Sedentary Behaviour and Diabetes Information as a Source of Motivation to Reduce Daily Sitting Time in Office Workers: A Pilot Randomised Controlled Trial
Bibliographic record
Abstract
Background Using the motivational phase of the Health Action Process Approach (HAPA), this study examined whether sedentary behaviour and diabetes information is a meaningful source of motivation to reduce daily sitting time among preintending office workers. Methods Participants ( N = 218) were randomised into HAPA‐intervention (sedentary behaviour), HAPA‐attention control (physical activity), or control (no treatment) conditions. Following treatment, purpose‐built sedentary‐related HAPA motivational constructs (risk perception, outcome expectancies, self‐efficacy) and goal intentions were assessed. Only participants who had given little thought to how much time they spent sitting (preintenders) were used in subsequent analyses (n = 96). Results Significant main effects favouring the intervention group were reported for goal intentions: to increase number and length of daily breaks from sitting at work; to reduce daily sitting time outside of work; to increase daily time spent standing outside of work, as well as for outcome expectancies ( p values ≤ .05; ɳ p 2 values ≥.08). Only self‐efficacy ( β range = 0.39–0.50) made significant and unique contributions to work and leisure‐time‐related goal intentions, explaining 11–21 per cent of the response variance. Conclusions A brief, HAPA‐based online intervention providing information regarding sedentary behaviour and diabetes risk may be an effective source of motivation.
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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 | 0.003 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".