Identifying the facilitators, constraints and barriers of community indoor walking programmes: protocol for a realist synthesis
Bibliographic record
Abstract
INTRODUCTION: Physical inactivity is a costly and leading health risk factor. Engaging in moderate or more intense regular physical activity reduces premature mortality at the population level. Walking is a viable option for achieving the recommended level of physical activity. Yet, the sedentary lifestyle is trending. Determinants of physical activity may be personal, social or environmental. Health promotion endeavours aiming to enhance population-level physical activity are reported in the literature. However, a full range of factors influencing the development and implementation of sustainable indoor walking programmes is unclear. The current review protocol is aimed at describing a process of realist synthesis to uncover contexts, mechanisms and outcomes of indoor walking intervention programmes, which might reveal facilitators, constraints and barriers of planning, implementing and participating in indoor walking initiatives open for the members of the general public. METHODS AND ANALYSIS: We will employ a realist synthesis to determine successes or failures in certain circumstances for specific stakeholders, which will aid in developing a sustainable mall walking health promotion and community engagement programme. Qualitative, quantitative and mixed-method articles and reports will be screened for intervention theories and models in order to identify elements of programmes that may be linked to the success or failure of the interventions. Data related to the context, mechanism and outcome of the interventions will be collected, analysed and synthesised iteratively until a theoretical understanding develops, which might explain the intricacies of the success and failure of identified indoor walking programmes. The review process will be conducted and evaluated by using the recommended tools. ETHICS AND DISSEMINATION: Ethical approval, such as Conjoint Health Research Ethics Board, was not required for this study because no direct interaction with patients will occur for data collection and analysis. We will disseminate directly to the scholarly community through publication and presentation and may post on social media or websites. PROSPERO REGISTRATION NUMBER: CRD42020150415.
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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 | 0.193 | 0.210 |
| Meta-epidemiology (narrow) | 0.006 | 0.006 |
| Meta-epidemiology (broad) | 0.011 | 0.015 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.006 | 0.008 |
| Research integrity | 0.011 | 0.011 |
| Insufficient payload (model declined to judge) | 0.093 | 0.019 |
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".