Pandemic preparedness from the perspective of Occupational Health professionals
Bibliographic record
Abstract
BACKGROUND: Prior to any infectious disease emergence as a public health concern, early occupational preparedness is crucial for protecting employees from novel pathogens- coronavirus disease 2019 (COVID-19) is no different. AIMS: This study ascertains how occupational safety and health (OSH)/Human Resource (HR) professionals in the Republic of Ireland had managed to prepare their workplaces prior to the advent of COVID-19. METHODS: As part of a larger COVID-19 workplace study, online focus groups were conducted with OSH/HR professionals. Collected data were transcribed verbatim and entered into NVivo for thematic analysis incorporating intercoder reliability testing. RESULTS: Fifteen focus groups were conducted with OSH/HR professionals (n = 60) from various occupational settings. Three levels of organizational preparedness were identified: 'early awareness and preparation'; 'unaware and not ready' and 'aware, but not ready'. Most organizations were aware of the COVID-19 severity, but not fully prepared for the pandemic, especially stand-alone enterprises that may not have sufficient resources to cope with an unanticipated crisis. The experiences shared by OSH professionals illustrate their agility in applying risk management and control skills to unanticipated public/occupational health crises that arise. CONCLUSIONS: General pandemic preparedness such as the availability of work-from-home policies, emergency scenario planning and prior experience in workplace outbreaks of infectious diseases were helpful for workplace-associated COVID-19 prevention. This is the first study conducted with OSH/HR professionals in Ireland regarding COVID-19 preparedness in workplaces, which provides valuable insights into research literature, as well as empirical experience for the preparation of future public health emergencies.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".