Sedentary behaviour: theory-based interventions and measurement considerations in high-risk populations
Bibliographic record
Abstract
High amounts of total and prolonged sedentary behaviour (SB) are detrimental to both short and long-term health. SB describes any waking behaviour performed in a seated, lying, or reclining posture at a low energy expenditure. While the average Canadian spends over 9.5 hours sedentary per day, high-risk populations such as university students and office workers report up to 14 hours per day. Interventions targeting these at-risk populations are needed. This dissertation aimed to build and contribute to the knowledge surrounding theory-based interventions and measurement amongst these high-risk populations. First, in a randomized controlled trial (study 1), we evaluated the effectiveness of a Health Action Process Approach (HAPA) based intervention, augmented with text messages to reduce student- related sitting, and showed a significant reduction in student-related sitting time for the intervention group compared to the controls. Next, in response to the COVID-19 pandemic, many office working adults were quickly transitioned from working in-office to working from home. Since this population has been shown to be at an even higher risk for more sedentary time, we took immediate action. Building from study 1, study 2 investigated whether augmenting the HAPA intervention with choice architecture principles grounded in behavior economics (i.e., the ability to choose or not) will affect SB break frequency (BF) in adults working from home. Interestingly, results measured with a device versus self-report were different. With the device, BF improved over the intervention period, but was no different between choice vs. nonchoice groups. With self-report, the group that was able to choose demonstrated more favourable BF patterns compared to the group that did not get to choose. Finally, since working from home has become a permanent switch for most, it is imperative to validate an appropriate self-report measure to assess sitting patterns in this setting. Thus, studies 3A and 3B are secondary analyses of the data in study 2 and aimed to validate the occupational sitting and physical activity questionnaire (OSPAQ-study 3A) and the modified 7-day Sit questionnaire (SITQ-7d-study 3B) against an activPAL4TM in full-time home-based ‘office’ workers, respectively. The findings suggest that the OSPAQ is an easily administered and valid questionnaire to measure group level total sitting while the SITQ-7d requires further validation before confidently recommending this self-report tool for assessing BF. Implications of these intervention and measurement studies are discussed.
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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 | 0.090 | 0.106 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".