Going to work ill: A meta-analysis of the correlates of presenteeism and a dual-path model.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Interest in presenteeism, attending work while ill, has flourished in light of its consequences for individual well-being and organizational productivity. Our goal was to identify its most significant causes and correlates by quantitatively summarizing the extant research. Additionally, we built an empirical model of some key correlates and compared the etiology of presenteeism versus absenteeism. We used meta-analysis (in total, K = 109 samples, N = 175,965) to investigate the correlates of presenteeism and meta-analytic structural equation modeling to test the empirical model. Salient correlates of working while ill included general ill health, constraints on absenteeism (e.g., strict absence policies, job insecurity), elevated job demands and felt stress, lack of job and personal resources (e.g., low support and low optimism), negative relational experiences (e.g., perceived discrimination), and positive attitudes (satisfaction, engagement, and commitment). Moreover, our dual process model clarified how job demands and job and personal resources elicit presenteeism via both health impairment and motivational paths, and they explained more variation in presenteeism than absenteeism. The study sheds light on the controversial act of presenteeism, uncovering both positive and negative underlying mechanisms. The greater variance explained in presenteeism as opposed to absenteeism underlines the opportunities for researchers to meaningfully investigate the behavior and for organizations to manage it. (PsycINFO Database Record
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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 | 0.008 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 it