The impact of self-efficacy and implementation intentions-based interventions on fruit and vegetable intake among adults
Bibliographic record
Abstract
This study tested the effect of interventions designed for people who do not eat yet the recommended daily fruit and vegetable intake (FVI) but have a positive intention to do so. Adults (N = 163) aged 20-65 were randomised into four groups: implementation intentions (II group), self-efficacy (SE group), combination of II + SE group) and a control group receiving written information on nutrition. Study variables were measured at baseline, post-intervention and at 3-month follow-up. At follow-up, compared to the control group, FVI increased significantly in the II and II + SE groups (1.5 and 1.9 servings per day, respectively). Most psychosocial variables significantly increased compared to the control group, with the exception of SE for vegetable intake (VI). Moreover, at 3-month follow-up, change in FVI was mediated by changes in fruit intake (FI) intention and VI action planning. In conclusion, II interventions were efficient to increase FVI, with or without consideration for the development of SE. Thus, future studies should favour the adoption of this approach to bridge the intention-behaviour gap for FVI.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".