The effect of health messaging on sedentary behaviour risk perceptions: Does immediacy of risk matter?
Bibliographic record
Abstract
The past decade has seen increasing research on sedentary behaviour (SB) reduction, such as environmental interventions, wearable technology, and policy. However, there is little evidence to suggest that these resource-intensive interventions produce clinically-significant changes in behaviour. One potential explanation for this limitation is a poor understanding of sedentary psychology (Biddle, 2011), including individuals' perceptions of SB as a health risk. For instance, whereas empirical work tends to emphasise SB's relationship with chronic disease (e.g., Tremblay et al, 2010), early research suggests individuals associate SB with musculoskeletal pain, poor fitness, and negative emotions (Gierc & Brawley, 2014; Gilson et al, 2011). The purpose of this study was to examine two questions. First, can a simple health education message about SB risk affect individuals' perceptions of SB? Second, does the type of risk information presented matter? Participants (N=175) completed an online questionnaire. After obtaining baseline beliefs and knowledge of SB, they were randomised to receive one of three messages: control, proximal risk, or distal risk. Messages were followed by scaled items on perceptions of SB (e.g., I think SB is a health risk to me). Analysis indicated no between-group differences in message readability or quality, p>0.05. Significant differences were observed between participants who received risk information (proximal/distal) versus those randomised to the control, ?=0.874, F(8,154)=2.764, p 0.05. Collectively, results suggest that the receipt of any information regarding the health risks of SB may be an effective way to increase risk perceptions about prolonged sitting.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".