The Effect ofa Web-based Physical Activity Promotion Program on Sedentary Behavior
Bibliographic record
Abstract
Time spent engaging in sedentary behavior represents a growing public health concern, with many national physical activity guidelines now also including recommendations on reducing sedentary time. Sedentary behavior contributes to a range of poor health outcomes. Web-based interventions are increasingly used in health promotion given their broad reach and ability to engage participants through Web 2.0 technologies. The WALK 2.0 intervention (a Web 2.0-based physical activity intervention) has demonstrated effectiveness in increasing physical activity, yet its impact on sedentary behaviour is unknown. PURPOSE: To investigate the effectiveness of the WALK 2.0 intervention on sedentary behaviour. METHODS: Participants were 504 (328 female and 176 male, mean age 50.8±13.1 years) adults randomised to one of two web-based interventions or a paper-based Logbook group. Those in the Web 1.0 group participated in the existing 10,000 Steps program and those in the Web 2.0 group participated in a Web 2.0-enabled physical activity intervention that included social networking capabilities. Sedentary behaviour was assessed using ActiGraph GT3X activity monitors and was recorded in terms of total minutes of sedentary time per day and number of bouts (> 10 minutes) of sedentary time per day. RESULTS: For total daily minutes of sedentary behaviour, repeated measures analysis showed no significant group x time interactions in either the unadjusted model (p=0.46) or the model adjusted for gender, age at baseline, BMI, education, and accelerometer wear time (p=0.58). No significant group x time interactions were shown for daily bouts of sedentary time in either the unadjusted (p=0.21) or adjusted (p=0.21) models. There were no significant changes in total minutes or number of bouts of sedentary behaviour within groups or across time. CONCLUSIONS: The WALK 2.0 intervention is not effective in reducing sedentary behavior. Specific behavior strategies targeting both sedentary behaviour and physical activity are necessary and their implementation requires careful consideration in the design phase.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".