Healthy lifestyle initiatives for increasing fruit and vegetable intake among Aboriginal and Torres Strait Islander peoples
Bibliographic record
Abstract
Adequate fruit and vegetable intake is key to reducing chronic disease risk among Australian Aboriginal and Torres Strait Islander peoples. This rapid review collated evidence on healthy lifestyle initiatives that focused on increasing fruit and vegetable intake among Australian Aboriginal and Torres Strait Islander peoples residing in major cities. Due to limited studies conducted within major cities, we extended our inclusion criteria to regional and remote areas. Sixteen studies were included. Five (31%) studies were rated as good quality (least risk of bias), 10 (63%) studies were rated as fair, and 1 (6%) study was rated as poor (significant risk of bias). Five (31%) studies employed participatory research in the design and/or execution, and 7 (44%) studies included minimal community involvement. Only 5 (31%) studies were undertaken in major cities; 4 of these combined major cities with regional and/or remote areas. All 5 studies reported positive findings, such as an increase in fresh fruit availability, usage of fresh vegetables, or self-reported fruit and vegetable intake. This review provides evidence confirming the need for high-quality healthy lifestyle initiatives to increase fruit and vegetable intake targeted at Aboriginal and Torres Strait Islander peoples living in major cities. This evidence will assist community organisations in designing effective health promotion interventions, providing insight into improving the structure and function of such programs. PROSPERO registration number: CRD42020194522. Novelty Five studies were undertaken in major cities and all reported positive findings; only 1 study was rated as good quality. Presented data supports the need for high-quality studies to be conducted among those residing in major cities.
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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 | 0.011 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".