Health Care Professionals' Perception of Stress During COVID-19 Pandemic in Iran: A Qualitative Study

Stress and burnout in the context of workplace psychosocial factors among mental health professionals during the later waves of the COVID-19 pandemic in Hungary

Background

While literature is abundant on the negative mental health impact of the COVID-19 outbreak, few studies focus on the Central and Eastern European region.

Objectives

We examined stress, burnout, and sleeping troubles among mental health professionals in the context of psychosocial risk factors related to participation in COVID care during the fourth and fifth waves.

Materials and methods

Mental health professionals (N=268) completed an online cross-sectional survey in Hungary, between November 2021 and April 2022. Of the respondents, 58.2% directly participated in COVID care. The main data collection instrument was the Copenhagen Psychosocial Questionnaire (COPSOQ II), including 20 subscales on work-related psychosocial factors and 3 outcome scales (stress, burnout, and sleeping troubles). We added a question on competence transgression, and items on sociodemographic and professional background.

Results

Participation in COVID care was associated with higher work pace (59.08 versus 49.78), more role conflicts (55.21 versus 45.93), lower scores on the influence at work (38.18 versus 51.79), predictability (44.71 versus 57.03), reward (55.82 versus 65.03), role clarity (70.19 versus 75.37), social support from supervisor (59.24 versus 65.55), job satisfaction (54.36 versus 62.84), trust regarding management (55.89 versus 67.86), justice and respect (44.51 versus 54.35) scales. Among those involved in COVID care, only the stress score was higher (47.96 vs. 42.35) in the total sample; however, among psychiatrists, both stress (52.16 vs. 38.60) and burnout scores (58.30 vs. 47.06) were higher. Stepwise multiple regression revealed that work-family conflict, emotional demands and workplace commitment were independent predictors of higher stress and burnout scores; furthermore, competence transgression had a significant effect on stress, and being a psychiatric specialist had a significant effect on burnout. These models explained 40.5% of the variance for stress and 39.8% for burnout.

Conclusion

During the fourth and fifth waves, although COVID care was more well-organized, psychiatrists, as specialist physicians responsible for the quality of the care, were still experiencing challenges regarding their competence and influence at work, which may explain their increased levels of stress and burnout.

Impacts for health and care workers of Covid-19 and other public health emergencies of international concern: living systematic review, meta-analysis and policy recommendations

BACKGROUND

Health and care workers (HCW) faced the double burden of the SARS-CoV-2 pandemic: as members of a society affected by a public health emergency and as HWC who experienced fear of becoming infected and of infecting others, stigma, violence, increased workloads, changes in scope of practice, among others. To understand the short and long-term impacts in terms of the COVID-19 pandemic and other public health emergencies of international concern (PHEICs) on HCW and relevant interventions to address them, we designed and conducted a living systematic review (LSR).

METHODS

We reviewed literature retrieved from MEDLINE-PubMed, Embase, SCOPUS, LILACS, the World Health Organization COVID-19 database, the ClinicalTrials.org and the ILO database, published from January 2000 until December 2021. We included quantitative observational studies, experimental studies, quasi-experimental, mixed methods or qualitative studies; addressing mental, physical health and well-being and quality of life. The review targeted HCW; and interventions and exposures, implemented during the COVID-19 pandemic or other PHEICs. To assess the risk of bias of included studies, we used the Johanna Briggs Institute (JBI) Critical Appraisal Tools. Data were qualitatively synthetized using meta-aggregation and meta-analysis was performed to estimate pooled prevalence of some of the outcomes.

RESULTS

The 1013 studies included in the review were mainly quantitative research, cross-sectional, with medium risk of bias/quality, addressing at least one of the following: mental health issue, violence, physical health and well-being, and quality of life. Additionally, interventions to address short- and long-term impact of PHEICs on HCW included in the review, although scarce, were mainly behavioral and individual oriented, aimed at improving mental health through the development of individual interventions. A lack of interventions addressing organizational or systemic bottlenecks was noted.

DISCUSSION

PHEICs impacted the mental and physical health of HCW with the greatest toll on mental health. The impact PHEICs are intricate and complex. The review revealed the consequences for health and care service delivery, with increased unplanned absenteeism, service disruption and occupation turnover that subvert the capacity to answer to the PHEICs, specifically challenging the resilience of health systems.

Suicidal ideation, burnout, and their correlation among health care workers at the end of the fourth wave of the COVID-19 pandemic in Alborz Province, Iran

Background

During the COVID-19 pandemic, Health Care Workers (HCWs) were more vulnerable than ever to Burnout and Suicidal thoughts due to stressful work conditions. This study, investigated the level of Burnout and Suicidal thoughts among HCWs during the fourth wave of the pandemic in Alborz Province in Iran and compared it with the conditions at the beginning of the pandemic.

