Exploring Multilevel Workplace Tobacco Control Interventions: A Scoping Review
Bibliographic record
Abstract
BACKGROUND: The workplace provides a unique opportunity to intervene on tobacco use, by implementing multilevel interventions engaging diverse employees. Using the social ecological model (SEM), this scoping review aimed to synthesize descriptions of multilevel workplace tobacco control programs to create a health equity informed framework for intervention planning. METHODS: Multiple databases were searched for articles published from January 2010 to December 2020 meeting inclusion criteria (i.e., discussed multilevel tobacco cessation interventions that intervene, target, or incorporate two or more levels of influence, and one of the levels must be the workplace). Articles were screened by two independent researchers and included if they discussed multilevel tobacco cessation interventions that intervened, targeted, or incorporated two or more levels of influence. To integrate the extracted information into the SEM, we utilized the McLeroy et al. model and definitions to describe potential multilevel interventions and their determinants. RESULTS: Nine articles were included in this review. No studies intervened across all five levels (individual, interpersonal, institutional, community, and policy), and the most common levels of intervention were individual (e.g., individual counseling), interpersonal (e.g., group therapy), and institutional (e.g., interventions during work hours). Participation rates varied by key social determinants of health (SDOHs) such as age, gender, education and income. Barriers including cost and sustainability influenced successful implementation, while leadership endorsement and accessibility facilitated successful implementation. DISCUSSION/APPLICATION TO PRACTICE: Multilevel interventions targeting at least two SEM levels may reduce persistent health inequities if they address how SDOHs influence individual health behaviors. Employee characteristics impacted the success of tobacco cessation interventions, but more research is needed to understand the barriers and facilitators related to workplace characteristics.
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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 | 0.026 | 0.096 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.024 | 0.021 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".