.15-6.21). In the multivariate analysis, only burnout was significantly associated with post-traumatic distress (OR = 9.26, 95% CI: 4.11-23.14). CONCLUSIONS:Six months after Irma, post-traumatic distress among hospital staff was strongly linked to burnout. This study revealed the lack of electricity as a new factor related to post-traumatic distress. It also suggested that psychological intervention should be strengthened.

SUBMITTER: Metregiste D

PROVIDER: S-EPMC7064261 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Explanatory factors of post-traumatic distress and burnout among hospital staff 6 months after Hurricane Irma in Saint-Martin and Saint-Barthelemy.

Metregiste Damien D Boucaud-Maitre Denis D Aubert Lyderic L Noubou Lazare L Jehel Louis L

PloS one 20200310 3

<h4>Background</h4>In September 2017, the Hurricane Irma devastated the islands of Saint-Martin and Saint-Barthelemy (French West Indies). This was a particularly distressing time for the local healthcare staff in charge of rescuing the population. The aim of this study was to identify the explanatory factors of post-traumatic distress and burnout in hospital staff.<h4>Methods</h4>An anonymous questionnaire was sent to all 509 hospital workers of Saint-Martin and Saint-Barthelemy. Post-traumatic ...[more]

PMID: 32155185

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Project description:ImportanceNursing home residents are at heightened risk for morbidity and mortality following an exposure to a disaster such as a hurricane or the COVID19 pandemic. Previous research has shown that nursing home resident mortality related to disasters is frequently underreported. There is a need to better understand the consequences of disasters on nursing home residents and to differentiate vulnerability based on patient characteristics.ObjectiveTo evaluate mortality and morbidity associated with exposure to Hurricane Irma, a Category 4 storm that made landfall on September 10, 2017, in Cudjoe Key, Florida, among short-stay (<90-day residence) and long-stay (≥90-day residence) residents of nursing homes.Design, setting, and participantsCohort study of Florida nursing home residents comparing residents exposed to Hurricane Irma in September 2017 to a control group of residents residing at the same nursing homes over the same time period in calendar year 2015. Data were analyzed from August 28, 2019, to July 22, 2020.ExposureResidents who experienced Hurricane Irma were considered exposed; those who did not were considered unexposed.Main outcome and measuresOutcome variables included 30-day and 90-day mortality and first hospitalizations after the storm in both the short term and the long term.ResultsA total of 61 564 residents who were present in 640 Florida nursing home facilities on September 7, 2017, were identified. A comparison cohort of 61 813 residents was evaluated in 2015. Both cohorts were mostly female (2015, 68%; 2017, 67%), mostly White (2015, 79%; 2017, 78%), and approximately 40% of the residents in each group were over the age of 85 years. Compared with the control group in 2015, an additional 262 more nursing home deaths were identified at 30 days and 433 more deaths at 90 days. The odds of a first hospitalization for those exposed (vs nonexposed) were 1.09 (95% CI, 1.05-1.13) within the first 30 days after the storm and 1.05 (95% CI, 1.02-1.08) at 90 days; the odds of mortality were 1.12 (95% CI, 1.05-1.18) at 30 days and 1.07 (95% CI, 1.03-1.11) at 90 days. Among long-stay residents, the odds of mortality for those exposed to Hurricane Irma were 1.18 (95% CI, 1.08-1.29) times those unexposed and the odds of hospitalization were 1.11 (95% CI, 1.04-1.18) times those unexposed in the post 30-day period.Conclusions and relevanceThe findings of this study suggest that nursing home residents are at considerable risk to the consequences of disasters. These risks may be underreported by state and federal agencies. Long-stay residents, those who have resided in a nursing home for 90 days or more, may be most vulnerable to the consequences of hurricane disasters.

