Testing a novel multicomponent intervention to reduce meat consumption in young men
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Both epidemiological studies and randomised controlled trials have shown that meat-eating can be harmful to human health. Meat-eating is also considered to be a moral issue, impacting negatively on the environment and the welfare of animals. To date, very little scientific research has aimed to reduce this dietary behavior. Therefore, the current research tests the effectiveness of a 4-week multicomponent intervention designed to reduce meat-eating. Using a randomised controlled trial procedure, thirty-two young men (mean age: 23.5 ± 3.1 years old) were randomly assigned into two equal groups, the intervention vs control group. Based on research in social and health psychology, the intervention was composed of five components expected to reduce meat consumption: a social norm component; an informational/educational component; an appeal to fear; a mind attribution induction; and a goal setting/self-monitoring component. Measures of different types of meat intake (using dietary journals) were taken at baseline (Time 1) as well as 2 (Time 2) and 4 weeks later (Time 3). Emotions and attitudes toward meat-eating and animals were also assessed at Time 3. Significant reductions in total and weekend red meat consumption as well as cold cuts consumed on the weekend were observed in the intervention condition from Time 1 to Time 3. Moreover, reduced positive emotions toward eating meat mediated the reduction in red meat consumption. The component of the intervention that participants most often perceived as having led to a reduction in their meat consumption was the informational component. In conclusion, results provide support for the effectiveness of the multicomponent intervention and for the mediating role of positive emotions when predicting behavioral changes in meat consumption.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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 it