ReviewFrontiers in public health2025
Risk factors for harmful alcohol consumption among employees and intervention strategies used in the workplace: current state of knowledge based on a literature review.
Review in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- The national and provincial disease and indirect economic burden of high alcohol use in China from 1990 to 2023 with forecasting to 2050.Military Medical Research · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Harmful alcohol consumption among employees is a significant public health problem, leading to adverse health and social outcomes, as well as impaired occupational functioning. Identifying risk factors and effective prevention strategies is crucial to address this issue in the workplace. The aim of this study was to analyze the main determinants of harmful alcohol use among employees and to assess the effectiveness of interventions in occupational settings. Methods: A literature review was conducted on studies published between 2020 and 2024. The PubMed, Scopus, and Web of Science databases were searched for international studies on workplace alcohol consumption and intervention strategies. Key risk factors, workplace interventions, and their effectiveness were analyzed. Inclusion criteria included peer-reviewed articles published in English, a focus on employees or the occupational context, and a clear analysis of risk factors or interventions addressing harmful alcohol consumption. Titles and abstracts were independently reviewed by two researchers, and any discrepancies were resolved by a third. Data on risk factors, types of interventions, target populations, and outcome measures were extracted and summarized in tables. Results: Key risk factors identified comprise high job strain, workplace-related stress, low social support, job insecurity, unfavorable organizational culture, and shift work. Harmful alcohol use was associated with increased risk of workplace accidents, absenteeism, and diminished productivity. Effective preventive approaches included the implementation of digital interventions (e.g., mobile health applications, online brief interventions), involvement of management in educational campaigns, organizational policy changes, and multi-level, sustained action plans. Interventions targeting both individual and organizational levels demonstrated the greatest potential for sustainable impact. Conclusion: Reducing harmful alcohol use in the workplace requires a comprehensive, multi-level approach tailored to organizational context and providing long-term employee support. Continued evaluation and adaptation of intervention strategies to specific workplace environments are recommended.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.