Workplace standing breaks: What can planned behaviour constructs tell us?
Bibliographic record
Abstract
In 2008, Healy and colleagues observed that office workers who frequently interrupted their sitting had better metabolic profiles than office workers who engaged in prolonged bouts of sitting. Since then, standing breaks – short bouts of physical activity – have been proposed as one solution to excessive sedentary behaviour. Despite growing interest, no research has examined the psychological predictors of standing breaks in the workplace. The purpose of our research was to investigate standing breaks via the Theory of Planned Behaviour (TPB). STUDY ONE was a qualitative elicitation study. Participants (N=95) reported beliefs regarding workplace standing breaks and sitting. Content analysis identified both individual- and workplace-centred themes, which were used to inform a TPB measure as per Ajzen's web-based guide. STUDY TWO used a prospective design in which 413 participants completed a TPB-based survey about standing breaks and sitting. Content validity of measures was demonstrated via a 3-factor solution corresponding to the TPB constructs of attitudes, social norms, and perceived behavioural control (PBC). The three factors significantly predicted intentions to engage in standing breaks, p
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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 | 0.017 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.011 |
| Scholarly communication | 0.005 | 0.011 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".