Environmental, behavioural and multicomponent interventions to reduce adults' sitting time: a systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVE: To examine the overall effectiveness of interventions for reducing adult sedentary behaviour and to directly compare environmental, behavioural and multicomponent interventions. DESIGN: Intervention systematic review with meta-analysis. DATA SOURCES: Ovid PsycINFO, Ovid MEDLINE, EBSCOHost CINAHL, EBSCOHost SPORTDiscus and PubMed were searched from inception to 26 July 2017. ELIGIBILITY CRITERIA: Trials including randomised controlled trials, quasi-randomised, cluster-randomised, parallel group, prepost, factorial and crossover trials where the primary aim was to change the sedentary behaviour of healthy adults assessed by self-report (eg, questionnaires, logs) or objective measures (eg, accelerometry). RESULTS: Thirty-eight trials of 5983 participants published between 2003 and 2017 were included in the qualitative synthesis; 35 studies were included in the quantitative analysis (meta-analysis). The pooled effect was a significant reduction in daily sitting time of -30.37 min/day (95% CI -40.86 to -19.89) favouring the intervention group. Reductions in sitting time were similar between workplace (-29.96 min/day; 95% CI -44.05 to -15.87) and other settings (-30.47 min/day; 95% CI -44.68 to -16.26), which included community, domestic and recreational environments. Environmental interventions had the largest reduction in daily sitting time (-40.59 min/day; 95% CI -61.65 to -19.53), followed by multicomponent (-35.53 min/day; 95% CI -57.27 to -13.79) and behavioural (-23.87 min/day; 95% CI -37.24 to -10.49) interventions. CONCLUSION: Interventions targeting adult sedentary behaviour reduced daily sitting time by an average of 30 min/day, which was likely clinically meaningful.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.011 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".