Influencing Health Beliefs and sedentary Behaviours in Working Adults: A Video-Based Intervention Study
Bibliographic record
Abstract
Adults working in academic occupations are at risk for exposure to sedentary behaviours. The aim of this study was to determine the influence of an educational video on viewerâs health beliefs and sedentary behaviours. Data was collected between March and April 2017 from healthy adults employed in an academic institution in Ontario, Canada (n=71; age= 40.0±12.1 y) using a single-group, pre-post design. Evidence-based strategies to reduce sedentary behaviour at home and at work were summarized and presented as cues to action in a 5-minute video. Self-reported physical activity, sedentary behaviours, health beliefs, and readiness to change were measured using the International Physical Activity Questionnaire, Sedentary behaviour Health Belief Questionnaire, and Readiness Ruler, respectively, one week before (T1), immediately after (T2), and one week after watching the video (T3). Occupational and leisure-time sitting time was assessed daily via participant log. Participants reduced weekday and weekend sitting time by-35.9 minutes/day (p=0.03) and-21.1 minutes/day (p=0.01), respectively. Readiness to change increased between T2 and T3 (p=0.004). Perceived severity of (p=0.03) and susceptibility to (p=0.01) the health risks associated with sedentary behaviour increased from T1 to T2. Perceived benefit scores (rs=-0.25, p=0.04) at T2 were inversely associated with reductions in sitting time from T2 to T3. It is possible that exposure to the video influenced several health benefits constructs and reduced daily sitting time in healthy adults working in academic occupations.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".