Impacts for Health and Care Workers of Covid-19 and Other Public Health Emergencies of International Concern: Living Systematic Review, Meta-analysis & Policy Recommendations
Bibliographic record
Abstract
Abstract 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 workplace hazards, mental health, unplanned absenteeism, attrition and intention to leave the occupation, performance, violence and quality of life. The review targeted HCW, health systems, health services users and the public; 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 metaggregation and meta-analysis was performed to estimate pooled prevalence of some of the outcomes.Key Findings The 1,013 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 also included in the review 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.Conclusions 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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.072 | 0.177 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.024 |
| Bibliometrics | 0.017 | 0.013 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".