Community intervention delivered by frontline healthcare professionals to promote eating self-efficacy
Bibliographic record
Abstract
Purpose The goal of this study was to assess changes in eating self-efficacy after participating in a brief psychoeducational group intervention, grounded in the cognitive-behavioral model, delivered by dieticians in community-based health facilities. Design/methodology/approach The study was conducted using a quasi-experimental, pre-post design. A total of 110 program participants took part in the study. They were asked to complete the Eating Self-Efficacy Scale before the start of the intervention, at the end of the intervention, and three months after the intervention ended. Data were analyzed using the Linear Mixed Model. Findings Participants’ personal sense of control over their eating behaviors significantly increased after they completed the program and continued to increase up to the three-month follow-up. The effect of the intervention remained significant after controlling for differences in age and whether participants had access to other forms of individual support or completed the follow-up during the COVID-19 general lockdown. Practical implications By promoting participants’ sense of eating self-efficacy, this intervention could lead to positive dietary changes, which in turn could promote better health and healthy aging. Social implications This community intervention is readily accessible and represents a cost-effective approach to promote healthy eating, reducing the risk of chronic disease and the need for medical care, thereby cutting costs for the healthcare system. Originality/value (1) This study addresses a gap in the scientific literature as there was limited published research to date that investigated this intervention. (2) The three-month follow-up made it possible to evaluate whether changes in eating self-efficacy were maintained over time. (3) Potential confounding variables, including age, having access to other forms of individual support and the COVID-19 general lockdown, were taken into account.
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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 | 0.001 | 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 | 0.001 |
| 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".