Association between alcohol consumption and impaired work performance (presenteeism): a systematic review
Bibliographic record
Abstract
Objectives The aim of this review was to explore the notion of alcohol-related presenteeism; that is, whether evidence in the research literature supports an association between employee alcohol consumption and impaired work performance. Design Systematic review of observational studies. Data sources MEDLINE, Web of Science, PsycINFO, CINAHL, AMED, Embase and Swemed+ were searched through October 2018. Reference lists in included studies were hand searched for potential relevant studies. Eligibility criteria We included observational studies, published 1990 or later as full-text empirical articles in peer-reviewed journals in English or a Scandinavian language, containing one or more statistical tests regarding a relationship between a measure of alcohol consumption and a measure of work performance. Data extraction and synthesis Two independent reviewers extracted data. Tested associations between alcohol consumption and work performance within the included studies were quality assessed and analysed with frequency tables, cross-tabulations and χ 2 tests of independence. Results Twenty-six studies were included, containing 132 tested associations. The vast majority of associations (77%) indicated that higher levels of alcohol consumption were associated with higher levels of impaired work performance, and these positive associations were considerably more likely than negative associations to be statistically significant (OR=14.00, phi= 0.37, p<0.001). Alcohol exposure measured by hangover episodes and composite instruments were over-represented among significant positive associations of moderate and high quality (15 of 17 associations). Overall, 61% of the associations were characterised by low quality. Conclusions Evidence does provide some support for the notion of alcohol-related presenteeism. However, due to low research quality and lack of longitudinal designs, evidence should be characterised as somewhat inconclusive. More robust and less heterogeneous research is warranted. This review, however, does provide support for targeting alcohol consumption within the frame of workplace interventions aimed at improving employee health and productivity. PROSPERO registration number CRD42017059620.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.012 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".