Employee Mental Health During COVID-19 Adaptation: Observations of Occupational Safety and Health/Human Resource Professionals in Ireland
Bibliographic record
Abstract
Objectives: This study aims to understand mental health issues among Irish employees arising from COVID-19 adaptation from the perspective of Occupational Safety and Health (OSH) and/or Human Resource (HR) professionals. Methods: Fifteen focus groups including 60 OSH/HR professionals from various sectors were conducted covering four predetermined themes. The data were transcribed verbatim, with transcripts entered into Nvivo for thematic analysis incorporating intercoder reliability testing. Results: The mental health impacts among employees are identified from three stages: pre-adaptation, during adaptation, and post-adaptation. Most issues were reported during the second stage when working conditions dramatically changed to follow emerging COVID-19 policies. The identified mental health support from participating organizations included providing timely and reliable information, Employee Assistance Programme (EAP), informal communication channels, hybrid work schedules and reinforcement of control measures. Conclusion: This study explores the challenges facing employees during the different stages of COVID-19 adaptation and the associated mental health impacts. Gender’s influence on mental health consultations should be considered when planning for public health emergencies, and further research conducted in male dominated industries.
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 | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".