The Effect of an Acute Sedentary Behaviour Reducing Intervention on Subjective Well-Being among University Students: A Pilot Randomized Trial
Bibliographic record
Abstract
Background: The effect of sedentary behaviour (SB) on subjective well-being (SWB), particularly through a SB-reducing intervention largely remains unknown. This pilot trial examined whether an acute intervention designed to reduce SB would enhance SWB in a sample of university students.Methods: A three-week (i.e., baseline, intervention, follow-up) randomized controlled pilot trial was conducted. Thirty-two sedentary university students were randomized to an acute behavioural counseling intervention (n = 17) or control group (n = 15). Behavioural counseling grounded in the health action process approach aimed at reducing daily SB for 1 week. Device-measured outcomes (i.e., steps, standing, sitting, sit-to-stand transitions), self-reported SBs (i.e., self-compared, domain-specific), and SWB measures (i.e., affect, life satisfaction, subjective vitality, overall SWB) were assessed weekly.Results: Repeated-measures ANOVAs revealed non-significant medium-to-large effects for self-reported SBs (i.e., 0.116 ≤ ηp2 ≤ 0.253), device-measured standing time (i.e., ηp2 = 0.161), and life satisfaction and overall SWB (i.e., 0.141 ≤ ηp2 ≤ 0.178) favouring the treatment group over the control group.Conclusions: Overall, this acute intervention was ineffective in reducing SB among university students. Comparatived to previous acute SB-inducing interventions, results suggest that SB-reducing interventions may require more robust treatment application than the current pilot study. Strategies such as prompts/cues, repeated intervention delivery, and longer intervention periods are recommended. Strategies that promote larger non-convenient sampling (e.g., longer recruitment periods) also are recommended. Taken together, these strategies will increase treatment effects and statistical power of subsequent intervention trials.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".