Remote work transition amidst COVID-19: Impacts on presenteeism, absenteeism, and worker well-being—A scoping review
Bibliographic record
Abstract
BACKGROUND: The COVID-19 pandemic has accelerated the transition to remote work, leading to increased attention on presenteeism and absenteeism among remote workers. Understanding the implications of these phenomena on worker health and productivity is crucial for optimizing remote work arrangements and developing policies to improve employee well-being. OBJECTIVES: This scoping review aims to examine the occurrence of presenteeism and absenteeism among remote workers during the COVID-19 pandemic and the interrelated physical and mental health issues during these periods. METHODS: PsycINFO, Medline, Embase, CINAHL, Eric, Business Source Premier, SCOPUS, and sociological abstracts were searched resulting in 1792 articles. Articles were included if the population of interest was 18+ (i.e., working age), engaged in full or part-time work, and the employees shifted from in-person to remote work due to the COVID-19 pandemic. All study designs, geographical areas, and papers written post-onset of the COVID-19 pandemic were included; however, systematic reviews were excluded. Data was charted into Microsoft Excel by 2 independent reviewers. RESULTS: The literature search identified 10 studies (i.e., seven cross-sectional studies, two qualitative studies, and one observational study). Five major overarching themes were identified specifically (1) telework and mental health (2) telework and physical health (3) worker benefits (4) gender dynamics and (5) difficulty navigating the teleworking environment. While remote work offers flexibility in terms of saved commute time and flexible work schedules, it also exacerbates challenges related to presenteeism, absenteeism, and work-life balance. These challenges include experiencing psychological distress, depression, anxiety, stress, sleep deprivation, musculoskeletal pain, difficulties concentrating at work for both women and working parents, struggles disconnecting after hours, and the inability to delineate between the work and home environment. DISCUSSION: The findings suggest that remote work during the COVID-19 pandemic has both positive and negative implications for worker well-being and productivity. However, future research needs to incorporate the potential effects of telework frequency (full time vs. part time) on employee productivity and its role on presenteeism and absenteeism, to gain a more comprehensive understanding on remote work difficulties. Addressing these challenges requires proactive interventions and support mechanisms to promote worker health and productivity in remote settings.
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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) | 0.000 | 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".