Longitudinal designs to study neighbourhood effects on the development of obesity: a scoping review protocol
Bibliographic record
Abstract
INTRODUCTION: The prevalence of obesity has increased significantly in the last three decades and became an important public health concern. Evidence of weight status variability at the neighbourhood level has led researchers to look more precisely at the characteristics of local geographic areas that might influence energy balance related behaviours, giving rise to the field of the 'neighbourhood effect' in public health research. Among an abundant literature about neighbourhood effects and obesity, we propose a protocol for a scoping review that will aim at determining how temporal measurements of residential neighbourhood exposure, individual covariates and weight outcome are integrated in longitudinal designs. METHODS AND ANALYSIS: A list of relevant citations will be obtained through a comprehensive systematic database search in Pubmed, Web of Science and Embase. The search strategy will be designed using a broad definition of neighbourhood to take into account the heterogeneity of this concept in research. Two investigators will screen titles, abstracts and entire publications using predetermined eligibility criteria yielding a list of selected publications. Data from the publications included in the scoping review will be charted according to bibliographic information, study population, exposure, outcomes and results. DISCUSSION AND CONCLUSION: To our knowledge, our protocol will yield the first scoping review regarding longitudinal designs of neighbourhood effect on obesity. Describing how longitudinal designs include temporal measurements of exposure, covariates and outcome is a necessary step in the quest to determine if or which contextual characteristics are likely to be involved in the development of obesity. Such information would bring new knowledge to complement current aetiological investigations and would contribute to enhancing resource allocation strategies for stakeholders in developing relevant interventions to prevent obesity and its negative impacts.
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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 | 0.173 | 0.156 |
| Meta-epidemiology (narrow) | 0.005 | 0.005 |
| Meta-epidemiology (broad) | 0.012 | 0.013 |
| Bibliometrics | 0.019 | 0.016 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.007 | 0.008 |
| Research integrity | 0.013 | 0.007 |
| Insufficient payload (model declined to judge) | 0.063 | 0.018 |
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".