Methods

A total of 305 HCWs from 3 referral hospitals for COVID-19, including 155 men and 150 women, participated in the study. A cross-sectional study was carried out with a sample of HCWs dealing with COVID-19 patients using the available sampling method. The results of this online survey, which was conducted from June 7 to July 5, 2021 (at the end of the Fourth Wave of the COVID-19 Pandemic in Iran), have been compared with the conditions of the First Wave of the Pandemic (from February 24 to April 27, 2020). The participants were evaluated by the Beck Scale for Suicidal Ideations (BSSI) and Maslach Burnout Inventory (MBI).

Results

The mean age of the participants was 36.34 ± 7.37. The means of Suicide Index (SI), Emotional Exhaustion (EE), Depersonalization (DP), and Personal Accomplishment (PA) scores were 0.76 ± 1.74, 19.94 ± 4.69, 4.92 ± 1.51, and 31.30 ± 5.88, respectively. SI and PA were significantly higher in workers other than nurses and physicians and EE was higher among workers with night shifts (p value<0.05 in all indices). Age had a significant and negative correlation with EE (p value<0.01) and DP (p value<0.05) and a significant and positive correlation with PA (p value<0.01).

Conclusion

This study showed a high level of SI and Burnout indices among HCWs in the fourth wave of the pandemic in Iran. Paying attention to the factors affecting the development of social capital and creating health policy changes may be effective in reducing Burnout indices and high Suicide index among HCWs.

Breath-centered virtual mind-body medicine reduces COVID-related stress in women healthcare workers of the Regional Integrated Support for Education in Northern Ireland: a single group study

Background

During the COVID-19 pandemic, healthcare workers endured prolonged stress affecting their psychological well-being. Objectives: (1) Evaluate the effects of the Breath-Body-Mind Introductory Course (BBMIC) on COVID-related stress among employees of the Regional Integrated Support for Education, Northern Ireland, (2) Reduce the risk of adverse effects from COVID-related stress, and (3) Evaluate the effects of BBMIC on indicators of psychophysiological states and the consistency with hypothesized mechanisms of action.

Methods

In this single group study, a convenience sample of 39 female healthcare workers completed informed consent and baseline measures: Perceived Stress Scale (PSS), Stress Overload Scale-Short (SOS-S), and Exercise-Induced Feelings Inventory (EFI). Following the online BBMIC 4 h/day for 3 days and the 6 week solo (20 min/day) and group practice (45 min weekly), repeat testing plus the Indicators of Psychophysiological State (IPSS) and Program Evaluation were obtained.

Results

Baseline (T1) mean PSS score was significantly elevated compared to a normative sample: PSS = 18.2 vs. 13.7 (p < 0.001) and improved significantly 11 weeks post-BBMIC (T4). SOS-S mean score declined from 10.7(T1) to 9.7 at 6 week post-test (T3). The SOS-S proportion of High Risk scores found in 22/29 participants (T1), dropped to 7/29 (T3). EFI mean subscale scores improved significantly from T1 to T2 and T3 for Revitalization (p < 0.001); Exhaustion (p < 0.002); and Tranquility (p < 0.001); but not Engagement (p < 0.289).

Conclusion

Among RISE NI healthcare workers affected by COVID-related stress, participation in the BBMIC significantly reduced scores for Perceived Stress, Stress Overload, and Exhaustion. EFI Revitalization and Tranquility scores significantly improved. More than 60% of participants reported moderate to very strong improvements in 22 indicators of psychophysiological state, e.g., tension, mood, sleep, mental focus, anger, connectedness, awareness, hopefulness, and empathy. These results are consistent with the hypothesized mechanisms of action whereby voluntarily regulated breathing exercises change interoceptive messaging to brain regulatory networks that shift psychophysiological states of distress and defense to states of calmness and connection. These positive findings warrant validation in larger, controlled studies to extend the understanding of how breath-centered Mind-body Medicine practices could mitigate adverse effects of stress.

Mental Health Status of Healthcare Workers During the Coronavirus Disease 2019 Pandemic: A Survey of Hospitals in Shiraz, Iran

BACKGROUND

Healthcare workers (HCWs) directly or indirectly involved in the coronavirus disease 2019 (COVID-19) treatment process may experience severe mental consequences of the pandemic. Hence, this study aimed to evaluate the mental health status of HCWs in hospitals affiliated with Shiraz University of Medical Sciences, Iran.

