Implementation Intention Strategy to Reduce Salt Intake among Heart Failure Patients: A Randomized Controlled Trial
Bibliographic record
Abstract
Introduction: An Implementation Intention strategy might be effective in transforming a positive intention to reduce salt intake into effective action among heart-failure patients. Objective: To assess the potential efficacy of an Implementation Intention intervention to reduce salt intake among heart-failure patients. Methods: Randomized controlled trial. The 60 heart-failure patients recruited were first randomized into 2 groups: an experimental group (EG) and a control group (CG). The study population was further broken down into 4 groups depending on whether the individuals prepared their own meals: 2 individual groups (EG-Individual and CG-Individual); and 2 collaborative groups, involving the patient and a social referent (EG-Collaborative and CG- Collaborative). The experimental groups developed action and coping plans based on the Implementation Intention. Total salt intake was calculated through discretionary salt, sodium-food frequency questionnaires, and 24-hour recall, obtained at the baseline (T0) and at the 2-month follow-up (T3). Results: 56 patients ended the follow-up. A reduction in the total salt intake was observed in the EGs (Individual and Collaborative) compared to baseline (5.04g/day vs. 12.21g/day for the EG-Individual (p≤0.001); 4.79g/day vs. 11.43g/day for the EG-Collaborative; p≤0.001). The multivariate analysis showed that the 2 EGs had lower salt intake at T3 than the 2 CGs (95% CI 4.19-9.29 for individual groups vs. 95% CI 4.84-10.22 for collaborative groups). There were no differences between the 2 EGs (95% CI –2.77 to 2.41). The total variance explained (R2) by these comparisons was 0.70. Discussion and conclusion: This study suggests that Implementation Intention might be effective in reducing salt intake among heart-failure patients, either individually or collaboratively. Further research testing mediator and moderator effects of the psychosocial variables are recommended.
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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 | 0.008 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".