The association between sedentary behaviour and indicators of stress: a systematic review
Bibliographic record
Abstract
BACKGROUND: Emerging evidence shows sedentary behaviour may be associated with mental health outcomes. Yet, the strength of the evidence linking sedentary behaviour and stress is still unclear. This study aimed to synthesise evidence regarding associations between time spent in sedentary behaviour and stress in adults. METHODS: A systematic search was conducted (January 1990 - September 2019). Following PRISMA guidelines, an evaluation of methodological quality, and best-evidence synthesis of associations between time in sedentary behaviour (including sitting time, TV viewing, computer use) and stress were presented. Twenty-six studies reporting on data from n = 72,795 people (age 18-98y, 62.7% women) were included. RESULTS: Across the studies (n = 2 strong-, n = 10 moderate- and n = 14 weak-quality), there was insufficient evidence that overall time spent in sedentary behaviour and sitting time were associated with stress, particularly when using self-report measures of sedentary behaviour or stress. There was strong evidence of no association between TV viewing, or computer use and stress. Amongst studies using objective measures of sedentary behaviour and/or stress there was also strong evidence of no association. CONCLUSION: Although previous research suggested sedentary behaviour may be linked to mental health outcomes such as depression and anxiety, the evidence for an association between various types of sedentary behaviour and stress is limited in quality, and associations are either inconsistent or null. High-quality longitudinal/interventional research is required to confirm findings and determine the direction of associations between different contexts (i.e. purpose) and domains (i.e. leisure, occupational, transport) of sedentary behaviour and stress.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.011 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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".