Project description:ObjectivesTo investigate the factors associated with whether assisted living communities (ALCs) in Florida evacuated or sheltered in place for Hurricane Irma in 2017, focusing on license type as a proxy for acuity of care.DesignCross-sectional study using data collected by the state through its emergency reporting system and a post-hurricane survey.Setting and participantsAnalyses included all 3112 ALCs in the emergency reporting system. A subset of 1880 that completed the survey provided supplementary data.Methodsχ2 tests were used to examine differences between ALC characteristics (license type, size, payment, profit status, rural location, geographical region, and being under an evacuation order) and whether they evacuated. Logistic regression was used to test associations between characteristics and evacuation status.ResultsOf 3112 ALCs, 560 evacuated and 2552 sheltered in place. Bivariate analysis found significant associations between evacuation status and evacuation order, license type (mental health care), payment, and region. In the adjusted analysis, medium and larger ALCs were 43% (P < .001) and 53% (P < .001) less likely to evacuate than ALCs with fewer than 25 beds. Compared with ALCs in the Southeast, nearly every region was more likely to evacuate, with the highest likelihood in the Central West (odds ratio 1.76, 95% confidence interval 1.35‒2.30). ALCs under an evacuation order were 8 times more likely to evacuate (P < .001). We found no relationship between evacuation status and having a license to provide higher care.Conclusions and implicationsPrior research highlighting harm associated with evacuation has led to recommendations that long-term care facilities carefully consider resident impairment in evacuation decision-making. Evidence that small ALCs are more likely to evacuate and that having a higher-care license is not associated with evacuation likelihood shows research is needed to understand how ALCs weigh resident risks in decisions to evacuate or shelter in place.

Project description:BackgroundClinicians and healthcare staff report high levels of burnout. Two common burnout assessments are the Maslach Burnout Inventory (MBI) and a single-item, self-defined burnout measure. Relatively little is known about how the measures compare.ObjectiveTo identify the sensitivity, specificity, and concurrent validity of the self-defined burnout measure compared to the more established MBI measure.DesignCross-sectional survey (November 2016-January 2017).ParticipantsFour hundred forty-four primary care clinicians and 606 staff from three San Francisco Aarea healthcare systems.Main measuresThe MBI measure, calculated from a high score on either the emotional exhaustion or cynicism subscale, and a single-item measure of self-defined burnout. Concurrent validity was assessed using a validated, 7-item team culture scale as reported by Willard-Grace et al. (J Am Board Fam Med 27(2):229-38, 2014) and a standard question about workplace atmosphere as reported by Rassolian et al. (JAMA Intern Med 177(7):1036-8, 2017) and Linzer et al. (Ann Intern Med 151(1):28-36, 2009).Key resultsSimilar to other nationally representative burnout estimates, 52% of clinicians (95% CI: 47-57%) and 46% of staff (95% CI: 42-50%) reported high MBI emotional exhaustion or high MBI cynicism. In contrast, 29% of clinicians (95% CI: 25-33%) and 31% of staff (95% CI: 28-35%) reported "definitely burning out" or more severe symptoms on the self-defined burnout measure. The self-defined measure's sensitivity to correctly identify MBI-assessed burnout was 50.4% for clinicians and 58.6% for staff; specificity was 94.7% for clinicians and 92.3% for staff. Area under the receiver operator curve was 0.82 for clinicians and 0.81 for staff. Team culture and atmosphere were significantly associated with both self-defined burnout and the MBI, confirming concurrent validity.ConclusionsPoint estimates of burnout notably differ between the self-defined and MBI measures. Compared to the MBI, the self-defined burnout measure misses half of high-burnout clinicians and more than 40% of high-burnout staff. The self-defined burnout measure has a low response burden, is free to administer, and yields similar associations across two burnout predictors from prior studies. However, the self-defined burnout and MBI measures are not interchangeable.

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Explanatory factors of post-traumatic distress and burnout among hospital staff 6 months after Hurricane Irma in Saint-Martin and Saint-Barthelemy.

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Explanatory factors of post-traumatic distress and burnout among hospital staff 6 months after Hurricane Irma in Saint-Martin and Saint-Barthelemy.

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