Burnout, anxiety and depression in healthcare workers during the early COVID-19 period in Singapore

acceptedVersionPeer reviewe

Perceptions of mobile health apps and features to support psychosocial well-being among frontline health care workers involved in the COVID-19 pandemic response: Qualitative study

10.2196/26282Journal of Medical Internet Research235e2628

Leveraging Large-Scale Electronic Health Records and Interpretable Machine Learning for Clinical Decision Making at the Emergency Department: Protocol for System Development and Validation

BackgroundThere is a growing demand globally for emergency department (ED) services. An increase in ED visits has resulted in overcrowding and longer waiting times. The triage process plays a crucial role in assessing and stratifying patients’ risks and ensuring that the critically ill promptly receive appropriate priority and emergency treatment. A substantial amount of research has been conducted on the use of machine learning tools to construct triage and risk prediction models; however, the black box nature of these models has limited their clinical application and interpretation. ObjectiveIn this study, we plan to develop an innovative, dynamic, and interpretable System for Emergency Risk Triage (SERT) for risk stratification in the ED by leveraging large-scale electronic health records (EHRs) and machine learning. MethodsTo achieve this objective, we will conduct a retrospective, single-center study based on a large, longitudinal data set obtained from the EHRs of the largest tertiary hospital in Singapore. Study outcomes include adverse events experienced by patients, such as the need for an intensive care unit and inpatient death. With preidentified candidate variables drawn from expert opinions and relevant literature, we will apply an interpretable machine learning–based AutoScore to develop 3 SERT scores. These 3 scores can be used at different times in the ED, that is, on arrival, during ED stay, and at admission. Furthermore, we will compare our novel SERT scores with established clinical scores and previously described black box machine learning models as baselines. Receiver operating characteristic analysis will be conducted on the testing cohorts for performance evaluation. ResultsThe study is currently being conducted. The extracted data indicate approximately 1.8 million ED visits by over 810,000 unique patients. Modelling results are expected to be published in 2022. ConclusionsThe SERT scoring system proposed in this study will be unique and innovative because of its dynamic nature and modelling transparency. If successfully validated, our proposed solution will establish a standard for data processing and modelling by taking advantage of large-scale EHRs and interpretable machine learning tools. International Registered Report Identifier (IRRID)DERR1-10.2196/3420

Spillover Effects of COVID-19 on Essential Chronic Care and Ways to Foster Health System Resilience to Support Vulnerable Non-COVID Patients: A Multistakeholder Study

10.1016/j.jamda.2021.11.004JOURNAL OF THE AMERICAN MEDICAL DIRECTORS ASSOCIATION2317-1

The Psychological Well-Being of Southeast Asian Frontline Healthcare Workers during COVID-19 : A Multi-Country Study

Objectives: This study examined the prevalence of anxiety, depression, and job burnout among frontline healthcare workers (HCWs) across six Southeast Asian countries (Indonesia, Malaysia, Philippines, Singapore, Thailand, Vietnam) during the COVID-19 pandemic in 2021. We also inves-tigated the associated risk and protective factors. Methods: Frontline HCWs (N = 1381) from the participating countries participated between 4 January and 14 June 2021. The participants completed self-reported surveys on anxiety (GAD-7), depression (PHQ-8), and job burnout (PWLS). Multivariate logistic regressions were performed with anxiety, depression, and job burnout as outcomes and sociodemographic and job characteristics and HCW perceptions as predictors. Results: The average proportion of HCWs reporting moderate anxiety, moderately severe depression, and job burnout across all countries were 10%, 4%, and 20%, respectively. Working longer hours than usual (Odds ratio [OR] = 1.82; 3.51), perceived high job risk (1.98; 2.22), and inadequate personal protective equipment (1.89; 2.11) were associated with increased odds of anxiety and job burnout while working night shifts was associated with increased risk of depression (3.23). Perceived good teamwork was associated with lower odds of anxiety (0.46), depression (0.43), and job burnout (0.39). Conclusion: Job burnout remains a foremost issue among HCWs. Potential opportunities to improve HCW wellness are discussed.publishedVersionPeer reviewe

Healthcare worker stress, anxiety and burnout during the COVID-19 pandemic in Singapore : A 6-month multi-centre prospective study

Aim The long-term stress, anxiety and job burnout experienced by healthcare workers (HCWs) are important to consider as the novel coronavirus disease (COVID-19) pandemic stresses healthcare systems globally. The primary objective was to examine the changes in the proportion of HCWs reporting stress, anxiety, and job burnout over six months during the peak of the pandemic in Singapore. The secondary objective was to examine the extent that objective job characteristics, HCW-perceived job factors, and HCW personal resources were associated with stress, anxiety, and job burnout. Method A sample of HCWs (doctors, nurses, allied health professionals, administrative and operations staff; N = 2744) was recruited via invitation to participate in an online survey from four tertiary hospitals. Data were gathered between March-August 2020, which included a 2-month lockdown period. HCWs completed monthly web-based self-reported assessments of stress (Perceived Stress Scale-4), anxiety (Generalized Anxiety Disorder-7), and job burnout (Physician Work Life Scale). Results The majority of the sample consisted of female HCWs (81%) and nurses (60%). Using random-intercept logistic regression models, elevated perceived stress, anxiety and job burnout were reported by 33%, 13%, and 24% of the overall sample at baseline respectively. The proportion of HCWs reporting stress and job burnout increased by approximately 1·0% and 1·2% respectively per month. Anxiety did not significantly increase. Working long hours was associated with higher odds, while teamwork and feeling appreciated at work were associated with lower odds, of stress, anxiety, and job burnout. Conclusions Perceived stress and job burnout showed a mild increase over six months, even after exiting the lockdown. Teamwork and feeling appreciated at work were protective and are targets for developing organizational interventions to mitigate expected poor outcomes among frontline HCWs.publishedVersionPeer reviewe