Impact of the COVID-19 Pandemic on Health, Well-being, and Quality of Work-Life Outcomes Among Direct Care Nursing Staff Working in Nursing Home Settings: Protocol for a Systematic Review
Bibliographic record
Abstract
BACKGROUND: Increased workload, lack of resources, fear of infection, and the suffering and loss of residents have placed a significant emotional burden on regulated and unregulated direct care nursing staff (eg, registered nurses, licensed practical nurses, and care aides) in nursing homes (residential long-term care homes). Psychological distress and burnout related to COVID-19 have been cited among direct care staff within nursing homes. Studies have also emphasized the resilience of direct care staff, who, despite the significant challenges created by the pandemic, remained committed to providing quality care. To date, only one nursing home-specific review has synthesized evidence from 15 studies conducted early in the pandemic, which reported anxiety, posttraumatic stress disorder, and depression among direct care staff. OBJECTIVE: The objectives of this systematic review are to (1) synthesize all empirical evidence on the impact of the COVID-19 pandemic on direct care staffs' mental health, physical health, and work-life outcomes; (2) identify specific risks and protective factors; and (3) examine the effect of strategies or interventions that have been developed to improve these outcomes. METHODS: We will include all study designs reporting objective or subjective measurements of direct care staffs' mental health, physical health, and quality of work-life in nursing home settings during the COVID-19 pandemic (January 2020 onward). We will search multiple databases (MEDLINE, CINAHL, Embase, Scopus, and PsycINFO) and gray literature sources with no language restrictions. Two authors will independently screen, assess data quality, and extract data for synthesis. Given the heterogeneity in research designs, we will use multiple data synthesis methods that are suitable for quantitative and qualitative studies. RESULTS: As of December 2022, full text screening has been completed and data extraction is underway. The expected completion date is June 30, 2023. CONCLUSIONS: This systematic review will uncover gaps in current knowledge, increase our understanding of the disparate findings to date, identify risks and factors that protect against the sustained effects of the pandemic, and elucidate the feasibility and effects of interventions to support the mental health, physical health, and quality of work-life of frontline nursing staff. This study will inform future research exploring how the health care system can be more proactive in improving quality of work-life and supporting the health and psychological needs of frontline staff amid extreme stressors such as the pandemic and within the wider context of prepandemic conditions. TRIAL REGISTRATION: PROSPERO CRD42021248420; https://tinyurl.com/4djk7rpm. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/40390.
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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 | 0.051 | 0.074 |
| Meta-epidemiology (narrow) | 0.006 | 0.005 |
| Meta-epidemiology (broad) | 0.024 | 0.019 |
| Bibliometrics | 0.014 | 0.012 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.041 | 0.005 |
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".