Mental well-being of healthcare workers in 2 hospital districts during the first wave of the COVID-19 pandemic in Finland: a cross-sectional study.

OBJECTIVES: The COVID-19 pandemic has caused unseen pressure on healthcare systems in many countries, jeopardizing the mental well-being of healthcare workers. The authors aimed to assess the mental well-being of Finnish healthcare workers from 2 hospital districts (Helsinki University Hospital [HUS] and Social and Health Services in Kymenlaakso [Kymsote]) with differing COVID-19 incidence rates during the first wave of the COVID-19 pandemic in spring 2020. MATERIAL AND METHODS: A total number of 996 healthcare workers (HUS N = 862, Kymsote N = 134) participated in this prospectively conducted survey study during summer 2020. Symptom criteria of self-reported mental health symptoms followed ICD-10 classification, excluding duration criteria. Participants were divided into symptom categories "often/sometimes", and "rarely/never". These groups were compared to sociodemographic factors and factors related to work, workload, and well-being. RESULTS: The degree of mental health symptoms did not differ between the 2 healthcare districts despite differing COVID-19 incidences (p = 1). The authors observed a significant relationship between self-reported diagnostic mental health symptoms and experiences of insufficient instructions for protection against COVID-19 (in HUS cohort p < 0.001), insufficient recovery from work (p < 0.001), and subjective increased workload (p < 0.001). CONCLUSIONS: The authors' results show the importance of well-planned and sufficient instructions for protection from SARS-CoV-2 for healthcare workers, indicating their need to feel safe and protected at work. The workload of healthcare workers should be carefully monitored to keep it moderate and ensure sufficient recovery. Sufficient control of the epidemic to keep the burden of the healthcare system low is vital for healthcare workers' well-being. Int J Occup Med Environ Health. 2022;35(6):708-18.

A machine learning approach to predict resilience and sickness absence in the healthcare workforce during the COVID-19 pandemic.

During the COVID-19 pandemic, healthcare workers (HCWs) have faced unprecedented workloads and personal health risks leading to mental disorders and surges in sickness absence. Previous work has shown that interindividual differences in psychological resilience might explain why only some individuals are vulnerable to these consequences. However, no prognostic tools to predict individual HCW resilience during the pandemic have been developed. We deployed machine learning (ML) to predict psychological resilience during the pandemic. The models were trained in HCWs of the largest Finnish hospital, Helsinki University Hospital (HUS, N = 487), with a six-month follow-up, and prognostic generalizability was evaluated in two independent HCW validation samples (Social and Health Services in Kymenlaakso: Kymsote, N = 77 and the City of Helsinki, N = 322) with similar follow-ups never used for training the models. Using the most predictive items to predict future psychological resilience resulted in a balanced accuracy (BAC) of 72.7-74.3% in the HUS sample. Similar performances (BAC = 67-77%) were observed in the two independent validation samples. The models' predictions translated to a high probability of sickness absence during the pandemic. Our results provide the first evidence that ML techniques could be harnessed for the early detection of COVID-19-related distress among HCWs, thereby providing an avenue for potential targeted interventions.

Sources of healthcare workers' COVID­19 infections and related safety guidelines.

OBJECTIVES: To evaluate the effectiveness of safety guidelines in the workplace, the authors analyzed the work-related exposure to SARS-CoV-2 and the source of COVID­19 infections among healthcare workers (HCWs), together with the use of personal protective equipment (PPE). MATERIAL AND METHODS: A cross-sectional prospective study was conducted in tertiary hospitals in the Uusimaa region, Finland, with 1072 volunteers being enrolled in the study from among the HCWs at the Helsinki University Hospital. Overall, 866 (80.8%) HCWs (including 588 nurses, 170 doctors, and 108 laboratory and medical imaging nurses) completed the questionnaire by July 15, 2020, with 52% of the participants taking care of COVID­19 patients. The participants answered a structured questionnaire regarding their use of PPE, the ability to follow safety guidelines, exposure to COVID­19, and the source of potential COVID­19 infections. The participants with COVID­19 symptoms were tested with the SARS-CoV-2 realtime polymerase chain reaction method. All infected participants were contacted, and their answers were confirmed regarding COVID­19 exposure. RESULTS: In total, 41 (4.7%) participants tested positive for SARS-CoV-2, with 22 (53.6%) of infections being confirmed or likely occupational, and 12 (29.3%) originating from colleagues. In 14 cases (63.6%), occupational infections occurred while using a surgical mask, and all infections originating from patients occurred while using a surgical mask or no mask at all. No occupational infections were found while using an FFP2/3 respirator and following aerosol precautions. The combined odds ratio for working at an intensive care unit, an emergency department, or a ward was 3.4 (95% CI: 1.2-9.2, p = 0.016). CONCLUSIONS: A high infection rate was found among HCWs despite safety guidelines. Based on these findings, the authors recommend the use of FFP2/3 respirators in all patient contacts with confirmed or suspected COVID­19, along with the use of universal masking, also in personnel rooms. Int J Occup Med Environ Health. 2021;34(2):239-49.