Sick leave or work sick? Examining the antecedents and conceptualizations of presenteeism and absenteeism among teleworkers during COVID-19: A scoping review
Bibliographic record
Abstract
Many organizations have shifted to hybrid or remote work arrangements in response to the COVID-19 pandemic. Illness, whether physical or psychological, can manifest during telework (remote or home-based work), leading to presenteeism and absenteeism behaviour. However, varying definitions of presenteeism and absenteeism have made measuring presenteeism, absenteeism, and their antecedents increasingly challenging. This scoping study seeks to define presenteeism and absenteeism in the (tele)workplace and systematically identify the factors contributing to their occurrence. A systematic literature search was performed on seven online databases: MEDLINE, CINAHL, PsycINFO, ABI Inform Global, SCOPUS, Web of Science and Business Source Premier. We applied the PRISMA-ScR guidelines and Joanna Briggs Institute framework to systematically collect, identify, and report studies. The inclusion criteria encompassed studies with participants aged 18 to 65 years old who currently work in a telework environment for at least 50% of their work hours. Of 826 initially identified studies, 18 studies were included after screening (11 quantitative, three qualitative and two mixed-methods studies). A total of 26,805 workers were included in this review across 16 empirical studies. Overall, presenteeism is defined as working while ill, and absenteeism is known as being absent from work or taking sick leave. We identified three major categories for the antecedents of presenteeism and absenteeism behaviour: organizational (i.e., job demand and telework), environmental (i.e., work and home environment), and individual (i.e., poor mental health and job perception). Presenteeism and absenteeism among teleworkers manifest from organizational, environmental, and individual forces that lead to working while sick, or being absent from work, respectively. We found that each of these antecedents relates to one another through the social determinants of health framework. Our conceptual findings guide developing top-down organizational policies and strategies that address presenteeism and absenteeism behaviour, particularly in telework 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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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".