Impact of COVID-19 on mental health and health-related quality of life of humanitarian and healthcare workers in low-income countries. The case of Eastern Africa.
Bibliographic record
Abstract
BACKGROUND: The COVID-19 pandemic has had a direct impact on the health care system, adversely affecting services delivery and continuity, particularly in low-income countries. The overwhelming workload, the shortage of personal protective equipment, and the lack of specific Personal protective equipment (PPE), and drugs are some noted challenges. As a result of this critical situation, healthcare and humanitarian workers who are directly involved in the diagnosis, management, and prevention of COVID-19 are at high risk of contracting COVID-19 disease and developing psychological disorders, distress, and other mental health symptoms. OBJECTIVE: To assess the magnitude of mental health and health-related quality of life (HRQoL) outcomes and associated factors among humanitarian and healthcare workers (HCW) working on prevention and management of COVID-19 in East African Countries (EAC). DESIGN, SETTINGS, AND PARTICIPANTS: This cross-sectional, online-based survey study collected socio-demographic, mental health, and HRQoL data from 739 frontline and second-line workers in healthcare facilities and humanitarian NGOs working on COVID-19 prevention and management in seven Eastern African countries (Burundi, Kenya, Tanzania, South Sudan, Somalia, Ethiopia, and Rwanda). MAIN OUTCOMES AND MEASURES: The degree of symptoms of depression, anxiety, insomnia, and distress, alcohol, and tobacco consumption, HRQoL (SF-6Dv2 and CORE-6D), and fear of COVID-19. ANALYSIS: Multivariable logistic regression analysis, one-way ANOVA, and T-test to identify factors associated with mental health and HRQoL outcomes. RESULTS: A total of 739 contacted individuals in December 2020 completed the survey. The study participants included 62.7% of males and 37.3% of females. Among them, 12.4% were humanitarians and 87.6% were healthcare workers. About 83% were from Burundi and 17% from other Eastern African countries. The HRQoL mean scores measured by the SF-6Dv2 and the CORE-6D were respectively 0.86 and 0.80. Multivariable logistic regression analysis showed that country of origin, chronic disease, being tested positively to COVID-19, being exposed to death due to COVID-19, increased alcohol uptake, having experienced nightmare, insomnia, distress, stress, and fear of COVID-19 were independent predictors of HRQoL of front- and second-line workers. Multivariable Logistic Regression Analysis also found that having a chronic disease, being exposed to patients and death due to COVID-19 cases, depression, insomnia, stress, and fear of COVID-19 were independent predictors of the CORE-6D score. CONCLUSION: This study showed that healthcare and humanitarian workers are affected by mental health disorders such as depression, anxiety, stress, and insomnia, which negatively impacted their Health-related quality of life (HRQoL). The study findings suggested that psychological support to ensure humanitarian and healthcare worker's safety and wellbeing is required during and after this pandemic.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".