MATERIALS AND METHODS

This cross-sectional study was performed on 503 HCWs from five hospitals in Shiraz, including one COVID-19 front-line hospital, two COVID-19 second-line hospitals, and two without COVID-19 wards. Then, to assess the levels of anxiety, depression, insomnia, and post-traumatic stress disorder (PTSD) among HCWs, the Persian versions of the Hospital Anxiety and Depression Scale (HADS), Insomnia Severity Index (ISI), and Global Psychotrauma Screen (GPS) questionnaires were placed, respectively.

RESULTS

The mean age of participants was 33.94±8.26 years, and 252 (50.1%) were females. Anxiety, depression, insomnia, and moderate to high levels of PTSD were observed in 40.4%, 37.8%, 24.5%, and 71% of participants, respectively. A history of mental disorders was associated with all four outcomes (P0.05). Females gender and living with elderly and/or children were correlated with anxiety and PTSD (P0.05). Working at COVID-19 front- and second-line hospitals were similarly linked to higher insomnia and PTSD levels (P0.05). Also, working in COVID-19 wards or non-clinical settings was associated with anxiety and depression (P0.05).

CONCLUSION

Most of the HCWs in this study may experience mental difficulties. Some factors may increase their risk of experiencing these difficulties. Hence, in the crisis era, mental health monitoring and identification of groups with predisposing factors are required to provide appropriate care as quickly as feasible.

Increased anxiety and stress-related visits to the Shanghai psychiatric emergency department during the COVID-19 pandemic in 2020 compared to 2018-2019

Background

The coronavirus disease 2019 (COVID-19) pandemic has had a significant and far-reaching impact on mental health. The psychiatric emergency department (PED) is pivotal in the management of acute and severe mental illnesses, especially anxiety-and stress-related disorders.

Aims

This study aimed to evaluate whether changes in the frequency or patients' demographics of visiting the PED occurred during the COVID-19 pandemic among individuals with anxiety and stress-related disorders.

Methods

This cross-sectional study used data on PED visit counts from the largest psychiatric hospital in China between 2018 and 2020 (before and during the COVID-19 pandemic). Data from 2020, representing the COVID-19 pandemic period, were extracted from electronic medical records and compared using descriptive statistics for the same periods in 2018 and 2019.

Results

The number of PED visits related to anxiety and stress disorders per year increased from 83 in 2018 to 136 (63.9% increase) in 2019 and 239 (188.0% increase) in 2020. Compared to that in 2018 and 2019, the proportion of PED visits in 2020 among patients with anxiety and stress disorders increased significantly. Patients with anxiety-and stress-related disorders during PED visits in 2020 were younger than those in 2018 and 2019 (three-year groups: F = 9.124, df = 2, p < 0.001).

Conclusion

Despite the epidemic-policy barriers against PED visits, PED care seeking has increased, thereby underscoring the need for crisis prevention services for patients with stress and anxiety disorders.

Usability of the IDDEAS prototype in child and adolescent mental health services: A qualitative study for clinical decision support system development

INTRODUCTION

Child and adolescent mental health services (CAMHS) clinical decision support system (CDSS) provides clinicians with real-time support as they assess and treat patients. CDSS can integrate diverse clinical data for identifying child and adolescent mental health needs earlier and more comprehensively. Individualized Digital Decision Assist System (IDDEAS) has the potential to improve quality of care with enhanced efficiency and effectiveness.

METHODS

We examined IDDEAS usability and functionality in a prototype for attention deficit hyperactivity disorder (ADHD), using a user-centered design process and qualitative methods with child and adolescent psychiatrists and clinical psychologists. Participants were recruited from Norwegian CAMHS and were randomly assigned patient case vignettes for clinical evaluation, with and without IDDEAS. Semi-structured interviews were conducted as one part of testing the usability of the prototype following a five-question interview guide. All interviews were recorded, transcribed, and analyzed following qualitative content analysis.

RESULTS

Participants were the first 20 individuals from the larger IDDEAS prototype usability study. Seven participants explicitly stated a need for integration with the patient electronic health record system. Three participants commended the step-by-step guidance as potentially helpful for novice clinicians. One participant did not like the aesthetics of the IDDEAS at this stage. All participants were pleased about the display of the patient information along with guidelines and suggested that wider guideline coverage will make IDDEAS much more useful. Overall, participants emphasized the importance of maintaining the clinician as the decision-maker in the clinical process, and the overall potential utility of IDDEAS within Norwegian CAMHS.

