Designing a Co-created Intervention to Promote Motivation and Maintenance of Time-Restricted Eating in Individuals With Overweight and Type 2 Diabetes
Bibliographic record
Abstract
OBJECTIVE: To design an appealing time-restricted eating (TRE) intervention by exploring behavioral and social mechanisms to improve TRE adoption and maintenance among people with type 2 diabetes (T2D) and overweight. Time-restricted eating is an intermittent fasting regimen suggested to improve glycemic control and body weight. METHODS: Intervention development combined coherence theory and empirical data (workshops and semistructured interviews with the target group, their relatives, and health care professionals [HCPs]). Abductive analysis was applied. RESULTS: The analysis suggested designing the TRE intervention in 2 phases: a short period with strict TRE, followed by a longer period focusing on adapting TRE to individual needs with support from HCPs, relatives, and peers. To reinforce TRE motivation and maintenance, HCPs should adopt a whole-person approach that focuses on participants' previous experiences. CONCLUSIONS AND IMPLICATIONS: Important intervention elements to promote TRE adoption and maintenance are suggested to include a 2-phase design and support from professionals, family, and peers.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".