Effectiveness of Multicomponent Interventions in Office-Based Workers to Mitigate Occupational Sedentary Behavior: Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Sedentary time in workplaces has been linked to increased risks of chronic occupational diseases, obesity, and overall mortality. Currently, there is a burgeoning research interest in the implementation of multicomponent interventions aimed at decreasing sedentary time among office workers, which encompass a comprehensive amalgamation of individual, organizational, and environmental strategies. OBJECTIVE: This meta-analysis aims at evaluating the effectiveness of multicomponent interventions to mitigate occupational sedentary behavior at work compared with no intervention. METHODS: PubMed, Web of Science, EMBASE, and Cochrane Central Register of Controlled Trials (CENTRAL) databases were searched from database inception until March 2023 to obtain randomized controlled trials (RCTs) assessing the efficacy of multicomponent interventions on occupational sedentary behavior among office-based workers. Two reviewers independently extracted the data and assessed the risk of bias by using the Cochrane Collaboration's risk of bias tool. The average intervention effect on sedentary time was calculated using Stata 15.1. Mean differences (MDs) with 95% CIs were used to calculate the continuous variables. Subgroup analyses were performed to determine whether sit-stand workstation, feedback, and prompt elements played an important role in multicomponent interventions. Further, the GRADE (Grading of Recommendations, Assessment, Development, and Evaluation) system was used to evaluate the certainty of evidence. RESULTS: A total of 11 RCTs involving 1894 patients were included in the analysis. Five studies were rated as low risk of bias, 2 as unclear risk of bias, and 4 as high risk. The meta-analysis results showed that compared with no intervention, multicomponent interventions significantly reduced occupational sitting time (MD=-52.25 min/8-h workday, 95% CI -73.06 to -31.44; P<.001) and occupational prolonged sitting time (MD=-32.63 min/8-h workday, 95% CI -51.93 to -13.33; P=.001) and increased occupational standing time (MD=44.30 min/8-h workday, 95% CI 23.11-65.48; P<.001), whereas no significant differences were found in occupational stepping time (P=.06). The results of subgroup analysis showed that compared with multicomponent interventions without installment of sit-stand workstations, multicomponent interventions with sit-stand workstation installment showed better effects for reducing occupational sitting time (MD=-71.95 min/8-h workday, 95% CI -92.94 to -51.15), increasing occupational standing time (MD=66.56 min/8-h workday, 95% CI 43.45-89.67), and reducing occupational prolonged sitting time (MD=-47.05 min/8-h workday, 95% CI -73.66 to -20.43). The GRADE evidence summary showed that all 4 outcomes were rated as moderate certainty. CONCLUSIONS: Multicomponent interventions, particularly those incorporating sit-stand workstations for all participants, are effective at reducing workplace sedentary time. However, given their cost, further research is needed to understand the effectiveness of low-cost/no-cost multicomponent interventions.
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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 | 0.015 | 0.038 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.037 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".