Environmental determinants of infectious and chronic disease prevention behaviours: A systematic review and thematic synthesis of qualitative research
Bibliographic record
Abstract
Regulatory health policies facilitate desired health behaviours in communities, and among them, smoke-free policies and COVID-19 restrictions have been widely implemented. Qualitative research studies have explored how these measures and other environmental influences shape preventive behaviours. The objective of this systematic review was to synthesize previously published qualitative research, generate across-study themes, and propose recommendations for behaviour change interventions. We used a comprehensive search strategy, relevance screening and confirmation, data extraction, quality assessment, thematic synthesis, and quality-of-evidence assessment. In total, 87 relevant studies were identified. Findings were grouped under six overarching themes and mapped under three categories: (i) the political environment, (ii) the sociocultural environment, and (iii) the physical environment. These findings provide insights into the environmental influences of behaviour and indicate future interventions may be more effective by considering moral norms, community norms, policy support, and group identity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.021 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".