CONCLUSION

Child and adolescent mental health services psychiatrists and psychologists expressed strong support for the IDDEAS clinical decision support system if better integrated in daily workflow. Further usability assessments and identification of additional IDDEAS requirements are necessary. A fully functioning, integrated version of IDDEAS has the potential to be an important support for clinicians in the early identification of risks for youth mental disorders and contribute to improved assessment and treatment of children and adolescents.

An investigation of the incidence of post-traumatic stress disorder, turnover intention and psychological resilience among medical staff in a public hospital in China during the outbreak of the omicron variant in the COVID-19 pandemic in 2022

OBJECTIVE

To investigate the incidence of post-traumatic stress disorder (PTSD), turnover intention and psychological resilience of medical staff during the Outbreak of the Omicron Variant in the COVID-19 pandemic in 2022 and to provide a basis for adopting relevant psychological interventions to reduce medical staff turnover.

METHODS

Using the PTSD Checklist-Civilian Version (PCL-C) and a total score ranging from 17 to 85 points, a total score ≥ 38 indicates significant PTSD symptoms and a diagnosis of PTSD. The Chinese version of the Turnover Intention Scale (TIS) has a total score of 6 to 24 points; the higher the score, the stronger the turnover intention. The Chinese version of the Connor-Davidson Resilience Scale (CD-RISC) has a total score of 0 to 100 points, with higher scores indicating a better level of psychological resilience. A total of 443 front-line medical staff working in Chinese public hospitals and still treating all patients normally during COVID-19 were invited via the internet to complete a survey from 15 May to 30 May 2022 in China.

RESULTS

The incidence of PTSD was 14.4%, the total turnover intention score was 13.38 ± 4.08, and the total psychological resilience score was 87.16 ± 18.42. The prevalence of PTSD was higher among medical staff who were married, had children, and were worried about being infected; in addition, the PTSD group had a higher level of education, higher turnover intention, and lower psychological resilience than the non-PTSD group. The total scores for turnover intention and fear of being infected were risk factors for PTSD, while a high total psychological resilience score and high education level were protective factors for PTSD; the differences were statistically significant (all P < 0.05).

CONCLUSION

Post-traumatic stress disorder among Chinese medical personnel was associated with the marital status, childbirth, education level, turnover intention, and psychological resilience. Among these factors, psychological resilience might be exploited as a protective factor.

Machine Learning-Based Prediction Models for Depression Symptoms Among Chinese Healthcare Workers During the Early COVID-19 Outbreak in 2020: A Cross-Sectional Study

BACKGROUND

The 2019 novel coronavirus (COVID-19)-related depression symptoms of healthcare workers have received worldwide recognition. Although many studies identified risk exposures associated with depression symptoms among healthcare workers, few have focused on a predictive model using machine learning methods. As a society, governments, and organizations are concerned about the need for immediate interventions and alert systems for healthcare workers who are mentally at-risk. This study aims to develop and validate machine learning-based models for predicting depression symptoms using survey data collected during the COVID-19 outbreak in China.

METHOD

Surveys were conducted of 2,574 healthcare workers in hospitals designated to care for COVID-19 patients between 20 January and 11 February 2020. The patient health questionnaire (PHQ)-9 was used to measure the depression symptoms and quantify the severity, a score of ≥5 on the PHQ-9 represented depression symptoms positive, respectively. Four machine learning approaches were trained (75% of data) and tested (25% of data). Cross-validation with 100 repetitions was applied to the training dataset for hyperparameter tuning. Finally, all models were compared to evaluate their predictive performances and screening utility: decision tree, logistics regression with least absolute shrinkage and selection operator (LASSO), random forest, and gradient-boosting tree.

RESULTS

Important risk predictors identified and ranked by the machine learning models were highly consistent: self-perceived health status factors always occupied the top five most important predictors, followed by worried about infection, working on the frontline, a very high level of uncertainty, having received any form of psychological support material and having COVID-19-like symptoms. The area under the curve [95% CI] of machine learning models were as follows: LASSO model, 0.824 [0.792-0.856]; random forest, 0.828 [0.797-0.859]; gradient-boosting tree, 0.829 [0.798-0.861]; and decision tree, 0.785 [0.752-0.819]. The calibration plot indicated that the LASSO model, random forest, and gradient-boosting tree fit the data well. Decision curve analysis showed that all models obtained net benefits for predicting depression symptoms.

CONCLUSIONS

This study shows that machine learning prediction models are suitable for making predictions about mentally at-risk healthcare workers predictions in a public health emergency setting. The application of multidimensional machine learning models could support hospitals' and healthcare workers' decision-making on possible psychological interventions and proper mental health management.