WALK 2.0: Examining the effectiveness of Web 2.0 features to increase physical activity in a ‘real world’ setting: an ecological trial protocol
Bibliographic record
Abstract
INTRODUCTION: Low levels of health-enhancing physical activity require novel approaches that have the potential to reach broad populations. Web-based interventions are a popular approach for behaviour change given their wide reach and accessibility. However, challenges with participant engagement and retention reduce the long-term maintenance of behaviour change. Web 2.0 features present a new and innovative online environment supporting greater interactivity, with the potential to increase engagement and retention. In order to understand the applicability of these innovative interventions for the broader population, 'real-world' interventions implemented under 'everyday conditions' are required. The aim of this study is to investigate the difference in physical activity behaviour between individuals using a traditional Web 1.0 website with those using a novel Web 2.0 website. METHODS AND ANALYSIS: In this study we will aim to recruit 2894 participants. Participants will be recruited from individuals who register with a pre-existing health promotion website that currently provides Web 1.0 features (http://www.10000steps.org.au). Eligible participants who provide informed consent will be randomly assigned to one of the two trial conditions: the pre-existing 10 000 Steps website (with Web 1.0 features) or the newly developed WALK 2.0 website (with Web 2.0 features). Primary and secondary outcome measures will be assessed by self-report at baseline, 3 months and 12 months, and include: physical activity behaviour, height and weight, Internet self-efficacy, website usability, website usage and quality of life. ETHICS AND DISSEMINATION: This study has received ethics approval from the University of Western Sydney Human Research Ethics Committee (Reference Number H8767) and has been funded by the National Health and Medical Research Council (Reference Number 589903). Study findings will be disseminated widely through peer-reviewed publications, academic conferences and local community-based presentations. TRIAL REGISTRATION NUMBER: Australian New Zealand Clinical Trials Registry Number: ACTRN12611000253909, WHO Universal Trial Number: U111-1119-1755.
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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 | 0.039 | 0.030 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.030 | 0.006 |
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".