The effect of culinary interventions (cooking classes) on dietary intake and behavioral change: a systematic review and evidence map
Bibliographic record
Abstract
BACKGROUND: Culinary interventions (cooking classes) have been used to improve the quality of dietary intake and change behavior. The aim of this systematic review is to investigate the effects of culinary interventions on dietary intake and behavioral and cardiometabolic outcomes. METHODS: We conducted a systematic review of MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, and Scopus for comparative studies that evaluated culinary interventions to a control group or baseline values. The intervention was defined as a cooking class regardless of its length or delivery approach. Studies included populations of children, healthy adults or adults with morbidities. The risk of bias was assessed using the Cochrane Risk of Bias tool and the Newcastle-Ottawa Scale. Outcomes were pooled using the random-effects model and descriptive statistics and depicted in an evidence map. Simple logistic regression was used to evaluate factors associated with intervention success. RESULTS: , 95% CI: -1.53, 1.40), systolic (- 5.31 mmHg, 95% CI: -34.2, 23.58) or diastolic blood pressure (- 3.1 mmHg, 95% CI: -23.82, 17.62) or LDL cholesterol (- 8.09 mg/dL, 95% CI: -84.43, 68.25). Culinary interventions were associated with improved attitudes, self-efficacy and healthy dietary intake in adults and children. We were unable to demonstrate whether the effect of a culinary intervention was modified by various characteristics of the intervention such as its delivery or intensity. Interventions with additional components such as education on nutrition, physical activity or gardening were particularly effective. CONCLUSIONS: Culinary interventions were not associated with a significant change in cardiometabolic risk factors, but were associated with improved attitudes, self-efficacy and a healthier dietary intake in adults and children.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.018 | 0.070 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.011 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".